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Zhai S, Tan Y, Zhu C, Zhang C, Gao Y, Mao Q, Zhang Y, Duan H, Yin Y. PepExplainer: An explainable deep learning model for selection-based macrocyclic peptide bioactivity prediction and optimization. Eur J Med Chem 2024; 275:116628. [PMID: 38944933 DOI: 10.1016/j.ejmech.2024.116628] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/17/2024] [Revised: 06/21/2024] [Accepted: 06/24/2024] [Indexed: 07/02/2024]
Abstract
Macrocyclic peptides possess unique features, making them highly promising as a drug modality. However, evaluating their bioactivity through wet lab experiments is generally resource-intensive and time-consuming. Despite advancements in artificial intelligence (AI) for bioactivity prediction, challenges remain due to limited data availability and the interpretability issues in deep learning models, often leading to less-than-ideal predictions. To address these challenges, we developed PepExplainer, an explainable graph neural network based on substructure mask explanation (SME). This model excels at deciphering amino acid substructures, translating macrocyclic peptides into detailed molecular graphs at the atomic level, and efficiently handling non-canonical amino acids and complex macrocyclic peptide structures. PepExplainer's effectiveness is enhanced by utilizing the correlation between peptide enrichment data from selection-based focused library and bioactivity data, and employing transfer learning to improve bioactivity predictions of macrocyclic peptides against IL-17C/IL-17 RE interaction. Additionally, PepExplainer underwent further validation for bioactivity prediction using an additional set of thirteen newly synthesized macrocyclic peptides. Moreover, it enabled the optimization of the IC50 of a macrocyclic peptide, reducing it from 15 nM to 5.6 nM based on the contribution score provided by PepExplainer. This achievement underscores PepExplainer's skill in deciphering complex molecular patterns, highlighting its potential to accelerate the discovery and optimization of macrocyclic peptides.
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Affiliation(s)
- Silong Zhai
- School of Pharmaceutical Sciences, Zhejiang University of Technology, Hangzhou, 310014, China
| | - Yahong Tan
- State Key Laboratory of Microbial Technology, Institute of Microbial Technology, Shandong University, Qingdao, 266237, China
| | - Cheng Zhu
- School of Pharmaceutical Sciences, Zhejiang University of Technology, Hangzhou, 310014, China
| | - Chengyun Zhang
- School of Pharmaceutical Sciences, Zhejiang University of Technology, Hangzhou, 310014, China
| | - Yan Gao
- Qilu Institute of Technology, Jinan, 250200, China
| | - Qingyi Mao
- School of Pharmaceutical Sciences, Zhejiang University of Technology, Hangzhou, 310014, China
| | - Youming Zhang
- State Key Laboratory of Microbial Technology, Institute of Microbial Technology, Shandong University, Qingdao, 266237, China
| | - Hongliang Duan
- Faculty of Applied Sciences, Macao Polytechnic University, Macao, 999078, China.
| | - Yizhen Yin
- State Key Laboratory of Microbial Technology, Institute of Microbial Technology, Shandong University, Qingdao, 266237, China; Shandong Research Institute of Industrial Technology, Jinan, 250101, China.
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2
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Deal PE, Lee H, Mondal A, Lolicato M, Mendonça PRFD, Black H, Jang S, El-Hilali X, Bryant C, Isacoff EY, Renslo AR, Minor DL. Development of covalent chemogenetic K 2P channel activators. Cell Chem Biol 2024; 31:1305-1323.e9. [PMID: 39029456 DOI: 10.1016/j.chembiol.2024.06.006] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/01/2023] [Revised: 04/19/2024] [Accepted: 06/19/2024] [Indexed: 07/21/2024]
Abstract
K2P potassium channels regulate excitability by affecting cellular resting membrane potential in the brain, cardiovascular system, immune cells, and sensory organs. Despite their important roles in anesthesia, arrhythmia, pain, hypertension, sleep, and migraine, the ability to control K2P function remains limited. Here, we describe a chemogenetic strategy termed CATKLAMP (covalent activation of TREK family K+ channels to clamp membrane potential) that leverages the discovery of a K2P modulator pocket site that reacts with electrophile-bearing derivatives of a TREK subfamily small-molecule activator, ML335, to activate the channel irreversibly. We show that CATKLAMP can be used to probe fundamental aspects of K2P function, as a switch to silence neuronal firing, and is applicable to all TREK subfamily members. Together, our findings exemplify a means to alter K2P channel activity that should facilitate molecular and systems level studies of K2P function and enable the search for new K2P modulators.
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Affiliation(s)
- Parker E Deal
- Cardiovascular Research Institute, University of California, San Francisco, San Francisco, CA 93858-2330, USA; Department of Pharmaceutical Chemistry, University of California, San Francisco, San Francisco, CA 93858-2330, USA
| | - Haerim Lee
- Cardiovascular Research Institute, University of California, San Francisco, San Francisco, CA 93858-2330, USA
| | - Abhisek Mondal
- Cardiovascular Research Institute, University of California, San Francisco, San Francisco, CA 93858-2330, USA
| | - Marco Lolicato
- Cardiovascular Research Institute, University of California, San Francisco, San Francisco, CA 93858-2330, USA
| | | | - Holly Black
- Department of Molecular and Cell Biology, University of California, Berkeley, Berkeley, CA 94720, USA
| | - Seil Jang
- Cardiovascular Research Institute, University of California, San Francisco, San Francisco, CA 93858-2330, USA
| | - Xochina El-Hilali
- Department of Pharmaceutical Chemistry, University of California, San Francisco, San Francisco, CA 93858-2330, USA
| | - Clifford Bryant
- Department of Pharmaceutical Chemistry, University of California, San Francisco, San Francisco, CA 93858-2330, USA
| | - Ehud Y Isacoff
- Department of Molecular and Cell Biology, University of California, Berkeley, Berkeley, CA 94720, USA; Helen Wills Neuroscience Institute, University of California, Berkeley, Berkeley, CA 94720, USA; Weill Neurohub, University of California, Berkeley, Berkeley, CA 94720, USA; Molecular Biophysics and Integrated Bio-imaging Division, Lawrence Berkeley National Laboratory, Berkeley, CA 94720 USA
| | - Adam R Renslo
- Department of Pharmaceutical Chemistry, University of California, San Francisco, San Francisco, CA 93858-2330, USA.
| | - Daniel L Minor
- Cardiovascular Research Institute, University of California, San Francisco, San Francisco, CA 93858-2330, USA; Molecular Biophysics and Integrated Bio-imaging Division, Lawrence Berkeley National Laboratory, Berkeley, CA 94720 USA; Departments of Biochemistry and Biophysics, and Cellular and Molecular Pharmacology, University of California, San Francisco, San Francisco, CA 93858-2330, USA; California Institute for Quantitative Biomedical Research, University of California, San Francisco, San Francisco, CA 93858-2330, USA; Kavli Institute for Fundamental Neuroscience, University of California, San Francisco, San Francisco, CA 93858-2330, USA.
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3
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Somsen BA, Cossar PJ, Arkin MR, Brunsveld L, Ottmann C. 14-3-3 Protein-Protein Interactions: From Mechanistic Understanding to Their Small-Molecule Stabilization. Chembiochem 2024; 25:e202400214. [PMID: 38738787 DOI: 10.1002/cbic.202400214] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/08/2024] [Revised: 05/11/2024] [Accepted: 05/13/2024] [Indexed: 05/14/2024]
Abstract
Protein-protein interactions (PPIs) are of utmost importance for maintenance of cellular homeostasis. Herein, a central role can be found for 14-3-3 proteins. These hub-proteins are known to bind hundreds of interaction partners, thereby regulating their activity, localization, and/or stabilization. Due to their ability to bind a large variety of client proteins, studies of 14-3-3 protein complexes flourished over the last decades, aiming to gain greater molecular understanding of these complexes and their role in health and disease. Because of their crucial role within the cell, 14-3-3 protein complexes are recognized as highly interesting therapeutic targets, encouraging the discovery of small molecule modulators of these PPIs. We discuss various examples of 14-3-3-mediated regulation of its binding partners on a mechanistic level, highlighting the versatile and multi-functional role of 14-3-3 within the cell. Furthermore, an overview is given on the development of stabilizers of 14-3-3 protein complexes, from initially used natural products to fragment-based approaches. These studies show the potential of 14-3-3 PPI stabilizers as novel agents in drug discovery and as tool compounds to gain greater molecular understanding of the role of 14-3-3-based protein regulation.
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Affiliation(s)
- Bente A Somsen
- Department of Biomedical Engineering and Institute for Complex Molecular Systems, Laboratory of Chemical Biology, Eindhoven University of Technology, P.O. Box 513, MB Eindhoven, 5600, Eindhoven, The Netherlands
| | - Peter J Cossar
- Department of Biomedical Engineering and Institute for Complex Molecular Systems, Laboratory of Chemical Biology, Eindhoven University of Technology, P.O. Box 513, MB Eindhoven, 5600, Eindhoven, The Netherlands
| | - Michelle R Arkin
- Department of Pharmaceutical Chemistry and Small Molecule Discovery Center (SMDC), University of California, San Francisco, California, 94143, United States
| | - Luc Brunsveld
- Department of Biomedical Engineering and Institute for Complex Molecular Systems, Laboratory of Chemical Biology, Eindhoven University of Technology, P.O. Box 513, MB Eindhoven, 5600, Eindhoven, The Netherlands
| | - Christian Ottmann
- Department of Biomedical Engineering and Institute for Complex Molecular Systems, Laboratory of Chemical Biology, Eindhoven University of Technology, P.O. Box 513, MB Eindhoven, 5600, Eindhoven, The Netherlands
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4
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Zhou Z, Huang S, Fan S, Li X, Wang C, Yu W, Du D, Zhang Y, Chen K, Fu W, Luo C. Structure-Based Design and Discovery of a Potent and Cell-Active LC3A/B Covalent Inhibitor. J Med Chem 2024. [PMID: 39010658 DOI: 10.1021/acs.jmedchem.4c00898] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 07/17/2024]
Abstract
Autophagy is a highly conserved cellular homeostasis maintenance mechanism in eukaryotes. Microtubule-associated protein light chain 3 (LC3) plays a crucial role in autophagy. It has multiple pairs of protein-protein interactions (PPIs) with other proteins, and these PPIs have an effect on the regulation of autophagosome formation and the recruitment of autophagic substrates. In our previous work, a small molecule covalent inhibitor DC-LC3in-D5 which could inhibit LC3A/B PPIs was identified, but a detailed study of structure-activity relationships (SARs) was lacking. Herein, a new molecule LC3in-C42 was discovered utilizing the hybridization of advantageous fragments, whose potency (IC50 = 7.6 nM) had been greatly improved compared with that of DC-LC3in-D5. LC3in-C42 inhibits autophagy at the cellular level and its efficacy far exceeds that of DC-LC3in-D5. Thus far, LC3in-C42 stands as the most potent LC3A/B small molecule inhibitor. LC3in-C42 could serve as a powerful tool for LC3A/B protein and autophagy research.
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Affiliation(s)
- Zhenfei Zhou
- Department of Medicinal Chemistry, School of Pharmacy, Fudan University, Shanghai 201203, China
- Drug Discovery and Design Center and The Center for Chemical Biology, Shanghai Institute of Materia Medica, Chinese Academy of Sciences, Shanghai 201203, China
- Zhongshan Institute for Drug Discovery, Shanghai Institute of Materia Medica, Chinese Academy of Sciences, Guangdong 528400, China
| | - Siqi Huang
- Drug Discovery and Design Center and The Center for Chemical Biology, Shanghai Institute of Materia Medica, Chinese Academy of Sciences, Shanghai 201203, China
- University of Chinese Academy of Sciences, Beijing 100049, China
| | - Shijie Fan
- Zhongshan Institute for Drug Discovery, Shanghai Institute of Materia Medica, Chinese Academy of Sciences, Guangdong 528400, China
| | - Xueyuan Li
- Zhongshan Institute for Drug Discovery, Shanghai Institute of Materia Medica, Chinese Academy of Sciences, Guangdong 528400, China
- School of Pharmaceutical Sciences, Southern Medical University, Guangzhou 510515, Guangdong, China
| | - Chengyu Wang
- Zhongshan Institute for Drug Discovery, Shanghai Institute of Materia Medica, Chinese Academy of Sciences, Guangdong 528400, China
| | - Wanlin Yu
- Zhongshan Institute for Drug Discovery, Shanghai Institute of Materia Medica, Chinese Academy of Sciences, Guangdong 528400, China
- School of Pharmaceutical Sciences, Southern Medical University, Guangzhou 510515, Guangdong, China
| | - Daohai Du
- Drug Discovery and Design Center and The Center for Chemical Biology, Shanghai Institute of Materia Medica, Chinese Academy of Sciences, Shanghai 201203, China
| | - Yuanyuan Zhang
- Drug Discovery and Design Center and The Center for Chemical Biology, Shanghai Institute of Materia Medica, Chinese Academy of Sciences, Shanghai 201203, China
- University of Chinese Academy of Sciences, Beijing 100049, China
| | - Kaixian Chen
- Department of Medicinal Chemistry, School of Pharmacy, Fudan University, Shanghai 201203, China
- Drug Discovery and Design Center and The Center for Chemical Biology, Shanghai Institute of Materia Medica, Chinese Academy of Sciences, Shanghai 201203, China
- University of Chinese Academy of Sciences, Beijing 100049, China
| | - Wei Fu
- Department of Medicinal Chemistry, School of Pharmacy, Fudan University, Shanghai 201203, China
| | - Cheng Luo
- Drug Discovery and Design Center and The Center for Chemical Biology, Shanghai Institute of Materia Medica, Chinese Academy of Sciences, Shanghai 201203, China
- University of Chinese Academy of Sciences, Beijing 100049, China
- Zhongshan Institute for Drug Discovery, Shanghai Institute of Materia Medica, Chinese Academy of Sciences, Guangdong 528400, China
- State Key Laboratory of Functions and Applications of Medicinal Plants, Guizhou Medical University, Guiyang 550014, China
- School of Pharmaceutical Science and Technology, Hangzhou Institute for Advanced Study, University of Chinese Academy of Sciences, Hangzhou 310024, China
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5
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Lima MCP, Hornsby BD, Lim CS, Cheatham TE. Molecular Modeling of Single- and Double-Hydrocarbon-Stapled Coiled-Coil Inhibitors against Bcr-Abl: Toward a Treatment Strategy for CML. J Phys Chem B 2024; 128:6476-6491. [PMID: 38951498 PMCID: PMC11247501 DOI: 10.1021/acs.jpcb.4c02699] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 07/03/2024]
Abstract
The chimeric oncoprotein Bcr-Abl is the causative agent of virtually all chronic myeloid leukemias and a subset of acute lymphoblastic leukemias. As a result of the so-called Philadelphia chromosome translocation t(9;22), Bcr-Abl manifests as a constitutively active tyrosine kinase, which promotes leukemogenesis by activation of cell cycle signaling pathways. Constitutive and oncogenic activation is mediated by an N-terminal coiled-coil oligomerization domain in Bcr (Bcr-CC), presenting a therapeutic target for inhibition of Bcr-Abl activity toward the treatment of Bcr-Abl+ leukemias. Previously, we demonstrated that a rationally designed Bcr-CC mutant, CCmut3, exerts a dominant negative effect upon Bcr-Abl activity by preferential oligomerization with Bcr-CC. Moreover, we have shown that conjugation to a leukemia-specific cell-penetrating peptide (CPP-CCmut3) improves intracellular delivery and activity. However, our full-length CPP-CCmut3 construct (81 aa) is encumbered by an intrinsically high degree of conformational variability and susceptibility to proteolytic degradation relative to traditional small-molecule therapeutics. Here, we iterate a new generation of CCmut3 inhibitors against Bcr-CC-mediated Bcr-Abl assembly designed to address these constraints through incorporation of all-hydrocarbon staples spanning i and i + 7 positions in α-helix 2 (CPP-CCmut3-st). We utilize computational modeling and biomolecular simulation to evaluate single- and double-stapled CCmut3 candidates in silico for dynamics and binding energetics. We further model a truncated system characterized by the deletion of α-helix 1 and the flexible loop linker, which are known to impart high conformational variability. To study the impact of the N-terminal cyclic CPP toward model stability and inhibitor activity, we also model the full-length and truncated systems devoid of the CPP, with a cyclized CPP, and with an open-configuration CPP, for a total of six systems that comprise our library. From this library, we present lead-stapled peptide candidates to be synthesized and evaluated experimentally as our next iteration of inhibitors against Bcr-Abl.
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MESH Headings
- Fusion Proteins, bcr-abl/antagonists & inhibitors
- Fusion Proteins, bcr-abl/metabolism
- Fusion Proteins, bcr-abl/chemistry
- Leukemia, Myelogenous, Chronic, BCR-ABL Positive/drug therapy
- Leukemia, Myelogenous, Chronic, BCR-ABL Positive/metabolism
- Humans
- Protein Kinase Inhibitors/chemistry
- Protein Kinase Inhibitors/pharmacology
- Protein Kinase Inhibitors/metabolism
- Models, Molecular
- Molecular Dynamics Simulation
- Antineoplastic Agents/chemistry
- Antineoplastic Agents/pharmacology
- Cell-Penetrating Peptides/chemistry
- Cell-Penetrating Peptides/pharmacology
- Cell-Penetrating Peptides/metabolism
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Affiliation(s)
- Maria Carolina P Lima
- Department of Medicinal Chemistry, University of Utah, Salt Lake City, Utah 84112, United States
| | - Braxten D Hornsby
- Department of Molecular Pharmaceutics, University of Utah, Salt Lake City, Utah 84112, United States
| | - Carol S Lim
- Department of Molecular Pharmaceutics, University of Utah, Salt Lake City, Utah 84112, United States
| | - Thomas E Cheatham
- Department of Medicinal Chemistry, University of Utah, Salt Lake City, Utah 84112, United States
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6
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Kage M, Hayashi R, Matsuo A, Tamiya M, Kuramoto S, Ohara K, Irie M, Chiyoda A, Takano K, Ito T, Kotake T, Takeyama R, Ishikawa S, Nomura K, Furuichi N, Morita Y, Hashimoto S, Kawada H, Nishimura Y, Nii K, Sase H, Ohta A, Kojima T, Iikura H, Tanada M, Shiraishi T. Structure-activity relationships of middle-size cyclic peptides, KRAS inhibitors derived from an mRNA display. Bioorg Med Chem 2024; 110:117830. [PMID: 38981216 DOI: 10.1016/j.bmc.2024.117830] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/27/2024] [Revised: 06/30/2024] [Accepted: 07/01/2024] [Indexed: 07/11/2024]
Abstract
Cyclic peptides are attracting attention as therapeutic agents due to their potential for oral absorption and easy access to tough intracellular targets. LUNA18, a clinical KRAS inhibitor, was transformed-without scaffold hopping-from the initial hit by using an mRNA display library that met our criteria for drug-likeness. In drug discovery using mRNA display libraries, hit compounds always possess a site linked to an mRNA tag. Here, we describe our examination of the Structure-Activity Relationship (SAR) using X-ray structures for chemical optimization near the site linked to the mRNA tag, equivalent to the C-terminus. Structural modifications near the C-terminus demonstrated a relatively wide range of tolerance for side chains. Furthermore, we show that a single atom modification is enough to change the pharmacokinetic (PK) profile. Since there are four positions where side chain modification is permissible in terms of activity, it is possible to flexibly adjust the pharmacokinetic profile by structurally optimizing the side chain. The side chain transformation findings demonstrated here may be generally applicable to hits obtained from mRNA display libraries.
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Affiliation(s)
- Mirai Kage
- Research Division, Chugai Pharmaceutical Co. Ltd., 216, Totsuka-cho, Totsuka-ku, Yokohama, Kanagawa 244-8602, Japan
| | - Ryuji Hayashi
- Research Division, Chugai Pharmaceutical Co. Ltd., 216, Totsuka-cho, Totsuka-ku, Yokohama, Kanagawa 244-8602, Japan.
| | - Atsushi Matsuo
- Research Division, Chugai Pharmaceutical Co. Ltd., 216, Totsuka-cho, Totsuka-ku, Yokohama, Kanagawa 244-8602, Japan
| | - Minoru Tamiya
- Research Division, Chugai Pharmaceutical Co. Ltd., 216, Totsuka-cho, Totsuka-ku, Yokohama, Kanagawa 244-8602, Japan
| | - Shino Kuramoto
- Research Division, Chugai Pharmaceutical Co. Ltd., 216, Totsuka-cho, Totsuka-ku, Yokohama, Kanagawa 244-8602, Japan
| | - Kazuhiro Ohara
- Research Division, Chugai Pharmaceutical Co. Ltd., 216, Totsuka-cho, Totsuka-ku, Yokohama, Kanagawa 244-8602, Japan
| | - Machiko Irie
- Research Division, Chugai Pharmaceutical Co. Ltd., 216, Totsuka-cho, Totsuka-ku, Yokohama, Kanagawa 244-8602, Japan
| | - Aya Chiyoda
- Research Division, Chugai Pharmaceutical Co. Ltd., 216, Totsuka-cho, Totsuka-ku, Yokohama, Kanagawa 244-8602, Japan
| | - Koji Takano
- Research Division, Chugai Pharmaceutical Co. Ltd., 216, Totsuka-cho, Totsuka-ku, Yokohama, Kanagawa 244-8602, Japan
| | - Toshiya Ito
- Research Division, Chugai Pharmaceutical Co. Ltd., 216, Totsuka-cho, Totsuka-ku, Yokohama, Kanagawa 244-8602, Japan
| | - Tomoya Kotake
- Research Division, Chugai Pharmaceutical Co. Ltd., 216, Totsuka-cho, Totsuka-ku, Yokohama, Kanagawa 244-8602, Japan
| | - Ryuuichi Takeyama
- Research Division, Chugai Pharmaceutical Co. Ltd., 216, Totsuka-cho, Totsuka-ku, Yokohama, Kanagawa 244-8602, Japan
| | - Shiho Ishikawa
- Research Division, Chugai Pharmaceutical Co. Ltd., 216, Totsuka-cho, Totsuka-ku, Yokohama, Kanagawa 244-8602, Japan
| | - Kenichi Nomura
- Research Division, Chugai Pharmaceutical Co. Ltd., 216, Totsuka-cho, Totsuka-ku, Yokohama, Kanagawa 244-8602, Japan
| | - Noriyuki Furuichi
- Research Division, Chugai Pharmaceutical Co. Ltd., 216, Totsuka-cho, Totsuka-ku, Yokohama, Kanagawa 244-8602, Japan
| | - Yuya Morita
- Research Division, Chugai Pharmaceutical Co. Ltd., 216, Totsuka-cho, Totsuka-ku, Yokohama, Kanagawa 244-8602, Japan
| | - Satoshi Hashimoto
- Research Division, Chugai Pharmaceutical Co. Ltd., 216, Totsuka-cho, Totsuka-ku, Yokohama, Kanagawa 244-8602, Japan
| | - Hatsuo Kawada
- Research Division, Chugai Pharmaceutical Co. Ltd., 216, Totsuka-cho, Totsuka-ku, Yokohama, Kanagawa 244-8602, Japan
| | - Yoshikazu Nishimura
- Research Division, Chugai Pharmaceutical Co. Ltd., 216, Totsuka-cho, Totsuka-ku, Yokohama, Kanagawa 244-8602, Japan
| | - Keiji Nii
- Research Division, Chugai Pharmaceutical Co. Ltd., 216, Totsuka-cho, Totsuka-ku, Yokohama, Kanagawa 244-8602, Japan
| | - Hitoshi Sase
- Research Division, Chugai Pharmaceutical Co. Ltd., 216, Totsuka-cho, Totsuka-ku, Yokohama, Kanagawa 244-8602, Japan
| | - Atsushi Ohta
- Research Division, Chugai Pharmaceutical Co. Ltd., 216, Totsuka-cho, Totsuka-ku, Yokohama, Kanagawa 244-8602, Japan
| | - Tetsuo Kojima
- Research Division, Chugai Pharmaceutical Co. Ltd., 216, Totsuka-cho, Totsuka-ku, Yokohama, Kanagawa 244-8602, Japan
| | - Hitoshi Iikura
- Research Division, Chugai Pharmaceutical Co. Ltd., 216, Totsuka-cho, Totsuka-ku, Yokohama, Kanagawa 244-8602, Japan
| | - Mikimasa Tanada
- Research Division, Chugai Pharmaceutical Co. Ltd., 216, Totsuka-cho, Totsuka-ku, Yokohama, Kanagawa 244-8602, Japan.
| | - Takuya Shiraishi
- Research Division, Chugai Pharmaceutical Co. Ltd., 216, Totsuka-cho, Totsuka-ku, Yokohama, Kanagawa 244-8602, Japan.
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7
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Vijay A, Mukherjee A. Unraveling the folding-assisted unbinding mechanism of TCF with its binding partner β-catenin. Phys Chem Chem Phys 2024; 26:17481-17488. [PMID: 38887991 DOI: 10.1039/d4cp01451k] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/20/2024]
Abstract
This study utilizes molecular dynamics simulations aided with multiple walker parallel bias metadynamics to investigate the TCF unbinding mechanism from the β-catenin interface. The results, consistent with experimental binding affinity calculations, unveil a folding-assisted unbinding mechanism.
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Affiliation(s)
- Amal Vijay
- Department of Chemistry, Indian Institute of Science Education and Research, Pune-411008, Maharashtra, India.
| | - Arnab Mukherjee
- Department of Chemistry, Indian Institute of Science Education and Research, Pune-411008, Maharashtra, India.
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8
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Liu Y, Sundah NR, Ho NRY, Shen WX, Xu Y, Natalia A, Yu Z, Seet JE, Chan CW, Loh TP, Lim BY, Shao H. Bidirectional linkage of DNA barcodes for the multiplexed mapping of higher-order protein interactions in cells. Nat Biomed Eng 2024:10.1038/s41551-024-01225-3. [PMID: 38898172 DOI: 10.1038/s41551-024-01225-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/28/2023] [Accepted: 05/05/2024] [Indexed: 06/21/2024]
Abstract
Capturing the full complexity of the diverse hierarchical interactions in the protein interactome is challenging. Here we report a DNA-barcoding method for the multiplexed mapping of pairwise and higher-order protein interactions and their dynamics within cells. The method leverages antibodies conjugated with barcoded DNA strands that can bidirectionally hybridize and covalently link to linearize closely spaced interactions within individual 3D protein complexes, encoding and decoding the protein constituents and the interactions among them. By mapping protein interactions in cancer cells and normal cells, we found that tumour cells exhibit a larger diversity and abundance of protein complexes with higher-order interactions. In biopsies of human breast-cancer tissue, the method accurately identified the cancer subtype and revealed that higher-order protein interactions are associated with cancer aggressiveness.
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Affiliation(s)
- Yu Liu
- Institute for Health Innovation and Technology, National University of Singapore, Singapore, Singapore
- Department of Biomedical Engineering, College of Design and Engineering, National University of Singapore, Singapore, Singapore
| | - Noah R Sundah
- Institute for Health Innovation and Technology, National University of Singapore, Singapore, Singapore
- Department of Biomedical Engineering, College of Design and Engineering, National University of Singapore, Singapore, Singapore
| | - Nicholas R Y Ho
- Institute for Health Innovation and Technology, National University of Singapore, Singapore, Singapore
| | - Wan Xiang Shen
- Department of Pharmacy and Pharmaceutical Sciences, Faculty of Science, National University of Singapore, Singapore, Singapore
| | - Yun Xu
- Institute for Health Innovation and Technology, National University of Singapore, Singapore, Singapore
- Department of Biomedical Engineering, College of Design and Engineering, National University of Singapore, Singapore, Singapore
| | - Auginia Natalia
- Institute for Health Innovation and Technology, National University of Singapore, Singapore, Singapore
- Department of Biomedical Engineering, College of Design and Engineering, National University of Singapore, Singapore, Singapore
| | - Zhonglang Yu
- Institute for Health Innovation and Technology, National University of Singapore, Singapore, Singapore
- Department of Biomedical Engineering, College of Design and Engineering, National University of Singapore, Singapore, Singapore
| | - Ju Ee Seet
- Department of Pathology, National University Hospital, Singapore, Singapore
| | - Ching Wan Chan
- Department of Surgery, National University Hospital, Singapore, Singapore
- Department of Surgery, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
| | - Tze Ping Loh
- Institute for Health Innovation and Technology, National University of Singapore, Singapore, Singapore
- Department of Laboratory Medicine, National University Hospital, Singapore, Singapore
| | - Brian Y Lim
- Institute for Health Innovation and Technology, National University of Singapore, Singapore, Singapore.
- Department of Computer Science, School of Computing, National University of Singapore, Singapore, Singapore.
| | - Huilin Shao
- Institute for Health Innovation and Technology, National University of Singapore, Singapore, Singapore.
- Department of Biomedical Engineering, College of Design and Engineering, National University of Singapore, Singapore, Singapore.
- Department of Surgery, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore.
- Institute of Molecular and Cell Biology, Agency for Science, Technology and Research, Singapore, Singapore.
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9
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Hec-Gałązka A, Tyrcha U, Barczyński J, Bielski P, Mikitiuk M, Gudz GP, Kitel R, Musielak B, Plewka J, Sitar T, Holak TA. Nonsymmetrically Substituted 1,1'-Biphenyl-Based Small Molecule Inhibitors of the PD-1/PD-L1 Interaction. ACS Med Chem Lett 2024; 15:828-836. [PMID: 38894909 PMCID: PMC11181486 DOI: 10.1021/acsmedchemlett.4c00042] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/26/2024] [Revised: 05/27/2024] [Accepted: 05/28/2024] [Indexed: 06/21/2024] Open
Abstract
Therapeutic antibodies directed against either programmed cell death-1 protein (PD-1) or its ligand PD-L1 have demonstrated efficacy in the treatment of various cancers. In contrast with antibodies, small molecules have the potential for increased tissue penetration; better pharmacology; and therefore, improved antitumor activity. A series of nonsymmetric C2 inhibitors were synthesized and evaluated for PD-1/PD-L1 interaction inhibition. These compounds induced PD-L1 dimerization and effectively blocked PD-L1/PD-1 interaction in a homogeneous time-resolved fluorescence (HTRF) assay with most inhibitors exhibiting IC50 values in the single-digit nM range and below. Their high inhibitory potency was also demonstrated in a cell-based coculture PD-1 signaling assay where 2 exhibited an EC50 inhibitory activity of 21.8 nM, which approached that of the PD-L1 antibody durvalumab (EC50 = 0.3-1.8 nM). Structural insight into how these inhibitors interact with PD-L1 was gained by using NMR and X-ray cocrystal structure studies. These data support further preclinical evaluation of these compounds as antibody alternatives.
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Affiliation(s)
- Aleksandra Hec-Gałązka
- Jagiellonian
University, Doctoral School
of Exact and Natural Sciences, prof. S. Łojasiewicza 11, 30-348 Krakow, Poland
- Department
of Organic Chemistry, Faculty of Chemistry, Jagiellonian University, Gronostajowa 2, 30-387 Krakow, Poland
- Recepton
Sp. z o.o., ul. Trzy
Lipy 3, 80-172 Gdansk, Poland
| | - Urszula Tyrcha
- Recepton
Sp. z o.o., ul. Trzy
Lipy 3, 80-172 Gdansk, Poland
| | - Jan Barczyński
- Recepton
Sp. z o.o., ul. Trzy
Lipy 3, 80-172 Gdansk, Poland
| | - Przemyslaw Bielski
- Jagiellonian
University, Doctoral School
of Exact and Natural Sciences, prof. S. Łojasiewicza 11, 30-348 Krakow, Poland
- Department
of Organic Chemistry, Faculty of Chemistry, Jagiellonian University, Gronostajowa 2, 30-387 Krakow, Poland
- Recepton
Sp. z o.o., ul. Trzy
Lipy 3, 80-172 Gdansk, Poland
| | | | - Ganna P. Gudz
- Department
of Organic Chemistry, Faculty of Chemistry, Jagiellonian University, Gronostajowa 2, 30-387 Krakow, Poland
| | - Radosław Kitel
- Department
of Organic Chemistry, Faculty of Chemistry, Jagiellonian University, Gronostajowa 2, 30-387 Krakow, Poland
| | - Bogdan Musielak
- Department
of Organic Chemistry, Faculty of Chemistry, Jagiellonian University, Gronostajowa 2, 30-387 Krakow, Poland
| | - Jacek Plewka
- Department
of Organic Chemistry, Faculty of Chemistry, Jagiellonian University, Gronostajowa 2, 30-387 Krakow, Poland
| | - Tomasz Sitar
- Recepton
Sp. z o.o., ul. Trzy
Lipy 3, 80-172 Gdansk, Poland
| | - Tad A. Holak
- Recepton
Sp. z o.o., ul. Trzy
Lipy 3, 80-172 Gdansk, Poland
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10
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Xu X, Closson J, Marcelino LP, Favaro DC, Silvestrini ML, Solazzo R, Chong LT, Gardner KH. Identification of Small Molecule Ligand Binding Sites On and In the ARNT PAS-B Domain. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2023.11.03.565595. [PMID: 37961463 PMCID: PMC10635134 DOI: 10.1101/2023.11.03.565595] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/15/2023]
Abstract
Transcription factors are generally challenging to target with small molecule inhibitors due to their structural plasticity and lack of catalytic sites. Notable exceptions include several naturally ligand-regulated transcription factors, including our prior work with the heterodimeric HIF-2 transcription factor which showed that small molecule binding within an internal pocket of the HIF-2α PAS-B domain can disrupt its interactions with its dimerization partner, ARNT. Here, we explore the feasibility of similarly targeting small molecules to the analogous ARNT PAS-B domain itself, potentially opening a promising route to simultaneously modulate several ARNT-mediated signaling pathways. Using solution NMR screening of an in-house fragment library, we previously identified several compounds that bind ARNT PAS-B and, in certain cases, antagonize ARNT association with the TACC3 transcriptional coactivator. However, these ligands have only modest binding affinities, complicating characterization of their binding sites. We address this challenge by combining NMR, MD simulations, and ensemble docking to identify ligand-binding 'hotspots' on and within the ARNT PAS-B domain. Our data indicate that the two ARNT/TACC3 inhibitors, KG-548 and KG-655, bind to a β-sheet surface implicated in both HIF-2 dimerization and coactivator recruitment. Furthermore, while KG-548 binds exclusively to the β-sheet surface, KG-655 can additionally bind within a water-accessible internal cavity in ARNT PAS-B. Finally, KG-279, while not a coactivator inhibitor, exemplifies ligands that preferentially bind only to the internal cavity. All three ligands promoted ARNT PAS-B homodimerization, albeit to varying degrees. Taken together, our findings provide a comprehensive overview of ARNT PAS-B ligand-binding sites and may guide the development of more potent coactivator inhibitors for cellular and functional studies.
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11
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Zheng W, Wuyun Q, Zhang Y. One step forward towards deep-learning protein complex structure prediction by precise multiple sequence alignment construction. Clin Transl Med 2024; 14:e1689. [PMID: 38880984 PMCID: PMC11180690 DOI: 10.1002/ctm2.1689] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/20/2024] [Accepted: 04/26/2024] [Indexed: 06/18/2024] Open
Affiliation(s)
- Wei Zheng
- Department of Computational Medicine and BioinformaticsUniversity of MichiganAnn ArborMichiganUSA
| | - Qiqige Wuyun
- Department of Computer Science and EngineeringMichigan State UniversityEast LansingMichiganUSA
| | - Yang Zhang
- Cancer Science Institute of SingaporeNational University of SingaporeSingaporeSingapore
- Department of Computer Science, School of ComputingNational University of SingaporeSingaporeSingapore
- Department of Biochemistry, Yong Loo Lin School of MedicineNational University of SingaporeSingaporeSingapore
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12
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Wang L, Sun F, Li Q, Ma H, Zhong J, Zhang H, Cheng S, Wu H, Zhao Y, Wang N, Xie Z, Zhao M, Zhu P, Zheng H. CytoSIP: an annotated structural atlas for interactions involving cytokines or cytokine receptors. Commun Biol 2024; 7:630. [PMID: 38789577 PMCID: PMC11126726 DOI: 10.1038/s42003-024-06289-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/23/2023] [Accepted: 05/03/2024] [Indexed: 05/26/2024] Open
Abstract
Therapeutic agents targeting cytokine-cytokine receptor (CK-CKR) interactions lead to the disruption in cellular signaling and are effective in treating many diseases including tumors. However, a lack of universal and quick access to annotated structural surface regions on CK/CKR has limited the progress of a structure-driven approach in developing targeted macromolecular drugs and precision medicine therapeutics. Herein we develop CytoSIP (Single nucleotide polymorphisms (SNPs), Interface, and Phenotype), a rich internet application based on a database of atomic interactions around hotspots in experimentally determined CK/CKR structural complexes. CytoSIP contains: (1) SNPs on CK/CKR; (2) interactions involving CK/CKR domains, including CK/CKR interfaces, oligomeric interfaces, epitopes, or other drug targeting surfaces; and (3) diseases and phenotypes associated with CK/CKR or SNPs. The database framework introduces a unique tri-level SIP data model to bridge genetic variants (atomic level) to disease phenotypes (organism level) using protein structure (complexes) as an underlying framework (molecule level). Customized screening tools are implemented to retrieve relevant CK/CKR subset, which reduces the time and resources needed to interrogate large datasets involving CK/CKR surface hotspots and associated pathologies. CytoSIP portal is publicly accessible at https://CytoSIP.biocloud.top , facilitating the panoramic investigation of the context-dependent crosstalk between CK/CKR and the development of targeted therapeutic agents.
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Affiliation(s)
- Lu Wang
- Bioinformatics Center, Hunan University College of Biology, Changsha, Hunan, 410082, China
- Guangdong Cardiovascular Institute, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, Guangdong, 510100, China
- Guangdong Provincial Key Laboratory of Pathogenesis, Targeted Prevention and Treatment of Heart Disease, Guangzhou Key Laboratory of Cardiac Pathogenesis and Prevention, Guangzhou, Guangdong, 510100, China
| | - Fang Sun
- Bioinformatics Center, Hunan University College of Biology, Changsha, Hunan, 410082, China
- Department of Pediatrics, The Third Xiangya Hospital, Central South University, Changsha, Hunan, 410006, China
| | - Qianying Li
- Bioinformatics Center, Hunan University College of Biology, Changsha, Hunan, 410082, China
| | - Haojie Ma
- Bioinformatics Center, Hunan University College of Biology, Changsha, Hunan, 410082, China
| | - Juanhong Zhong
- Bioinformatics Center, Hunan University College of Biology, Changsha, Hunan, 410082, China
| | - Huihui Zhang
- Bioinformatics Center, Hunan University College of Biology, Changsha, Hunan, 410082, China
| | - Siyi Cheng
- Guangdong Cardiovascular Institute, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, Guangdong, 510100, China
- Guangdong Provincial Key Laboratory of Pathogenesis, Targeted Prevention and Treatment of Heart Disease, Guangzhou Key Laboratory of Cardiac Pathogenesis and Prevention, Guangzhou, Guangdong, 510100, China
| | - Hao Wu
- Guangdong Cardiovascular Institute, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, Guangdong, 510100, China
- Guangdong Provincial Key Laboratory of Pathogenesis, Targeted Prevention and Treatment of Heart Disease, Guangzhou Key Laboratory of Cardiac Pathogenesis and Prevention, Guangzhou, Guangdong, 510100, China
| | - Yanmin Zhao
- Bioinformatics Center, Hunan University College of Biology, Changsha, Hunan, 410082, China
| | - Nasui Wang
- Division of Endocrinology and Metabolism, The First Affiliated Hospital of Shantou University Medical College, No. 57 Changping Road, Shantou, 515041, China
| | - Zhongqiu Xie
- Department of Pathology, School of Medicine, University of Virginia, Charlottesville, VA, 22908, USA
| | - Mingyi Zhao
- Department of Pediatrics, The Third Xiangya Hospital, Central South University, Changsha, Hunan, 410006, China.
| | - Ping Zhu
- Guangdong Cardiovascular Institute, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, Guangdong, 510100, China.
- Guangdong Provincial Key Laboratory of Pathogenesis, Targeted Prevention and Treatment of Heart Disease, Guangzhou Key Laboratory of Cardiac Pathogenesis and Prevention, Guangzhou, Guangdong, 510100, China.
| | - Heping Zheng
- Bioinformatics Center, Hunan University College of Biology, Changsha, Hunan, 410082, China.
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13
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Xia S, Li D, Deng X, Liu Z, Zhu H, Liu Y, Li D. Integration of protein sequence and protein-protein interaction data by hypergraph learning to identify novel protein complexes. Brief Bioinform 2024; 25:bbae274. [PMID: 38851299 PMCID: PMC11162299 DOI: 10.1093/bib/bbae274] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/22/2024] [Revised: 05/22/2024] [Accepted: 05/24/2024] [Indexed: 06/10/2024] Open
Abstract
Protein-protein interactions (PPIs) are the basis of many important biological processes, with protein complexes being the key forms implementing these interactions. Understanding protein complexes and their functions is critical for elucidating mechanisms of life processes, disease diagnosis and treatment and drug development. However, experimental methods for identifying protein complexes have many limitations. Therefore, it is necessary to use computational methods to predict protein complexes. Protein sequences can indicate the structure and biological functions of proteins, while also determining their binding abilities with other proteins, influencing the formation of protein complexes. Integrating these characteristics to predict protein complexes is very promising, but currently there is no effective framework that can utilize both protein sequence and PPI network topology for complex prediction. To address this challenge, we have developed HyperGraphComplex, a method based on hypergraph variational autoencoder that can capture expressive features from protein sequences without feature engineering, while also considering topological properties in PPI networks, to predict protein complexes. Experiment results demonstrated that HyperGraphComplex achieves satisfactory predictive performance when compared with state-of-art methods. Further bioinformatics analysis shows that the predicted protein complexes have similar attributes to known ones. Moreover, case studies corroborated the remarkable predictive capability of our model in identifying protein complexes, including 3 that were not only experimentally validated by recent studies but also exhibited high-confidence structural predictions from AlphaFold-Multimer. We believe that the HyperGraphComplex algorithm and our provided proteome-wide high-confidence protein complex prediction dataset will help elucidate how proteins regulate cellular processes in the form of complexes, and facilitate disease diagnosis and treatment and drug development. Source codes are available at https://github.com/LiDlab/HyperGraphComplex.
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Affiliation(s)
- Simin Xia
- School of Basic Medical Sciences, Anhui Medical University, 81 Meishan Road, Shushan District, Hefei 230032, China
- State Key Laboratory of Medical Proteomics, Beijing Proteome Research Center, National Center for Protein Sciences (Beijing), Beijing Institute of Lifeomics, 38 Life Science Park, Changping District, Beijing 102206, China
| | - Dianke Li
- State Key Laboratory of Medical Proteomics, Beijing Proteome Research Center, National Center for Protein Sciences (Beijing), Beijing Institute of Lifeomics, 38 Life Science Park, Changping District, Beijing 102206, China
- State Key Laboratory of Farm Animal Biotech Breeding, College of Biological Sciences, China Agricultural University, 2 Yuanmingyuan West Road, Haidian District, Beijing 100193, China
| | - Xinru Deng
- State Key Laboratory of Medical Proteomics, Beijing Proteome Research Center, National Center for Protein Sciences (Beijing), Beijing Institute of Lifeomics, 38 Life Science Park, Changping District, Beijing 102206, China
| | - Zhongyang Liu
- State Key Laboratory of Medical Proteomics, Beijing Proteome Research Center, National Center for Protein Sciences (Beijing), Beijing Institute of Lifeomics, 38 Life Science Park, Changping District, Beijing 102206, China
| | - Huaqing Zhu
- School of Basic Medical Sciences, Anhui Medical University, 81 Meishan Road, Shushan District, Hefei 230032, China
| | - Yuan Liu
- State Key Laboratory of Medical Proteomics, Beijing Proteome Research Center, National Center for Protein Sciences (Beijing), Beijing Institute of Lifeomics, 38 Life Science Park, Changping District, Beijing 102206, China
| | - Dong Li
- School of Basic Medical Sciences, Anhui Medical University, 81 Meishan Road, Shushan District, Hefei 230032, China
- State Key Laboratory of Medical Proteomics, Beijing Proteome Research Center, National Center for Protein Sciences (Beijing), Beijing Institute of Lifeomics, 38 Life Science Park, Changping District, Beijing 102206, China
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14
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Kavčič L, Ilc G, Wang B, Vlahoviček-Kahlina K, Jerić I, Plavec J. α-Hydrazino Acid Insertion Governs Peptide Organization in Solution by Local Structure Ordering. ACS OMEGA 2024; 9:22175-22185. [PMID: 38799301 PMCID: PMC11112695 DOI: 10.1021/acsomega.4c00804] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 01/24/2024] [Revised: 04/18/2024] [Accepted: 04/29/2024] [Indexed: 05/29/2024]
Abstract
In this work, we have applied the concept of α-hydrazino acid insertion in a peptide sequence as a means of structurally organizing a potential protein-protein interactions (PPI) inhibitor. Hydrazino peptides characterized by the incorporation of an α-hydrazino acid at specific positions introduce an additional nitrogen atom into their backbone. This modification leads to a change in the electrostatic properties of the peptide and induces the restructuring of its hydrogen bonding network, resulting in conformational changes toward more stable structural motifs. Despite the successful use of synthetic hydrazino oligomers in binding to nucleic acids, the structural changes due to the incorporation of α-hydrazino acid into short natural peptides in solution are still poorly understood. Based on NMR data, we report structural models of p53-derived hydrazino peptides with elements of localized peptide structuring in the form of an α-, β-, or γ-turn as a result of hydrazino modification in the peptide backbone. The modifications could potentially lead to the preorganization of a helical secondary peptide structure in a solution that is favorable for binding to a biological receptor. Spectroscopically, we observed that the ensemble averaged rapidly interconverting conformations, including isomerization of the E-Z hydrazide bond. This further increases the adaptability by expanding the conformational space of hydrazine peptides as potential protein-protein interaction antagonists.
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Affiliation(s)
- Luka Kavčič
- Slovenian
NMR Centre, National Institute of Chemistry, Ljubljana 1000, Slovenia
| | - Gregor Ilc
- Slovenian
NMR Centre, National Institute of Chemistry, Ljubljana 1000, Slovenia
- EN-FIST
Centre of Excellence, Ljubljana 1000, Slovenia
| | - Baifan Wang
- Slovenian
NMR Centre, National Institute of Chemistry, Ljubljana 1000, Slovenia
| | | | - Ivanka Jerić
- Division
of Organic Chemistry and Biochemistry, Rudjer
Bošković Institute, Zagreb 10000, Croatia
| | - Janez Plavec
- Slovenian
NMR Centre, National Institute of Chemistry, Ljubljana 1000, Slovenia
- EN-FIST
Centre of Excellence, Ljubljana 1000, Slovenia
- Faculty
of Chemistry and Chemical Technology, University
of Ljubljana, Ljubljana 1000, Slovenia
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15
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Liu JX, Zhang X, Huang YQ, Hao GF, Yang GF. Multi-level bioinformatics resources support drug target discovery of protein-protein interactions. Drug Discov Today 2024; 29:103979. [PMID: 38608830 DOI: 10.1016/j.drudis.2024.103979] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/12/2024] [Revised: 03/14/2024] [Accepted: 04/05/2024] [Indexed: 04/14/2024]
Abstract
Drug discovery often begins with a new target. Protein-protein interactions (PPIs) are crucial to multitudinous cellular processes and offer a promising avenue for drug-target discovery. PPIs are characterized by multi-level complexity: at the protein level, interaction networks can be used to identify potential targets, whereas at the residue level, the details of the interactions of individual PPIs can be used to examine a target's druggability. Much great progress has been made in target discovery through multi-level PPI-related computational approaches, but these resources have not been fully discussed. Here, we systematically survey bioinformatics tools for identifying and assessing potential drug targets, examining their characteristics, limitations and applications. This work will aid the integration of the broader protein-to-network context with the analysis of detailed binding mechanisms to support the discovery of drug targets.
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Affiliation(s)
- Jia-Xin Liu
- National Key Laboratory of Green Pesticide, Key Laboratory of Pesticide & Chemical Biology, Ministry of Education, International Joint Research Center for Intelligent Biosensor Technology and Health, Central China Normal University, Wuhan 430079, PR China
| | - Xiao Zhang
- State Key Laboratory of Green Pesticide, Key Laboratory of Green Pesticide and Agricultural Bioengineering, Ministry of Education, Center for R&D of Fine Chemicals, Guizhou University, Guiyang 550025, PR China
| | - Yuan-Qin Huang
- State Key Laboratory of Green Pesticide, Key Laboratory of Green Pesticide and Agricultural Bioengineering, Ministry of Education, Center for R&D of Fine Chemicals, Guizhou University, Guiyang 550025, PR China
| | - Ge-Fei Hao
- National Key Laboratory of Green Pesticide, Key Laboratory of Pesticide & Chemical Biology, Ministry of Education, International Joint Research Center for Intelligent Biosensor Technology and Health, Central China Normal University, Wuhan 430079, PR China; State Key Laboratory of Green Pesticide, Key Laboratory of Green Pesticide and Agricultural Bioengineering, Ministry of Education, Center for R&D of Fine Chemicals, Guizhou University, Guiyang 550025, PR China.
| | - Guang-Fu Yang
- National Key Laboratory of Green Pesticide, Key Laboratory of Pesticide & Chemical Biology, Ministry of Education, International Joint Research Center for Intelligent Biosensor Technology and Health, Central China Normal University, Wuhan 430079, PR China.
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16
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Yuan Q, Tian C, Yang Y. Genome-scale annotation of protein binding sites via language model and geometric deep learning. eLife 2024; 13:RP93695. [PMID: 38630609 PMCID: PMC11023698 DOI: 10.7554/elife.93695] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/19/2024] Open
Abstract
Revealing protein binding sites with other molecules, such as nucleic acids, peptides, or small ligands, sheds light on disease mechanism elucidation and novel drug design. With the explosive growth of proteins in sequence databases, how to accurately and efficiently identify these binding sites from sequences becomes essential. However, current methods mostly rely on expensive multiple sequence alignments or experimental protein structures, limiting their genome-scale applications. Besides, these methods haven't fully explored the geometry of the protein structures. Here, we propose GPSite, a multi-task network for simultaneously predicting binding residues of DNA, RNA, peptide, protein, ATP, HEM, and metal ions on proteins. GPSite was trained on informative sequence embeddings and predicted structures from protein language models, while comprehensively extracting residual and relational geometric contexts in an end-to-end manner. Experiments demonstrate that GPSite substantially surpasses state-of-the-art sequence-based and structure-based approaches on various benchmark datasets, even when the structures are not well-predicted. The low computational cost of GPSite enables rapid genome-scale binding residue annotations for over 568,000 sequences, providing opportunities to unveil unexplored associations of binding sites with molecular functions, biological processes, and genetic variants. The GPSite webserver and annotation database can be freely accessed at https://bio-web1.nscc-gz.cn/app/GPSite.
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Affiliation(s)
- Qianmu Yuan
- School of Computer Science and Engineering, Sun Yat-sen UniversityGuangzhouChina
| | - Chong Tian
- School of Computer Science and Engineering, Sun Yat-sen UniversityGuangzhouChina
| | - Yuedong Yang
- School of Computer Science and Engineering, Sun Yat-sen UniversityGuangzhouChina
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17
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Obermann R, Yemane B, Jarvis C, Franco FM, Kyriukha Y, Nolan W, Gohara B, Krezel AM, Wildman SA, Janetka JW. Small Molecule Antagonists of the DNA Repair ERCC1/XPA Protein-Protein Interaction. ChemMedChem 2024; 19:e202300648. [PMID: 38300970 PMCID: PMC11031295 DOI: 10.1002/cmdc.202300648] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/20/2023] [Revised: 01/31/2024] [Accepted: 02/01/2024] [Indexed: 02/03/2024]
Abstract
The DNA excision repair protein ERCC1 and the DNA damage sensor protein, XPA are highly overexpressed in patient samples of cisplatin-resistant solid tumors including lung, bladder, ovarian, and testicular cancer. The repair of cisplatin-DNA crosslinks is dependent upon nucleotide excision repair (NER) that is modulated by protein-protein binding interactions of ERCC1, the endonuclease, XPF, and XPA. Thus, inhibition of their function is a potential therapeutic strategy for the selective sensitization of tumors to DNA-damaging platinum-based cancer therapy. Here, we report on new small-molecule antagonists of the ERCC1/XPA protein-protein interaction (PPI) discovered using a high-throughput competitive fluorescence polarization binding assay. We discovered a unique structural class of thiopyridine-3-carbonitrile PPI antagonists that block a truncated XPA polypeptide from binding to ERCC1. Preliminary hit-to-lead studies from compound 1 reveal structure-activity relationships (SAR) and identify lead compound 27 o with an EC50 of 4.7 μM. Furthermore, chemical shift perturbation mapping by NMR confirms that 1 binds within the same site as the truncated XPA67-80 peptide. These novel ERCC1 antagonists are useful chemical biology tools for investigating DNA damage repair pathways and provide a good starting point for medicinal chemistry optimization as therapeutics for sensitizing tumors to DNA damaging agents and overcoming resistance to platinum-based chemotherapy.
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Affiliation(s)
| | | | - Cassie Jarvis
- Washington University School of Medicine, Department of Biochemistry and Molecular Biophysics, 660 S. Euclid Ave., Box 8231, St. Louis, MO 63110 USA
| | - Francisco M. Franco
- Washington University School of Medicine, Department of Biochemistry and Molecular Biophysics, 660 S. Euclid Ave., Box 8231, St. Louis, MO 63110 USA
| | - Yevhenii Kyriukha
- Washington University School of Medicine, Department of Biochemistry and Molecular Biophysics, 660 S. Euclid Ave., Box 8231, St. Louis, MO 63110 USA
| | - William Nolan
- Washington University School of Medicine, Department of Biochemistry and Molecular Biophysics, 660 S. Euclid Ave., Box 8231, St. Louis, MO 63110 USA
| | - Beth Gohara
- Washington University School of Medicine, Department of Biochemistry and Molecular Biophysics, 660 S. Euclid Ave., Box 8231, St. Louis, MO 63110 USA
| | - Andrzej M. Krezel
- Washington University School of Medicine, Department of Biochemistry and Molecular Biophysics, 660 S. Euclid Ave., Box 8231, St. Louis, MO 63110 USA
| | - Scott A. Wildman
- Washington University School of Medicine, Department of Biochemistry and Molecular Biophysics, 660 S. Euclid Ave., Box 8231, St. Louis, MO 63110 USA
| | - James W. Janetka
- Washington University School of Medicine, Department of Biochemistry and Molecular Biophysics, 660 S. Euclid Ave., Box 8231, St. Louis, MO 63110 USA
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18
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Bouvier B. Substituted Oligosaccharides as Protein Mimics: Deep Learning Free Energy Landscapes. J Chem Inf Model 2024; 64:2195-2204. [PMID: 37040394 DOI: 10.1021/acs.jcim.3c00179] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/12/2023]
Abstract
Protein-protein complexes power the majority of cellular processes. Interfering with the formation of such complexes using well-designed mimics is a difficult, yet actively pursued, research endeavor. Due to the limited availability of results on the conformational preferences of oligosaccharides compared to polypeptides, the former have been much less explored than the latter as protein mimics, despite interesting ADMET characteristics. In this work, the conformational landscapes of a series of 956 substituted glucopyranose oligomers of lengths 3 to 12 designed as protein interface mimics are revealed using microsecond-time-scale, enhanced-sampling molecular dynamics simulations. Deep convolutional networks are trained on these large conformational ensembles, to predict the stability of longer oligosaccharide structures from those of their constituent trimer motifs. Deep generative adversarial networks are then designed to suggest plausible conformations for oligosaccharide mimics of arbitrary length and substituent sequences that can subsequently be used as input to docking simulations. Analyzing the performance of the neural networks also yields insights into the intricate collective effects that dominate oligosaccharide conformational dynamics.
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Affiliation(s)
- Benjamin Bouvier
- Enzyme and Cell Engineering, CNRS UMR7025/Université de Picardie Jules Verne, 10, rue Baudelocque, 80039 Amiens Cedex, France
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19
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Zeng J, Loi GWZ, Saipuljumri EN, Romero Durán MA, Silva-García O, Perez-Aguilar JM, Baizabal-Aguirre VM, Lo CH. Peptide-based allosteric inhibitor targets TNFR1 conformationally active region and disables receptor-ligand signaling complex. Proc Natl Acad Sci U S A 2024; 121:e2308132121. [PMID: 38551841 PMCID: PMC10998571 DOI: 10.1073/pnas.2308132121] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/15/2023] [Accepted: 01/23/2024] [Indexed: 04/02/2024] Open
Abstract
Tumor necrosis factor (TNF) receptor 1 (TNFR1) plays a pivotal role in mediating TNF induced downstream signaling and regulating inflammatory response. Recent studies have suggested that TNFR1 activation involves conformational rearrangements of preligand assembled receptor dimers and targeting receptor conformational dynamics is a viable strategy to modulate TNFR1 signaling. Here, we used a combination of biophysical, biochemical, and cellular assays, as well as molecular dynamics simulation to show that an anti-inflammatory peptide (FKCRRWQWRMKK), which we termed FKC, inhibits TNFR1 activation allosterically by altering the conformational states of the receptor dimer without blocking receptor-ligand interaction or disrupting receptor dimerization. We also demonstrated the efficacy of FKC by showing that the peptide inhibits TNFR1 signaling in HEK293 cells and attenuates inflammation in mice with intraperitoneal TNF injection. Mechanistically, we found that FKC binds to TNFR1 cysteine-rich domains (CRD2/3) and perturbs the conformational dynamics required for receptor activation. Importantly, FKC increases the frequency in the opening of both CRD2/3 and CRD4 in the receptor dimer, as well as induces a conformational opening in the cytosolic regions of the receptor. This results in an inhibitory conformational state that impedes the recruitment of downstream signaling molecules. Together, these data provide evidence on the feasibility of targeting TNFR1 conformationally active region and open new avenues for receptor-specific inhibition of TNFR1 signaling.
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Affiliation(s)
- Jialiu Zeng
- Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore308232, Singapore
| | - Gavin Wen Zhao Loi
- Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore308232, Singapore
| | - Eka Norfaishanty Saipuljumri
- Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore308232, Singapore
- School of Applied Science, Republic Polytechnic, Singapore738964, Singapore
| | - Marco Antonio Romero Durán
- Centro Multidisciplinario de Estudios en Biotecnología, Facultad de Medicina Veterinaria y Zootecnia, Universidad Michoacana de San Nicolás de Hidalgo, Morelia58893, México
| | - Octavio Silva-García
- Centro Multidisciplinario de Estudios en Biotecnología, Facultad de Medicina Veterinaria y Zootecnia, Universidad Michoacana de San Nicolás de Hidalgo, Morelia58893, México
| | - Jose Manuel Perez-Aguilar
- School of Chemical Sciences, Meritorious Autonomous University of Puebla, University City, Puebla72570, México
| | - Víctor M. Baizabal-Aguirre
- Centro Multidisciplinario de Estudios en Biotecnología, Facultad de Medicina Veterinaria y Zootecnia, Universidad Michoacana de San Nicolás de Hidalgo, Morelia58893, México
| | - Chih Hung Lo
- Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore308232, Singapore
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20
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Jia P, Zhang F, Wu C, Li M. A comprehensive review of protein-centric predictors for biomolecular interactions: from proteins to nucleic acids and beyond. Brief Bioinform 2024; 25:bbae162. [PMID: 38739759 PMCID: PMC11089422 DOI: 10.1093/bib/bbae162] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/01/2024] [Revised: 02/17/2024] [Accepted: 03/31/2024] [Indexed: 05/16/2024] Open
Abstract
Proteins interact with diverse ligands to perform a large number of biological functions, such as gene expression and signal transduction. Accurate identification of these protein-ligand interactions is crucial to the understanding of molecular mechanisms and the development of new drugs. However, traditional biological experiments are time-consuming and expensive. With the development of high-throughput technologies, an increasing amount of protein data is available. In the past decades, many computational methods have been developed to predict protein-ligand interactions. Here, we review a comprehensive set of over 160 protein-ligand interaction predictors, which cover protein-protein, protein-nucleic acid, protein-peptide and protein-other ligands (nucleotide, heme, ion) interactions. We have carried out a comprehensive analysis of the above four types of predictors from several significant perspectives, including their inputs, feature profiles, models, availability, etc. The current methods primarily rely on protein sequences, especially utilizing evolutionary information. The significant improvement in predictions is attributed to deep learning methods. Additionally, sequence-based pretrained models and structure-based approaches are emerging as new trends.
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Affiliation(s)
- Pengzhen Jia
- School of Computer Science and Engineering, Central South University, 932 Lushan Road(S), Changsha 410083, China
| | - Fuhao Zhang
- School of Computer Science and Engineering, Central South University, 932 Lushan Road(S), Changsha 410083, China
- College of Information Engineering, Northwest A&F University, No. 3 Taicheng Road, Yangling, Shaanxi 712100, China
| | - Chaojin Wu
- School of Computer Science and Engineering, Central South University, 932 Lushan Road(S), Changsha 410083, China
| | - Min Li
- School of Computer Science and Engineering, Central South University, 932 Lushan Road(S), Changsha 410083, China
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21
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Li P, Mei C, Raza SHA, Cheng G, Ning Y, Zhang L, Zan L. Arginine (315) is required for the PLIN2-CGI-58 interface and plays a functional role in regulating nascent LDs formation in bovine adipocytes. Genomics 2024; 116:110817. [PMID: 38431031 DOI: 10.1016/j.ygeno.2024.110817] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/06/2023] [Revised: 02/02/2024] [Accepted: 02/28/2024] [Indexed: 03/05/2024]
Abstract
Perilipin-2 (PLIN2) can anchor to lipid droplets (LDs) and play a crucial role in regulating nascent LDs formation. Bimolecular fluorescence complementation (BiFC) and flow cytometry were examined to verify the PLIN2-CGI-58 interaction efficiency in bovine adipocytes. GST-Pulldown assay was used to detect the key site arginine315 function in PLIN2-CGI-58 interaction. Experiments were also examined to research these mutations function of PLIN2 in LDs formation during adipocytes differentiation, LDs were measured after staining by BODIPY, lipogenesis-related genes were also detected. Results showed that Leucine (L371A, L311A) and glycine (G369A, G376A) mutations reduced interaction efficiencies. Serine (S367A) mutations enhanced the interaction efficiency. Arginine (R315A) mutations resulted in loss of fluorescence in the cytoplasm and disrupted the interaction with CGI-58, as verified by pulldown assay. R315W mutations resulted in a significant increase in the number of LDs compared with wild-type (WT) PLIN2 or the R315A mutations. Lipogenesis-related genes were either up- or downregulated when mutated PLIN2 interacted with CGI-58. Arginine315 in PLIN2 is required for the PLIN2-CGI-58 interface and could regulate nascent LD formation and lipogenesis. This study is the first to study amino acids on the PLIN2 interface during interaction with CGI-58 in bovine and highlight the role played by PLIN2 in the regulation of bovine adipocyte lipogenesis.
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Affiliation(s)
- Peiwei Li
- Shaanxi Institute of Zoology, Xi'an, Shaanxi, 710032, China
| | - Chugang Mei
- College of Grassland Agriculture, Northwest A&F University, Yangling, Shaanxi 712100, China
| | - Sayed Haidar Abbas Raza
- Research Center for Machining and Safety of Livestock and Poultry Products, South China Agricultural University, Guangzhou 510642, China; College of Animal Science &Technology, Northwest A&F University, Yangling, Shaanxi 712100, China
| | - Gong Cheng
- College of Animal Science &Technology, Northwest A&F University, Yangling, Shaanxi 712100, China
| | - Yue Ning
- College of Animal Science &Technology, Northwest A&F University, Yangling, Shaanxi 712100, China
| | - Le Zhang
- School of Physical Education, Yan'an University, Yan'an, Shaanxi, 716000, China
| | - Linsen Zan
- College of Animal Science &Technology, Northwest A&F University, Yangling, Shaanxi 712100, China.
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22
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Sayin AZ, Abali Z, Senyuz S, Cankara F, Gursoy A, Keskin O. Conformational diversity and protein-protein interfaces in drug repurposing in Ras signaling pathway. Sci Rep 2024; 14:1239. [PMID: 38216592 PMCID: PMC10786864 DOI: 10.1038/s41598-023-50913-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/14/2023] [Accepted: 12/27/2023] [Indexed: 01/14/2024] Open
Abstract
We focus on drug repurposing in the Ras signaling pathway, considering structural similarities of protein-protein interfaces. The interfaces formed by physically interacting proteins are found from PDB if available and via PRISM (PRotein Interaction by Structural Matching) otherwise. The structural coverage of these interactions has been increased from 21 to 92% using PRISM. Multiple conformations of each protein are used to include protein dynamics and diversity. Next, we find FDA-approved drugs bound to structurally similar protein-protein interfaces. The results suggest that HIV protease inhibitors tipranavir, indinavir, and saquinavir may bind to EGFR and ERBB3/HER3 interface. Tipranavir and indinavir may also bind to EGFR and ERBB2/HER2 interface. Additionally, a drug used in Alzheimer's disease can bind to RAF1 and BRAF interface. Hence, we propose a methodology to find drugs to be potentially used for cancer using a dataset of structurally similar protein-protein interface clusters rather than pockets in a systematic way.
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Affiliation(s)
- Ahenk Zeynep Sayin
- Department of Chemical and Biological Engineering, College of Engineering, Koc University, Rumeli Feneri Yolu Sariyer, 34450, Istanbul, Turkey
| | - Zeynep Abali
- Graduate School of Science and Engineering, Computational Sciences and Engineering, Koc University, 34450, Istanbul, Turkey
| | - Simge Senyuz
- Graduate School of Science and Engineering, Computational Sciences and Engineering, Koc University, 34450, Istanbul, Turkey
| | - Fatma Cankara
- Graduate School of Science and Engineering, Computational Sciences and Engineering, Koc University, 34450, Istanbul, Turkey
| | - Attila Gursoy
- Department of Computer Engineering, Koc University, 34450, Istanbul, Turkey
| | - Ozlem Keskin
- Department of Chemical and Biological Engineering, College of Engineering, Koc University, Rumeli Feneri Yolu Sariyer, 34450, Istanbul, Turkey.
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23
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Pei J, Zhang J, Cong Q. Computational analysis of protein-protein interactions of cancer drivers in renal cell carcinoma. FEBS Open Bio 2024; 14:112-126. [PMID: 37964489 PMCID: PMC10761929 DOI: 10.1002/2211-5463.13732] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/16/2023] [Revised: 10/30/2023] [Accepted: 11/06/2023] [Indexed: 11/16/2023] Open
Abstract
Renal cell carcinoma (RCC) is the most common type of kidney cancer with rising cases in recent years. Extensive research has identified various cancer driver proteins associated with different subtypes of RCC. Most RCC drivers are encoded by tumor suppressor genes and exhibit enrichment in functional categories such as protein degradation, chromatin remodeling, and transcription. To further our understanding of RCC, we utilized powerful deep-learning methods based on AlphaFold to predict protein-protein interactions (PPIs) involving RCC drivers. We predicted high-confidence complexes formed by various RCC drivers, including TCEB1, KMT2C/D and KDM6A of the COMPASS-related complexes, TSC1 of the MTOR pathway, and TRRAP. These predictions provide valuable structural insights into the interaction interfaces, some of which are promising targets for cancer drug design, such as the NRF2-MAFK interface. Cancer somatic missense mutations from large datasets of genome sequencing of RCCs were mapped to the interfaces of predicted and experimental structures of PPIs involving RCC drivers, and their effects on the binding affinity were evaluated. We observed more than 100 cancer somatic mutations affecting the binding affinity of complexes formed by key RCC drivers such as VHL and TCEB1. These findings emphasize the importance of these mutations in RCC pathogenesis and potentially offer new avenues for targeted therapies.
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Affiliation(s)
- Jimin Pei
- Eugene McDermott Center for Human Growth and DevelopmentUniversity of Texas Southwestern Medical CenterDallasTXUSA
- Department of BiophysicsUniversity of Texas Southwestern Medical CenterDallasTXUSA
- Harold C. Simmons Comprehensive Cancer CenterUniversity of Texas Southwestern Medical CenterDallasTXUSA
| | - Jing Zhang
- Eugene McDermott Center for Human Growth and DevelopmentUniversity of Texas Southwestern Medical CenterDallasTXUSA
- Department of BiophysicsUniversity of Texas Southwestern Medical CenterDallasTXUSA
- Harold C. Simmons Comprehensive Cancer CenterUniversity of Texas Southwestern Medical CenterDallasTXUSA
| | - Qian Cong
- Eugene McDermott Center for Human Growth and DevelopmentUniversity of Texas Southwestern Medical CenterDallasTXUSA
- Department of BiophysicsUniversity of Texas Southwestern Medical CenterDallasTXUSA
- Harold C. Simmons Comprehensive Cancer CenterUniversity of Texas Southwestern Medical CenterDallasTXUSA
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24
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Rui M, Zhang W, Mi K, Ni H, Ji W, Yu X, Qin J, Feng C. Design and evaluation of α-helix-based peptide inhibitors for blocking PD-1/PD-L1 interaction. Int J Biol Macromol 2023; 253:126811. [PMID: 37690647 DOI: 10.1016/j.ijbiomac.2023.126811] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/19/2023] [Revised: 09/06/2023] [Accepted: 09/07/2023] [Indexed: 09/12/2023]
Abstract
The current research in tumor immunotherapy indicates that blocking the protein-protein interaction (PPI) between PD-1 and its ligand, PD-L1, may be one of the most effective treatments for cancer patients. The α-helix is a common elements of protein secondary structure and is often involved in protein interaction. Thus, α-helix-based peptides could mimic proteins involved in such interactions and are also capable of modulating PPI in vivo. In this study, starting from a potential α-helix-rich protein, we designed a series of α-helix-based peptide candidates to block PD-1/PD-L1 interaction. These candidates were first screened using molecular docking and molecular dynamics simulations, and then their capacities to inhibit PD-1/PD-L1 interactions and to restore antitumor immune activities were investigated using the HTRF assay, SPR assay, cellular co-culture experiments and animal model experiments. Two peptides exhibited the best anti-tumor effects and the strong ability to restore the immunity of tumor-infiltrating T-cells. Further D-amino acid substitution was employed to improve the serum stability of peptide candidate, making the intravenous administration easier while maintaining the therapeutic efficacy. The resultant peptides showed promise as checkpoint inhibitors for application in tumor immunotherapy. These findings suggested that our strategy for developing peptides starting from an α-helical structure could be used in the design of bioactive inhibitors to potential block protein-protein interactions.
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Affiliation(s)
- Mengjie Rui
- Department of Pharmaceutics, School of Pharmacy, Jiangsu University, Zhenjiang, PR China
| | - Wen Zhang
- Department of Pharmaceutics, School of Pharmacy, Jiangsu University, Zhenjiang, PR China
| | - Ke Mi
- Department of Pharmaceutics, School of Pharmacy, Jiangsu University, Zhenjiang, PR China
| | - Hairong Ni
- Department of Pharmaceutics, School of Pharmacy, Jiangsu University, Zhenjiang, PR China
| | - Wei Ji
- Department of Pharmaceutics, School of Pharmacy, Jiangsu University, Zhenjiang, PR China
| | - Xuefei Yu
- Zhejiang Cancer Hospital, Hangzhou Institute of Medicine (HIM), Chinese Academy of Sciences, Key Laboratory of Head & Neck Cancer Translational Research of Zhejiang Province, Hangzhou, PR China
| | - Jiangjiang Qin
- Institute of Basic Medicine and Cancer (IBMC), Chinese Academy of Sciences, Hangzhou, PR China
| | - Chunlai Feng
- Department of Pharmaceutics, School of Pharmacy, Jiangsu University, Zhenjiang, PR China; Key Laboratory of Spine and Spinal Cord Injury Repair and Regeneration, Tongji University, Ministry of Education, Shanghai, PR China.
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25
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Roy C, Islam RNU, Banerjee S, Bandyopadhyay AK. Underlying features for the enhanced electrostatic strength of the extremophilic malate dehydrogenase interface salt-bridge compared to the mesophilic one. J Biomol Struct Dyn 2023:1-16. [PMID: 38147414 DOI: 10.1080/07391102.2023.2295972] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/13/2023] [Accepted: 10/20/2023] [Indexed: 12/28/2023]
Abstract
Malate dehydrogenase (MDH) exists in multimeric form in normal and extreme solvent conditions where residues of the interface are involved in specific interactions. The interface salt-bridge (ISB) and its microenvironment (ME) residues may have a crucial role in the stability and specificity of the interface. To gain insight into this, we have analyzed 218 ISBs from 42 interfaces of 15 crystal structures along with their sequences. Comparative analyses demonstrate that the ISB strength is ∼30 times greater in extremophilic cases than that of the normal one. To this end, the interface residue propensity, ISB design and pair selection, and ME-residue's types, i.e., type-I and type-II, are seen to be intrinsically involved. Although Type-I is a common type, Type-II appears to be extremophile-specific, where the net ME-residue count is much lower with an excessive net ME-energy contribution, which seems to be a novel interface compaction strategy. Furthermore, the interface strength can be enhanced by selecting the desired mutant from the net-energy profile of all possible mutations of an unfavorable ME-residue. The study that applies to other similar systems finds applications in protein-protein interaction and protein engineering.Communicated by Ramaswamy H. Sarma.
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Affiliation(s)
- Chittran Roy
- Department of Biotechnology, The University of Burdwan, Burdwan, West Bengal, India
- Faculty of Chemistry, Technion-Israel Institute of Technology, Haifa, Israel
| | | | - Sahini Banerjee
- Department of Biological Sciences, Indian Statistical Institute, Kolkata, West Bengal, India
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26
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Niazi SK, Mariam Z. Computer-Aided Drug Design and Drug Discovery: A Prospective Analysis. Pharmaceuticals (Basel) 2023; 17:22. [PMID: 38256856 PMCID: PMC10819513 DOI: 10.3390/ph17010022] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/10/2023] [Revised: 12/13/2023] [Accepted: 12/20/2023] [Indexed: 01/24/2024] Open
Abstract
In the dynamic landscape of drug discovery, Computer-Aided Drug Design (CADD) emerges as a transformative force, bridging the realms of biology and technology. This paper overviews CADDs historical evolution, categorization into structure-based and ligand-based approaches, and its crucial role in rationalizing and expediting drug discovery. As CADD advances, incorporating diverse biological data and ensuring data privacy become paramount. Challenges persist, demanding the optimization of algorithms and robust ethical frameworks. Integrating Machine Learning and Artificial Intelligence amplifies CADDs predictive capabilities, yet ethical considerations and scalability challenges linger. Collaborative efforts and global initiatives, exemplified by platforms like Open-Source Malaria, underscore the democratization of drug discovery. The convergence of CADD with personalized medicine offers tailored therapeutic solutions, though ethical dilemmas and accessibility concerns must be navigated. Emerging technologies like quantum computing, immersive technologies, and green chemistry promise to redefine the future of CADD. The trajectory of CADD, marked by rapid advancements, anticipates challenges in ensuring accuracy, addressing biases in AI, and incorporating sustainability metrics. This paper concludes by highlighting the need for proactive measures in navigating the ethical, technological, and educational frontiers of CADD to shape a healthier, brighter future in drug discovery.
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Affiliation(s)
| | - Zamara Mariam
- Centre for Health and Life Sciences, Coventry University, Coventry City CV1 5FB, UK
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27
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Patalano SD, Fuxman Bass P, Fuxman Bass JI. Transcription factors in the development and treatment of immune disorders. Transcription 2023:1-23. [PMID: 38100543 DOI: 10.1080/21541264.2023.2294623] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/13/2023] [Accepted: 12/08/2023] [Indexed: 12/17/2023] Open
Abstract
Immune function is highly controlled at the transcriptional level by the binding of transcription factors (TFs) to promoter and enhancer elements. Several TF families play major roles in immune gene expression, including NF-κB, STAT, IRF, AP-1, NRs, and NFAT, which trigger anti-pathogen responses, promote cell differentiation, and maintain immune system homeostasis. Aberrant expression, activation, or sequence of isoforms and variants of these TFs can result in autoimmune and inflammatory diseases as well as hematological and solid tumor cancers. For this reason, TFs have become attractive drug targets, even though most were previously deemed "undruggable" due to their lack of small molecule binding pockets and the presence of intrinsically disordered regions. However, several aspects of TF structure and function can be targeted for therapeutic intervention, such as ligand-binding domains, protein-protein interactions between TFs and with cofactors, TF-DNA binding, TF stability, upstream signaling pathways, and TF expression. In this review, we provide an overview of each of the important TF families, how they function in immunity, and some related diseases they are involved in. Additionally, we discuss the ways of targeting TFs with drugs along with recent research developments in these areas and their clinical applications, followed by the advantages and disadvantages of targeting TFs for the treatment of immune disorders.
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Affiliation(s)
- Samantha D Patalano
- Biology Department, Boston University, Boston, MA, USA
- Molecular Biology, Cellular Biology and Biochemistry Program, Boston University, Boston, MA, USA
| | - Paula Fuxman Bass
- Facultad de Medicina, Universidad de Buenos Aires, Ciudad Autónoma de Buenos Aires, Argentina
| | - Juan I Fuxman Bass
- Biology Department, Boston University, Boston, MA, USA
- Molecular Biology, Cellular Biology and Biochemistry Program, Boston University, Boston, MA, USA
- Bioinformatics Program, Boston University, Boston, MA, USA
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28
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Sun H, Wang J, Wu H, Lin S, Chen J, Wei J, Lv S, Xiong Y, Wei DQ. A Multimodal Deep Learning Framework for Predicting PPI-Modulator Interactions. J Chem Inf Model 2023; 63:7363-7372. [PMID: 38037990 DOI: 10.1021/acs.jcim.3c01527] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/02/2023]
Abstract
Protein-protein interactions (PPIs) are essential for various biological processes and diseases. However, most existing computational methods for identifying PPI modulators require either target structure or reference modulators, which restricts their applicability to novel PPI targets. To address this challenge, we propose MultiPPIMI, a sequence-based deep learning framework that predicts the interaction between any given PPI target and modulator. MultiPPIMI integrates multimodal representations of PPI targets and modulators and uses a bilinear attention network to capture intermolecular interactions. Experimental results on our curated benchmark data set show that MultiPPIMI achieves an average AUROC of 0.837 in three cold-start scenarios and an AUROC of 0.994 in the random-split scenario. Furthermore, the case study shows that MultiPPIMI can assist molecular docking simulations in screening inhibitors of Keap1/Nrf2 PPI interactions. We believe that the proposed method provides a promising way to screen PPI-targeted modulators.
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Affiliation(s)
- Heqi Sun
- State Key Laboratory of Microbial Metabolism, Shanghai-Islamabad-Belgrade Joint Innovation Center on Antibacterial Resistances, Joint International Research Laboratory of Metabolic & Developmental Sciences and School of Life Sciences and Biotechnology, Shanghai Jiao Tong University, Shanghai 200240, China
| | - Jianmin Wang
- The Interdisciplinary Graduate Program in Integrative Biotechnology and Translational Medicine, Yonsei University, Incheon 21983, Republic of Korea
| | - Hongyan Wu
- Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, China
| | - Shenggeng Lin
- State Key Laboratory of Microbial Metabolism, Shanghai-Islamabad-Belgrade Joint Innovation Center on Antibacterial Resistances, Joint International Research Laboratory of Metabolic & Developmental Sciences and School of Life Sciences and Biotechnology, Shanghai Jiao Tong University, Shanghai 200240, China
| | - Junwei Chen
- State Key Laboratory of Microbial Metabolism, Shanghai-Islamabad-Belgrade Joint Innovation Center on Antibacterial Resistances, Joint International Research Laboratory of Metabolic & Developmental Sciences and School of Life Sciences and Biotechnology, Shanghai Jiao Tong University, Shanghai 200240, China
| | - Jinghua Wei
- Department of Chemistry, University of Toronto, Toronto M5R 0A3, Canada
| | - Shuai Lv
- State Key Laboratory of Microbial Metabolism, Shanghai-Islamabad-Belgrade Joint Innovation Center on Antibacterial Resistances, Joint International Research Laboratory of Metabolic & Developmental Sciences and School of Life Sciences and Biotechnology, Shanghai Jiao Tong University, Shanghai 200240, China
| | - Yi Xiong
- State Key Laboratory of Microbial Metabolism, Shanghai-Islamabad-Belgrade Joint Innovation Center on Antibacterial Resistances, Joint International Research Laboratory of Metabolic & Developmental Sciences and School of Life Sciences and Biotechnology, Shanghai Jiao Tong University, Shanghai 200240, China
- Shanghai Artificial Intelligence Laboratory, Shanghai 200232, China
| | - Dong-Qing Wei
- State Key Laboratory of Microbial Metabolism, Shanghai-Islamabad-Belgrade Joint Innovation Center on Antibacterial Resistances, Joint International Research Laboratory of Metabolic & Developmental Sciences and School of Life Sciences and Biotechnology, Shanghai Jiao Tong University, Shanghai 200240, China
- Peng Cheng National Laboratory, Shenzhen 518055, China
- Zhongjing Research and Industrialization Institute of Chinese Medicine, Nanyang 473006, China
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29
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Mi T, Siriwibool S, Burgess K. Streamlined Protein-Protein Interface Loop Mimicry. Angew Chem Int Ed Engl 2023; 62:e202307092. [PMID: 37849440 DOI: 10.1002/anie.202307092] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/01/2023] [Revised: 10/12/2023] [Accepted: 10/17/2023] [Indexed: 10/19/2023]
Abstract
Cyclic peptides comprising endocyclic organic fragments, "cyclo-organopeptides", can be probes for perturbing protein-protein interactions (PPIs). Finding loop mimics is difficult because of high conformational variability amongst targets. Backbone Matching (BM), introduced here, helps solve this problem in the illustrative cases by facilitating efficient evaluation of virtual cyclo-organopeptide core-structure libraries. Thus, 86 rigid organic fragments were selected to build a library of 602 cyclo-organopeptides comprising Ala and organic parts: "cyclo-{-(Ala)n -organo-}". The central hypothesis is "hit" library members have accessible low energy conformers corresponding to backbone structures of target protein loops, while library members which cannot attain this conformation are probably unworthy of further evaluation. BM thereby prioritizes candidate loop mimics, so that less than 10 cyclo-organopeptides are needed to be prepared to find leads for two illustrative PPIs: iNOS ⋅ SPSB2, and uPA ⋅ uPAR.
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Affiliation(s)
- Tianxiong Mi
- Department of Chemistry, Texas A & M University, 77842, College Station, TX, USA
| | - Siriwalee Siriwibool
- School of Chemistry, Institute of Science, Suranaree University of Technology, 30000, Nakhon Ratchasima, Thailand
| | - Kevin Burgess
- Department of Chemistry, Texas A & M University, 77842, College Station, TX, USA
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30
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Fang Y, Jiang Y, Wei L, Ma Q, Ren Z, Yuan Q, Wei DQ. DeepProSite: structure-aware protein binding site prediction using ESMFold and pretrained language model. Bioinformatics 2023; 39:btad718. [PMID: 38015872 PMCID: PMC10723037 DOI: 10.1093/bioinformatics/btad718] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/21/2023] [Revised: 11/04/2023] [Accepted: 11/27/2023] [Indexed: 11/30/2023] Open
Abstract
MOTIVATION Identifying the functional sites of a protein, such as the binding sites of proteins, peptides, or other biological components, is crucial for understanding related biological processes and drug design. However, existing sequence-based methods have limited predictive accuracy, as they only consider sequence-adjacent contextual features and lack structural information. RESULTS In this study, DeepProSite is presented as a new framework for identifying protein binding site that utilizes protein structure and sequence information. DeepProSite first generates protein structures from ESMFold and sequence representations from pretrained language models. It then uses Graph Transformer and formulates binding site predictions as graph node classifications. In predicting protein-protein/peptide binding sites, DeepProSite outperforms state-of-the-art sequence- and structure-based methods on most metrics. Moreover, DeepProSite maintains its performance when predicting unbound structures, in contrast to competing structure-based prediction methods. DeepProSite is also extended to the prediction of binding sites for nucleic acids and other ligands, verifying its generalization capability. Finally, an online server for predicting multiple types of residue is established as the implementation of the proposed DeepProSite. AVAILABILITY AND IMPLEMENTATION The datasets and source codes can be accessed at https://github.com/WeiLab-Biology/DeepProSite. The proposed DeepProSite can be accessed at https://inner.wei-group.net/DeepProSite/.
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Affiliation(s)
- Yitian Fang
- State Key Laboratory of Microbial Metabolism, Shanghai-Islamabad-Belgrade Joint Innovation Center on Antibacterial Resistances, Joint International Research Laboratory of Metabolic & Developmental Sciences and School of Life Sciences and Biotechnology, Shanghai Jiao Tong University, Shanghai 200040, China
- Peng Cheng Laboratory, Shenzhen 518055, China
| | - Yi Jiang
- Department of Biomedical Informatics, College of Medicine, The Ohio State University, Columbus, OH 43210, USA
| | - Leyi Wei
- School of Software, Shandong University, Jinan, Shandong 250100, China
| | - Qin Ma
- Department of Biomedical Informatics, College of Medicine, The Ohio State University, Columbus, OH 43210, USA
| | | | - Qianmu Yuan
- School of Computer Science and Engineering, Sun Yat-sen University, Guangzhou 510000, China
| | - Dong-Qing Wei
- State Key Laboratory of Microbial Metabolism, Shanghai-Islamabad-Belgrade Joint Innovation Center on Antibacterial Resistances, Joint International Research Laboratory of Metabolic & Developmental Sciences and School of Life Sciences and Biotechnology, Shanghai Jiao Tong University, Shanghai 200040, China
- Peng Cheng Laboratory, Shenzhen 518055, China
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Khramtsov YV, Ulasov AV, Slastnikova TA, Rosenkranz AA, Lupanova TN, Georgiev GP, Sobolev AS. Modular Nanotransporters Delivering Biologically Active Molecules to the Surface of Mitochondria. Pharmaceutics 2023; 15:2687. [PMID: 38140028 PMCID: PMC10748074 DOI: 10.3390/pharmaceutics15122687] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/06/2023] [Revised: 11/23/2023] [Accepted: 11/24/2023] [Indexed: 12/24/2023] Open
Abstract
Treatment of various diseases, in particular cancer, usually requires the targeting of biologically active molecules at a selected subcellular compartment. We modified our previously developed modular nanotransporters (MNTs) for targeting mitochondria. The new MNTs are capable of binding to the protein predominantly localized on the outer mitochondrial membrane, Keap1. These MNTs possessing antiKeap1 monobody co-localize with mitochondria upon addition to the cells. They efficiently interact with Keap1 both in solution and within living cells. A conjugate of the MNT with a photosensitizer, chlorin e6, demonstrated significantly higher photocytotoxicity than chlorin e6 alone. We assume that MNTs of this kind can improve efficiency of therapeutic photosensitizers and radionuclides emitting short-range particles.
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Affiliation(s)
- Yuri V. Khramtsov
- Laboratory of Molecular Genetics of Intracellular Transport, Institute of Gene Biology of Russian Academy of Sciences, 34/5 Vavilov St., 119334 Moscow, Russia; (Y.V.K.); (A.V.U.); (T.A.S.); (A.A.R.); (T.N.L.); (G.P.G.)
| | - Alexey V. Ulasov
- Laboratory of Molecular Genetics of Intracellular Transport, Institute of Gene Biology of Russian Academy of Sciences, 34/5 Vavilov St., 119334 Moscow, Russia; (Y.V.K.); (A.V.U.); (T.A.S.); (A.A.R.); (T.N.L.); (G.P.G.)
| | - Tatiana A. Slastnikova
- Laboratory of Molecular Genetics of Intracellular Transport, Institute of Gene Biology of Russian Academy of Sciences, 34/5 Vavilov St., 119334 Moscow, Russia; (Y.V.K.); (A.V.U.); (T.A.S.); (A.A.R.); (T.N.L.); (G.P.G.)
| | - Andrey A. Rosenkranz
- Laboratory of Molecular Genetics of Intracellular Transport, Institute of Gene Biology of Russian Academy of Sciences, 34/5 Vavilov St., 119334 Moscow, Russia; (Y.V.K.); (A.V.U.); (T.A.S.); (A.A.R.); (T.N.L.); (G.P.G.)
- Faculty of Biology, Lomonosov Moscow State University, 1-12 Leninskie Gory St., 119234 Moscow, Russia
| | - Tatiana N. Lupanova
- Laboratory of Molecular Genetics of Intracellular Transport, Institute of Gene Biology of Russian Academy of Sciences, 34/5 Vavilov St., 119334 Moscow, Russia; (Y.V.K.); (A.V.U.); (T.A.S.); (A.A.R.); (T.N.L.); (G.P.G.)
| | - Georgii P. Georgiev
- Laboratory of Molecular Genetics of Intracellular Transport, Institute of Gene Biology of Russian Academy of Sciences, 34/5 Vavilov St., 119334 Moscow, Russia; (Y.V.K.); (A.V.U.); (T.A.S.); (A.A.R.); (T.N.L.); (G.P.G.)
| | - Alexander S. Sobolev
- Laboratory of Molecular Genetics of Intracellular Transport, Institute of Gene Biology of Russian Academy of Sciences, 34/5 Vavilov St., 119334 Moscow, Russia; (Y.V.K.); (A.V.U.); (T.A.S.); (A.A.R.); (T.N.L.); (G.P.G.)
- Faculty of Biology, Lomonosov Moscow State University, 1-12 Leninskie Gory St., 119234 Moscow, Russia
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Lima MCP, Hornsby BD, Lim CS, Cheatham TE. Computational Modeling of Stapled Coiled-Coil Inhibitors Against Bcr-Abl: Toward a Treatment Strategy for CML. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.11.15.566894. [PMID: 38014060 PMCID: PMC10680756 DOI: 10.1101/2023.11.15.566894] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/29/2023]
Abstract
The chimeric oncoprotein Bcr-Abl is the causative agent of virtually all chronic myeloid leukemias (CML) and a subset of acute lymphoblastic leukemias (ALL). As a result of the so-called Philadelphia Chromosome translocation t(9;22), Bcr-Abl manifests as a constitutively active tyrosine kinase which promotes leukemogenesis by activation of cell cycle signaling pathways. Constitutive and oncogenic activation is mediated by an N-terminal coiled-coil oligomerization domain in Bcr (Bcr-CC), presenting a therapeutic target for inhibition of Bcr-Abl activity toward the treatment of Bcr-Abl+ leukemias. Previously, we demonstrated that a rationally designed Bcr-CC mutant, CCmut3, exerts a dominant negative effect upon Bcr-Abl activity by preferential oligomerization with Bcr-CC. Moreover, we have shown conjugation to a leukemia-specific cell-penetrating peptide (CPP-CCmut3) improves intracellular delivery and activity. However, our full-length CPP-CCmut3 construct (81 aa) is encumbered by an intrinsically high degree of conformational variability and susceptibility to proteolytic degradation, relative to traditional small molecule therapeutics. Here, we iterate a new generation of our inhibitor against Bcr-CC mediated Bcr-Abl assembly that is designed to address these constraints through incorporation of all-hydrocarbon staples spanning i, i + 7 positions in helix α2 (CPP-CCmut3-st). We utilize computational modeling and biomolecular simulation to design and characterize single and double staple candidates in silico, evaluating binding energetics and building upon our seminal work modeling single hydrocarbon staples when applied to a truncated Bcr-CC sequence. This strategy enables us to efficiently build, characterize, and screen lead single/double stapled CPP-CCmut3-st candidates for experimental studies and validation in vitro and in vivo. In addition to full-length CPP-CCmut, we model a truncated system characterized by deletion of helix α1 and the flexible-loop linker, which are known to impart high conformational variability. To study the impact of the N-terminal cyclic CPP toward model stability and inhibitor activity, we also model the full-length and truncated systems without CPP, with cyclized CPP, and with linear CPP, for a total of six systems which comprise our library. From this library, we present lead stapled peptide candidates to be synthesized and evaluated experimentally as our next-generation inhibitors against Bcr-Abl.
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Affiliation(s)
- Maria Carolina P. Lima
- Department of Medicinal Chemistry, University of Utah, Salt Lake City, Utah 84112, United States
| | - Braxten D. Hornsby
- Department of Molecular Pharmaceutics, University of Utah, Salt Lake City, Utah 84112, United States
| | - Carol S. Lim
- Department of Molecular Pharmaceutics, University of Utah, Salt Lake City, Utah 84112, United States
| | - Thomas E. Cheatham
- Department of Medicinal Chemistry, University of Utah, Salt Lake City, Utah 84112, United States
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Troisi R, Balasco N, Autiero I, Vitagliano L, Sica F. Structural Insights into Protein-Aptamer Recognitions Emerged from Experimental and Computational Studies. Int J Mol Sci 2023; 24:16318. [PMID: 38003510 PMCID: PMC10671752 DOI: 10.3390/ijms242216318] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/20/2023] [Revised: 11/10/2023] [Accepted: 11/12/2023] [Indexed: 11/26/2023] Open
Abstract
Aptamers are synthetic nucleic acids that are developed to target with high affinity and specificity chemical entities ranging from single ions to macromolecules and present a wide range of chemical and physical properties. Their ability to selectively bind proteins has made these compounds very attractive and versatile tools, in both basic and applied sciences, to such an extent that they are considered an appealing alternative to antibodies. Here, by exhaustively surveying the content of the Protein Data Bank (PDB), we review the structural aspects of the protein-aptamer recognition process. As a result of three decades of structural studies, we identified 144 PDB entries containing atomic-level information on protein-aptamer complexes. Interestingly, we found a remarkable increase in the number of determined structures in the last two years as a consequence of the effective application of the cryo-electron microscopy technique to these systems. In the present paper, particular attention is devoted to the articulated architectures that protein-aptamer complexes may exhibit. Moreover, the molecular mechanism of the binding process was analyzed by collecting all available information on the structural transitions that aptamers undergo, from their protein-unbound to the protein-bound state. The contribution of computational approaches in this area is also highlighted.
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Affiliation(s)
- Romualdo Troisi
- Department of Chemical Sciences, University of Naples Federico II, 80126 Naples, Italy;
- Institute of Biostructures and Bioimaging, CNR, 80131 Naples, Italy;
| | - Nicole Balasco
- Institute of Molecular Biology and Pathology, CNR c/o Department of Chemistry, University of Rome Sapienza, 00185 Rome, Italy;
| | - Ida Autiero
- Institute of Biostructures and Bioimaging, CNR, 80131 Naples, Italy;
| | - Luigi Vitagliano
- Institute of Biostructures and Bioimaging, CNR, 80131 Naples, Italy;
| | - Filomena Sica
- Department of Chemical Sciences, University of Naples Federico II, 80126 Naples, Italy;
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Ohta A, Tanada M, Shinohara S, Morita Y, Nakano K, Yamagishi Y, Takano R, Kariyuki S, Iida T, Matsuo A, Ozeki K, Emura T, Sakurai Y, Takano K, Higashida A, Kojima M, Muraoka T, Takeyama R, Kato T, Kimura K, Ogawa K, Ohara K, Tanaka S, Kikuchi Y, Hisada N, Hayashi R, Nishimura Y, Nomura K, Tachibana T, Irie M, Kawada H, Torizawa T, Murao N, Kotake T, Tanaka M, Ishikawa S, Miyake T, Tamiya M, Arai M, Chiyoda A, Akai S, Sase H, Kuramoto S, Ito T, Shiraishi T, Kojima T, Iikura H. Validation of a New Methodology to Create Oral Drugs beyond the Rule of 5 for Intracellular Tough Targets. J Am Chem Soc 2023; 145:24035-24051. [PMID: 37874670 DOI: 10.1021/jacs.3c07145] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/26/2023]
Abstract
Establishing a technological platform for creating clinical compounds inhibiting intracellular protein-protein interactions (PPIs) can open the door to many valuable drugs. Although small molecules and antibodies are mainstream modalities, they are not suitable for a target protein that lacks a deep cavity for a small molecule to bind or a protein found in intracellular space out of an antibody's reach. One possible approach to access these targets is to utilize so-called middle-size cyclic peptides (defined here as those with a molecular weight of 1000-2000 g/mol). In this study, we validated a new methodology to create oral drugs beyond the rule of 5 for intracellular tough targets by elucidating structural features and physicochemical properties for drug-like cyclic peptides and developing library technologies to afford highly N-alkylated cyclic peptide hits. We discovered a KRAS inhibitory clinical compound (LUNA18) as the first example of our platform technology.
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Affiliation(s)
- Atsushi Ohta
- Research Division, Chugai Pharmaceutical Co., Ltd., 216, Totsuka-cho,Totsuka-ku, Yokohama 244-8602, Kanagawa, Japan
| | - Mikimasa Tanada
- Research Division, Chugai Pharmaceutical Co., Ltd., 216, Totsuka-cho,Totsuka-ku, Yokohama 244-8602, Kanagawa, Japan
| | - Shojiro Shinohara
- Research Division, Chugai Pharmaceutical Co., Ltd., 216, Totsuka-cho,Totsuka-ku, Yokohama 244-8602, Kanagawa, Japan
| | - Yuya Morita
- Research Division, Chugai Pharmaceutical Co., Ltd., 216, Totsuka-cho,Totsuka-ku, Yokohama 244-8602, Kanagawa, Japan
| | - Kazuhiko Nakano
- Research Division, Chugai Pharmaceutical Co., Ltd., 216, Totsuka-cho,Totsuka-ku, Yokohama 244-8602, Kanagawa, Japan
| | - Yusuke Yamagishi
- Research Division, Chugai Pharmaceutical Co., Ltd., 216, Totsuka-cho,Totsuka-ku, Yokohama 244-8602, Kanagawa, Japan
| | - Ryusuke Takano
- Research Division, Chugai Pharmaceutical Co., Ltd., 216, Totsuka-cho,Totsuka-ku, Yokohama 244-8602, Kanagawa, Japan
| | - Shiori Kariyuki
- Research Division, Chugai Pharmaceutical Co., Ltd., 216, Totsuka-cho,Totsuka-ku, Yokohama 244-8602, Kanagawa, Japan
| | - Takeo Iida
- Research Division, Chugai Pharmaceutical Co., Ltd., 216, Totsuka-cho,Totsuka-ku, Yokohama 244-8602, Kanagawa, Japan
| | - Atsushi Matsuo
- Research Division, Chugai Pharmaceutical Co., Ltd., 216, Totsuka-cho,Totsuka-ku, Yokohama 244-8602, Kanagawa, Japan
| | - Kazuhisa Ozeki
- Research Division, Chugai Pharmaceutical Co., Ltd., 216, Totsuka-cho,Totsuka-ku, Yokohama 244-8602, Kanagawa, Japan
| | - Takashi Emura
- Research Division, Chugai Pharmaceutical Co., Ltd., 216, Totsuka-cho,Totsuka-ku, Yokohama 244-8602, Kanagawa, Japan
| | - Yuuji Sakurai
- Research Division, Chugai Pharmaceutical Co., Ltd., 216, Totsuka-cho,Totsuka-ku, Yokohama 244-8602, Kanagawa, Japan
| | - Koji Takano
- Research Division, Chugai Pharmaceutical Co., Ltd., 216, Totsuka-cho,Totsuka-ku, Yokohama 244-8602, Kanagawa, Japan
| | - Atsuko Higashida
- Research Division, Chugai Pharmaceutical Co., Ltd., 216, Totsuka-cho,Totsuka-ku, Yokohama 244-8602, Kanagawa, Japan
| | - Miki Kojima
- Research Division, Chugai Pharmaceutical Co., Ltd., 216, Totsuka-cho,Totsuka-ku, Yokohama 244-8602, Kanagawa, Japan
| | - Terushige Muraoka
- Research Division, Chugai Pharmaceutical Co., Ltd., 216, Totsuka-cho,Totsuka-ku, Yokohama 244-8602, Kanagawa, Japan
| | - Ryuuichi Takeyama
- Research Division, Chugai Pharmaceutical Co., Ltd., 216, Totsuka-cho,Totsuka-ku, Yokohama 244-8602, Kanagawa, Japan
| | - Tatsuya Kato
- Research Division, Chugai Pharmaceutical Co., Ltd., 216, Totsuka-cho,Totsuka-ku, Yokohama 244-8602, Kanagawa, Japan
| | - Kaori Kimura
- Research Division, Chugai Pharmaceutical Co., Ltd., 216, Totsuka-cho,Totsuka-ku, Yokohama 244-8602, Kanagawa, Japan
| | - Kotaro Ogawa
- Research Division, Chugai Pharmaceutical Co., Ltd., 216, Totsuka-cho,Totsuka-ku, Yokohama 244-8602, Kanagawa, Japan
| | - Kazuhiro Ohara
- Research Division, Chugai Pharmaceutical Co., Ltd., 216, Totsuka-cho,Totsuka-ku, Yokohama 244-8602, Kanagawa, Japan
| | - Shota Tanaka
- Research Division, Chugai Pharmaceutical Co., Ltd., 216, Totsuka-cho,Totsuka-ku, Yokohama 244-8602, Kanagawa, Japan
| | - Yasufumi Kikuchi
- Research Division, Chugai Pharmaceutical Co., Ltd., 216, Totsuka-cho,Totsuka-ku, Yokohama 244-8602, Kanagawa, Japan
| | - Nozomi Hisada
- Research Division, Chugai Pharmaceutical Co., Ltd., 216, Totsuka-cho,Totsuka-ku, Yokohama 244-8602, Kanagawa, Japan
| | - Ryuji Hayashi
- Research Division, Chugai Pharmaceutical Co., Ltd., 216, Totsuka-cho,Totsuka-ku, Yokohama 244-8602, Kanagawa, Japan
| | - Yoshikazu Nishimura
- Research Division, Chugai Pharmaceutical Co., Ltd., 216, Totsuka-cho,Totsuka-ku, Yokohama 244-8602, Kanagawa, Japan
| | - Kenichi Nomura
- Research Division, Chugai Pharmaceutical Co., Ltd., 216, Totsuka-cho,Totsuka-ku, Yokohama 244-8602, Kanagawa, Japan
| | - Tatsuhiko Tachibana
- Research Division, Chugai Pharmaceutical Co., Ltd., 216, Totsuka-cho,Totsuka-ku, Yokohama 244-8602, Kanagawa, Japan
| | - Machiko Irie
- Research Division, Chugai Pharmaceutical Co., Ltd., 216, Totsuka-cho,Totsuka-ku, Yokohama 244-8602, Kanagawa, Japan
| | - Hatsuo Kawada
- Research Division, Chugai Pharmaceutical Co., Ltd., 216, Totsuka-cho,Totsuka-ku, Yokohama 244-8602, Kanagawa, Japan
| | - Takuya Torizawa
- Research Division, Chugai Pharmaceutical Co., Ltd., 216, Totsuka-cho,Totsuka-ku, Yokohama 244-8602, Kanagawa, Japan
| | - Naoaki Murao
- Research Division, Chugai Pharmaceutical Co., Ltd., 216, Totsuka-cho,Totsuka-ku, Yokohama 244-8602, Kanagawa, Japan
| | - Tomoya Kotake
- Research Division, Chugai Pharmaceutical Co., Ltd., 216, Totsuka-cho,Totsuka-ku, Yokohama 244-8602, Kanagawa, Japan
| | - Masahiko Tanaka
- Research Division, Chugai Pharmaceutical Co., Ltd., 216, Totsuka-cho,Totsuka-ku, Yokohama 244-8602, Kanagawa, Japan
| | - Shiho Ishikawa
- Research Division, Chugai Pharmaceutical Co., Ltd., 216, Totsuka-cho,Totsuka-ku, Yokohama 244-8602, Kanagawa, Japan
| | - Taiji Miyake
- Research Division, Chugai Pharmaceutical Co., Ltd., 216, Totsuka-cho,Totsuka-ku, Yokohama 244-8602, Kanagawa, Japan
| | - Minoru Tamiya
- Research Division, Chugai Pharmaceutical Co., Ltd., 216, Totsuka-cho,Totsuka-ku, Yokohama 244-8602, Kanagawa, Japan
| | - Masako Arai
- Research Division, Chugai Pharmaceutical Co., Ltd., 216, Totsuka-cho,Totsuka-ku, Yokohama 244-8602, Kanagawa, Japan
| | - Aya Chiyoda
- Research Division, Chugai Pharmaceutical Co., Ltd., 216, Totsuka-cho,Totsuka-ku, Yokohama 244-8602, Kanagawa, Japan
| | - Sho Akai
- Research Division, Chugai Pharmaceutical Co., Ltd., 216, Totsuka-cho,Totsuka-ku, Yokohama 244-8602, Kanagawa, Japan
| | - Hitoshi Sase
- Research Division, Chugai Pharmaceutical Co., Ltd., 216, Totsuka-cho,Totsuka-ku, Yokohama 244-8602, Kanagawa, Japan
| | - Shino Kuramoto
- Research Division, Chugai Pharmaceutical Co., Ltd., 216, Totsuka-cho,Totsuka-ku, Yokohama 244-8602, Kanagawa, Japan
| | - Toshiya Ito
- Research Division, Chugai Pharmaceutical Co., Ltd., 216, Totsuka-cho,Totsuka-ku, Yokohama 244-8602, Kanagawa, Japan
| | - Takuya Shiraishi
- Research Division, Chugai Pharmaceutical Co., Ltd., 216, Totsuka-cho,Totsuka-ku, Yokohama 244-8602, Kanagawa, Japan
| | - Tetsuo Kojima
- Research Division, Chugai Pharmaceutical Co., Ltd., 216, Totsuka-cho,Totsuka-ku, Yokohama 244-8602, Kanagawa, Japan
| | - Hitoshi Iikura
- Research Division, Chugai Pharmaceutical Co., Ltd., 216, Totsuka-cho,Totsuka-ku, Yokohama 244-8602, Kanagawa, Japan
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Santos TG, Silva KS, Lima RM, Silva LC, Pereira M. State of the art in protein-protein interactions within the fungi kingdom. Future Microbiol 2023; 18:1119-1131. [PMID: 37540069 DOI: 10.2217/fmb-2022-0274] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 08/05/2023] Open
Abstract
Proteins rarely exert their function by themselves. Protein-protein interactions (PPIs) regulate virtually every biological process that takes place in a cell. Such interactions are targets for new therapeutic agents against all sorts of diseases, through the screening and design of a variety of inhibitors. Here we discuss several aspects of PPIs that contribute to prediction of protein function and drug discovery. As the high-throughput techniques continue to release biological data, targets for fungal therapeutics that rely on PPIs are being proposed worldwide. Computational approaches have reduced the time taken to develop new therapeutic approaches. The near future brings the possibility of developing new PPI and interaction network inhibitors and a revolution in the way we treat fungal diseases.
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Affiliation(s)
- Thaynara G Santos
- Laboratório de Biologia Molecular, Instituto de Ciências Biológicas, Universidade Federal de Goiás, Goiânia, Goiás, 74 000, Brazil
| | - Kleber Sf Silva
- Laboratório de Biologia Molecular, Instituto de Ciências Biológicas, Universidade Federal de Goiás, Goiânia, Goiás, 74 000, Brazil
| | - Raisa M Lima
- Laboratório de Biologia Molecular, Instituto de Ciências Biológicas, Universidade Federal de Goiás, Goiânia, Goiás, 74 000, Brazil
| | - Lívia C Silva
- Laboratório de Biologia Molecular, Instituto de Ciências Biológicas, Universidade Federal de Goiás, Goiânia, Goiás, 74 000, Brazil
| | - Maristela Pereira
- Laboratório de Biologia Molecular, Instituto de Ciências Biológicas, Universidade Federal de Goiás, Goiânia, Goiás, 74 000, Brazil
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36
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Deal PE, Lee H, Mondal A, Lolicato M, de Mendonca PRF, Black H, El-Hilali X, Bryant C, Isacoff EY, Renslo AR, Minor DL. Development of covalent chemogenetic K 2P channel activators. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.10.15.561774. [PMID: 37905049 PMCID: PMC10614804 DOI: 10.1101/2023.10.15.561774] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/02/2023]
Abstract
K2P potassium channels regulate excitability by affecting cellular resting membrane potential in the brain, cardiovascular system, immune cells, and sensory organs. Despite their important roles in anesthesia, arrhythmia, pain, hypertension, sleep, and migraine, the ability to control K2P function remains limited. Here, we describe a chemogenetic strategy termed CATKLAMP (Covalent Activation of TREK family K+ channels to cLAmp Membrane Potential) that leverages the discovery of a site in the K2P modulator pocket that reacts with electrophile-bearing derivatives of a TREK subfamily small molecule activator, ML335, to activate the channel irreversibly. We show that the CATKLAMP strategy can be used to probe fundamental aspects of K2P function, as a switch to silence neuronal firing, and is applicable to all TREK subfamily members. Together, our findings exemplify a new means to alter K2P channel activity that should facilitate studies both molecular and systems level studies of K2P function and enable the search for new K2P modulators.
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Affiliation(s)
- Parker E. Deal
- Cardiovascular Research Institute, University of California, San Francisco, California 93858-2330 USA
- Department of Pharmaceutical Chemistry, University of California, San Francisco, California 93858-2330 USA
| | - Haerim Lee
- Cardiovascular Research Institute, University of California, San Francisco, California 93858-2330 USA
| | - Abhisek Mondal
- Cardiovascular Research Institute, University of California, San Francisco, California 93858-2330 USA
| | - Marco Lolicato
- Cardiovascular Research Institute, University of California, San Francisco, California 93858-2330 USA
| | | | - Holly Black
- Department of Molecular and Cell Biology, University of California, Berkeley, Berkeley, California 94720, United States
| | - Xochina El-Hilali
- Department of Pharmaceutical Chemistry, University of California, San Francisco, California 93858-2330 USA
| | - Clifford Bryant
- Department of Pharmaceutical Chemistry, University of California, San Francisco, California 93858-2330 USA
| | - Ehud Y. Isacoff
- Department of Molecular and Cell Biology, University of California, Berkeley, Berkeley, California 94720, United States
- Helen Wills Neuroscience Institute, University of California, Berkeley, Berkeley, California 94720, United States
- Weill Neurohub, University of California, Berkeley, Berkeley, California 94720, United States
- Molecular Biophysics and Integrated Bio-imaging Division, Lawrence Berkeley National Laboratory, Berkeley, CA 94720 USA
| | - Adam R. Renslo
- Department of Pharmaceutical Chemistry, University of California, San Francisco, California 93858-2330 USA
| | - Daniel L. Minor
- Cardiovascular Research Institute, University of California, San Francisco, California 93858-2330 USA
- Molecular Biophysics and Integrated Bio-imaging Division, Lawrence Berkeley National Laboratory, Berkeley, CA 94720 USA
- Departments of Biochemistry and Biophysics, and Cellular and Molecular Pharmacology, University of California, San Francisco, California 93858-2330 USA
- California Institute for Quantitative Biomedical Research, University of California, San Francisco, California 93858-2330 USA
- Kavli Institute for Fundamental Neuroscience, University of California, San Francisco, California 93858-2330 USA
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37
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Fancher AT, Hua Y, Close DA, Xu W, McDermott LA, Strock CJ, Santiago U, Camacho CJ, Johnston PA. Characterization of allosteric modulators that disrupt androgen receptor co-activator protein-protein interactions to alter transactivation-Drug leads for metastatic castration resistant prostate cancer. SLAS DISCOVERY : ADVANCING LIFE SCIENCES R & D 2023; 28:325-343. [PMID: 37549772 DOI: 10.1016/j.slasd.2023.08.001] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/05/2023] [Revised: 07/06/2023] [Accepted: 08/04/2023] [Indexed: 08/09/2023]
Abstract
Three series of compounds were prioritized from a high content screening campaign that identified molecules that blocked dihydrotestosterone (DHT) induced formation of Androgen Receptor (AR) protein-protein interactions (PPIs) with the Transcriptional Intermediary Factor 2 (TIF2) coactivator and also disrupted preformed AR-TIF2 PPI complexes; the hydrobenzo-oxazepins (S1), thiadiazol-5-piperidine-carboxamides (S2), and phenyl-methyl-indoles (S3). Compounds from these series inhibited AR PPIs with TIF2 and SRC-1, another p160 coactivator, in mammalian 2-hybrid assays and blocked transcriptional activation in reporter assays driven by full length AR or AR-V7 splice variants. Compounds inhibited the growth of five prostate cancer cell lines, with many exhibiting differential cytotoxicity towards AR positive cell lines. Representative compounds from the 3 series substantially reduced both endogenous and DHT-enhanced expression and secretion of the prostate specific antigen (PSA) cancer biomarker in the C4-2 castration resistant prostate cancer (CRPC) cell line. The comparatively weak activities of series compounds in the H3-DHT and/or TIF2 box 3 LXXLL-peptide binding assays to the recombinant ligand binding domain of AR suggest that direct antagonism at the orthosteric ligand binding site or AF-2 surface respectively are unlikely mechanisms of action. Cellular enhanced thermal stability assays (CETSA) indicated that compounds engaged AR and reduced the maximum efficacy and right shifted the EC50 of DHT-enhanced AR thermal stabilization consistent with the effects of negative allosteric modulators. Molecular docking of potent representative hits from each series to AR structures suggest that S1-1 and S2-6 engage a novel binding pocket (BP-1) adjacent to the orthosteric ligand binding site, while S3-11 occupies the AR binding function 3 (BF-3) allosteric pocket. Hit binding poses indicate spaces and residues adjacent to the BP-1 and BF-3 pockets that will be exploited in future medicinal chemistry optimization studies. Small molecule allosteric modulators that prevent/disrupt AR PPIs with coactivators like TIF2 to alter transcriptional activation in the presence of orthosteric agonists might evade the resistance mechanisms to existing prostate cancer drugs and provide novel starting points for medicinal chemistry lead optimization and future development into therapies for metastatic CRPC.
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Affiliation(s)
- Ashley T Fancher
- Department of Pharmaceutical Sciences, School of Pharmacy, University of Pittsburgh, Pittsburgh, PA 15261, USA; Nucleus Global, 2 Ravinia Drive, Suite 605, Atlanta, GA 30346, USA
| | - Yun Hua
- Department of Pharmaceutical Sciences, School of Pharmacy, University of Pittsburgh, Pittsburgh, PA 15261, USA
| | - David A Close
- Department of Pharmaceutical Sciences, School of Pharmacy, University of Pittsburgh, Pittsburgh, PA 15261, USA
| | - Wei Xu
- Department of Pharmaceutical Sciences, School of Pharmacy, University of Pittsburgh, Pittsburgh, PA 15261, USA
| | - Lee A McDermott
- Department of Pharmaceutical Sciences, School of Pharmacy, University of Pittsburgh, Pittsburgh, PA 15261, USA; PsychoGenics Inc, 215 College Road, Paramus, NJ 07652, USA
| | | | - Ulises Santiago
- Department of Computational and Systems Biology, School of Medicine, at the University of Pittsburgh, USA
| | - Carlos J Camacho
- Department of Computational and Systems Biology, School of Medicine, at the University of Pittsburgh, USA
| | - Paul A Johnston
- Department of Pharmaceutical Sciences, School of Pharmacy, University of Pittsburgh, Pittsburgh, PA 15261, USA; University of Pittsburgh Hillman Cancer Center, Pittsburgh, PA 15232, USA.
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Wu H, Han J, Zhang S, Xin G, Mou C, Liu J. Spatom: a graph neural network for structure-based protein-protein interaction site prediction. Brief Bioinform 2023; 24:bbad345. [PMID: 37779247 DOI: 10.1093/bib/bbad345] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/06/2023] [Revised: 08/22/2023] [Accepted: 09/13/2023] [Indexed: 10/03/2023] Open
Abstract
Accurate identification of protein-protein interaction (PPI) sites remains a computational challenge. We propose Spatom, a novel framework for PPI site prediction. This framework first defines a weighted digraph for a protein structure to precisely characterize the spatial contacts of residues, then performs a weighted digraph convolution to aggregate both spatial local and global information and finally adds an improved graph attention layer to drive the predicted sites to form more continuous region(s). Spatom was tested on a diverse set of challenging protein-protein complexes and demonstrated the best performance among all the compared methods. Furthermore, when tested on multiple popular proteins in a case study, Spatom clearly identifies the interaction interfaces and captures the majority of hotspots. Spatom is expected to contribute to the understanding of protein interactions and drug designs targeting protein binding.
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Affiliation(s)
- Haonan Wu
- School of Mathematics and Statistics, Shandong University, Weihai 264209, China
- School of Mathematics, Shandong University, Jinan 250100, China
| | - Jiyun Han
- School of Mathematics and Statistics, Shandong University, Weihai 264209, China
| | - Shizhuo Zhang
- School of Mathematics and Statistics, Shandong University, Weihai 264209, China
| | - Gaojia Xin
- School of Mathematics and Statistics, Shandong University, Weihai 264209, China
| | - Chaozhou Mou
- School of Mathematics and Statistics, Shandong University, Weihai 264209, China
| | - Juntao Liu
- School of Mathematics and Statistics, Shandong University, Weihai 264209, China
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Shoaib TH, Abdelmoniem N, Mukhtar RM, Alqhtani AT, Alalawi AL, Alawaji R, Althubyani MS, Mohamed SGA, Mohamed GA, Ibrahim SRM, Hussein HGA, Alzain AA. Molecular Docking and Molecular Dynamics Studies Reveal the Anticancer Potential of Medicinal-Plant-Derived Lignans as MDM2-P53 Interaction Inhibitors. Molecules 2023; 28:6665. [PMID: 37764441 PMCID: PMC10536213 DOI: 10.3390/molecules28186665] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/27/2023] [Revised: 09/11/2023] [Accepted: 09/12/2023] [Indexed: 09/29/2023] Open
Abstract
The interaction between the tumor suppressor protein p53 and its negative regulator, the MDM2 oncogenic protein, has gained significant attention in cancer drug discovery. In this study, 120 lignans reported from Ferula sinkiangensis and Justicia procumbens were assessed for docking simulations on the active pocket of the MDM2 crystal structure bound to Nutlin-3a. The docking analysis identified nine compounds with higher docking scores than the co-crystallized reference. Subsequent AMDET profiling revealed satisfactory pharmacokinetic and safety parameters for these natural products. Three compounds, namely, justin A, 6-hydroxy justicidin A, and 6'-hydroxy justicidin B, were selected for further investigation due to their strong binding affinities of -7.526 kcal/mol, -7.438 kcal/mol, and -7.240 kcal/mol, respectively, which surpassed the binding affinity of the reference inhibitor Nutlin-3a (-6.830 kcal/mol). To assess the stability and reliability of the binding of the candidate hits, a molecular dynamics simulation was performed over a duration of 100 ns. Remarkably, the thorough analysis demonstrated that all the hits exhibited stable molecular dynamics profiles. Based on their effective binding to MDM2, favorable pharmacokinetic properties, and molecular dynamics behavior, these compounds represent a promising starting point for further refinement. Nevertheless, it is essential to synthesize the suggested compounds and evaluate their activity through in vitro and in vivo experiments.
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Affiliation(s)
- Tagyedeen H. Shoaib
- Department of Pharmaceutical Chemistry, Faculty of Pharmacy, University of Gezira, Wad Madani 21111, Sudan; (T.H.S.); (N.A.); (R.M.M.)
| | - Nihal Abdelmoniem
- Department of Pharmaceutical Chemistry, Faculty of Pharmacy, University of Gezira, Wad Madani 21111, Sudan; (T.H.S.); (N.A.); (R.M.M.)
| | - Rua M. Mukhtar
- Department of Pharmaceutical Chemistry, Faculty of Pharmacy, University of Gezira, Wad Madani 21111, Sudan; (T.H.S.); (N.A.); (R.M.M.)
| | - Amal Th. Alqhtani
- Pharmaceutical Care Services, Madinah Cardiac Center, MOH, Al Madinah Al Munawwarah 11176, Saudi Arabia; (A.T.A.); (M.S.A.)
| | - Abdullah L. Alalawi
- Pharmaceutical Care Services, King Salman Medical City, MOH, Al Madinah Al Munawwarah 11176, Saudi Arabia;
| | - Razan Alawaji
- Department of Pharmacology and Toxicology, College of Pharmacy, Qassim University, Qassim 51452, Saudi Arabia;
| | - Mashael S. Althubyani
- Pharmaceutical Care Services, Madinah Cardiac Center, MOH, Al Madinah Al Munawwarah 11176, Saudi Arabia; (A.T.A.); (M.S.A.)
| | - Shaimaa G. A. Mohamed
- Faculty of Dentistry, British University, El Sherouk City, Suez Desert Road, Cairo 11837, Egypt;
| | - Gamal A. Mohamed
- Department of Natural Products and Alternative Medicine, Faculty of Pharmacy, King Abdulaziz University, Jeddah 21589, Saudi Arabia;
| | - Sabrin R. M. Ibrahim
- Preparatory Year Program, Department of Chemistry, Batterjee Medical College, Jeddah 21442, Saudi Arabia
- Department of Pharmacognosy, Faculty of Pharmacy, Assiut University, Assiut 71526, Egypt
| | - Hazem G. A. Hussein
- Preparatory Year Program, Batterjee Medical College, Jeddah 21442, Saudi Arabia;
| | - Abdulrahim A. Alzain
- Department of Pharmaceutical Chemistry, Faculty of Pharmacy, University of Gezira, Wad Madani 21111, Sudan; (T.H.S.); (N.A.); (R.M.M.)
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Senoo A, Nagatoishi S, Kuroda D, Ito S, Ueno G, Caaveiro JMM, Tsumoto K. Modulation of a conformational ensemble by a small molecule that inhibits key protein-protein interactions involved in cell adhesion. Protein Sci 2023; 32:e4744. [PMID: 37531208 PMCID: PMC10443342 DOI: 10.1002/pro.4744] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/19/2023] [Revised: 07/24/2023] [Accepted: 07/28/2023] [Indexed: 08/03/2023]
Abstract
Small molecules that regulate protein-protein interactions can be valuable drugs; however, the development of such small molecules is challenging as the molecule must interfere with an interaction that often involves a large surface area. Herein, we propose that modulating the conformational ensemble of the proteins participating in a given interaction, rather than blocking the interaction by directly binding to the interface, is a relevant strategy for interfering with a protein-protein interaction. In this study, we applied this concept to P-cadherin, a cell surface protein forming homodimers that are essential for cell-cell adhesion in various biological contexts. We first determined the crystal structure of P-cadherin with a small molecule inhibitor whose inhibitory mechanism was unknown. Molecular dynamics simulations suggest that the inhibition of cell adhesion by this small molecule results from modulation of the conformational ensemble of P-cadherin. Our study demonstrates the potential of small molecules altering the conformation ensemble of a protein as inhibitors of biological relevant protein-protein interactions.
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Affiliation(s)
- Akinobu Senoo
- Department of Chemistry and Biotechnology, Graduate School of EngineeringThe University of TokyoTokyoJapan
- Department of Global Healthcare, Graduate School of Pharmaceutical SciencesKyushu UniversityFukuokaJapan
| | - Satoru Nagatoishi
- Medical Device Development and Regulation Research Center, School of EngineeringThe University of TokyoTokyoJapan
- Department of Bioengineering, Graduate School of EngineeringThe University of TokyoTokyoJapan
| | - Daisuke Kuroda
- Department of Chemistry and Biotechnology, Graduate School of EngineeringThe University of TokyoTokyoJapan
- Department of Bioengineering, Graduate School of EngineeringThe University of TokyoTokyoJapan
- Research Center for Drug and Vaccine DevelopmentNational Institute of Infectious DiseasesTokyoJapan
| | - Sho Ito
- DIC Central Research LaboratoriesChibaJapan
| | - Go Ueno
- RIKEN SPring‐8 CenterSayo‐gunHyogoJapan
| | - Jose M. M. Caaveiro
- Department of Global Healthcare, Graduate School of Pharmaceutical SciencesKyushu UniversityFukuokaJapan
| | - Kouhei Tsumoto
- Department of Chemistry and Biotechnology, Graduate School of EngineeringThe University of TokyoTokyoJapan
- Medical Device Development and Regulation Research Center, School of EngineeringThe University of TokyoTokyoJapan
- Department of Bioengineering, Graduate School of EngineeringThe University of TokyoTokyoJapan
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Dahal A, Subramanian V, Shrestha P, Liu D, Gauthier T, Jois S. Conformationally constrained cyclic grafted peptidomimetics targeting protein-protein interactions. Pept Sci (Hoboken) 2023; 115:e24328. [PMID: 38188985 PMCID: PMC10769001 DOI: 10.1002/pep2.24328] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/24/2022] [Accepted: 07/03/2023] [Indexed: 01/09/2024]
Abstract
Sunflower trypsin inhibitor-1 (SFTI-1) structure is used for designing grafted peptides as a possible therapeutic agent. The grafted peptide exhibits multiple conformations in solution due to the presence of proline in the structure of the peptide. To lock the grafted peptide into a major conformation in solution, a dibenzofuran moiety (DBF) was incorporated in the peptide backbone structure, replacing the Pro-Pro sequence. NMR studies indicated a major conformation of the grafted peptide in solution. Detailed structural studies suggested that SFTI-DBF adopts a twisted beta-strand structure in solution. The surface plasmon resonance analysis showed that SFTI-DBF binds to CD58 protein. A model for the protein-SFTI-DBF complex was proposed based on docking studies. These studies suggested that SFTI-1 grafted peptide can be used to design stable peptides for therapeutic purposes by grafting organic functional groups and amino acids. However, when a similar strategy was used with another grafted peptide, the resulting peptide did not produce a single major conformation, and its biological activity was lost. Thus, conformational constraints depend on the sequence of amino acids used for SFTI-1 grafting.
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Affiliation(s)
- Achyut Dahal
- School of Basic Pharmaceutical and Toxicological Sciences, College of Pharmacy, University of Louisiana Monroe, Monroe LA 71201
| | - Vivekanandan Subramanian
- Department of Pharmaceutical Sciences, College of Pharmacy, University of Kentucky, Lexington, KY 40536
| | - Prajesh Shrestha
- School of Basic Pharmaceutical and Toxicological Sciences, College of Pharmacy, University of Louisiana Monroe, Monroe LA 71201
- Department of Pathobiological Sciences, School of Veterinary Medicine, Louisiana State University, Baton Rouge 70803
| | - Dong Liu
- AgCenter Biotechnology Laboratory, LSU Agricultural Center, Baton Rouge, LA, 70803
| | - Ted Gauthier
- AgCenter Biotechnology Laboratory, LSU Agricultural Center, Baton Rouge, LA, 70803
| | - Seetharama Jois
- School of Basic Pharmaceutical and Toxicological Sciences, College of Pharmacy, University of Louisiana Monroe, Monroe LA 71201
- Department of Pathobiological Sciences, School of Veterinary Medicine, Louisiana State University, Baton Rouge 70803
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42
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Chenna A, Khan WH, Dash R, Saraswat S, Chugh A, Rathore AS, Goel G. An efficient computational protocol for template-based design of peptides that inhibit interactions involving SARS-CoV-2 proteins. Proteins 2023; 91:1222-1234. [PMID: 37283297 DOI: 10.1002/prot.26511] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/07/2022] [Revised: 02/17/2023] [Accepted: 04/25/2023] [Indexed: 06/08/2023]
Abstract
The RNA-dependent RNA polymerase (RdRp) complex of SARS-CoV-2 lies at the core of its replication and transcription processes. The interfaces between holo-RdRp subunits are highly conserved, facilitating the design of inhibitors with high affinity for the interaction interface hotspots. We, therefore, take this as a model protein complex for the application of a structural bioinformatics protocol to design peptides that inhibit RdRp complexation by preferential binding at the interface of its core subunit nonstructural protein, nsp12, with accessory factor nsp7. Here, the interaction hotspots of the nsp7-nsp12 subunit of RdRp, determined from a long molecular dynamics trajectory, are used as a template. A large library of peptide sequences constructed from multiple hotspot motifs of nsp12 is screened in-silico to determine sequences with high geometric complementarity and interaction specificity for the binding interface of nsp7 (target) in the complex. Two lead designed peptides are extensively characterized using orthogonal bioanalytical methods to determine their suitability for inhibition of RdRp complexation. Binding affinity of these peptides to accessory factor nsp7, determined using a surface plasmon resonance (SPR) assay, is slightly better than that of nsp12: dissociation constant of 133nM and 167nM, respectively, compared to 473nM for nsp12. A competitive ELISA is used to quantify inhibition of nsp7-nsp12 complexation, with one of the lead peptides giving an IC50 of 25μM . Cell penetrability and cytotoxicity are characterized using a cargo delivery assay and MTT cytotoxicity assay, respectively. Overall, this work presents a proof-of-concept of an approach for rational discovery of peptide inhibitors of SARS-CoV-2 protein-protein interactions.
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Affiliation(s)
- Akshay Chenna
- Department of Chemical Engineering, Indian Institute of Technology Delhi, New Delhi, India
| | - Wajihul Hasan Khan
- Department of Chemical Engineering, Indian Institute of Technology Delhi, New Delhi, India
- Virology Unit, Department of Microbiology, All India Institute of Medical Sciences, New Delhi, India
| | - Rozaleen Dash
- Department of Chemical Engineering, Indian Institute of Technology Delhi, New Delhi, India
| | - Saurabh Saraswat
- Kusuma School of Biological Sciences, Indian Institute of Technology Delhi, New Delhi, India
| | - Archana Chugh
- Kusuma School of Biological Sciences, Indian Institute of Technology Delhi, New Delhi, India
| | - Anurag S Rathore
- Department of Chemical Engineering, Indian Institute of Technology Delhi, New Delhi, India
| | - Gaurav Goel
- Department of Chemical Engineering, Indian Institute of Technology Delhi, New Delhi, India
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Morehead A, Chen C, Sedova A, Cheng J. DIPS-Plus: The enhanced database of interacting protein structures for interface prediction. Sci Data 2023; 10:509. [PMID: 37537186 PMCID: PMC10400622 DOI: 10.1038/s41597-023-02409-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/20/2023] [Accepted: 07/24/2023] [Indexed: 08/05/2023] Open
Abstract
In this work, we expand on a dataset recently introduced for protein interface prediction (PIP), the Database of Interacting Protein Structures (DIPS), to present DIPS-Plus, an enhanced, feature-rich dataset of 42,112 complexes for machine learning of protein interfaces. While the original DIPS dataset contains only the Cartesian coordinates for atoms contained in the protein complex along with their types, DIPS-Plus contains multiple residue-level features including surface proximities, half-sphere amino acid compositions, and new profile hidden Markov model (HMM)-based sequence features for each amino acid, providing researchers a curated feature bank for training protein interface prediction methods. We demonstrate through rigorous benchmarks that training an existing state-of-the-art (SOTA) model for PIP on DIPS-Plus yields new SOTA results, surpassing the performance of some of the latest models trained on residue-level and atom-level encodings of protein complexes to date.
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Affiliation(s)
- Alex Morehead
- University of Missouri, Electrical Engineering & Computer Science, Columbia, MO, 65211, USA.
| | - Chen Chen
- University of Missouri, Electrical Engineering & Computer Science, Columbia, MO, 65211, USA
| | - Ada Sedova
- Oak Ridge National Laboratory, Oak Ridge, TN, 37830, USA
| | - Jianlin Cheng
- University of Missouri, Electrical Engineering & Computer Science, Columbia, MO, 65211, USA
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Tanada M, Tamiya M, Matsuo A, Chiyoda A, Takano K, Ito T, Irie M, Kotake T, Takeyama R, Kawada H, Hayashi R, Ishikawa S, Nomura K, Furuichi N, Morita Y, Kage M, Hashimoto S, Nii K, Sase H, Ohara K, Ohta A, Kuramoto S, Nishimura Y, Iikura H, Shiraishi T. Development of Orally Bioavailable Peptides Targeting an Intracellular Protein: From a Hit to a Clinical KRAS Inhibitor. J Am Chem Soc 2023. [PMID: 37463267 DOI: 10.1021/jacs.3c03886] [Citation(s) in RCA: 17] [Impact Index Per Article: 17.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 07/20/2023]
Abstract
Cyclic peptides as a therapeutic modality are attracting a lot of attention due to their potential for oral absorption and accessibility to intracellular tough targets. Here, starting with a drug-like hit discovered using an mRNA display library, we describe a chemical optimization that led to the orally available clinical compound known as LUNA18, an 11-mer cyclic peptide inhibitor for the intracellular tough target RAS. The key findings are as follows: (i) two peptide side chains were identified that each increase RAS affinity over 10-fold; (ii) physico-chemical properties (PCP) including Clog P can be adjusted by side-chain modification to increase membrane permeability; (iii) restriction of cyclic peptide conformation works effectively to adjust PCP and improve bio-activity; (iv) cellular efficacy was observed in peptides with a permeability of around 0.4 × 10-6 cm/s or more in a Caco-2 permeability assay; and (v) while keeping the cyclic peptide's main-chain conformation, we found one example where the RAS protein structure was changed dramatically through induced-fit to our peptide side chain. This study demonstrates how the chemical optimization of bio-active peptides can be achieved without scaffold hopping, much like the processes for small molecule drug discovery that are guided by Lipinski's rule of five. Our approach provides a versatile new strategy for generating peptide drugs starting from drug-like hits.
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Affiliation(s)
- Mikimasa Tanada
- Research Division, Chugai Pharmaceutical Co. Ltd., 216, Totsuka-cho, Totsuka-ku, Yokohama, Kanagawa 244-8602, Japan
| | - Minoru Tamiya
- Research Division, Chugai Pharmaceutical Co. Ltd., 216, Totsuka-cho, Totsuka-ku, Yokohama, Kanagawa 244-8602, Japan
| | - Atsushi Matsuo
- Research Division, Chugai Pharmaceutical Co. Ltd., 216, Totsuka-cho, Totsuka-ku, Yokohama, Kanagawa 244-8602, Japan
| | - Aya Chiyoda
- Research Division, Chugai Pharmaceutical Co. Ltd., 216, Totsuka-cho, Totsuka-ku, Yokohama, Kanagawa 244-8602, Japan
| | - Koji Takano
- Research Division, Chugai Pharmaceutical Co. Ltd., 216, Totsuka-cho, Totsuka-ku, Yokohama, Kanagawa 244-8602, Japan
| | - Toshiya Ito
- Research Division, Chugai Pharmaceutical Co. Ltd., 216, Totsuka-cho, Totsuka-ku, Yokohama, Kanagawa 244-8602, Japan
| | - Machiko Irie
- Research Division, Chugai Pharmaceutical Co. Ltd., 216, Totsuka-cho, Totsuka-ku, Yokohama, Kanagawa 244-8602, Japan
| | - Tomoya Kotake
- Research Division, Chugai Pharmaceutical Co. Ltd., 216, Totsuka-cho, Totsuka-ku, Yokohama, Kanagawa 244-8602, Japan
| | - Ryuuichi Takeyama
- Research Division, Chugai Pharmaceutical Co. Ltd., 216, Totsuka-cho, Totsuka-ku, Yokohama, Kanagawa 244-8602, Japan
| | - Hatsuo Kawada
- Research Division, Chugai Pharmaceutical Co. Ltd., 216, Totsuka-cho, Totsuka-ku, Yokohama, Kanagawa 244-8602, Japan
| | - Ryuji Hayashi
- Research Division, Chugai Pharmaceutical Co. Ltd., 216, Totsuka-cho, Totsuka-ku, Yokohama, Kanagawa 244-8602, Japan
| | - Shiho Ishikawa
- Research Division, Chugai Pharmaceutical Co. Ltd., 216, Totsuka-cho, Totsuka-ku, Yokohama, Kanagawa 244-8602, Japan
| | - Kenichi Nomura
- Research Division, Chugai Pharmaceutical Co. Ltd., 216, Totsuka-cho, Totsuka-ku, Yokohama, Kanagawa 244-8602, Japan
| | - Noriyuki Furuichi
- Research Division, Chugai Pharmaceutical Co. Ltd., 216, Totsuka-cho, Totsuka-ku, Yokohama, Kanagawa 244-8602, Japan
| | - Yuya Morita
- Research Division, Chugai Pharmaceutical Co. Ltd., 216, Totsuka-cho, Totsuka-ku, Yokohama, Kanagawa 244-8602, Japan
| | - Mirai Kage
- Research Division, Chugai Pharmaceutical Co. Ltd., 216, Totsuka-cho, Totsuka-ku, Yokohama, Kanagawa 244-8602, Japan
| | - Satoshi Hashimoto
- Research Division, Chugai Pharmaceutical Co. Ltd., 216, Totsuka-cho, Totsuka-ku, Yokohama, Kanagawa 244-8602, Japan
| | - Keiji Nii
- Research Division, Chugai Pharmaceutical Co. Ltd., 216, Totsuka-cho, Totsuka-ku, Yokohama, Kanagawa 244-8602, Japan
| | - Hitoshi Sase
- Research Division, Chugai Pharmaceutical Co. Ltd., 216, Totsuka-cho, Totsuka-ku, Yokohama, Kanagawa 244-8602, Japan
| | - Kazuhiro Ohara
- Research Division, Chugai Pharmaceutical Co. Ltd., 216, Totsuka-cho, Totsuka-ku, Yokohama, Kanagawa 244-8602, Japan
| | - Atsushi Ohta
- Research Division, Chugai Pharmaceutical Co. Ltd., 216, Totsuka-cho, Totsuka-ku, Yokohama, Kanagawa 244-8602, Japan
| | - Shino Kuramoto
- Research Division, Chugai Pharmaceutical Co. Ltd., 216, Totsuka-cho, Totsuka-ku, Yokohama, Kanagawa 244-8602, Japan
| | - Yoshikazu Nishimura
- Research Division, Chugai Pharmaceutical Co. Ltd., 216, Totsuka-cho, Totsuka-ku, Yokohama, Kanagawa 244-8602, Japan
| | - Hitoshi Iikura
- Research Division, Chugai Pharmaceutical Co. Ltd., 216, Totsuka-cho, Totsuka-ku, Yokohama, Kanagawa 244-8602, Japan
| | - Takuya Shiraishi
- Research Division, Chugai Pharmaceutical Co. Ltd., 216, Totsuka-cho, Totsuka-ku, Yokohama, Kanagawa 244-8602, Japan
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Wang Y, Li W, Ye B, Bi X. Chemical and Biological Strategies for Profiling Protein-Protein Interactions in Living Cells. Chem Asian J 2023; 18:e202300226. [PMID: 37089007 PMCID: PMC10946512 DOI: 10.1002/asia.202300226] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/16/2023] [Revised: 04/19/2023] [Accepted: 04/20/2023] [Indexed: 04/25/2023]
Abstract
Protein-protein interactions (PPIs) play critical roles in almost all cellular signal transduction events. Characterization of PPIs without interfering with the functions of intact cells is very important for basic biology study and drug developments. However, the ability to profile PPIs especially those weak/transient interactions in their native states remains quite challenging. To this end, many endeavors are being made in developing new methods with high efficiency and strong operability. By coupling with advanced fluorescent microscopy and mass spectroscopy techniques, these strategies not only allow us to visualize the subcellular locations and monitor the functions of protein of interest (POI) in real time, but also enable the profiling and identification of potential unknown interacting partners in high-throughput manner, which greatly facilitates the elucidation of molecular mechanisms underlying numerous pathophysiological processes. In this review, we will summarize the typical methods for PPIs identification in living cells and their principles, advantages and limitations will also be discussed in detail.
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Affiliation(s)
- You‐Yu Wang
- Collaborative Innovation Center of Yangtze River Delta Region Green Pharmaceuticals & College of Pharmaceutical SciencesZhejiang University of TechnologyHangzhou310014, Zhejiang ProvinceP. R. China
| | - Wenyi Li
- Department of Biochemistry and Chemistry, La Trobe Institute for Molecular ScienceLa Trobe UniversityVictoria3086Australia
| | - Bang‐Ce Ye
- Collaborative Innovation Center of Yangtze River Delta Region Green Pharmaceuticals & College of Pharmaceutical SciencesZhejiang University of TechnologyHangzhou310014, Zhejiang ProvinceP. R. China
| | - Xiao‐Bao Bi
- Collaborative Innovation Center of Yangtze River Delta Region Green Pharmaceuticals & College of Pharmaceutical SciencesZhejiang University of TechnologyHangzhou310014, Zhejiang ProvinceP. R. China
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Takayama KI, Matsuoka S, Adachi S, Honma T, Yoshida M, Doi T, Shin-ya K, Yoshida M, Osada H, Inoue S. Identification of small-molecule inhibitors against the interaction of RNA-binding protein PSF and its target RNA for cancer treatment. PNAS NEXUS 2023; 2:pgad203. [PMID: 37388923 PMCID: PMC10304769 DOI: 10.1093/pnasnexus/pgad203] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 05/25/2023] [Accepted: 06/12/2023] [Indexed: 07/01/2023]
Abstract
Diverse cellular activities are modulated through a variety of RNAs, including long noncoding RNAs (lncRNAs), by binding to certain proteins. The inhibition of oncogenic proteins or RNAs is expected to suppress cancer cell proliferation. We have previously demonstrated that PSF interaction with its target RNAs, such as androgen-induced lncRNA CTBP1-AS, is critical for hormone therapy resistance in prostate and breast cancers. However, the action of protein-RNA interactions remains almost undruggable to date. High-throughput screening (HTS) has facilitated the discovery of drugs for protein-protein interactions. In the present study, we developed an in vitro alpha assay using Flag peptide-conjugated lncRNA, CTBP1-AS, and PSF. We then constructed an effective HTS screening system to explore small compounds that inhibit PSF-RNA interactions. Thirty-six compounds were identified and dose-dependently inhibited PSF-RNA interaction in vitro. Moreover, chemical optimization of these lead compounds and evaluation of cancer cell proliferation revealed two promising compounds, N-3 and C-65. These compounds induced apoptosis and inhibited cell growth in prostate and breast cancer cells. By inhibiting PSF-RNA interaction, N-3 and C-65 up-regulated signals that are repressed by PSF, such as the cell cycle signals by p53 and p27. Furthermore, using a mouse xenograft model for hormone therapy-resistant prostate cancer, we revealed that N-3 and C-65 can significantly suppress tumor growth and downstream target gene expression, such as the androgen receptor (AR). Thus, our findings highlight a therapeutic strategy through the development of inhibitors for RNA-binding events in advanced cancers.
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Affiliation(s)
- Ken-ichi Takayama
- Department of Systems Aging Science and Medicine, Tokyo Metropolitan Institute for Geriatrics and Gerontology, itabashi-ku, Tokyo 173-0015, Japan
| | - Seiji Matsuoka
- Seed Compounds Exploratory Unit for Drug Discovery Platform, RIKEN Center for Sustainable Resource Science, Wako, Saitama 351-0198, Japan
| | - Shungo Adachi
- National Institute of Advanced Industrial Science and Technology (AIST), Koto-ku, Tokyo 135-0064, Japan
| | - Teruki Honma
- Drug Discovery Computational Chemistry Platform Unit, RIKEN Center for Biosystems Dynamics Research, Yokohama, Kanagawa 230-0045, Japan
| | - Masahito Yoshida
- Graduate School of Pharmaceutical Sciences, Tohoku University, Sendai, Miyagi 980-8578, Japan
| | - Takayuki Doi
- Graduate School of Pharmaceutical Sciences, Tohoku University, Sendai, Miyagi 980-8578, Japan
| | - Kazuo Shin-ya
- National Institute of Advanced Industrial Science and Technology (AIST), Koto-ku, Tokyo 135-0064, Japan
| | - Minoru Yoshida
- Chemical Genomics Research Group, RIKEN Center for Sustainable Resource Science, Wako, Saitama 351-0198, Japan
| | - Hiroyuki Osada
- Drug Discovery Chemical Bank Unit, RIKEN Center for Sustainable Resource Science, Wako, Saitama 351-0198, Japan
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47
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Chen SY, Zacharias M. What Makes a Good Protein-Protein Interaction Stabilizer: Analysis and Application of the Dual-Binding Mechanism. ACS CENTRAL SCIENCE 2023; 9:969-979. [PMID: 37252344 PMCID: PMC10214505 DOI: 10.1021/acscentsci.3c00003] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 01/05/2023] [Indexed: 05/31/2023]
Abstract
Protein-protein interactions (PPIs) are essential for biological processes including immune reactions and diseases. Inhibition of PPIs by drug-like compounds is a common basis for therapeutic approaches. In many cases the flat interface of PP complexes prevents discovery of specific compound binding to cavities on one partner and PPI inhibition. However, frequently new pockets are formed at the PP interface that allow accommodation of stabilizers which is often as desirable as inhibition but a much less explored alternative strategy. Herein, we employ molecular dynamics simulations and pocket detection to investigate 18 known stabilizers and associated PP complexes. For most cases, we find that a dual-binding mechanism, a similar stabilizer interaction strength with each protein partner, is an important prerequisite for effective stabilization. A few stabilizers follow an allosteric mechanism by stabilizing the protein bound structure and/or increase the PPI indirectly. On 226 protein-protein complexes, we find in >75% of the cases interface cavities suitable for binding of drug-like compounds. We propose a computational compound identification workflow that exploits new PP interface cavities and optimizes the dual-binding mechanism and apply it to 5 PP complexes. Our study demonstrates a great potential for in silico PPI stabilizers discovery with a wide range of therapeutic applications.
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48
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Pathak P, Alexander KK, Helton LG, Kentros M, LeClair TJ, Zhang X, Ho FY, Moore TT, Hall S, Guaitoli G, Gloeckner CJ, Kortholt A, Rideout H, Kennedy EJ. Doubly Constrained C-terminal of Roc (COR) Domain-Derived Peptides Inhibit Leucine-Rich Repeat Kinase 2 (LRRK2) Dimerization. ACS Chem Neurosci 2023. [PMID: 37200505 DOI: 10.1021/acschemneuro.3c00259] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/20/2023] Open
Abstract
Missense mutations along the leucine-rich repeat kinase 2 (LRRK2) protein are a major contributor to Parkinson's Disease (PD), the second most commonly occurring neurodegenerative disorder worldwide. We recently reported the development of allosteric constrained peptide inhibitors that target and downregulate LRRK2 activity through disruption of LRRK2 dimerization. In this study, we designed doubly constrained peptides with the objective of inhibiting C-terminal of Roc (COR)-COR mediated dimerization at the LRRK2 dimer interface. We show that the doubly constrained peptides are cell-permeant, bind wild-type and pathogenic LRRK2, inhibit LRRK2 dimerization and kinase activity, and inhibit LRRK2-mediated neuronal apoptosis, and in contrast to ATP-competitive LRRK2 kinase inhibitors, they do not induce the mislocalization of LRRK2 to skein-like structures in cells. This work highlights the significance of COR-mediated dimerization in LRRK2 activity while also highlighting the use of doubly constrained peptides to stabilize discrete secondary structural folds within a peptide sequence.
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Affiliation(s)
- Pragya Pathak
- Department of Cell Biochemistry, University of Groningen, Nijenborgh 7, 9747AG Groningen, Netherlands
| | - Krista K Alexander
- Department of Pharmaceutical and Biomedical Sciences, College of Pharmacy, University of Georgia, Athens, Georgia 30602, United States
| | - Leah G Helton
- Department of Pharmaceutical and Biomedical Sciences, College of Pharmacy, University of Georgia, Athens, Georgia 30602, United States
| | - Michalis Kentros
- Center for Clinical, Experimental Surgery, and Translational Research, Biomedical Research Foundation of the Academy of Athens, 11527 Athens, Greece
| | - Timothy J LeClair
- Department of Pharmaceutical and Biomedical Sciences, College of Pharmacy, University of Georgia, Athens, Georgia 30602, United States
| | - Xiaojuan Zhang
- Department of Cell Biochemistry, University of Groningen, Nijenborgh 7, 9747AG Groningen, Netherlands
| | - Franz Y Ho
- Department of Cell Biochemistry, University of Groningen, Nijenborgh 7, 9747AG Groningen, Netherlands
| | - Timothy T Moore
- Department of Pharmaceutical and Biomedical Sciences, College of Pharmacy, University of Georgia, Athens, Georgia 30602, United States
| | - Scotty Hall
- Department of Pharmaceutical and Biomedical Sciences, College of Pharmacy, University of Georgia, Athens, Georgia 30602, United States
| | | | - Christian Johannes Gloeckner
- DZNE German Center for Neurodegenerative Diseases, 72076 Tübingen, Germany
- Core Facility for Medical Bioanalytics, Center for Ophthalmology, Institute for Ophthalmic Research, University of Tübingen, 72076 Tübingen, Germany
| | - Arjan Kortholt
- Department of Cell Biochemistry, University of Groningen, Nijenborgh 7, 9747AG Groningen, Netherlands
- YETEM-Innovative Technologies Application and Research Centre, Suleyman Demirel University, 32260 Isparta, Turkey
| | - Hardy Rideout
- Center for Clinical, Experimental Surgery, and Translational Research, Biomedical Research Foundation of the Academy of Athens, 11527 Athens, Greece
| | - Eileen J Kennedy
- Department of Pharmaceutical and Biomedical Sciences, College of Pharmacy, University of Georgia, Athens, Georgia 30602, United States
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49
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Lazear MR, Remsberg JR, Jaeger MG, Rothamel K, Her HL, DeMeester KE, Njomen E, Hogg SJ, Rahman J, Whitby LR, Won SJ, Schafroth MA, Ogasawara D, Yokoyama M, Lindsey GL, Li H, Germain J, Barbas S, Vaughan J, Hanigan TW, Vartabedian VF, Reinhardt CJ, Dix MM, Koo SJ, Heo I, Teijaro JR, Simon GM, Ghosh B, Abdel-Wahab O, Ahn K, Saghatelian A, Melillo B, Schreiber SL, Yeo GW, Cravatt BF. Proteomic discovery of chemical probes that perturb protein complexes in human cells. Mol Cell 2023; 83:1725-1742.e12. [PMID: 37084731 PMCID: PMC10198961 DOI: 10.1016/j.molcel.2023.03.026] [Citation(s) in RCA: 28] [Impact Index Per Article: 28.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/10/2021] [Revised: 01/09/2023] [Accepted: 03/28/2023] [Indexed: 04/23/2023]
Abstract
Most human proteins lack chemical probes, and several large-scale and generalizable small-molecule binding assays have been introduced to address this problem. How compounds discovered in such "binding-first" assays affect protein function, nonetheless, often remains unclear. Here, we describe a "function-first" proteomic strategy that uses size exclusion chromatography (SEC) to assess the global impact of electrophilic compounds on protein complexes in human cells. Integrating the SEC data with cysteine-directed activity-based protein profiling identifies changes in protein-protein interactions that are caused by site-specific liganding events, including the stereoselective engagement of cysteines in PSME1 and SF3B1 that disrupt the PA28 proteasome regulatory complex and stabilize a dynamic state of the spliceosome, respectively. Our findings thus show how multidimensional proteomic analysis of focused libraries of electrophilic compounds can expedite the discovery of chemical probes with site-specific functional effects on protein complexes in human cells.
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Affiliation(s)
- Michael R Lazear
- Department of Chemistry, Scripps Research, La Jolla, CA 92037, USA
| | | | - Martin G Jaeger
- Department of Chemistry, Scripps Research, La Jolla, CA 92037, USA
| | - Katherine Rothamel
- Department of Cellular and Molecular Medicine, University of California, San Diego, La Jolla, CA, USA
| | - Hsuan-Lin Her
- Department of Cellular and Molecular Medicine, University of California, San Diego, La Jolla, CA, USA
| | | | - Evert Njomen
- Department of Chemistry, Scripps Research, La Jolla, CA 92037, USA
| | - Simon J Hogg
- Human Oncology and Pathogenesis Program, Memorial Sloan Kettering Cancer Center, New York, NY 10021, USA
| | - Jahan Rahman
- Human Oncology and Pathogenesis Program, Memorial Sloan Kettering Cancer Center, New York, NY 10021, USA
| | - Landon R Whitby
- Vividion Therapeutics, 5820 Nancy Ridge Drive, San Diego, CA 92121, USA
| | - Sang Joon Won
- Department of Chemistry, Scripps Research, La Jolla, CA 92037, USA
| | | | | | - Minoru Yokoyama
- Department of Chemistry, Scripps Research, La Jolla, CA 92037, USA
| | | | - Haoxin Li
- Department of Chemistry, Scripps Research, La Jolla, CA 92037, USA
| | - Jason Germain
- Department of Chemistry, Scripps Research, La Jolla, CA 92037, USA
| | - Sabrina Barbas
- Department of Chemistry, Scripps Research, La Jolla, CA 92037, USA
| | - Joan Vaughan
- Clayton Foundation Laboratories for Peptide Biology, The Salk Institute for Biological Studies, La Jolla, CA, USA
| | - Thomas W Hanigan
- Department of Chemistry, Scripps Research, La Jolla, CA 92037, USA
| | - Vincent F Vartabedian
- Department of Immunology and Microbiology, Scripps Research, La Jolla, CA 92037, USA
| | | | - Melissa M Dix
- Department of Chemistry, Scripps Research, La Jolla, CA 92037, USA
| | - Seong Joo Koo
- Molecular and Cellular Pharmacology, Discovery Technologies and Molecular Pharmacology, Janssen Research and Development, Turnhoutseweg 30, 2340 Beerse, Belgium
| | - Inha Heo
- Molecular and Cellular Pharmacology, Discovery Technologies and Molecular Pharmacology, Janssen Research and Development, Turnhoutseweg 30, 2340 Beerse, Belgium
| | - John R Teijaro
- Department of Immunology and Microbiology, Scripps Research, La Jolla, CA 92037, USA
| | - Gabriel M Simon
- Vividion Therapeutics, 5820 Nancy Ridge Drive, San Diego, CA 92121, USA
| | - Brahma Ghosh
- Discovery Chemistry, Janssen Research & Development, Spring House, PA 19477, USA
| | - Omar Abdel-Wahab
- Human Oncology and Pathogenesis Program, Memorial Sloan Kettering Cancer Center, New York, NY 10021, USA
| | - Kay Ahn
- Molecular and Cellular Pharmacology, Discovery Technologies and Molecular Pharmacology, Janssen Research and Development, Spring House, PA 19477, USA
| | - Alan Saghatelian
- Clayton Foundation Laboratories for Peptide Biology, The Salk Institute for Biological Studies, La Jolla, CA, USA
| | - Bruno Melillo
- Department of Chemistry, Scripps Research, La Jolla, CA 92037, USA; Chemical Biology and Therapeutics Science Program, Broad Institute, Cambridge, MA 02142, USA
| | - Stuart L Schreiber
- Chemical Biology and Therapeutics Science Program, Broad Institute, Cambridge, MA 02142, USA; Department of Chemistry and Chemical Biology, Harvard University, Cambridge, MA 02138, USA
| | - Gene W Yeo
- Department of Cellular and Molecular Medicine, University of California, San Diego, La Jolla, CA, USA
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50
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Gao M, Zhao L, Zhang Z, Wang J, Wang C. Using a stacked ensemble learning framework to predict modulators of protein-protein interactions. Comput Biol Med 2023; 161:107032. [PMID: 37230018 DOI: 10.1016/j.compbiomed.2023.107032] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/14/2023] [Revised: 04/13/2023] [Accepted: 05/10/2023] [Indexed: 05/27/2023]
Abstract
Identifying small molecule protein-protein interaction modulators (PPIMs) is a highly promising and meaningful research direction for drug discovery, cancer treatment, and other fields. In this study, we developed a stacking ensemble computational framework, SELPPI, based on a genetic algorithm and tree-based machine learning method for effectively predicting new modulators targeting protein-protein interactions. More specifically, extremely randomized trees (ExtraTrees), adaptive boosting (AdaBoost), random forest (RF), cascade forest, light gradient boosting machine (LightGBM), and extreme gradient boosting (XGBoost) were used as basic learners. Seven types of chemical descriptors were taken as the input characteristic parameters. Primary predictions were obtained with each basic learner-descriptor pair. Then, the 6 methods mentioned above were used as meta learners and trained on the primary prediction in turn. The most efficient method was utilized as the meta learner. Finally, the genetic algorithm was used to select the optimal primary prediction output as the input of the meta learner for secondary prediction to obtain the final result. We systematically evaluated our model on the pdCSM-PPI datasets. To our knowledge, our model outperformed all existing models, which demonstrates its great power.
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Affiliation(s)
- Mengyao Gao
- Faculty of Computing, Harbin Institute of Technology, Harbin, China.
| | - Lingling Zhao
- Faculty of Computing, Harbin Institute of Technology, Harbin, China.
| | - Zitong Zhang
- Faculty of Computing, Harbin Institute of Technology, Harbin, China.
| | - Junjie Wang
- School of Biomedical Engineering and Informatics, Nanjing Medical University, Nanjing, China.
| | - Chunyu Wang
- Faculty of Computing, Harbin Institute of Technology, Harbin, China.
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