1
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Xia Y, Pan X, Shen HB. A comprehensive survey on protein-ligand binding site prediction. Curr Opin Struct Biol 2024; 86:102793. [PMID: 38447285 DOI: 10.1016/j.sbi.2024.102793] [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: 12/20/2023] [Revised: 02/18/2024] [Accepted: 02/18/2024] [Indexed: 03/08/2024]
Abstract
Protein-ligand binding site prediction is critical for protein function annotation and drug discovery. Biological experiments are time-consuming and require significant equipment, materials, and labor resources. Developing accurate and efficient computational methods for protein-ligand interaction prediction is essential. Here, we summarize the key challenges associated with ligand binding site (LBS) prediction and introduce recently published methods from their input features, computational algorithms, and ligand types. Furthermore, we investigate the specificity of allosteric site identification as a particular LBS type. Finally, we discuss the prospective directions for machine learning-based LBS prediction in the near future.
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Affiliation(s)
- Ying Xia
- Institute of Image Processing and Pattern Recognition, Shanghai Jiao Tong University, and Key Laboratory of System Control and Information Processing, Ministry of Education of China, Shanghai 200240, China
| | - Xiaoyong Pan
- Institute of Image Processing and Pattern Recognition, Shanghai Jiao Tong University, and Key Laboratory of System Control and Information Processing, Ministry of Education of China, Shanghai 200240, China.
| | - Hong-Bin Shen
- Institute of Image Processing and Pattern Recognition, Shanghai Jiao Tong University, and Key Laboratory of System Control and Information Processing, Ministry of Education of China, Shanghai 200240, China.
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2
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Scrima S, Lambrughi M, Tiberti M, Fadda E, Papaleo E. ASM variants in the spotlight: A structure-based atlas for unraveling pathogenic mechanisms in lysosomal acid sphingomyelinase. Biochim Biophys Acta Mol Basis Dis 2024:167260. [PMID: 38782304 DOI: 10.1016/j.bbadis.2024.167260] [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: 12/14/2023] [Revised: 04/30/2024] [Accepted: 05/18/2024] [Indexed: 05/25/2024]
Abstract
Lysosomal acid sphingomyelinase (ASM), a critical enzyme in lipid metabolism encoded by the SMPD1 gene, plays a crucial role in sphingomyelin hydrolysis in lysosomes. ASM deficiency leads to acid sphingomyelinase deficiency, a rare genetic disorder with diverse clinical manifestations, and the protein can be found mutated in other diseases. We employed a structure-based framework to comprehensively understand the functional implications of ASM variants, integrating pathogenicity predictions with molecular insights derived from a molecular dynamics simulation in a lysosomal membrane environment. Our analysis, encompassing over 400 variants, establishes a structural atlas of missense variants of lysosomal ASM, associating mechanistic indicators with pathogenic potential. Our study highlights variants that influence structural stability or exert local and long-range effects at functional sites. To validate our predictions, we compared them to available experimental data on residual catalytic activity in 135 ASM variants. Notably, our findings also suggest applications of the resulting data for identifying cases suited for enzyme replacement therapy. This comprehensive approach enhances the understanding of ASM variants and provides valuable insights for potential therapeutic interventions.
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Affiliation(s)
- Simone Scrima
- Cancer Structural Biology, Danish Cancer Institute, 2100 Copenhagen, Denmark; Cancer Systems Biology, Section for Bioinformatics, Department of Health and Technology, Technical University of Denmark, 2800 Lyngby, Denmark
| | - Matteo Lambrughi
- Cancer Structural Biology, Danish Cancer Institute, 2100 Copenhagen, Denmark
| | - Matteo Tiberti
- Cancer Structural Biology, Danish Cancer Institute, 2100 Copenhagen, Denmark
| | - Elisa Fadda
- Department of Chemistry and Hamilton Institute, Maynooth University, Maynooth, co. Kildare, Ireland
| | - Elena Papaleo
- Cancer Structural Biology, Danish Cancer Institute, 2100 Copenhagen, Denmark; Cancer Systems Biology, Section for Bioinformatics, Department of Health and Technology, Technical University of Denmark, 2800 Lyngby, Denmark.
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3
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Tee WV, Berezovsky IN. Allosteric drugs: New principles and design approaches. Curr Opin Struct Biol 2024; 84:102758. [PMID: 38171188 DOI: 10.1016/j.sbi.2023.102758] [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: 09/29/2023] [Accepted: 11/30/2023] [Indexed: 01/05/2024]
Abstract
Focusing on an important biomedical implication of allostery - design of allosteric drugs, we describe characteristics of allosteric sites, effectors, and their modes of actions distinguishing them from the orthosteric counterparts and calling for new principles and protocols in the quests for allosteric drugs. We show the importance of considering both binding affinity and allosteric signaling in establishing the structure-activity relationships (SARs) toward design of allosteric effectors, arguing that pairs of allosteric sites and their effector ligands - the site-effector pairs - should be generated and adjusted simultaneously in the framework of what we call directed design protocol. Key ideas and approaches for designing allosteric effectors including reverse perturbation, targeted and agnostic analysis are also discussed here. Several promising computational approaches are highlighted, along with the need for and potential advantages of utilizing generative models to facilitate discovery/design of new allosteric drugs.
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Affiliation(s)
- Wei-Ven Tee
- Bioinformatics Institute (BII), Agency for Science, Technology and Research (A∗STAR), 30 Biopolis Street, #07-01, Matrix, Singapore 138671.
| | - Igor N Berezovsky
- Bioinformatics Institute (BII), Agency for Science, Technology and Research (A∗STAR), 30 Biopolis Street, #07-01, Matrix, Singapore 138671; Department of Biological Sciences (DBS), National University of Singapore (NUS), 8 Medical Drive, 117579, Singapore.
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4
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Li M, Lan X, Lu X, Zhang J. A Structure-Based Allosteric Modulator Design Paradigm. HEALTH DATA SCIENCE 2023; 3:0094. [PMID: 38487194 PMCID: PMC10904074 DOI: 10.34133/hds.0094] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 07/02/2023] [Accepted: 10/11/2023] [Indexed: 03/17/2024]
Abstract
Importance: Allosteric drugs bound to topologically distal allosteric sites hold a substantial promise in modulating therapeutic targets deemed undruggable at their orthosteric sites. Traditionally, allosteric modulator discovery has predominantly relied on serendipitous high-throughput screening. Nevertheless, the landscape has undergone a transformative shift due to recent advancements in our understanding of allosteric modulation mechanisms, coupled with a significant increase in the accessibility of allosteric structural data. These factors have extensively promoted the development of various computational methodologies, especially for machine-learning approaches, to guide the rational design of structure-based allosteric modulators. Highlights: We here presented a comprehensive structure-based allosteric modulator design paradigm encompassing 3 critical stages: drug target acquisition, allosteric binding site, and modulator discovery. The recent advances in computational methods in each stage are encapsulated. Furthermore, we delve into analyzing the successes and obstacles encountered in the rational design of allosteric modulators. Conclusion: The structure-based allosteric modulator design paradigm holds immense potential for the rational design of allosteric modulators. We hope that this review would heighten awareness of the use of structure-based computational methodologies in advancing the field of allosteric drug discovery.
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Affiliation(s)
- Mingyu Li
- College of Pharmacy,
Ningxia Medical University, Yinchuan, NingxiaHui Autonomous Region, China
- State Key Laboratory of Medical Genomics, National Research Center for Translational Medicine at Shanghai, Ruijin Hospital,
Shanghai Jiao Tong University School of Medicine, Shanghai, China
- Medicinal Chemistry and Bioinformatics Center,
Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China
| | - Xiaobin Lan
- College of Pharmacy,
Ningxia Medical University, Yinchuan, NingxiaHui Autonomous Region, China
- Medicinal Chemistry and Bioinformatics Center,
Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China
| | - Xun Lu
- College of Pharmacy,
Ningxia Medical University, Yinchuan, NingxiaHui Autonomous Region, China
- State Key Laboratory of Medical Genomics, National Research Center for Translational Medicine at Shanghai, Ruijin Hospital,
Shanghai Jiao Tong University School of Medicine, Shanghai, China
- Medicinal Chemistry and Bioinformatics Center,
Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China
| | - Jian Zhang
- College of Pharmacy,
Ningxia Medical University, Yinchuan, NingxiaHui Autonomous Region, China
- State Key Laboratory of Medical Genomics, National Research Center for Translational Medicine at Shanghai, Ruijin Hospital,
Shanghai Jiao Tong University School of Medicine, Shanghai, China
- Medicinal Chemistry and Bioinformatics Center,
Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China
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5
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Godbole SS, Dokholyan NV. Allosteric regulation of kinase activity in living cells. eLife 2023; 12:RP90574. [PMID: 37943025 PMCID: PMC10635643 DOI: 10.7554/elife.90574] [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: 11/10/2023] Open
Abstract
The dysregulation of protein kinases is associated with multiple diseases due to the kinases' involvement in a variety of cell signaling pathways. Manipulating protein kinase function, by controlling the active site, is a promising therapeutic and investigative strategy to mitigate and study diseases. Kinase active sites share structural similarities, making it difficult to specifically target one kinase, and allosteric control allows specific regulation and study of kinase function without directly targeting the active site. Allosteric sites are distal to the active site but coupled via a dynamic network of inter-atomic interactions between residues in the protein. Establishing an allosteric control over a kinase requires understanding the allosteric wiring of the protein. Computational techniques offer effective and inexpensive mapping of the allosteric sites on a protein. Here, we discuss the methods to map and regulate allosteric communications in proteins, and strategies to establish control over kinase functions in live cells and organisms. Protein molecules, or 'sensors,' are engineered to function as tools to control allosteric activity of the protein as these sensors have high spatiotemporal resolution and help in understanding cell phenotypes after immediate activation or inactivation of a kinase. Traditional methods used to study protein functions, such as knockout, knockdown, or mutation, cannot offer a sufficiently high spatiotemporal resolution. We discuss the modern repertoire of tools to regulate protein kinases as we enter a new era in deciphering cellular signaling and developing novel approaches to treat diseases associated with signal dysregulation.
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Affiliation(s)
| | - Nikolay V Dokholyan
- Department of Pharmacology, Penn State College of MedicineHersheyUnited States
- Department of Biomedical Engineering, Penn State University, University ParkHersheyUnited States
- Department of Engineering Science and Mechanics, Penn State University, University ParkHersheyUnited States
- Department of Biochemistry & Molecular Biology, Penn State College of MedicineHersheyUnited States
- Department of Chemistry, Penn State University, University ParkHersheyUnited States
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6
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Godbole S, Dokholyan NV. Allosteric regulation of kinase activity in living cells. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.07.19.549709. [PMID: 37503033 PMCID: PMC10370130 DOI: 10.1101/2023.07.19.549709] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/29/2023]
Abstract
The dysregulation of protein kinases is associated with multiple diseases due to the kinases' involvement in a variety of cell signaling pathways. Manipulating protein kinase function, by controlling the active site, is a promising therapeutic and investigative strategy to mitigate and study diseases. Kinase active sites share structural similarities making it difficult to specifically target one kinase, allosteric control allows specific regulation and study of kinase function without directly targeting the active site. Allosteric sites are distal to the active site but coupled via a dynamic network of inter-atomic interactions between residues in the protein. Establishing an allosteric control over a kinase requires understanding the allosteric wiring of the protein. Computational techniques offer effective and inexpensive mapping of the allosteric sites on a protein. Here, we discuss methods to map and regulate allosteric communications in proteins, and strategies to establish control over kinase functions in live cells and organisms. Protein molecules, or "sensors" are engineered to function as tools to control allosteric activity of the protein as these sensors have high spatiotemporal resolution and help in understanding cell phenotypes after immediate activation or inactivation of a kinase. Traditional methods used to study protein functions, such as knockout, knockdown, or mutation, cannot offer a sufficiently high spatiotemporal resolution. We discuss the modern repertoire of tools to regulate protein kinases as we enter a new era in deciphering cellular signaling and developing novel approaches to treat diseases associated with signal dysregulation.
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Affiliation(s)
- Shivani Godbole
- Department of Pharmacology, Penn State College of Medicine, Hershey, PA 17033-0850, USA
| | - Nikolay V. Dokholyan
- Department of Pharmacology, Penn State College of Medicine, Hershey, PA 17033-0850, USA
- Department of Biomedical Engineering, Penn State University, University Park, PA 16802, USA
- Department of Engineering Science and Mechanics, Penn State University, University Park, PA 16802, USA
- Department of Biochemistry & Molecular Biology, Penn State College of Medicine, Hershey, PA 17033-0850, USA
- Department of Chemistry, Penn State University, University Park, PA 16802, USA
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7
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Naz S, Liu P, Farooq U, Ma H. Insight into de-regulation of amino acid feedback inhibition: a focus on structure analysis method. Microb Cell Fact 2023; 22:161. [PMID: 37612753 PMCID: PMC10464499 DOI: 10.1186/s12934-023-02178-z] [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: 06/07/2023] [Accepted: 08/13/2023] [Indexed: 08/25/2023] Open
Abstract
Regulation of amino acid's biosynthetic pathway is of significant importance to maintain homeostasis and cell functions. Amino acids regulate their biosynthetic pathway by end-product feedback inhibition of enzymes catalyzing committed steps of a pathway. Discovery of new feedback resistant enzyme variants to enhance industrial production of amino acids is a key objective in industrial biotechnology. Deregulation of feedback inhibition has been achieved for various enzymes using in vitro and in silico mutagenesis techniques. As enzyme's function, its substrate binding capacity, catalysis activity, regulation and stability are dependent on its structural characteristics, here, we provide detailed structural analysis of all feedback sensitive enzyme targets in amino acid biosynthetic pathways. Current review summarizes information regarding structural characteristics of various enzyme targets and effect of mutations on their structures and functions especially in terms of deregulation of feedback inhibition. Furthermore, applicability of various experimental as well as computational mutagenesis techniques to accomplish feedback resistance has also been discussed in detail to have an insight into various aspects of research work reported in this particular field of study.
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Affiliation(s)
- Sadia Naz
- Biodesign Center, Tianjin Institute of Industrial Biotechnology, Chinese Academy of Sciences, Tianjin, 300308, China
| | - Pi Liu
- Biodesign Center, Tianjin Institute of Industrial Biotechnology, Chinese Academy of Sciences, Tianjin, 300308, China
| | - Umar Farooq
- Department of Chemistry, COMSATS University Islamabad, Abbottabad Campus, Islamabad, 22060, Pakistan
| | - Hongwu Ma
- Biodesign Center, Tianjin Institute of Industrial Biotechnology, Chinese Academy of Sciences, Tianjin, 300308, China.
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8
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Pandey P, Ghimire S, Wu B, Alexov E. On the linkage of thermodynamics and pathogenicity. Curr Opin Struct Biol 2023; 80:102572. [PMID: 36965249 PMCID: PMC10239362 DOI: 10.1016/j.sbi.2023.102572] [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: 01/25/2023] [Revised: 02/16/2023] [Accepted: 02/21/2023] [Indexed: 03/27/2023]
Abstract
This review outlines the effect of disease-causing mutations on proteins' thermodynamics. Two major thermodynamics quantities, which are essential for structural integrity, the folding and binding free energy changes caused by missense mutations, are considered. It is emphasized that disease effects in case of complex diseases may originate from several mutations over several genes, while monogenic diseases are caused by mutation is a single gene. Nevertheless, in both cases it is shown that pathogenic mutations cause larger perturbations of the above-mentioned thermodynamics quantities as compared with the benign mutations. Recent works demonstrating the effect of pathogenic mutations on the above-mentioned thermodynamics quantities, as well as on structural dynamics and allosteric pathways, are reviewed.
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Affiliation(s)
- Preeti Pandey
- Department of Physics and Astronomy, Clemson University, Clemson, SC 29634, USA
| | - Sanjeev Ghimire
- Department of Physics and Astronomy, Clemson University, Clemson, SC 29634, USA
| | - Bohua Wu
- Department of Physics and Astronomy, Clemson University, Clemson, SC 29634, USA
| | - Emil Alexov
- Department of Physics and Astronomy, Clemson University, Clemson, SC 29634, USA.
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9
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Pan-cancer clinical impact of latent drivers from double mutations. Commun Biol 2023; 6:202. [PMID: 36808143 PMCID: PMC9941481 DOI: 10.1038/s42003-023-04519-5] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/22/2021] [Accepted: 01/23/2023] [Indexed: 02/22/2023] Open
Abstract
Here, we discover potential 'latent driver' mutations in cancer genomes. Latent drivers have low frequencies and minor observable translational potential. As such, to date they have escaped identification. Their discovery is important, since when paired in cis, latent driver mutations can drive cancer. Our comprehensive statistical analysis of the pan-cancer mutation profiles of ~60,000 tumor sequences from the TCGA and AACR-GENIE cohorts identifies significantly co-occurring potential latent drivers. We observe 155 same gene double mutations of which 140 individual components are cataloged as latent drivers. Evaluation of cell lines and patient-derived xenograft response data to drug treatment indicate that in certain genes double mutations may have a prominent role in increasing oncogenic activity, hence obtaining a better drug response, as in PIK3CA. Taken together, our comprehensive analyses indicate that same-gene double mutations are exceedingly rare phenomena but are a signature for some cancer types, e.g., breast, and lung cancers. The relative rarity of doublets can be explained by the likelihood of strong signals resulting in oncogene-induced senescence, and by doublets consisting of non-identical single residue components populating the background mutational load, thus not identified.
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10
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Tan ZW, Tee WV, Guarnera E, Berezovsky IN. AlloMAPS 2: allosteric fingerprints of the AlphaFold and Pfam-trRosetta predicted structures for engineering and design. Nucleic Acids Res 2022; 51:D345-D351. [PMID: 36169226 PMCID: PMC9825619 DOI: 10.1093/nar/gkac828] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/25/2022] [Revised: 08/26/2022] [Accepted: 09/15/2022] [Indexed: 01/29/2023] Open
Abstract
AlloMAPS 2 is an update of the Allosteric Mutation Analysis and Polymorphism of Signalling database, which contains data on allosteric communication obtained for predicted structures in the AlphaFold database (AFDB) and trRosetta-predicted Pfam domains. The data update contains Allosteric Signalling Maps (ASMs) and Allosteric Probing Maps (APMs) quantifying allosteric effects of mutations and of small probe binding, respectively. To ensure quality of the ASMs and APMs, we performed careful and accurate selection of protein sets containing high-quality predicted structures in both databases for each organism/structure, and the data is available for browsing and download. The data for remaining structures are available for download and should be used at user's discretion and responsibility. We believe these massive data can facilitate both diagnostics and drug design within the precision medicine paradigm. Specifically, it can be instrumental in the analysis of allosteric effects of pathological and rescue mutations, providing starting points for fragment-based design of allosteric effectors. The exhaustive character of allosteric signalling and probing fingerprints will be also useful in future developments of corresponding machine learning applications. The database is freely available at: http://allomaps.bii.a-star.edu.sg.
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Affiliation(s)
- Zhen Wah Tan
- Bioinformatics Institute (BII), Agency for Science, Technology and Research (A*STAR), 30 Biopolis Street, #07-01, Matrix, 138671, Singapore
| | - Wei-Ven Tee
- Bioinformatics Institute (BII), Agency for Science, Technology and Research (A*STAR), 30 Biopolis Street, #07-01, Matrix, 138671, Singapore
| | - Enrico Guarnera
- Bioinformatics Institute (BII), Agency for Science, Technology and Research (A*STAR), 30 Biopolis Street, #07-01, Matrix, 138671, Singapore
| | - Igor N Berezovsky
- To whom correspondence should be addressed. Tel: +65 6478 8269; Fax: +65 6478 9047;
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11
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Nussinov R, Zhang M, Maloney R, Liu Y, Tsai CJ, Jang H. Allostery: Allosteric Cancer Drivers and Innovative Allosteric Drugs. J Mol Biol 2022; 434:167569. [PMID: 35378118 PMCID: PMC9398924 DOI: 10.1016/j.jmb.2022.167569] [Citation(s) in RCA: 20] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/03/2022] [Revised: 03/11/2022] [Accepted: 03/25/2022] [Indexed: 01/12/2023]
Abstract
Here, we discuss the principles of allosteric activating mutations, propagation downstream of the signals that they prompt, and allosteric drugs, with examples from the Ras signaling network. We focus on Abl kinase where mutations shift the landscape toward the active, imatinib binding-incompetent conformation, likely resulting in the high affinity ATP outcompeting drug binding. Recent pharmacological innovation extends to allosteric inhibitor (GNF-5)-linked PROTAC, targeting Bcr-Abl1 myristoylation site, and broadly, allosteric heterobifunctional degraders that destroy targets, rather than inhibiting them. Designed chemical linkers in bifunctional degraders can connect the allosteric ligand that binds the target protein and the E3 ubiquitin ligase warhead anchor. The physical properties and favored conformational state of the engineered linker can precisely coordinate the distance and orientation between the target and the recruited E3. Allosteric PROTACs, noncompetitive molecular glues, and bitopic ligands, with covalent links of allosteric ligands and orthosteric warheads, increase the effective local concentration of productively oriented and placed ligands. Through covalent chemical or peptide linkers, allosteric drugs can collaborate with competitive drugs, degrader anchors, or other molecules of choice, driving innovative drug discovery.
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Affiliation(s)
- Ruth Nussinov
- Computational Structural Biology Section, Frederick National Laboratory for Cancer Research in the Laboratory of Cancer Immunometabolism, National Cancer Institute, Frederick, MD 21702, USA; Department of Human Molecular Genetics and Biochemistry, Sackler School of Medicine, Tel Aviv University, Tel Aviv 69978, Israel.
| | - Mingzhen Zhang
- Computational Structural Biology Section, Frederick National Laboratory for Cancer Research in the Laboratory of Cancer Immunometabolism, National Cancer Institute, Frederick, MD 21702, USA
| | - Ryan Maloney
- Computational Structural Biology Section, Frederick National Laboratory for Cancer Research in the Laboratory of Cancer Immunometabolism, National Cancer Institute, Frederick, MD 21702, USA
| | - Yonglan Liu
- Computational Structural Biology Section, Frederick National Laboratory for Cancer Research in the Laboratory of Cancer Immunometabolism, National Cancer Institute, Frederick, MD 21702, USA
| | - Chung-Jung Tsai
- Computational Structural Biology Section, Frederick National Laboratory for Cancer Research in the Laboratory of Cancer Immunometabolism, National Cancer Institute, Frederick, MD 21702, USA
| | - Hyunbum Jang
- Computational Structural Biology Section, Frederick National Laboratory for Cancer Research in the Laboratory of Cancer Immunometabolism, National Cancer Institute, Frederick, MD 21702, USA
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12
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Wah Tan Z, Tee WV, Berezovsky IN. Learning about allosteric drugs and ways to design them. J Mol Biol 2022; 434:167692. [PMID: 35738428 DOI: 10.1016/j.jmb.2022.167692] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/27/2022] [Revised: 05/23/2022] [Accepted: 06/15/2022] [Indexed: 11/16/2022]
Abstract
While the accelerating quest for precision medicine requires new individually targeting and selective drugs, and the ability to work with so-called undruggable targets, the realm of allosteric drugs meeting this need remains largely uncharted. Generalizing the observations on two major drug targets with widely observed inherent allostery, GPCRs and kinases, we describe and discuss basic allosteric modes of action that are universally applicable in all types of structures and functions. Using examples of Class A GPCRs and CMGC protein kinases, we show how Allosteric Signalling and Probing Fingerprints can be used to identify potential allosteric sites and reveal effector-leads that may serve as a starting point for the development of allosteric drugs targeting these regulatory sites. A set of distinct characteristics of allosteric ligands was established, which highlights the versatility of their design and make them advantageous before their orthosteric counterparts in personalized medicine. We argue that rational design of allosteric drugs should begin with the search for latent sites or design of non-natural binding sites followed by fragment-based design of allosteric ligands and by the mutual adjustment of the site-ligand pair in order to achieve required effects. On the basis of the perturbative nature and reversibility of allosteric communication, we propose a generic protocol for computational design of allosteric effectors, enabling also the allosteric tuning of biologics, in obtaining allosteric control over protein functions.
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Affiliation(s)
- Zhen Wah Tan
- Bioinformatics Institute (BII), Agency for Science, Technology and Research (A*STAR), 30 Biopolis Street, #07-01, Matrix, Singapore 138671
| | - Wei-Ven Tee
- Bioinformatics Institute (BII), Agency for Science, Technology and Research (A*STAR), 30 Biopolis Street, #07-01, Matrix, Singapore 138671
| | - Igor N Berezovsky
- Bioinformatics Institute (BII), Agency for Science, Technology and Research (A*STAR), 30 Biopolis Street, #07-01, Matrix, Singapore 138671; Department of Biological Sciences (DBS), National University of Singapore (NUS), 8 Medical Drive, 117579, Singapore.
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13
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Qiu Q, Abis G, Mattingly-Peck F, Lynham S, Fraternali F, Conte MR. Allosteric regulation of the soluble epoxide hydrolase by nitro fatty acids using a combined experimental and computational approach. J Mol Biol 2022; 434:167600. [PMID: 35460669 DOI: 10.1016/j.jmb.2022.167600] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/14/2022] [Revised: 03/31/2022] [Accepted: 04/17/2022] [Indexed: 11/18/2022]
Abstract
The human soluble epoxide hydrolase (hsEH) is a key regulator of epoxy fatty acid (EpFA) metabolism. Inhibition of sEH can maintain endogenous levels of beneficial EpFAs and reduce the levels of their corresponding diol products, thus ameliorating a variety of pathological conditions including cardiovascular, central nervous system and metabolic diseases. The quest for orthosteric drugs that bind directly to the catalytic crevice of hsEH has been prolonged and sustained over the past decades, but the disappointing outcome of clinical trials to date warrants alternative pharmacological approaches. Previously, we have shown that hsEH can be allosterically inhibited by the endogenous electrophilic lipid 15-deoxy-Δ12,14-Prostaglandin-J2, via covalent adduction to two cysteines, C423 and C522. In this study, we explore the properties and behaviour of three electrophilic lipids belonging to the class of the nitro fatty acids, namely 9- and 10-nitrooleate and 10-nitrolinoleate. Biochemical and biophysical investigations revealed that, in addition to C423 and C522, nitro fatty acids can covalently bind to additional nucleophilic residues in hsEH C-terminal domain (CTD), two of which predicted in this study to be latent allosteric sites. Systematic mapping of the protein mutational space and evaluation of possible propagation pathways delineated selected residues, both in the allosteric patches and in other regions of the enzyme, envisaged to play a role on allosteric signalling. The responses elicited by the ligands on the covalent adduction sites supports future fragment-based design studies of new allosteric effectors for hsEH with increased efficacy and selectivity.
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Affiliation(s)
- Qiongju Qiu
- Randall Centre for Cell and Molecular Biophysics, School of Basic and Medical Biosciences, King's College London, London SE1 1UL, UK
| | - Giancarlo Abis
- Randall Centre for Cell and Molecular Biophysics, School of Basic and Medical Biosciences, King's College London, London SE1 1UL, UK
| | - Florence Mattingly-Peck
- Randall Centre for Cell and Molecular Biophysics, School of Basic and Medical Biosciences, King's College London, London SE1 1UL, UK
| | - Steven Lynham
- Proteomics Facility, Centre of Excellence for Mass Spectrometry, The James Black Centre, King's College London, London SE5 9NU, UK
| | - Franca Fraternali
- Randall Centre for Cell and Molecular Biophysics, School of Basic and Medical Biosciences, King's College London, London SE1 1UL, UK.
| | - Maria R Conte
- Randall Centre for Cell and Molecular Biophysics, School of Basic and Medical Biosciences, King's College London, London SE1 1UL, UK.
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14
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Tee WV, Wah Tan Z, Guarnera E, Berezovsky IN. Conservation and diversity in allosteric fingerprints of proteins for evolutionary-inspired engineering and design. J Mol Biol 2022; 434:167577. [PMID: 35395233 DOI: 10.1016/j.jmb.2022.167577] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/05/2022] [Revised: 03/30/2022] [Accepted: 03/30/2022] [Indexed: 11/26/2022]
Abstract
Hand-in-hand work of physics and evolution delivered protein universe with diversity of forms, sizes, and functions. Pervasiveness and advantageous traits of allostery made it an important component of the protein function regulation, calling for thorough investigation of its structural determinants and evolution. Learning directly from nature, we explored here allosteric communication in several major folds and repeat proteins, including α/β and β-barrels, β-propellers, Ig-like fold, ankyrin and α/β leucine-rich repeat proteins, which provide structural platforms for many different enzymatic and signalling functions. We obtained a picture of conserved allosteric communication characteristic in different fold types, modifications of the structure-driven signalling patterns via sequence-determined divergence to specific functions, as well as emergence and potential diversification of allosteric regulation in multi-domain proteins and oligomeric assemblies. Our observations will be instrumental in facilitating the engineering and de novo design of proteins with allosterically regulated functions, including development of therapeutic biologics. In particular, results described here may guide the identification of the optimal structural platforms (e.g. fold type, size, and oligomerization states) and the types of diversifications/perturbations, such as mutations, effector binding, and order-disorder transition. The tunable allosteric linkage across distant regions can be used as a pivotal component in the design/engineering of modular biological systems beyond the traditional scaffolding function.
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Affiliation(s)
- Wei-Ven Tee
- Bioinformatics Institute (BII), Agency for Science, Technology and Research (A*STAR), 30 Biopolis Street, #07-01, Matrix, Singapore 138671
| | - Zhen Wah Tan
- Bioinformatics Institute (BII), Agency for Science, Technology and Research (A*STAR), 30 Biopolis Street, #07-01, Matrix, Singapore 138671
| | - Enrico Guarnera
- Bioinformatics Institute (BII), Agency for Science, Technology and Research (A*STAR), 30 Biopolis Street, #07-01, Matrix, Singapore 138671
| | - Igor N Berezovsky
- Bioinformatics Institute (BII), Agency for Science, Technology and Research (A*STAR), 30 Biopolis Street, #07-01, Matrix, Singapore 138671; Department of Biological Sciences (DBS), National University of Singapore (NUS), 8 Medical Drive, Singapore 117597.
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15
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Tastan Bishop Ö, Mutemi Musyoka T, Barozi V. Allostery and missense mutations as intermittently linked promising aspects of modern computational drug discovery. J Mol Biol 2022; 434:167610. [DOI: 10.1016/j.jmb.2022.167610] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/01/2022] [Revised: 04/21/2022] [Accepted: 04/22/2022] [Indexed: 12/15/2022]
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16
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Xiao F, Zhou Z, Song X, Gan M, Long J, Verkhivker G, Hu G. Dissecting mutational allosteric effects in alkaline phosphatases associated with different Hypophosphatasia phenotypes: An integrative computational investigation. PLoS Comput Biol 2022; 18:e1010009. [PMID: 35320273 PMCID: PMC8979438 DOI: 10.1371/journal.pcbi.1010009] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/22/2021] [Revised: 04/04/2022] [Accepted: 03/10/2022] [Indexed: 11/18/2022] Open
Abstract
Hypophosphatasia (HPP) is a rare inherited disorder characterized by defective bone mineralization and is highly variable in its clinical phenotype. The disease occurs due to various loss-of-function mutations in ALPL, the gene encoding tissue-nonspecific alkaline phosphatase (TNSALP). In this work, a data-driven and biophysics-based approach is proposed for the large-scale analysis of ALPL mutations-from nonpathogenic to severe HPPs. By using a pipeline of synergistic approaches including sequence-structure analysis, network modeling, elastic network models and atomistic simulations, we characterized allosteric signatures and effects of the ALPL mutations on protein dynamics and function. Statistical analysis of molecular features computed for the ALPL mutations showed a significant difference between the control, mild and severe HPP phenotypes. Molecular dynamics simulations coupled with protein structure network analysis were employed to analyze the effect of single-residue variation on conformational dynamics of TNSALP dimers, and the developed machine learning model suggested that the topological network parameters could serve as a robust indicator of severe mutations. The results indicated that the severity of disease-associated mutations is often linked with mutation-induced modulation of allosteric communications in the protein. This study suggested that ALPL mutations associated with mild and more severe HPPs can exert markedly distinct effects on the protein stability and long-range network communications. By linking the disease phenotypes with dynamic and allosteric molecular signatures, the proposed integrative computational approach enabled to characterize and quantify the allosteric effects of ALPL mutations and role of allostery in the pathogenesis of HPPs.
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Affiliation(s)
- Fei Xiao
- Center for Systems Biology, Department of Bioinformatics, School of Biology and Basic Medical Sciences, Soochow University, Suzhou, China
| | - Ziyun Zhou
- Center for Systems Biology, Department of Bioinformatics, School of Biology and Basic Medical Sciences, Soochow University, Suzhou, China
| | - Xingyu Song
- Department of Chemistry, Multiscale Research Institute of Complex Systems and Institute of Biomedical Sciences, Fudan University, Shanghai, China
| | - Mi Gan
- Center for Systems Biology, Department of Bioinformatics, School of Biology and Basic Medical Sciences, Soochow University, Suzhou, China
| | - Jie Long
- Center for Systems Biology, Department of Bioinformatics, School of Biology and Basic Medical Sciences, Soochow University, Suzhou, China
| | - Gennady Verkhivker
- Department of Computational and Data Sciences, Chapman University, One University Drive, Orange, California, United States of America
- Department of Biomedical and Pharmaceutical Sciences, Chapman University Pharmacy School 9401 Jeronimo Rd, Irvine, California, United States of America
| | - Guang Hu
- Center for Systems Biology, Department of Bioinformatics, School of Biology and Basic Medical Sciences, Soochow University, Suzhou, China
- * E-mail:
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17
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Ni D, Liu Y, Kong R, Yu Z, Lu S, Zhang J. Computational elucidation of allosteric communication in proteins for allosteric drug design. Drug Discov Today 2022; 27:2226-2234. [DOI: 10.1016/j.drudis.2022.03.012] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/25/2021] [Revised: 01/22/2022] [Accepted: 03/17/2022] [Indexed: 02/07/2023]
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18
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Chen J, Vishweshwaraiah YL, Dokholyan NV. Design and engineering of allosteric communications in proteins. Curr Opin Struct Biol 2022; 73:102334. [PMID: 35180676 PMCID: PMC8957532 DOI: 10.1016/j.sbi.2022.102334] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/11/2021] [Revised: 12/30/2021] [Accepted: 01/05/2022] [Indexed: 01/26/2023]
Abstract
Allostery in proteins plays an important role in regulating protein activities and influencing many biological processes such as gene expression, enzyme catalysis, and cell signaling. The process of allostery takes place when a signal detected at a site on a protein is transmitted via a mechanical pathway to a functional site and, thus, influences its activity. The pathway of allosteric communication consists of amino acids that form a network with covalent and non-covalent bonds. By mutating residues in this allosteric network, protein engineers have successfully established novel allosteric pathways to achieve desired properties in the target protein. In this review, we highlight the most recent and state-of-the-art techniques for allosteric communication engineering. We also discuss the challenges that need to be overcome and future directions for engineering protein allostery.
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Affiliation(s)
- Jiaxing Chen
- Department of Pharmacology, Penn State College of Medicine, Hershey, PA, 17033-0850, USA. https://twitter.com/JiaxingChen18
| | - Yashavantha L Vishweshwaraiah
- Department of Pharmacology, Penn State College of Medicine, Hershey, PA, 17033-0850, USA. https://twitter.com/IAmYashHegde
| | - Nikolay V Dokholyan
- Department of Pharmacology, Penn State College of Medicine, Hershey, PA, 17033-0850, USA; Department of Biochemistry & Molecular Biology, Penn State College of Medicine, Hershey, PA, 17033-0850, USA; Department of Chemistry, Pennsylvania State University, University Park, PA, 16802, USA; Department of Biomedical Engineering, Pennsylvania State University, University Park, PA, 16802, USA.
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19
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Tan ZW, Tee WV, Samsudin F, Guarnera E, Bond PJ, Berezovsky IN. Allosteric perspective on the mutability and druggability of the SARS-CoV-2 Spike protein. Structure 2022; 30:590-607.e4. [PMID: 35063064 PMCID: PMC8772014 DOI: 10.1016/j.str.2021.12.011] [Citation(s) in RCA: 20] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/02/2021] [Revised: 11/03/2021] [Accepted: 12/22/2021] [Indexed: 12/22/2022]
Abstract
Recent developments in the SARS-CoV-2 pandemic point to its inevitable transformation into an endemic disease, urging both refinement of diagnostics for emerging variants of concern (VOCs) and design of variant-specific drugs in addition to vaccine adjustments. Exploring the structure and dynamics of the SARS-CoV-2 Spike protein, we argue that the high-mutability characteristic of RNA viruses coupled with the remarkable flexibility and dynamics of viral proteins result in a substantial involvement of allosteric mechanisms. While allosteric effects of mutations should be considered in predictions and diagnostics of new VOCs, allosteric drugs advantageously avoid escape mutations via non-competitive inhibition originating from alternative distal locations. The exhaustive allosteric signaling and probing maps presented herein provide a comprehensive picture of allostery in the spike protein, making it possible to locate potential mutations that could work as new VOC “drivers” and to determine binding patches that may be targeted by newly developed allosteric drugs.
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20
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Fan J, Liu Y, Kong R, Ni D, Yu Z, Lu S, Zhang J. Harnessing Reversed Allosteric Communication: A Novel Strategy for Allosteric Drug Discovery. J Med Chem 2021; 64:17728-17743. [PMID: 34878270 DOI: 10.1021/acs.jmedchem.1c01695] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/12/2022]
Abstract
Allostery is a fundamental and extensive mechanism of intramolecular signal transmission. Allosteric drugs possess several unique pharmacological advantages over traditional orthosteric drugs, including greater selectivity, better physicochemical properties, and lower off-target toxicity. However, owing to the complexity of allosteric regulation, experimental approaches for the development of allosteric modulators are traditionally serendipitous. Recently, the reversed allosteric communication theory has been proposed, providing a feasible tool for the unbiased detection of allosteric sites. Herein, we review the latest research on the reversed allosteric communication effect using the examples of sirtuin 6, epidermal growth factor receptor, 3-phosphoinositide-dependent protein kinase 1, and Related to A and C kinases (RAC) serine/threonine protein kinase B and recapitulate the methodologies of reversed allosteric communication strategy. The novel reversed allosteric communication strategy greatly expands the horizon of allosteric site identification and allosteric mechanism exploration and is expected to accelerate an end-to-end framework for drug discovery.
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Affiliation(s)
- Jigang Fan
- College of Pharmacy, Ningxia Medical University, Yinchuan, Ningxia Hui Autonomous Region 750004, China.,State Key Laboratory of Oncogenes and Related Genes, Key Laboratory of Cell Differentiation and Apoptosis of Chinese Ministry of Education, Shanghai Jiao Tong University, School of Medicine, Shanghai 200025, China.,Zhiyuan Innovative Research Center, Shanghai Jiao Tong University, Shanghai 200240, China
| | - Yaqin Liu
- Medicinal Chemistry and Bioinformatics Center, Shanghai Jiao Tong University, School of Medicine, Shanghai 200025, China
| | - Ren Kong
- Institute of Bioinformatics and Medical Engineering, School of Electrical and Information Engineering, Jiangsu University of Technology, Changzhou 213001, China
| | - Duan Ni
- The Charles Perkins Centre, University of Sydney, Sydney, New South Wales 2006, Australia
| | | | - Shaoyong Lu
- College of Pharmacy, Ningxia Medical University, Yinchuan, Ningxia Hui Autonomous Region 750004, China.,State Key Laboratory of Oncogenes and Related Genes, Key Laboratory of Cell Differentiation and Apoptosis of Chinese Ministry of Education, Shanghai Jiao Tong University, School of Medicine, Shanghai 200025, China.,Medicinal Chemistry and Bioinformatics Center, Shanghai Jiao Tong University, School of Medicine, Shanghai 200025, China
| | - Jian Zhang
- College of Pharmacy, Ningxia Medical University, Yinchuan, Ningxia Hui Autonomous Region 750004, China.,State Key Laboratory of Oncogenes and Related Genes, Key Laboratory of Cell Differentiation and Apoptosis of Chinese Ministry of Education, Shanghai Jiao Tong University, School of Medicine, Shanghai 200025, China.,Medicinal Chemistry and Bioinformatics Center, Shanghai Jiao Tong University, School of Medicine, Shanghai 200025, China.,School of Pharmaceutical Sciences, Zhengzhou University, Zhengzhou 450001, China
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21
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Nussinov R, Tsai CJ, Jang H. Signaling in the crowded cell. Curr Opin Struct Biol 2021; 71:43-50. [PMID: 34218161 PMCID: PMC8648894 DOI: 10.1016/j.sbi.2021.05.009] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/31/2021] [Revised: 05/05/2021] [Accepted: 05/26/2021] [Indexed: 12/11/2022]
Abstract
High-resolution technologies have clarified some of the principles underlying cellular actions. However, understanding how cells receive, communicate, and respond to signals is still challenging. Questions include how efficient regulation of assemblies, which execute cell actions at the nanoscales, transmits productively at micrometer scales, especially considering the crowded environment, and how the cell organization makes it happen. Here, we describe how cells can navigate long-range diffusion-controlled signaling via association/dissociation of spatially proximal entities. Dynamic clusters can span the cell, engaging in most signaling steps. Effective local concentration, allostery, scaffolding, affinities, and the chemical and mechanical properties of the macromolecules and the environment play key roles. Signaling strength and duration matter, for example, deciding if a mutation promotes cancer or developmental syndromes.
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Affiliation(s)
- Ruth Nussinov
- Computational Structural Biology Section, Frederick National Laboratory for Cancer Research in the Laboratory of Cancer Immunometabolism, National Cancer Institute, Frederick, MD 21702, USA; Department of Human Molecular Genetics and Biochemistry, Sackler School of Medicine, Tel Aviv University, Tel Aviv 69978, Israel.
| | - Chung-Jung Tsai
- Computational Structural Biology Section, Frederick National Laboratory for Cancer Research in the Laboratory of Cancer Immunometabolism, National Cancer Institute, Frederick, MD 21702, USA
| | - Hyunbum Jang
- Computational Structural Biology Section, Frederick National Laboratory for Cancer Research in the Laboratory of Cancer Immunometabolism, National Cancer Institute, Frederick, MD 21702, USA
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22
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Qiu Y, Wang Y, Chai Z, Ni D, Li X, Pu J, Chen J, Zhang J, Lu S, Lv C, Ji M. Targeting RAS phosphorylation in cancer therapy: Mechanisms and modulators. Acta Pharm Sin B 2021; 11:3433-3446. [PMID: 34900528 PMCID: PMC8642438 DOI: 10.1016/j.apsb.2021.02.014] [Citation(s) in RCA: 20] [Impact Index Per Article: 6.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/26/2020] [Revised: 01/26/2021] [Accepted: 02/16/2021] [Indexed: 12/17/2022] Open
Abstract
RAS, a member of the small GTPase family, functions as a binary switch by shifting between inactive GDP-loaded and active GTP-loaded state. RAS gain-of-function mutations are one of the leading causes in human oncogenesis, accounting for ∼19% of the global cancer burden. As a well-recognized target in malignancy, RAS has been intensively studied in the past decades. Despite the sustained efforts, many failures occurred in the earlier exploration and resulted in an ‘undruggable’ feature of RAS proteins. Phosphorylation at several residues has been recently determined as regulators for wild-type and mutated RAS proteins. Therefore, the development of RAS inhibitors directly targeting the RAS mutants or towards upstream regulatory kinases supplies a novel direction for tackling the anti-RAS difficulties. A better understanding of RAS phosphorylation can contribute to future therapeutic strategies. In this review, we comprehensively summarized the current advances in RAS phosphorylation and provided mechanistic insights into the signaling transduction of associated pathways. Importantly, the preclinical and clinical success in developing anti-RAS drugs targeting the upstream kinases and potential directions of harnessing allostery to target RAS phosphorylation sites were also discussed.
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Key Words
- ABL, Abelson
- APC, adenomatous polyposis coli
- Allostery
- CK1, casein kinase 1
- CML, chronic myeloid leukemia
- ER, endoplasmic reticulum
- GAPs, GTPase-activating proteins
- GEFs, guanine nucleotide exchange-factors
- GSK3, glycogen synthase kinase 3
- HVR, hypervariable region
- IP3R, inositol trisphosphate receptors
- LRP6, lipoprotein-receptor-related protein 6
- OMM, outer mitochondrial membrane
- PI3K, phosphatidylinositol 3-kinase
- PKC, protein kinase C
- PPIs, protein−protein interactions
- Phosphorylation
- Protein kinases
- RAS
- RIN1, RAB-interacting protein 1
- SHP2, SRC homology 2 domain containing phosphatase 2
- SOS, Son of Sevenless
- STK19, serine/threonine-protein kinase 19
- TKIs, tyrosine kinase inhibitors
- Undruggable
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Affiliation(s)
- Yuran Qiu
- Department of Urology, Changzheng Hospital, Naval Military Medical University, Shanghai 200003, China
- Department of Pathophysiology, Key Laboratory of Cell Differentiation and Apoptosis of Chinese Ministry of Education, Shanghai Jiao Tong University, School of Medicine, Shanghai 200025, China
| | - Yuanhao Wang
- Department of Pathophysiology, Key Laboratory of Cell Differentiation and Apoptosis of Chinese Ministry of Education, Shanghai Jiao Tong University, School of Medicine, Shanghai 200025, China
| | - Zongtao Chai
- Department of Hepatic Surgery VI, Eastern Hepatobiliary Surgery Hospital, Second Military Medical University, Shanghai 200438, China
| | - Duan Ni
- Department of Pathophysiology, Key Laboratory of Cell Differentiation and Apoptosis of Chinese Ministry of Education, Shanghai Jiao Tong University, School of Medicine, Shanghai 200025, China
| | - Xinyi Li
- Department of Pathophysiology, Key Laboratory of Cell Differentiation and Apoptosis of Chinese Ministry of Education, Shanghai Jiao Tong University, School of Medicine, Shanghai 200025, China
| | - Jun Pu
- Department of Cardiology, Renji Hospital, Shanghai Jiao Tong University, School of Medicine, Shanghai 200120, China
| | - Jie Chen
- Department of Urology, Changzheng Hospital, Naval Military Medical University, Shanghai 200003, China
| | - Jian Zhang
- Department of Pathophysiology, Key Laboratory of Cell Differentiation and Apoptosis of Chinese Ministry of Education, Shanghai Jiao Tong University, School of Medicine, Shanghai 200025, China
- Corresponding authors.
| | - Shaoyong Lu
- Department of Pathophysiology, Key Laboratory of Cell Differentiation and Apoptosis of Chinese Ministry of Education, Shanghai Jiao Tong University, School of Medicine, Shanghai 200025, China
- Corresponding authors.
| | - Chuan Lv
- Department of Plastic Surgery, Changhai Hospital, Naval Military Medical University, Shanghai 200438, China
- Corresponding authors.
| | - Mingfei Ji
- Department of Urology, Changzheng Hospital, Naval Military Medical University, Shanghai 200003, China
- Corresponding authors.
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23
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Ni D, Chai Z, Wang Y, Li M, Yu Z, Liu Y, Lu S, Zhang J. Along the allostery stream: Recent advances in computational methods for allosteric drug discovery. WIRES COMPUTATIONAL MOLECULAR SCIENCE 2021. [DOI: 10.1002/wcms.1585] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/11/2022]
Affiliation(s)
- Duan Ni
- College of Pharmacy Ningxia Medical University Yinchuan China
- The Charles Perkins Centre University of Sydney Sydney New South Wales Australia
| | - Zongtao Chai
- Department of Hepatic Surgery VI, Eastern Hepatobiliary Surgery Hospital Second Military Medical University Shanghai China
| | - Ying Wang
- State Key Laboratory of Oncogenes and Related Genes, Key Laboratory of Cell Differentiation and Apoptosis of Chinese Ministry of Education Shanghai Jiao Tong University School of Medicine Shanghai China
| | - Mingyu Li
- State Key Laboratory of Oncogenes and Related Genes, Key Laboratory of Cell Differentiation and Apoptosis of Chinese Ministry of Education Shanghai Jiao Tong University School of Medicine Shanghai China
| | | | - Yaqin Liu
- Medicinal Chemistry and Bioinformatics Center Shanghai Jiao Tong University School of Medicine Shanghai China
| | - Shaoyong Lu
- College of Pharmacy Ningxia Medical University Yinchuan China
- State Key Laboratory of Oncogenes and Related Genes, Key Laboratory of Cell Differentiation and Apoptosis of Chinese Ministry of Education Shanghai Jiao Tong University School of Medicine Shanghai China
- Medicinal Chemistry and Bioinformatics Center Shanghai Jiao Tong University School of Medicine Shanghai China
| | - Jian Zhang
- College of Pharmacy Ningxia Medical University Yinchuan China
- State Key Laboratory of Oncogenes and Related Genes, Key Laboratory of Cell Differentiation and Apoptosis of Chinese Ministry of Education Shanghai Jiao Tong University School of Medicine Shanghai China
- Medicinal Chemistry and Bioinformatics Center Shanghai Jiao Tong University School of Medicine Shanghai China
- School of Pharmaceutical Sciences Zhengzhou University Zhengzhou China
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24
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Chatzigoulas A, Cournia Z. Rational design of allosteric modulators: Challenges and successes. WIRES COMPUTATIONAL MOLECULAR SCIENCE 2021. [DOI: 10.1002/wcms.1529] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/11/2022]
Affiliation(s)
- Alexios Chatzigoulas
- Biomedical Research Foundation Academy of Athens Athens Greece
- Department of Informatics and Telecommunications National and Kapodistrian University of Athens Athens Greece
| | - Zoe Cournia
- Biomedical Research Foundation Academy of Athens Athens Greece
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25
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Qiu Y, Yin X, Li X, Wang Y, Fu Q, Huang R, Lu S. Untangling Dual-Targeting Therapeutic Mechanism of Epidermal Growth Factor Receptor (EGFR) Based on Reversed Allosteric Communication. Pharmaceutics 2021; 13:747. [PMID: 34070173 PMCID: PMC8158526 DOI: 10.3390/pharmaceutics13050747] [Citation(s) in RCA: 35] [Impact Index Per Article: 11.7] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/23/2021] [Revised: 04/12/2021] [Accepted: 04/21/2021] [Indexed: 12/18/2022] Open
Abstract
Dual-targeting therapeutics by coadministration of allosteric and orthosteric drugs is drawing increased attention as a revolutionary strategy for overcoming the drug-resistance problems. It was further observed that the occupation of orthosteric sites by therapeutics agents has the potential to enhance allosteric ligand binding, which leads to improved potency of allosteric drugs. Epidermal growth factor receptor (EGFR), as one of the most critical anti-cancer targets belonging to the receptor tyrosine kinase family, represents a quintessential example. It was revealed that osimertinib, an ATP-competitive covalent EGFR inhibitor, remarkably enhanced the affinity of a recently developed allosteric inhibitor JBJ-04-125-02 for EGFRL858R/T790M. Here, we utilized extensive large-scale molecular dynamics simulations and the reversed allosteric communication to untangle the detailed molecular underpinning, in which occupation of osimertinib at the orthosteric site altered the overall conformational ensemble of EGFR mutant and reshaped the allosteric site via long-distance signaling. A unique intermediate state resembling the active conformation was identified, which was further stabilized by osimertinib loading. Based on the allosteric communication pathway, we predicted a novel allosteric site positioned around K867, E868, H893, and K960 within the intermediate state. Its correlation with the orthosteric site was validated by both structural and energetic analysis, and its low sequence conservation indicated the potential for selective targeting across the human kinome. Together, these findings not only provided a mechanistic basis for future clinical application of the dual-targeting therapeutics, but also explored an innovative perception of allosteric inhibition of tyrosine kinase signaling.
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Affiliation(s)
- Yuran Qiu
- Key Laboratory of Cell Differentiation and Apoptosis of Chinese Ministry of Education, Department of Pathophysiology, School of Medicine, Shanghai Jiao Tong University, Shanghai 200025, China; (Y.Q.); (X.L.); (Y.W.)
| | - Xiaolan Yin
- Department of Radiotherapy, Changhai Hospital (Hongkou District), Naval Medical University, Shanghai 200081, China;
| | - Xinyi Li
- Key Laboratory of Cell Differentiation and Apoptosis of Chinese Ministry of Education, Department of Pathophysiology, School of Medicine, Shanghai Jiao Tong University, Shanghai 200025, China; (Y.Q.); (X.L.); (Y.W.)
| | - Yuanhao Wang
- Key Laboratory of Cell Differentiation and Apoptosis of Chinese Ministry of Education, Department of Pathophysiology, School of Medicine, Shanghai Jiao Tong University, Shanghai 200025, China; (Y.Q.); (X.L.); (Y.W.)
| | - Qiang Fu
- Department of Orthopedics, Shanghai General Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai 200080, China
| | - Renhua Huang
- Department of Radiation, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai 200120, China
| | - Shaoyong Lu
- Key Laboratory of Cell Differentiation and Apoptosis of Chinese Ministry of Education, Department of Pathophysiology, School of Medicine, Shanghai Jiao Tong University, Shanghai 200025, China; (Y.Q.); (X.L.); (Y.W.)
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26
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Tee WV, Tan ZW, Lee K, Guarnera E, Berezovsky IN. Exploring the Allosteric Territory of Protein Function. J Phys Chem B 2021; 125:3763-3780. [PMID: 33844527 DOI: 10.1021/acs.jpcb.1c00540] [Citation(s) in RCA: 24] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/03/2023]
Abstract
While the pervasiveness of allostery in proteins is commonly accepted, we further show the generic nature of allosteric mechanisms by analyzing here transmembrane ion-channel viroporin 3a and RNA-dependent RNA polymerase (RdRp) from SARS-CoV-2 along with metabolic enzymes isocitrate dehydrogenase 1 (IDH1) and fumarate hydratase (FH) implicated in cancers. Using the previously developed structure-based statistical mechanical model of allostery (SBSMMA), we share our experience in analyzing the allosteric signaling, predicting latent allosteric sites, inducing and tuning targeted allosteric response, and exploring the allosteric effects of mutations. This, yet incomplete list of phenomenology, forms a complex and unique allosteric territory of protein function, which should be thoroughly explored. We propose a generic computational framework, which not only allows one to obtain a comprehensive allosteric control over proteins but also provides an opportunity to approach the fragment-based design of allosteric effectors and drug candidates. The advantages of allosteric drugs over traditional orthosteric compounds, complemented by the emerging role of the allosteric effects of mutations in the expansion of the cancer mutational landscape and in the increased mutability of viral proteins, leave no choice besides further extensive studies of allosteric mechanisms and their biomedical implications.
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Affiliation(s)
- Wei-Ven Tee
- Bioinformatics Institute (BII), Agency for Science, Technology and Research (A*STAR), 30 Biopolis Street, #07-01, Matrix, 138671, Singapore.,Department of Biological Sciences (DBS), National University of Singapore (NUS), 8 Medical Drive, 117597, Singapore
| | - Zhen Wah Tan
- Bioinformatics Institute (BII), Agency for Science, Technology and Research (A*STAR), 30 Biopolis Street, #07-01, Matrix, 138671, Singapore
| | - Keene Lee
- Bioinformatics Institute (BII), Agency for Science, Technology and Research (A*STAR), 30 Biopolis Street, #07-01, Matrix, 138671, Singapore
| | - Enrico Guarnera
- Bioinformatics Institute (BII), Agency for Science, Technology and Research (A*STAR), 30 Biopolis Street, #07-01, Matrix, 138671, Singapore
| | - Igor N Berezovsky
- Bioinformatics Institute (BII), Agency for Science, Technology and Research (A*STAR), 30 Biopolis Street, #07-01, Matrix, 138671, Singapore.,Department of Biological Sciences (DBS), National University of Singapore (NUS), 8 Medical Drive, 117597, Singapore
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27
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Prabantu VM, Naveenkumar N, Srinivasan N. Influence of Disease-Causing Mutations on Protein Structural Networks. Front Mol Biosci 2021; 7:620554. [PMID: 33778000 PMCID: PMC7987782 DOI: 10.3389/fmolb.2020.620554] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/23/2020] [Accepted: 12/17/2020] [Indexed: 01/18/2023] Open
Abstract
The interactions between residues in a protein tertiary structure can be studied effectively using the approach of protein structure network (PSN). A PSN is a node-edge representation of the structure with nodes representing residues and interactions between residues represented by edges. In this study, we have employed weighted PSNs to understand the influence of disease-causing mutations on proteins of known 3D structures. We have used manually curated information on disease mutations from UniProtKB/Swiss-Prot and their corresponding protein structures of wildtype and disease variant from the protein data bank. The PSNs of the wildtype and disease-causing mutant are compared to analyse variation of global and local dissimilarity in the overall network and at specific sites. We study how a mutation at a given site can affect the structural network at a distant site which may be involved in the function of the protein. We have discussed specific examples of the disease cases where the protein structure undergoes limited structural divergence in their backbone but have large dissimilarity in their all atom networks and vice versa, wherein large conformational alterations are observed while retaining overall network. We analyse the effect of variation of network parameters that characterize alteration of function or stability.
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Affiliation(s)
| | - Nagarajan Naveenkumar
- Molecular Biophysics Unit, Indian Institute of Science, Bangalore, India.,National Centre for Biological Sciences, TIFR, Bangalore, India.,Bharathidasan University, Tiruchirappalli, India
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28
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Vihinen M. Functional effects of protein variants. Biochimie 2020; 180:104-120. [PMID: 33164889 DOI: 10.1016/j.biochi.2020.10.009] [Citation(s) in RCA: 23] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/30/2020] [Revised: 10/15/2020] [Accepted: 10/19/2020] [Indexed: 12/11/2022]
Abstract
Genetic and other variations frequently affect protein functions. Scientific articles can contain confusing descriptions about which function or property is affected, and in many cases the statements are pure speculation without any experimental evidence. To clarify functional effects of protein variations of genetic or non-genetic origin, a systematic conceptualisation and framework are introduced. This framework describes protein functional effects on abundance, activity, specificity and affinity, along with countermeasures, which allow cells, tissues and organisms to tolerate, avoid, repair, attenuate or resist (TARAR) the effects. Effects on abundance discussed include gene dosage, restricted expression, mis-localisation and degradation. Enzymopathies, effects on kinetics, allostery and regulation of protein activity are subtopics for the effects of variants on activity. Variation outcomes on specificity and affinity comprise promiscuity, specificity, affinity and moonlighting. TARAR mechanisms redress variations with active and passive processes including chaperones, redundancy, robustness, canalisation and metabolic and signalling rewiring. A framework for pragmatic protein function analysis and presentation is introduced. All of the mechanisms and effects are described along with representative examples, most often in relation to diseases. In addition, protein function is discussed from evolutionary point of view. Application of the presented framework facilitates unambiguous, detailed and specific description of functional effects and their systematic study.
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Affiliation(s)
- Mauno Vihinen
- Department of Experimental Medical Science, BMC B13, Lund University, SE-22 184, Lund, Sweden.
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29
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Carofiglio F, Trisciuzzi D, Gambacorta N, Leonetti F, Stefanachi A, Nicolotti O. Bcr-Abl Allosteric Inhibitors: Where We Are and Where We Are Going to. Molecules 2020; 25:E4210. [PMID: 32937901 PMCID: PMC7570842 DOI: 10.3390/molecules25184210] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/07/2020] [Revised: 09/08/2020] [Accepted: 09/10/2020] [Indexed: 12/12/2022] Open
Abstract
The fusion oncoprotein Bcr-Abl is an aberrant tyrosine kinase responsible for chronic myeloid leukemia and acute lymphoblastic leukemia. The auto-inhibition regulatory module observed in the progenitor kinase c-Abl is lost in the aberrant Bcr-Abl, because of the lack of the N-myristoylated cap able to bind the myristoyl binding pocket also conserved in the Bcr-Abl kinase domain. A way to overcome the occurrence of resistance phenomena frequently observed for Bcr-Abl orthosteric drugs is the rational design of allosteric ligands approaching the so-called myristoyl binding pocket. The discovery of these allosteric inhibitors although very difficult and extremely challenging, represents a valuable option to minimize drug resistance, mostly due to the occurrence of mutations more frequently affecting orthosteric pockets, and to enhance target selectivity with lower off-target effects. In this perspective, we will elucidate at a molecular level the structural bases behind the Bcr-Abl allosteric control and will show how artificial intelligence can be effective to drive the automated de novo design towards off-patent regions of the chemical space.
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Affiliation(s)
- Francesca Carofiglio
- Dipartimento di Farmacia Scienze del Farmaco, Università degli Studi di Bari “Aldo Moro”, 70125 Bari, Italy; (F.C.); (D.T.); (N.G.); (F.L.)
| | - Daniela Trisciuzzi
- Dipartimento di Farmacia Scienze del Farmaco, Università degli Studi di Bari “Aldo Moro”, 70125 Bari, Italy; (F.C.); (D.T.); (N.G.); (F.L.)
- Molecular Horizon srl, Via Montelino 32, 06084 Bettona, Italy
| | - Nicola Gambacorta
- Dipartimento di Farmacia Scienze del Farmaco, Università degli Studi di Bari “Aldo Moro”, 70125 Bari, Italy; (F.C.); (D.T.); (N.G.); (F.L.)
| | - Francesco Leonetti
- Dipartimento di Farmacia Scienze del Farmaco, Università degli Studi di Bari “Aldo Moro”, 70125 Bari, Italy; (F.C.); (D.T.); (N.G.); (F.L.)
| | - Angela Stefanachi
- Dipartimento di Farmacia Scienze del Farmaco, Università degli Studi di Bari “Aldo Moro”, 70125 Bari, Italy; (F.C.); (D.T.); (N.G.); (F.L.)
| | - Orazio Nicolotti
- Dipartimento di Farmacia Scienze del Farmaco, Università degli Studi di Bari “Aldo Moro”, 70125 Bari, Italy; (F.C.); (D.T.); (N.G.); (F.L.)
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30
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Tee WV, Guarnera E, Berezovsky IN. Disorder driven allosteric control of protein activity. Curr Res Struct Biol 2020; 2:191-203. [PMID: 34235479 PMCID: PMC8244471 DOI: 10.1016/j.crstbi.2020.09.001] [Citation(s) in RCA: 19] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/31/2020] [Revised: 08/27/2020] [Accepted: 09/02/2020] [Indexed: 12/23/2022] Open
Abstract
Studies of protein allostery increasingly reveal an involvement of the back and forth order-disorder transitions in this mechanism of protein activity regulation. Here, we investigate the allosteric mechanisms mediated by structural disorder using the structure-based statistical mechanical model of allostery (SBSMMA) that we have previously developed. We show that SBSMMA accounts for the energetics and causality of allosteric communication underlying dimerization of the BirA biotin repressor, activation of the sortase A enzyme, and inhibition of the Rac1 GTPase. Using the SBSMMA, we also show that introducing structural order or disorder in various regions of esterases can originate tunable allosteric modulation of the catalytic triad. On the basis of obtained results, we propose that operating with the order-disorder continuum allows one to establish an allosteric control scale for achieving desired modulation of the protein activity. Back and forth order-disorder transitions can induce allosteric signaling. Allosteric signaling originated by order/disorder follow universal rules. Allosteric control scale facilitates engineering of the protein activity regulation.
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Affiliation(s)
- Wei-Ven Tee
- Bioinformatics Institute (BII), Agency for Science, Technology and Research (A∗STAR), 30 Biopolis Street, #07-01, Matrix 138671, Singapore.,Department of Biological Sciences (DBS), National University of Singapore (NUS), 8 Medical Drive 117597, Singapore
| | - Enrico Guarnera
- Bioinformatics Institute (BII), Agency for Science, Technology and Research (A∗STAR), 30 Biopolis Street, #07-01, Matrix 138671, Singapore
| | - Igor N Berezovsky
- Bioinformatics Institute (BII), Agency for Science, Technology and Research (A∗STAR), 30 Biopolis Street, #07-01, Matrix 138671, Singapore.,Department of Biological Sciences (DBS), National University of Singapore (NUS), 8 Medical Drive 117597, Singapore
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31
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Zhang M, Jang H, Nussinov R. PI3K inhibitors: review and new strategies. Chem Sci 2020; 11:5855-5865. [PMID: 32953006 PMCID: PMC7472334 DOI: 10.1039/d0sc01676d] [Citation(s) in RCA: 97] [Impact Index Per Article: 24.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/20/2020] [Accepted: 05/18/2020] [Indexed: 12/16/2022] Open
Abstract
The search is on for effective specific inhibitors for PI3Kα mutants. PI3Kα, a critical lipid kinase, has two subunits, catalytic and inhibitory. PIK3CA, the gene that encodes the p110α catalytic subunit is a highly mutated protein in cancer. Dysregulation of PI3Kα signalling is commonly associated with tumorigenesis and drug resistance. Despite its vast importance, only recently the FDA approved the first drug (alpelisib by Novartis) for breast cancer. A second (GDC0077), classified as PI3Kα isoform-specific, is undergoing clinical trials. Not surprisingly, these ATP-competitive drugs commonly elicit severe concentration-dependent side effects. Here we briefly review PI3Kα mutations, focus on PI3K drug repertoire and propose new, to-date unexplored PI3Kα therapeutic strategies. These include (1) an allosteric and orthosteric inhibitor combination and (2) taking advantage of allosteric rescue mutations to guide drug discovery.
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Affiliation(s)
- Mingzhen Zhang
- Computational Structural Biology Section , Frederick National Laboratory for Cancer Research , National Cancer Institute at Frederick , Frederick , MD 21702 , USA . ; Tel: +1-301-846-5579
| | - Hyunbum Jang
- Computational Structural Biology Section , Frederick National Laboratory for Cancer Research , National Cancer Institute at Frederick , Frederick , MD 21702 , USA . ; Tel: +1-301-846-5579
| | - Ruth Nussinov
- Computational Structural Biology Section , Frederick National Laboratory for Cancer Research , National Cancer Institute at Frederick , Frederick , MD 21702 , USA . ; Tel: +1-301-846-5579
- Department of Human Molecular Genetics and Biochemistry , Sackler School of Medicine , Tel Aviv University , Tel Aviv 69978 , Israel
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32
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Allosteric drugs and mutations: chances, challenges, and necessity. Curr Opin Struct Biol 2020; 62:149-157. [DOI: 10.1016/j.sbi.2020.01.010] [Citation(s) in RCA: 51] [Impact Index Per Article: 12.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/06/2019] [Accepted: 01/16/2020] [Indexed: 12/22/2022]
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33
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Liu X, Lu S, Song K, Shen Q, Ni D, Li Q, He X, Zhang H, Wang Q, Chen Y, Li X, Wu J, Sheng C, Chen G, Liu Y, Lu X, Zhang J. Unraveling allosteric landscapes of allosterome with ASD. Nucleic Acids Res 2020; 48:D394-D401. [PMID: 31665428 PMCID: PMC7145546 DOI: 10.1093/nar/gkz958] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/02/2019] [Revised: 09/30/2019] [Accepted: 10/10/2019] [Indexed: 12/17/2022] Open
Abstract
Allosteric regulation is one of the most direct and efficient ways to fine-tune protein function; it is induced by the binding of a ligand at an allosteric site that is topographically distinct from an orthosteric site. The Allosteric Database (ASD, available online at http://mdl.shsmu.edu.cn/ASD) was developed ten years ago to provide comprehensive information related to allosteric regulation. In recent years, allosteric regulation has received great attention in biological research, bioengineering, and drug discovery, leading to the emergence of entire allosteric landscapes as allosteromes. To facilitate research from the perspective of the allosterome, in ASD 2019, novel features were curated as follows: (i) >10 000 potential allosteric sites of human proteins were deposited for allosteric drug discovery; (ii) 7 human allosterome maps, including protease and ion channel maps, were built to reveal allosteric evolution within families; (iii) 1312 somatic missense mutations at allosteric sites were collected from patient samples from 33 cancer types and (iv) 1493 pharmacophores extracted from allosteric sites were provided for modulator screening. Over the past ten years, the ASD has become a central resource for studying allosteric regulation and will play more important roles in both target identification and allosteric drug discovery in the future.
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Affiliation(s)
- Xinyi Liu
- State Key Laboratory of Oncogenes and Related Genes, Renji Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200127, China.,Medicinal Bioinformatics Center, Shanghai Jiao Tong University School of Medicine (SJTU-SM), Shanghai 200025, China
| | - Shaoyong Lu
- State Key Laboratory of Oncogenes and Related Genes, Renji Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200127, China.,Medicinal Bioinformatics Center, Shanghai Jiao Tong University School of Medicine (SJTU-SM), Shanghai 200025, China
| | - Kun Song
- State Key Laboratory of Oncogenes and Related Genes, Renji Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200127, China.,Medicinal Bioinformatics Center, Shanghai Jiao Tong University School of Medicine (SJTU-SM), Shanghai 200025, China
| | - Qiancheng Shen
- State Key Laboratory of Oncogenes and Related Genes, Renji Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200127, China.,Medicinal Bioinformatics Center, Shanghai Jiao Tong University School of Medicine (SJTU-SM), Shanghai 200025, China.,Department of Assisted Reproduction, Shanghai Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine (SJTU-SM), Shanghai 200011, China
| | - Duan Ni
- State Key Laboratory of Oncogenes and Related Genes, Renji Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200127, China
| | - Qian Li
- Medicinal Bioinformatics Center, Shanghai Jiao Tong University School of Medicine (SJTU-SM), Shanghai 200025, China.,Department of Assisted Reproduction, Shanghai Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine (SJTU-SM), Shanghai 200011, China
| | - Xinheng He
- State Key Laboratory of Oncogenes and Related Genes, Renji Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200127, China.,Medicinal Bioinformatics Center, Shanghai Jiao Tong University School of Medicine (SJTU-SM), Shanghai 200025, China
| | - Hao Zhang
- Medicinal Bioinformatics Center, Shanghai Jiao Tong University School of Medicine (SJTU-SM), Shanghai 200025, China
| | - Qi Wang
- China National Pharmaceutical Industry Information Center, Shanghai, 200040, China
| | - Yingyi Chen
- State Key Laboratory of Oncogenes and Related Genes, Renji Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200127, China.,Medicinal Bioinformatics Center, Shanghai Jiao Tong University School of Medicine (SJTU-SM), Shanghai 200025, China
| | - Xinyi Li
- State Key Laboratory of Oncogenes and Related Genes, Renji Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200127, China.,Medicinal Bioinformatics Center, Shanghai Jiao Tong University School of Medicine (SJTU-SM), Shanghai 200025, China
| | - Jing Wu
- Medicinal Bioinformatics Center, Shanghai Jiao Tong University School of Medicine (SJTU-SM), Shanghai 200025, China.,Department of Assisted Reproduction, Shanghai Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine (SJTU-SM), Shanghai 200011, China
| | - Chunquan Sheng
- School of Pharmacy, Second Military Medical University, Shanghai, 200433, China.,School of Pharmaceutical Sciences, Zhengzhou University, Zhengzhou 450001, China
| | - Guoqiang Chen
- State Key Laboratory of Oncogenes and Related Genes, Renji Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200127, China
| | - Yaqin Liu
- State Key Laboratory of Oncogenes and Related Genes, Renji Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200127, China
| | - Xuefeng Lu
- Department of Assisted Reproduction, Shanghai Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine (SJTU-SM), Shanghai 200011, China
| | - Jian Zhang
- State Key Laboratory of Oncogenes and Related Genes, Renji Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200127, China.,Medicinal Bioinformatics Center, Shanghai Jiao Tong University School of Medicine (SJTU-SM), Shanghai 200025, China.,School of Pharmaceutical Sciences, Zhengzhou University, Zhengzhou 450001, China
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34
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Gosu V, Won K, Oh JD, Shin D. Conformational Changes Induced by S34Y and R98C Variants in the Death Domain of Myd88. Front Mol Biosci 2020; 7:27. [PMID: 32266286 PMCID: PMC7106778 DOI: 10.3389/fmolb.2020.00027] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/04/2019] [Accepted: 02/10/2020] [Indexed: 11/13/2022] Open
Abstract
Myeloid differentiating factor 88 (Myd88) is a universal adaptor protein that plays a critical role in innate immunity by mediating TLR downstream signaling. Myd88 death domain (DD) forms an oligomeric complex by association with other DD-containing proteins such as IRAK4. Despite its universal role, polymorphisms in Myd88 can result in several diseases. Previous studies have suggested that, out of several non-synonymous single-nucleotide polymorphisms (nsSNPs), the variants S34Y and R98C in the DD of Myd88 disrupt the formation of the Myddosome complex. Therefore, we performed molecular dynamics (MD) simulations on wild-type (Myd88WT) and mutant (Myd88S34Y, Myd88R98C) DDs to evaluate the subtle conformational changes induced by these mutations. Our results suggest that the S34Y variant induces large structural transitions compared to the R98C variant as evidenced by residual flexibility at the variable loop regions, particularly in the H1-H2 loop, and variations in the collective modes of motion observed for wild-type and mutant Myd88 DDs. The residue interaction network strongly suggests a distortion in the interaction pattern at the location of the mutated residue between the wild type and mutants. Moreover, betweenness centrality values indicate that variations in the distribution of functionally important residues may be reflected by distinct residue signal transductions in both wild-type and mutant Myd88 DDs, which may influence the interaction with other DDs in TLR downstream signaling.
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Affiliation(s)
- Vijayakumar Gosu
- Department of Animal Biotechnology, Jeonbuk National University, Jeonju-si, South Korea
| | - KyeongHye Won
- Department of Animal Biotechnology, Jeonbuk National University, Jeonju-si, South Korea
| | - Jae-Don Oh
- Department of Animal Biotechnology, Jeonbuk National University, Jeonju-si, South Korea
| | - Donghyun Shin
- The Animal Molecular Genetics and Breeding Center, Jeonbuk National University, Jeonju-si, South Korea
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35
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Ni D, Li Y, Qiu Y, Pu J, Lu S, Zhang J. Combining Allosteric and Orthosteric Drugs to Overcome Drug Resistance. Trends Pharmacol Sci 2020; 41:336-348. [PMID: 32171554 DOI: 10.1016/j.tips.2020.02.001] [Citation(s) in RCA: 55] [Impact Index Per Article: 13.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/24/2019] [Revised: 02/06/2020] [Accepted: 02/12/2020] [Indexed: 02/07/2023]
Abstract
Historically, most drugs target protein orthosteric sites. The gradual emergence of resistance hampers their therapeutic effectiveness, posing a challenge to drug development. Coadministration of allosteric and orthosteric drugs provides a revolutionary strategy to circumvent drug resistance, as drugs targeting the topologically distinct allosteric sites can restore or even enhance the efficacy of orthosteric drugs. Here, we comprehensively review the latest successful examples of such combination treatments against drug resistance, with a focus on their modes of action and the underlying structural mechanisms. Our work supplies an innovative insight into such promising methodology against the recalcitrant drug resistance conundrum and will be instructive for future clinical therapeutics.
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Affiliation(s)
- Duan Ni
- State Key Laboratory of Oncogenes and Related Genes, Renji Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200127, China; The Charles Perkins Centre, The University of Sydney, Sydney, NSW, 2006, Australia
| | - Yun Li
- State Key Laboratory of Oncogenes and Related Genes, Renji Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200127, China; Key Laboratory of Cell Differentiation and Apoptosis of Ministry of Education, Department of Pathophysiology, Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China
| | - Yuran Qiu
- State Key Laboratory of Oncogenes and Related Genes, Renji Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200127, China; Key Laboratory of Cell Differentiation and Apoptosis of Ministry of Education, Department of Pathophysiology, Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China
| | - Jun Pu
- State Key Laboratory of Oncogenes and Related Genes, Renji Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200127, China; Department of Cardiology, Renji Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Shaoyong Lu
- State Key Laboratory of Oncogenes and Related Genes, Renji Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200127, China; Key Laboratory of Cell Differentiation and Apoptosis of Ministry of Education, Department of Pathophysiology, Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China.
| | - Jian Zhang
- State Key Laboratory of Oncogenes and Related Genes, Renji Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200127, China; Key Laboratory of Cell Differentiation and Apoptosis of Ministry of Education, Department of Pathophysiology, Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China; Medicinal Bioinformatics Center, Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China.
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36
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The Determination of HIV-1 RT Mutation Rate, Its Possible Allosteric Effects, and Its Implications on Drug Resistance. Viruses 2020; 12:v12030297. [PMID: 32182845 PMCID: PMC7150816 DOI: 10.3390/v12030297] [Citation(s) in RCA: 19] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/06/2020] [Revised: 03/02/2020] [Accepted: 03/06/2020] [Indexed: 12/31/2022] Open
Abstract
The high mutation rate of the human immunodeficiency virus type 1 (HIV-1) plays a major role in treatment resistance, from the development of vaccines to therapeutic drugs. In addressing the crux of the issue, various attempts to estimate the mutation rate of HIV-1 resulted in a large range of 10−5–10−3 errors/bp/cycle due to the use of different types of investigation methods. In this review, we discuss the different assay methods, their findings on the mutation rates of HIV-1 and how the locations of mutations can be further analyzed for their allosteric effects to allow for new inhibitor designs. Given that HIV is one of the fastest mutating viruses, it serves as a good model for the comprehensive study of viral mutations that can give rise to a more horizontal understanding towards overall viral drug resistance as well as emerging viral diseases.
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37
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Zhang N, Chen Y, Lu H, Zhao F, Alvarez RV, Goncearenco A, Panchenko AR, Li M. MutaBind2: Predicting the Impacts of Single and Multiple Mutations on Protein-Protein Interactions. iScience 2020; 23:100939. [PMID: 32169820 PMCID: PMC7068639 DOI: 10.1016/j.isci.2020.100939] [Citation(s) in RCA: 80] [Impact Index Per Article: 20.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/15/2019] [Revised: 11/21/2019] [Accepted: 02/20/2020] [Indexed: 01/17/2023] Open
Abstract
Missense mutations may affect proteostasis by destabilizing or over-stabilizing protein complexes and changing the pathway flux. Predicting the effects of stabilizing mutations on protein-protein interactions is notoriously difficult because existing experimental sets are skewed toward mutations reducing protein-protein binding affinity and many computational methods fail to correctly evaluate their effects. To address this issue, we developed a method MutaBind2, which estimates the impacts of single as well as multiple mutations on protein-protein interactions. MutaBind2 employs only seven features, and the most important of them describe interactions of proteins with the solvent, evolutionary conservation of the site, and thermodynamic stability of the complex and each monomer. This approach shows a distinct improvement especially in evaluating the effects of mutations increasing binding affinity. MutaBind2 can be used for finding disease driver mutations, designing stable protein complexes, and discovering new protein-protein interaction inhibitors.
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Affiliation(s)
- Ning Zhang
- Center for Systems Biology, Department of Bioinformatics, School of Biology and Basic Medical Sciences, Soochow University, Suzhou 215123, China
| | - Yuting Chen
- Center for Systems Biology, Department of Bioinformatics, School of Biology and Basic Medical Sciences, Soochow University, Suzhou 215123, China
| | - Haoyu Lu
- Center for Systems Biology, Department of Bioinformatics, School of Biology and Basic Medical Sciences, Soochow University, Suzhou 215123, China
| | - Feiyang Zhao
- Center for Systems Biology, Department of Bioinformatics, School of Biology and Basic Medical Sciences, Soochow University, Suzhou 215123, China
| | - Roberto Vera Alvarez
- National Center for Biotechnology Information, National Institutes of Health, Bethesda, MD 20894, USA
| | - Alexander Goncearenco
- National Center for Biotechnology Information, National Institutes of Health, Bethesda, MD 20894, USA
| | - Anna R Panchenko
- National Center for Biotechnology Information, National Institutes of Health, Bethesda, MD 20894, USA.
| | - Minghui Li
- Center for Systems Biology, Department of Bioinformatics, School of Biology and Basic Medical Sciences, Soochow University, Suzhou 215123, China.
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38
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Kumar AP, Verma CS, Lukman S. Structural dynamics and allostery of Rab proteins: strategies for drug discovery and design. Brief Bioinform 2020; 22:270-287. [PMID: 31950981 DOI: 10.1093/bib/bbz161] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/17/2019] [Revised: 08/29/2019] [Accepted: 11/15/2019] [Indexed: 01/09/2023] Open
Abstract
Rab proteins represent the largest family of the Rab superfamily guanosine triphosphatase (GTPase). Aberrant human Rab proteins are associated with multiple diseases, including cancers and neurological disorders. Rab subfamily members display subtle conformational variations that render specificity in their physiological functions and can be targeted for subfamily-specific drug design. However, drug discovery efforts have not focused much on targeting Rab allosteric non-nucleotide binding sites which are subjected to less evolutionary pressures to be conserved, hence are likely to offer subfamily specificity and may be less prone to undesirable off-target interactions and side effects. To discover druggable allosteric binding sites, Rab structural dynamics need to be first incorporated using multiple experimentally and computationally obtained structures. The high-dimensional structural data may necessitate feature extraction methods to identify manageable representative structures for subsequent analyses. We have detailed state-of-the-art computational methods to (i) identify binding sites using data on sequence, shape, energy, etc., (ii) determine the allosteric nature of these binding sites based on structural ensembles, residue networks and correlated motions and (iii) identify small molecule binders through structure- and ligand-based virtual screening. To benefit future studies for targeting Rab allosteric sites, we herein detail a refined workflow comprising multiple available computational methods, which have been successfully used alone or in combinations. This workflow is also applicable for drug discovery efforts targeting other medically important proteins. Depending on the structural dynamics of proteins of interest, researchers can select suitable strategies for allosteric drug discovery and design, from the resources of computational methods and tools enlisted in the workflow.
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Affiliation(s)
- Ammu Prasanna Kumar
- Department of Chemistry, College of Arts and Sciences, Khalifa University, Abu Dhabi, United Arab Emirates.,Research Unit in Bioinformatics, Department of Biochemistry and Microbiology, Rhodes University, South Africa
| | - Chandra S Verma
- Bioinformatics Institute, Agency for Science, Technology and Research, Singapore.,Department of Biological Sciences, National University of Singapore, Singapore.,School of Biological Sciences, Nanyang Technological University, Singapore
| | - Suryani Lukman
- Department of Chemistry, College of Arts and Sciences, Khalifa University, Abu Dhabi, United Arab Emirates
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39
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Role of protein-protein interactions in allosteric drug design for DNA methyltransferases. ADVANCES IN PROTEIN CHEMISTRY AND STRUCTURAL BIOLOGY 2020; 121:49-84. [PMID: 32312426 DOI: 10.1016/bs.apcsb.2019.12.005] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/22/2022]
Abstract
DNA methyltransferases (DNMTs) not only play key roles in epigenetic gene regulation, but also serve as emerging targets for several diseases, especially for cancers. Due to the multi-domains of DNMT structures, targeting allosteric sites of protein-protein interactions (PPIs) is becoming an attractive strategy in epigenetic drug discovery. This chapter aims to review the major contemporary approaches utilized for the drug discovery based on PPIs in different dimensions, from the enumeration of allosteric mechanism to the identification of allosteric pockets. These include the construction of protein structure networks (PSNs) based on molecular dynamics (MD) simulations, performing elastic network models (ENMs) and perturbation response scanning (PRS) calculation, the sequence-based conservation and coupling analysis, and the allosteric pockets identification. Furthermore, we complement this methodology by highlighting the role of computational approaches in promising practical applications for the computer-aided drug design, with special focus on two DNMTs, namely, DNMT1 and DNMT3A.
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Nussinov R, Tsai CJ, Jang H. Why Are Some Driver Mutations Rare? Trends Pharmacol Sci 2019; 40:919-929. [PMID: 31699406 DOI: 10.1016/j.tips.2019.10.003] [Citation(s) in RCA: 26] [Impact Index Per Article: 5.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/16/2019] [Revised: 10/09/2019] [Accepted: 10/10/2019] [Indexed: 12/13/2022]
Abstract
Understanding why driver mutations that promote cancer are sometimes rare is important for precision medicine since it would help in their identification. Driver mutations are largely discovered through their frequencies. Thus, rare mutations often escape detection. Unlike high-frequency drivers, low-frequency drivers can be tissue specific; rare drivers have extremely low frequencies. Here, we discuss rare drivers and strategies to discover them. We suggest that allosteric driver mutations shift the protein ensemble from the inactive to the active state. Rare allosteric drivers are statistically rare since, to switch the protein functional state, they cooperate with additional mutations, and these are not considered in the patient cancer-specific protein sequence analysis. A complete landscape of mutations that drive cancer will reveal tumor-specific therapeutic vulnerabilities.
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Affiliation(s)
- Ruth Nussinov
- Computational Structural Biology Section, Basic Science Program, Frederick National Laboratory for Cancer Research, Frederick, MD 21702, USA; Department of Human Molecular Genetics and Biochemistry, Sackler School of Medicine, Tel Aviv University, Tel Aviv 69978, Israel.
| | - Chung-Jung Tsai
- Computational Structural Biology Section, Basic Science Program, Frederick National Laboratory for Cancer Research, Frederick, MD 21702, USA
| | - Hyunbum Jang
- Computational Structural Biology Section, Basic Science Program, Frederick National Laboratory for Cancer Research, Frederick, MD 21702, USA
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Emergence of allosteric drug-resistance mutations: new challenges for allosteric drug discovery. Drug Discov Today 2019; 25:177-184. [PMID: 31634592 DOI: 10.1016/j.drudis.2019.10.006] [Citation(s) in RCA: 59] [Impact Index Per Article: 11.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/04/2019] [Revised: 09/28/2019] [Accepted: 10/11/2019] [Indexed: 01/31/2023]
Abstract
Allosteric drugs have several significant advantages over traditional orthosteric drugs, encompassing higher selectivity and lower toxicity. Although allosteric drugs have potential advantages as therapeutic agents to treat human diseases, allosteric drug-resistance mutations still occur, rendering these drugs ineffective. Here, we review the emergence of allosteric drug-resistance mutations with an emphasis on examples covering clinically important therapeutic targets, including Breakpoint cluster region-Abelson tyrosine kinase (Bcr-Abl), Akt kinase [also called Protein Kinase B (PKB)], isocitrate dehydrogenase (IDH), MAPK/ERK kinase (MEK), and SRC homology 2 domain-containing phosphatase 2 (SHP2). We also discuss challenges associated with tackling allosteric drug resistance and the possible strategies to overcome this issue.
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Tee WV, Guarnera E, Berezovsky IN. On the Allosteric Effect of nsSNPs and the Emerging Importance of Allosteric Polymorphism. J Mol Biol 2019; 431:3933-3942. [PMID: 31306666 DOI: 10.1016/j.jmb.2019.07.012] [Citation(s) in RCA: 31] [Impact Index Per Article: 6.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/27/2019] [Revised: 06/11/2019] [Accepted: 07/04/2019] [Indexed: 12/19/2022]
Abstract
The molecular mechanisms of pathological non-synonymous single-nucleotide polymorphisms are still the object of intensive research. To this end, we explore here whether non-synonymous single-nucleotide polymorphisms can work via allosteric mechanisms. Using structure-based statistical mechanical model of allostery and analyzing energetics of the effects of mutations in a set of 27 proteins with at least 50 pathological SNPs in each molecule, we found that, indeed, some SNPs can work allosterically. We illustrate the molecular basis of disease phenotypes caused by allosteric SNPs with the case studies of human galactose 1-phosphate uridyltransferase (GALT) and glucose-6-phosphate dehydrogenase (G6PD). We also found that mutations of a number of other residues in the protein may cause modulation comparable to those observed for known pathological SNPs. In order to explain this, we propose a notion of allosteric polymorphism, which implies the presence of a number of critical positions in the protein sequence, whose mutations can allosterically disrupt the protein function and result in a disease phenotype. We conclude that the emerging importance of allosteric polymorphism calls for the development of computational framework for analyzing the allosteric effects of mutations and their role in the modulation of protein activity.
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Affiliation(s)
- Wei-Ven Tee
- Bioinformatics Institute (BII), Agency for Science, Technology and Research (A*STAR), 30 Biopolis Street, #07-01, Matrix, Singapore 138671; Department of Biological Sciences (DBS), National University of Singapore (NUS), 8 Medical Drive, Singapore 117597
| | - Enrico Guarnera
- Bioinformatics Institute (BII), Agency for Science, Technology and Research (A*STAR), 30 Biopolis Street, #07-01, Matrix, Singapore 138671
| | - Igor N Berezovsky
- Bioinformatics Institute (BII), Agency for Science, Technology and Research (A*STAR), 30 Biopolis Street, #07-01, Matrix, Singapore 138671; Department of Biological Sciences (DBS), National University of Singapore (NUS), 8 Medical Drive, Singapore 117597.
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Song K, Li Q, Gao W, Lu S, Shen Q, Liu X, Wu Y, Wang B, Lin H, Chen G, Zhang J. AlloDriver: a method for the identification and analysis of cancer driver targets. Nucleic Acids Res 2019; 47:W315-W321. [PMID: 31069394 PMCID: PMC6602569 DOI: 10.1093/nar/gkz350] [Citation(s) in RCA: 27] [Impact Index Per Article: 5.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/10/2019] [Revised: 04/23/2019] [Accepted: 04/25/2019] [Indexed: 12/16/2022] Open
Abstract
Identifying the variants that alter protein function is a promising strategy for deciphering the biological consequences of somatic mutations during tumorigenesis, which could provide novel targets for the development of cancer therapies. Here, based on our previously developed method, we present a strategy called AlloDriver that identifies cancer driver genes/proteins as possible targets from mutations. AlloDriver utilizes structural and dynamic features to prioritize potentially functional genes/proteins in individual cancers via mapping mutations generated from clinical cancer samples to allosteric/orthosteric sites derived from three-dimensional protein structures. This strategy exhibits desirable performance in the reemergence of known cancer driver mutations and genes/proteins from clinical samples. Significantly, the practicability of AlloDriver to discover novel cancer driver proteins in head and neck squamous cell carcinoma (HNSC) was tested in a real case of human protein tyrosine phosphatase, receptor type K (PTPRK) through a L1143F driver mutation located at the allosteric site of PTPRK, which was experimentally validated by cell proliferation assay. AlloDriver is expected to help to uncover innovative molecular mechanisms of tumorigenesis by perturbing proteins and to discover novel targets based on cancer driver mutations. The AlloDriver is freely available to all users at http://mdl.shsmu.edu.cn/ALD.
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MESH Headings
- Algorithms
- Allosteric Regulation
- Allosteric Site
- Antineoplastic Agents/chemistry
- Antineoplastic Agents/therapeutic use
- Carcinogenesis/drug effects
- Carcinogenesis/genetics
- Carcinogenesis/metabolism
- Carcinogenesis/pathology
- Carcinoma, Squamous Cell/chemistry
- Carcinoma, Squamous Cell/drug therapy
- Carcinoma, Squamous Cell/genetics
- Carcinoma, Squamous Cell/pathology
- Cell Line, Tumor
- Cell Proliferation
- Drug Discovery
- Head and Neck Neoplasms/chemistry
- Head and Neck Neoplasms/drug therapy
- Head and Neck Neoplasms/genetics
- Head and Neck Neoplasms/pathology
- Humans
- Internet
- Molecular Targeted Therapy
- Mutation
- Neoplasm Proteins/antagonists & inhibitors
- Neoplasm Proteins/chemistry
- Neoplasm Proteins/genetics
- Neoplasm Proteins/metabolism
- Protein Binding
- Protein Conformation, alpha-Helical
- Protein Conformation, beta-Strand
- Protein Interaction Domains and Motifs
- Protein Tyrosine Phosphatase, Non-Receptor Type 11/antagonists & inhibitors
- Protein Tyrosine Phosphatase, Non-Receptor Type 11/chemistry
- Protein Tyrosine Phosphatase, Non-Receptor Type 11/genetics
- Protein Tyrosine Phosphatase, Non-Receptor Type 11/metabolism
- Receptor-Like Protein Tyrosine Phosphatases, Class 2/antagonists & inhibitors
- Receptor-Like Protein Tyrosine Phosphatases, Class 2/chemistry
- Receptor-Like Protein Tyrosine Phosphatases, Class 2/genetics
- Receptor-Like Protein Tyrosine Phosphatases, Class 2/metabolism
- Software
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Affiliation(s)
- Kun Song
- Key Laboratory of Cell Differentiation and Apoptosis of Chinese Ministry of Education, Clinical and Fundamental Research Center, Department of Pharmacy, Renji Hospital, Shanghai Jiao-Tong University School of Medicine (SJTU-SM), Shanghai 200127, China
- Research Center for Marine Drugs, State Key Laboratory of Oncogenes and Related Genes, Department of Pharmacy, Renji Hospital, Shanghai Jiao-Tong University School of Medicine (SJTU-SM), Shanghai 200127, China
| | - Qian Li
- Key Laboratory of Cell Differentiation and Apoptosis of Chinese Ministry of Education, Clinical and Fundamental Research Center, Department of Pharmacy, Renji Hospital, Shanghai Jiao-Tong University School of Medicine (SJTU-SM), Shanghai 200127, China
- Medicinal Bioinformatics Center, Shanghai Jiao-Tong University School of Medicine (SJTU-SM), Shanghai 200025, China
| | - Wei Gao
- Shanxi Key Laboratory of Otorhinolaryngology Head and Neck Cancer, Department of Otolaryngology Head & Neck Surgery, the First Hospital, Shanxi Medical University, Taiyuan, Shanxi 030001, China
| | - Shaoyong Lu
- Key Laboratory of Cell Differentiation and Apoptosis of Chinese Ministry of Education, Clinical and Fundamental Research Center, Department of Pharmacy, Renji Hospital, Shanghai Jiao-Tong University School of Medicine (SJTU-SM), Shanghai 200127, China
| | - Qiancheng Shen
- Key Laboratory of Cell Differentiation and Apoptosis of Chinese Ministry of Education, Clinical and Fundamental Research Center, Department of Pharmacy, Renji Hospital, Shanghai Jiao-Tong University School of Medicine (SJTU-SM), Shanghai 200127, China
- Medicinal Bioinformatics Center, Shanghai Jiao-Tong University School of Medicine (SJTU-SM), Shanghai 200025, China
| | - Xinyi Liu
- Key Laboratory of Cell Differentiation and Apoptosis of Chinese Ministry of Education, Clinical and Fundamental Research Center, Department of Pharmacy, Renji Hospital, Shanghai Jiao-Tong University School of Medicine (SJTU-SM), Shanghai 200127, China
- Research Center for Marine Drugs, State Key Laboratory of Oncogenes and Related Genes, Department of Pharmacy, Renji Hospital, Shanghai Jiao-Tong University School of Medicine (SJTU-SM), Shanghai 200127, China
| | - Yongyan Wu
- Shanxi Key Laboratory of Otorhinolaryngology Head and Neck Cancer, Department of Otolaryngology Head & Neck Surgery, the First Hospital, Shanxi Medical University, Taiyuan, Shanxi 030001, China
| | - Binquan Wang
- Shanxi Key Laboratory of Otorhinolaryngology Head and Neck Cancer, Department of Otolaryngology Head & Neck Surgery, the First Hospital, Shanxi Medical University, Taiyuan, Shanxi 030001, China
| | - Houwen Lin
- Key Laboratory of Cell Differentiation and Apoptosis of Chinese Ministry of Education, Clinical and Fundamental Research Center, Department of Pharmacy, Renji Hospital, Shanghai Jiao-Tong University School of Medicine (SJTU-SM), Shanghai 200127, China
- Research Center for Marine Drugs, State Key Laboratory of Oncogenes and Related Genes, Department of Pharmacy, Renji Hospital, Shanghai Jiao-Tong University School of Medicine (SJTU-SM), Shanghai 200127, China
| | - Guoqiang Chen
- Research Center for Marine Drugs, State Key Laboratory of Oncogenes and Related Genes, Department of Pharmacy, Renji Hospital, Shanghai Jiao-Tong University School of Medicine (SJTU-SM), Shanghai 200127, China
| | - Jian Zhang
- Key Laboratory of Cell Differentiation and Apoptosis of Chinese Ministry of Education, Clinical and Fundamental Research Center, Department of Pharmacy, Renji Hospital, Shanghai Jiao-Tong University School of Medicine (SJTU-SM), Shanghai 200127, China
- Research Center for Marine Drugs, State Key Laboratory of Oncogenes and Related Genes, Department of Pharmacy, Renji Hospital, Shanghai Jiao-Tong University School of Medicine (SJTU-SM), Shanghai 200127, China
- Medicinal Bioinformatics Center, Shanghai Jiao-Tong University School of Medicine (SJTU-SM), Shanghai 200025, China
- Department of Pathophysiology, Shanghai Jiao-Tong University School of Medicine (SJTU-SM), Shanghai 200025, China
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On the perturbation nature of allostery: sites, mutations, and signal modulation. Curr Opin Struct Biol 2019; 56:18-27. [DOI: 10.1016/j.sbi.2018.10.008] [Citation(s) in RCA: 52] [Impact Index Per Article: 10.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/27/2018] [Revised: 10/27/2018] [Accepted: 10/30/2018] [Indexed: 10/27/2022]
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Lu S, He X, Ni D, Zhang J. Allosteric Modulator Discovery: From Serendipity to Structure-Based Design. J Med Chem 2019; 62:6405-6421. [PMID: 30817889 DOI: 10.1021/acs.jmedchem.8b01749] [Citation(s) in RCA: 99] [Impact Index Per Article: 19.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/14/2022]
Affiliation(s)
- Shaoyong Lu
- Key Laboratory of Cell Differentiation and Apoptosis of Chinese Ministry of Education, Clinical and Fundamental Research Center, Renji Hospital, Shanghai Jiao-Tong University School of Medicine, Shanghai 200025, China
- Medicinal Bioinformatics Center, Shanghai Jiao-Tong University School of Medicine, Shanghai 200025, China
| | - Xinheng He
- Key Laboratory of Cell Differentiation and Apoptosis of Chinese Ministry of Education, Clinical and Fundamental Research Center, Renji Hospital, Shanghai Jiao-Tong University School of Medicine, Shanghai 200025, China
| | - Duan Ni
- Key Laboratory of Cell Differentiation and Apoptosis of Chinese Ministry of Education, Clinical and Fundamental Research Center, Renji Hospital, Shanghai Jiao-Tong University School of Medicine, Shanghai 200025, China
| | - Jian Zhang
- Key Laboratory of Cell Differentiation and Apoptosis of Chinese Ministry of Education, Clinical and Fundamental Research Center, Renji Hospital, Shanghai Jiao-Tong University School of Medicine, Shanghai 200025, China
- Medicinal Bioinformatics Center, Shanghai Jiao-Tong University School of Medicine, Shanghai 200025, China
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Lu S, Shen Q, Zhang J. Allosteric Methods and Their Applications: Facilitating the Discovery of Allosteric Drugs and the Investigation of Allosteric Mechanisms. Acc Chem Res 2019; 52:492-500. [PMID: 30688063 DOI: 10.1021/acs.accounts.8b00570] [Citation(s) in RCA: 112] [Impact Index Per Article: 22.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/11/2022]
Abstract
Allostery, or allosteric regulation, is the phenomenon in which protein functional activity is altered by the binding of an effector at an allosteric site that is topographically distinct from the orthosteric, active site. As one of the most direct and efficient ways to regulate protein function, allostery has played a fundamental role in innumerable biological processes of all living organisms, including enzyme catalysis, signal transduction, cell metabolism, and gene transcription. It is thus considered as "the second secret of life". The abnormality of allosteric communication networks between allosteric and orthosteric sites is associated with the pathogenesis of human diseases. Allosteric modulators, by attaching to structurally diverse allosteric sites, offer the potential for differential selectivity and improved safety compared with orthosteric drugs that bind to conserved orthosteric sites. Harnessing allostery has thus been regarded as a novel strategy for drug discovery. Despite much progress having been made in the repertoire of allostery since the turn of the millennium, the identification of allosteric drugs for therapeutic targets and the elucidation of allosteric mechanisms still present substantial challenges. These challenges are derived from the difficulties in the identification of allosteric sites and mutations, the assessment of allosteric protein-modulator interactions, the screening of allosteric modulators, and the elucidation of allosteric mechanisms in biological systems. To address these issues, we have developed a panel of allosteric services for specific allosteric applications over the past decade, including (i) the creation of the Allosteric Database, with the aim of providing comprehensive allosteric information such as allosteric proteins, modulators, sites, pathways, etc., (ii) the construction of the ASBench benchmark of high-quality allosteric sites for the development of computational methods for predicting allosteric sites, (iii) the development of Allosite and AllositePro for the prediction of the location of allosteric sites in proteins, (iv) the development of the Alloscore scoring function for the evaluation of allosteric protein-modulator interactions, (v) the development of Allosterome for evolutionary analysis of query allosteric sites/modulators within the human proteome, (vi) the development of AlloDriver for the prediction of allosteric mutagenesis, and (vii) the development of AlloFinder for the virtual screening of allosteric modulators and the investigation of allosteric mechanisms. Importantly, we have validated computationally predicted allosteric sites, mutations, and modulators in the real cases of sirtuin 6, casein kinase 2α, phosphodiesterase 10A, and signal transduction and activation of transcription 3. Furthermore, our developed allosteric methods have been widely exploited by other users around the world for allosteric research. Therefore, these allosteric services are expected to expedite the discovery of allosteric drugs and the investigation of allosteric mechanisms.
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Affiliation(s)
- Shaoyong Lu
- Department of Pathophysiology, Key Laboratory of Cell Differentiation and Apoptosis of Chinese Ministry of Education, Shanghai Jiao Tong University, School of Medicine, Shanghai 200025, China
| | - Qiancheng Shen
- Medicinal Bioinformatics Center, Shanghai Jiao Tong University, School of Medicine, Shanghai 200025, China
| | - Jian Zhang
- Department of Pathophysiology, Key Laboratory of Cell Differentiation and Apoptosis of Chinese Ministry of Education, Shanghai Jiao Tong University, School of Medicine, Shanghai 200025, China
- Medicinal Bioinformatics Center, Shanghai Jiao Tong University, School of Medicine, Shanghai 200025, China
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