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Abbas A, Ye F. Computational methods and key considerations for in silico design of proteolysis targeting chimera (PROTACs). Int J Biol Macromol 2024; 277:134293. [PMID: 39084437 DOI: 10.1016/j.ijbiomac.2024.134293] [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: 05/29/2024] [Revised: 07/19/2024] [Accepted: 07/28/2024] [Indexed: 08/02/2024]
Abstract
Proteolysis-targeting chimeras (PROTACs), as heterobifunctional molecules, have garnered significant attention for their ability to target previously undruggable proteins. Due to the challenges in obtaining crystal structures of PROTAC molecules in the ternary complex, a plethora of computational tools have been developed to aid in PROTAC design. These computational tools can be broadly classified into artificial intelligence (AI)-based or non-AI-based methods. This review aims to provide a comprehensive overview of the latest computational methods for the PROTAC design process, covering both AI and non-AI approaches, from protein selection to ternary complex modeling and prediction. Key considerations for in silico PROTAC design are discussed, along with additional considerations for deploying AI-based models. These considerations are intended to guide subsequent model development in the PROTAC design process. Finally, future directions and recommendations are provided.
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Affiliation(s)
- Amr Abbas
- College of Life Sciences and Medicine, Zhejiang Sci-Tech University, Hangzhou 310018, China; Pharmaceutical Chemistry Department, Faculty of Pharmacy, Cairo University, Cairo 11562, Egypt
| | - Fei Ye
- College of Life Sciences and Medicine, Zhejiang Sci-Tech University, Hangzhou 310018, China.
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2
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Ge J, Li S, Weng G, Wang H, Fang M, Sun H, Deng Y, Hsieh CY, Li D, Hou T. PROTAC-DB 3.0: an updated database of PROTACs with extended pharmacokinetic parameters. Nucleic Acids Res 2024:gkae768. [PMID: 39225044 DOI: 10.1093/nar/gkae768] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/04/2024] [Revised: 08/09/2024] [Accepted: 08/22/2024] [Indexed: 09/04/2024] Open
Abstract
Proteolysis-targeting chimera (PROTAC) is an emerging therapeutic technology that leverages the ubiquitin-proteasome system to target protein degradation. Due to its event-driven mechanistic characteristics, PROTAC has the potential to regulate traditionally non-druggable targets. Recently, AI-aided drug design has accelerated the development of PROTAC drugs. However, the rational design of PROTACs remains a considerable challenge. Here, we present an updated online database, PROTAC-DB 3.0. In this third version, we have expanded the database to include 6111 PROTACs (87% increase compared to the 2.0 version). Additionally, the database now contains 569 warheads (small molecules targeting the protein), 2753 linkers, and 107 E3 ligands (small molecules recruiting E3 ligases). The number of target-PROTAC-E3 ternary complex structures has also increased to 959. Recognizing the importance of druggability in PROTAC design, we have incorporated pharmacokinetic data to PROTAC-DB 3.0. To enhance user experience, we have added features for sorting based on molecular similarity and literature publication date. PROTAC-DB 3.0 is accessible at http://cadd.zju.edu.cn/protacdb/.
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Affiliation(s)
- Jingxuan Ge
- College of Pharmaceutical Sciences, Zhejiang University, Hangzhou 310058 Zhejiang, China
- CarbonSilicon AI Technology Company, Ltd., Hangzhou 310018Zhejiang, China
| | - Shimeng Li
- College of Pharmaceutical Sciences, Zhejiang University, Hangzhou 310058 Zhejiang, China
| | - Gaoqi Weng
- College of Pharmaceutical Sciences, Zhejiang University, Hangzhou 310058 Zhejiang, China
| | - Huating Wang
- College of Pharmaceutical Sciences, Zhejiang University, Hangzhou 310058 Zhejiang, China
| | - Meijing Fang
- Polytechnic Institute, Zhejiang University, Hangzhou 310058 Zhejiang, China
| | - Huiyong Sun
- Department of Medicinal Chemistry, China Pharmaceutical University, Nanjing 210009 Jiangsu, China
| | - Yafeng Deng
- CarbonSilicon AI Technology Company, Ltd., Hangzhou 310018Zhejiang, China
| | - Chang-Yu Hsieh
- College of Pharmaceutical Sciences, Zhejiang University, Hangzhou 310058 Zhejiang, China
| | - Dan Li
- College of Pharmaceutical Sciences, Zhejiang University, Hangzhou 310058 Zhejiang, China
| | - Tingjun Hou
- College of Pharmaceutical Sciences, Zhejiang University, Hangzhou 310058 Zhejiang, China
- Polytechnic Institute, Zhejiang University, Hangzhou 310058 Zhejiang, China
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3
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Mslati H, Gentile F, Pandey M, Ban F, Cherkasov A. PROTACable Is an Integrative Computational Pipeline of 3-D Modeling and Deep Learning To Automate the De Novo Design of PROTACs. J Chem Inf Model 2024; 64:3034-3046. [PMID: 38504115 DOI: 10.1021/acs.jcim.3c01878] [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: 03/21/2024]
Abstract
Proteolysis-targeting chimeras (PROTACs) that engage two biological targets at once are a promising technology in degrading clinically relevant protein targets. Since factors that influence the biological activities of PROTACs are more complex than those of a small molecule drug, we explored a combination of computational chemistry and deep learning strategies to forecast PROTAC activity and enable automated design. A new method named PROTACable was developed for the de novo design of PROTACs, which includes a robust 3-D modeling workflow to model PROTAC ternary complexes using a library of E3 ligase and linker and an SE(3)-equivariant graph transformer network to predict the activity of newly designed PROTACs. PROTACable is available at https://github.com/giaguaro/PROTACable/.
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Affiliation(s)
- Hazem Mslati
- Vancouver Prostate Centre, The University of British Columbia, Vancouver, British Columbia V6H 3Z6, Canada
| | - Francesco Gentile
- Department of Chemistry and Biomolecular Sciences, University of Ottawa, Ottawa, Ontario K1N 6N5, Canada
- Ottawa Institute of Systems Biology, Ottawa, Ontario K1N 6N5, Canada
| | - Mohit Pandey
- Vancouver Prostate Centre, The University of British Columbia, Vancouver, British Columbia V6H 3Z6, Canada
| | - Fuqiang Ban
- Vancouver Prostate Centre, The University of British Columbia, Vancouver, British Columbia V6H 3Z6, Canada
| | - Artem Cherkasov
- Vancouver Prostate Centre, The University of British Columbia, Vancouver, British Columbia V6H 3Z6, Canada
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Danishuddin, Jamal MS, Song KS, Lee KW, Kim JJ, Park YM. Revolutionizing Drug Targeting Strategies: Integrating Artificial Intelligence and Structure-Based Methods in PROTAC Development. Pharmaceuticals (Basel) 2023; 16:1649. [PMID: 38139776 PMCID: PMC10747325 DOI: 10.3390/ph16121649] [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: 10/24/2023] [Revised: 11/20/2023] [Accepted: 11/22/2023] [Indexed: 12/24/2023] Open
Abstract
PROteolysis TArgeting Chimera (PROTAC) is an emerging technology in chemical biology and drug discovery. This technique facilitates the complete removal of the target proteins that are "undruggable" or challenging to target through chemical molecules via the Ubiquitin-Proteasome System (UPS). PROTACs have been widely explored and outperformed not only in cancer but also in other diseases. During the past few decades, several academic institutes and pharma companies have poured more efforts into PROTAC-related technologies, setting the stage for several major degrader trial readouts in clinical phases. Despite their promising results, the formation of robust ternary orientation, off-target activity, poor permeability, and binding affinity are some of the limitations that hinder their development. Recent advancements in computational technologies have facilitated progress in the development of PROTACs. Researchers have been able to utilize these technologies to explore a wider range of E3 ligases and optimize linkers, thereby gaining a better understanding of the effectiveness and safety of PROTACs in clinical settings. In this review, we briefly explore the computational strategies reported to date for the formation of PROTAC components and discuss the key challenges and opportunities for further research in this area.
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Affiliation(s)
- Danishuddin
- Department of Biotechnology, Yeungnam University, Gyeongsan 38541, Republic of Korea;
| | | | - Kyoung-Seob Song
- Department of Medical Science, Kosin University College of Medicine, 194 Wachi-ro, Yeongdo-gu, Busan 49104, Republic of Korea;
| | - Keun-Woo Lee
- Division of Life Science, Department of Bio & Medical Big-Data (BK4 Program), Research Institute of Natural Science (RINS), Gyeongsang National University (GNU), 501 Jinju-daero, Jinju 52828, Republic of Korea
- Angel i-Drug Design (AiDD), 33-3 Jinyangho-ro 44, Jinju 52650, Republic of Korea
| | - Jong-Joo Kim
- Department of Biotechnology, Yeungnam University, Gyeongsan 38541, Republic of Korea;
| | - Yeong-Min Park
- Department of Integrative Biological Sciences and Industry, Sejong University, 209, Neugdong-ro, Gwangjin-gu, Seoul 05006, Republic of Korea
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Pinzi L, Rastelli G. Trends and Applications in Computationally Driven Drug Repurposing. Int J Mol Sci 2023; 24:16511. [PMID: 38003701 PMCID: PMC10671888 DOI: 10.3390/ijms242216511] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/30/2023] [Accepted: 11/06/2023] [Indexed: 11/26/2023] Open
Abstract
Drug repurposing is a widely used approach originally developed to aid in the identification of new uses of already existing drugs outside the scope of the original medical indication [...].
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Affiliation(s)
| | - Giulio Rastelli
- Department of Life Sciences, University of Modena and Reggio Emilia, Via Giuseppe Campi 103, 41125 Modena, Italy;
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Karki R, Gadiya Y, Gribbon P, Zaliani A. Pharmacophore-Based Machine Learning Model To Predict Ligand Selectivity for E3 Ligase Binders. ACS OMEGA 2023; 8:30177-30185. [PMID: 37636935 PMCID: PMC10448689 DOI: 10.1021/acsomega.3c02803] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 04/26/2023] [Accepted: 07/06/2023] [Indexed: 08/29/2023]
Abstract
E3 ligases are enzymes that play a critical role in ubiquitin-mediated protein degradation and are involved in various cellular processes. Pharmacophore analysis is a useful approach for predicting E3 ligase binding selectivity, which involves identifying key chemical features necessary for a ligand to interact with a specific protein target cavity. While pharmacophore analysis is not always sufficient to accurately predict ligand binding affinity, it can be a valuable tool for filtering and/or designing focused libraries for screening campaigns. In this study, we present a fast and an inexpensive approach using a pharmacophore fingerprinting scheme known as ErG, which is used in a multi-class machine learning classification model. This model can assign the correct E3 ligase binder to its known E3 ligase and predict the probability of each molecule to bind to different E3 ligases. Practical applications of this approach are demonstrated on commercial libraries such as Asinex for the rational design of E3 ligase binders. The scripts and data associated with this study can be found on GitHub at https://github.com/Fraunhofer-ITMP/E3_binder_Model.
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Affiliation(s)
- Reagon Karki
- Fraunhofer
Institute for Translational Medicine and Pharmacology (ITMP), Schnackenburgallee 114, 22525 Hamburg, Germany
- Fraunhofer
Cluster of Excellence for Immune-Mediated Diseases (CIMD), Theodor Stern Kai 7, 60590 Frankfurt, Germany
| | - Yojana Gadiya
- Fraunhofer
Institute for Translational Medicine and Pharmacology (ITMP), Schnackenburgallee 114, 22525 Hamburg, Germany
- Fraunhofer
Cluster of Excellence for Immune-Mediated Diseases (CIMD), Theodor Stern Kai 7, 60590 Frankfurt, Germany
- Bonn-Aachen
International Center for Information Technology (B-IT), University of Bonn, 53113 Bonn, Germany
| | - Philip Gribbon
- Fraunhofer
Institute for Translational Medicine and Pharmacology (ITMP), Schnackenburgallee 114, 22525 Hamburg, Germany
- Fraunhofer
Cluster of Excellence for Immune-Mediated Diseases (CIMD), Theodor Stern Kai 7, 60590 Frankfurt, Germany
| | - Andrea Zaliani
- Fraunhofer
Institute for Translational Medicine and Pharmacology (ITMP), Schnackenburgallee 114, 22525 Hamburg, Germany
- Fraunhofer
Cluster of Excellence for Immune-Mediated Diseases (CIMD), Theodor Stern Kai 7, 60590 Frankfurt, Germany
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Seipp EK, Huang R. Design and synthesis of a fluorescent probe to develop a fluorescence polarization assay for the E3 ligase FEM1C. Bioorg Med Chem 2023; 90:117371. [PMID: 37339537 DOI: 10.1016/j.bmc.2023.117371] [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: 03/31/2023] [Revised: 05/31/2023] [Accepted: 06/07/2023] [Indexed: 06/22/2023]
Abstract
A proteolysis targeting chimera (PROTAC) is a bivalent molecule consisting of an E3 ligase ligand and a protein of interest ligand, which promotes the degradation of specific proteins by recruiting the ubiquitin-proteasome system. Although VHL and CRBN ligands have been extensively used in PROTAC development, the availability of small molecule E3 ligase ligands remains limited. Therefore, identifying novel E3 ligase ligands would expand the repertoire for PROTAC development. FEM1C, an E3 ligase that recognizes proteins with an R/K-X-R or R/K-X-X-R motif at the C-terminus, is a promising candidate for this purpose. In this study, we present the design and synthesis of a fluorescent probe ES148, exhibiting a Ki value of 1.6 ± 0.1 µM for FEM1C. Utilizing this fluorescent probe, we have established a robust fluorescence polarization (FP) based competition assay to characterize FEM1C ligands, with a Z' factor of 0.80 and a S/N ratio > 20 in a high-throughput format. Furthermore, we have validated binding affinities of FEM1C ligands using isothermal titration calorimetry, consistently corroborating the results from our FP assay. Thus, we anticipate that our FP competition assay will expedite the discovery of FEM1C ligands, offering new tools for PROTAC development.
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Affiliation(s)
- Emma K Seipp
- Department of Medicinal Chemistry and Molecular Pharmacology, Center for Cancer Research, Institute for Drug Discovery, Purdue University, 720 Clinic Drive, West Lafayette, IN 47907, United States
| | - Rong Huang
- Department of Medicinal Chemistry and Molecular Pharmacology, Center for Cancer Research, Institute for Drug Discovery, Purdue University, 720 Clinic Drive, West Lafayette, IN 47907, United States.
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Current Challenges in Small Molecule Proximity-Inducing Compound Development for Targeted Protein Degradation Using the Ubiquitin Proteasomal System. MOLECULES (BASEL, SWITZERLAND) 2022; 27:molecules27238119. [PMID: 36500212 PMCID: PMC9740444 DOI: 10.3390/molecules27238119] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 10/31/2022] [Revised: 11/14/2022] [Accepted: 11/18/2022] [Indexed: 11/23/2022]
Abstract
Bivalent proximity-inducing compounds represent a novel class of small molecule therapeutics with exciting potential and new challenges. The most prominent examples of such compounds are utilized in targeted protein degradation where E3 ligases are hijacked to recruit a substrate protein to the proteasome via ubiquitination. In this review we provide an overview of the current state of E3 ligases used in targeted protein degradation, their respective ligands as well as challenges and opportunities that present themselves with these compounds.
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Exploiting ELIOT for Scaffold-Repurposing Opportunities: TRIM33 a Possible Novel E3 Ligase to Expand the Toolbox for PROTAC Design. Int J Mol Sci 2022; 23:ijms232214218. [PMID: 36430693 PMCID: PMC9698485 DOI: 10.3390/ijms232214218] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/26/2022] [Revised: 11/11/2022] [Accepted: 11/15/2022] [Indexed: 11/19/2022] Open
Abstract
The field of targeted protein degradation, through the control of the ubiquitin-proteasome system (UPS), is progressing considerably; to exploit this new therapeutic modality, the proteolysis targeting chimera (PROTAC) technology was born. The opportunity to use PROTACs engaging of new E3 ligases that can hijack and control the UPS system could greatly extend the applicability of degrading molecules. To this end, here we show a potential application of the ELIOT (E3 LIgase pocketOme navigaTor) platform, previously published by this group, for a scaffold-repurposing strategy to identify new ligands for a novel E3 ligase, such as TRIM33. Starting from ELIOT, a case study of the cross-relationship using GRID Molecular Interaction Field (MIF) similarities between TRIM24 and TRIM33 binding sites was selected. Based on the assumption that similar pockets could bind similar ligands and considering that TRIM24 has 12 known co-crystalised ligands, we applied a scaffold-repurposing strategy for the identification of TRIM33 ligands exploiting the scaffold of TRIM24 ligands. We performed a deeper computational analysis to identify pocket similarities and differences, followed by docking and water analysis; selected ligands were synthesised and subsequently tested against TRIM33 via HTRF binding assay, and we obtained the first-ever X-ray crystallographic complexes of TRIM33α with three of the selected compounds.
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