1
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Bergman MT, Zhang W, Liu Y, Jang H, Nussinov R. Binding Modalities and Phase-Specific Regulation of Cyclin/Cyclin-Dependent Kinase Complexes in the Cell Cycle. J Phys Chem B 2024; 128:9315-9326. [PMID: 39314090 DOI: 10.1021/acs.jpcb.4c03243] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 09/25/2024]
Abstract
Cyclin-dependent kinases (CDKs) are activated upon cyclin-binding to enable progression through the cell cycle. Dominant CDKs and cyclins in mammalian cells include CDK1, CDK2, CDK4, and CDK6 and corresponding cyclins A, B, D, and E. While only certain, "typical" cyclin/CDK complexes are primarily responsible for cell cycle progression, "atypical" cyclin/CDK complexes can form and sometimes perform the same roles as typical complexes. We asked what structural features of cyclins and CDKs favor the formation of typical complexes, a vital yet not fully explored question. We use computational docking and biophysical analyses to exhaustively evaluate the structure and stability of all CDK and cyclin complexes listed above. We find that binding of the complexes is generally stronger for typical than for atypical complexes, especially when the CDK is in an active conformation. Typical complexes have denser clusters, indicating that they have more defined cyclin-binding sites than atypical complexes. Our results help explain three notable features of cyclin/CDK function in the cell cycle: (i) why CDK4 and cyclin-D have exceptionally high specificity for each other; (ii) why both cyclin-A and cyclin-B strongly activate CDK1, whereas CDK2 is only strongly activated by cyclin-A; and (iii) why cyclin-E normally activates CDK2 but not CDK1. Overall, this work reveals the binding modalities of cyclin/CDK complexes, how the modalities lead to the preference for typical complexes versus atypical complexes, and how binding modalities differ between typical complexes. Our observations suggest targeting CDK catalytic actions through destabilizing their native differential cyclin interfaces.
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Affiliation(s)
- Michael T Bergman
- Cancer Innovation Laboratory, National Cancer Institute, Frederick, Maryland 21702, United States
- Department of Chemical and Biomolecular Engineering, North Carolina State University, Raleigh, North Carolina 27606, United States
| | - Wengang Zhang
- Cancer Innovation Laboratory, National Cancer Institute, Frederick, Maryland 21702, United States
| | - Yonglan Liu
- Cancer Innovation Laboratory, National Cancer Institute, Frederick, Maryland 21702, United States
| | - Hyunbum Jang
- Cancer Innovation Laboratory, National Cancer Institute, Frederick, Maryland 21702, United States
- Computational Structural Biology Section, Frederick National Laboratory for Cancer Research, Frederick, Maryland 21702, United States
| | - Ruth Nussinov
- Cancer Innovation Laboratory, National Cancer Institute, Frederick, Maryland 21702, United States
- Computational Structural Biology Section, Frederick National Laboratory for Cancer Research, Frederick, Maryland 21702, United States
- Department of Human Molecular Genetics and Biochemistry, Sackler School of Medicine, Tel Aviv University, Tel Aviv 69978, Israel
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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; 1870:167260. [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] [MESH Headings] [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, Center for Autophagy, Recycling and Disease, 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, Center for Autophagy, Recycling and Disease, Danish Cancer Institute, 2100 Copenhagen, Denmark
| | - Matteo Tiberti
- Cancer Structural Biology, Center for Autophagy, Recycling and Disease, 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, Center for Autophagy, Recycling and Disease, 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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Niphakis MJ, Cravatt BF. Ligand discovery by activity-based protein profiling. Cell Chem Biol 2024; 31:1636-1651. [PMID: 39303700 DOI: 10.1016/j.chembiol.2024.08.006] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/16/2024] [Revised: 08/15/2024] [Accepted: 08/19/2024] [Indexed: 09/22/2024]
Abstract
Genomic technologies have led to massive gains in our understanding of human gene function and disease relevance. Chemical biologists are a primary beneficiary of this information, which can guide the prioritization of proteins for chemical probe and drug development. The vast functional and structural diversity of disease-relevant proteins, however, presents challenges for conventional small molecule screening libraries and assay development that in turn raise questions about the broader "druggability" of the human proteome. Here, we posit that activity-based protein profiling (ABPP), by generating global maps of small molecule-protein interactions in native biological systems, is well positioned to address major obstacles in human biology-guided chemical probe and drug discovery. We will support this viewpoint with case studies highlighting a range of small molecule mechanisms illuminated by ABPP that include the disruption and stabilization of biomolecular (protein-protein/nucleic acid) interactions and underscore allostery as a rich source of chemical tools for historically "undruggable" protein classes.
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4
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Blanco MJ, Buskes MJ, Govindaraj RG, Ipsaro JJ, Prescott-Roy JE, Padyana AK. Allostery Illuminated: Harnessing AI and Machine Learning for Drug Discovery. ACS Med Chem Lett 2024; 15:1449-1455. [PMID: 39291033 PMCID: PMC11403745 DOI: 10.1021/acsmedchemlett.4c00260] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/07/2024] [Revised: 08/15/2024] [Accepted: 08/20/2024] [Indexed: 09/19/2024] Open
Abstract
In the past several years there has been rapid adoption of artificial intelligence (AI) and machine learning (ML) tools for drug discovery. In this Microperspective, we comment on recent AI/ML applications to the discovery of allosteric modulators, focusing on breakthroughs with AlphaFold, structure-based drug discovery (SBDD), and medicinal chemistry applications. We discuss how these technologies are facilitating drug discovery and the remaining challenges to identify allosteric binding sites and ligands.
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Affiliation(s)
- Maria-Jesus Blanco
- Atavistik Bio, 101 Cambridgepark Drive, Cambridge, Massachusetts 02140, United States
| | - Melissa J Buskes
- Atavistik Bio, 101 Cambridgepark Drive, Cambridge, Massachusetts 02140, United States
| | - Rajiv G Govindaraj
- Atavistik Bio, 101 Cambridgepark Drive, Cambridge, Massachusetts 02140, United States
| | - Jonathan J Ipsaro
- Atavistik Bio, 101 Cambridgepark Drive, Cambridge, Massachusetts 02140, United States
| | - Joann E Prescott-Roy
- Atavistik Bio, 101 Cambridgepark Drive, Cambridge, Massachusetts 02140, United States
| | - Anil K Padyana
- Atavistik Bio, 101 Cambridgepark Drive, Cambridge, Massachusetts 02140, United States
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5
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Nussinov R, Jang H. The value of protein allostery in rational anticancer drug design: an update. Expert Opin Drug Discov 2024; 19:1071-1085. [PMID: 39068599 PMCID: PMC11390313 DOI: 10.1080/17460441.2024.2384467] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/15/2024] [Accepted: 07/22/2024] [Indexed: 07/30/2024]
Abstract
INTRODUCTION Allosteric drugs are advantageous. However, they still face hurdles, including identification of allosteric sites that will effectively alter the active site. Current strategies largely focus on identifying pockets away from the active sites into which the allosteric ligand will dock and do not account for exactly how the active site is altered. Favorable allosteric inhibitors dock into sites that are nearby the active sites and follow nature, mimicking diverse allosteric regulation strategies. AREAS COVERED The following article underscores the immense significance of allostery in drug design, describes current allosteric strategies, and especially offers a direction going forward. The article concludes with the authors' expert perspectives on the subject. EXPERT OPINION To select a productive venue in allosteric inhibitor development, we should learn from nature. Currently, useful strategies follow this route. Consider, for example, the mechanisms exploited in relieving autoinhibition and in harnessing allosteric degraders. Mimicking compensatory, or rescue mutations may also fall into such a thesis, as can molecular glues that capture features of scaffolding proteins. Capturing nature and creatively tailoring its mimicry can continue to innovate allosteric drug discovery.
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Affiliation(s)
- Ruth Nussinov
- Computational Structural Biology Section, Frederick National Laboratory for Cancer Research in the Cancer Innovation Laboratory, National Cancer Institute, Frederick, MD, USA
- Department of Human Molecular Genetics and Biochemistry, Sackler School of Medicine, Tel Aviv University, Tel Aviv, Israel
| | - Hyunbum Jang
- Computational Structural Biology Section, Frederick National Laboratory for Cancer Research in the Cancer Innovation Laboratory, National Cancer Institute, Frederick, MD, USA
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6
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Robinson SA, Co JA, Banik SM. Molecular glues and induced proximity: An evolution of tools and discovery. Cell Chem Biol 2024; 31:1089-1100. [PMID: 38688281 DOI: 10.1016/j.chembiol.2024.04.001] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/25/2023] [Revised: 01/23/2024] [Accepted: 04/02/2024] [Indexed: 05/02/2024]
Abstract
Small molecule molecular glues can nucleate protein complexes and rewire interactomes. Molecular glues are widely used as probes for understanding functional proximity at a systems level, and the potential to instigate event-driven pharmacology has motivated their application as therapeutics. Despite advantages such as cell permeability and the potential for low off-target activity, glues are still rare when compared to canonical inhibitors in therapeutic development. Their often simple structure and specific ability to reshape protein-protein interactions pose several challenges for widespread, designer applications. Molecular glue discovery and design campaigns can find inspiration from the fields of synthetic biology and biophysics to mine chemical libraries for glue-like molecules.
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Affiliation(s)
| | | | - Steven Mark Banik
- Department of Chemistry, Stanford University, Stanford, CA, USA; Sarafan ChEM-H, Stanford University, Stanford, CA, USA.
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7
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Inan T, Flinko R, Lewis GK, MacKerell AD, Kurkcuoglu O. Identifying and Assessing Putative Allosteric Sites and Modulators for CXCR4 Predicted through Network Modeling and Site Identification by Ligand Competitive Saturation. J Phys Chem B 2024; 128:5157-5174. [PMID: 38647430 PMCID: PMC11139592 DOI: 10.1021/acs.jpcb.4c00925] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/12/2024] [Revised: 04/04/2024] [Accepted: 04/08/2024] [Indexed: 04/25/2024]
Abstract
The chemokine receptor CXCR4 is a critical target for the treatment of several cancer types and HIV-1 infections. While orthosteric and allosteric modulators have been developed targeting its extracellular or transmembrane regions, the intramembrane region of CXCR4 may also include allosteric binding sites suitable for the development of allosteric drugs. To investigate this, we apply the Gaussian Network Model (GNM) to the monomeric and dimeric forms of CXCR4 to identify residues essential for its local and global motions located in the hinge regions of the protein. Residue interaction network (RIN) analysis suggests hub residues that participate in allosteric communication throughout the receptor. Mutual residues from the network models reside in regions with a high capacity to alter receptor dynamics upon ligand binding. We then investigate the druggability of these potential allosteric regions using the site identification by ligand competitive saturation (SILCS) approach, revealing two putative allosteric sites on the monomer and three on the homodimer. Two screening campaigns with Glide and SILCS-Monte Carlo docking using FDA-approved drugs suggest 20 putative hit compounds including antifungal drugs, anticancer agents, HIV protease inhibitors, and antimalarial drugs. In vitro assays considering mAB 12G5 and CXCL12 demonstrate both positive and negative allosteric activities of these compounds, supporting our computational approach. However, in vivo functional assays based on the recruitment of β-arrestin to CXCR4 do not show significant agonism and antagonism at a single compound concentration. The present computational pipeline brings a new perspective to computer-aided drug design by combining conformational dynamics based on network analysis and cosolvent analysis based on the SILCS technology to identify putative allosteric binding sites using CXCR4 as a showcase.
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Affiliation(s)
- Tugce Inan
- Department
of Chemical Engineering, Istanbul Technical
University, Istanbul 34469, Turkey
| | - Robin Flinko
- Institute
of Human Virology, University of Maryland
School of Medicine, Baltimore, Maryland 21201, United States
| | - George K. Lewis
- Institute
of Human Virology, University of Maryland
School of Medicine, Baltimore, Maryland 21201, United States
| | - Alexander D. MacKerell
- University
of Maryland Computer-Aided Drug Design Center, Department of Pharmaceutical
Sciences, School of Pharmacy, University
of Maryland, Baltimore, Maryland 21201, United States
| | - Ozge Kurkcuoglu
- Department
of Chemical Engineering, Istanbul Technical
University, Istanbul 34469, Turkey
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8
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Zhang W, Liu Y, Jang H, Nussinov R. CDK2 and CDK4: Cell Cycle Functions Evolve Distinct, Catalysis-Competent Conformations, Offering Drug Targets. JACS AU 2024; 4:1911-1927. [PMID: 38818077 PMCID: PMC11134382 DOI: 10.1021/jacsau.4c00138] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 02/15/2024] [Revised: 04/08/2024] [Accepted: 05/06/2024] [Indexed: 06/01/2024]
Abstract
Cyclin-dependent kinases (CDKs), particularly CDK4 and CDK2, are crucial for cell cycle progression from the Gap 1 (G1) to the Synthesis (S) phase by phosphorylating targets such as the Retinoblastoma Protein (Rb). CDK4, paired with cyclin-D, operates in the long G1 phase, while CDK2 with cyclin-E, manages the brief G1-to-S transition, enabling DNA replication. Aberrant CDK signaling leads to uncontrolled cell proliferation, which is a hallmark of cancer. Exactly how they accomplish their catalytic phosphorylation actions with distinct efficiencies poses the fundamental, albeit overlooked question. Here we combined available experimental data and modeling of the active complexes to establish their conformational functional landscapes to explain how the two cyclin/CDK complexes differentially populate their catalytically competent states for cell cycle progression. Our premise is that CDK catalytic efficiencies could be more important for cell cycle progression than the cyclin-CDK biochemical binding specificity and that efficiency is likely the prime determinant of cell cycle progression. We observe that CDK4 is more dynamic than CDK2 in the ATP binding site, the regulatory spine, and the interaction with its cyclin partner. The N-terminus of cyclin-D acts as an allosteric regulator of the activation loop and the ATP-binding site in CDK4. Integrated with a suite of experimental data, we suggest that the CDK4 complex is less capable of remaining in the active catalytically competent conformation, and may have a lower catalytic efficiency than CDK2, befitting their cell cycle time scales, and point to critical residues and motifs that drive their differences. Our mechanistic landscape may apply broadly to kinases, and we propose two drug design strategies: (i) allosteric Inhibition by conformational stabilization for targeting allosteric CDK4 regulation by cyclin-D, and (ii) dynamic entropy-optimized targeting which leverages the dynamic, entropic aspects of CDK4 to optimize drug binding efficacy.
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Affiliation(s)
- Wengang Zhang
- Cancer
Innovation Laboratory, National Cancer Institute, Frederick, Maryland 21702, United States
| | - Yonglan Liu
- Cancer
Innovation Laboratory, National Cancer Institute, Frederick, Maryland 21702, United States
| | - Hyunbum Jang
- Computational
Structural Biology Section, Frederick National
Laboratory for Cancer Research, Frederick, Maryland 21702, United States
| | - Ruth Nussinov
- Computational
Structural Biology Section, Frederick National
Laboratory for Cancer Research, Frederick, Maryland 21702, United States
- Department
of Human Molecular Genetics and Biochemistry, Sackler School of Medicine, Tel Aviv University, Tel Aviv 69978, Israel
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9
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Chen X, Zhang X, Qin M, Chen J, Wang M, Liu Z, An L, Song X, Yao L. Protein Allostery Study in Cells Using NMR Spectroscopy. Anal Chem 2024; 96:7065-7072. [PMID: 38652079 DOI: 10.1021/acs.analchem.4c00360] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/25/2024]
Abstract
Protein allostery is commonly observed in vitro. But how protein allostery behaves in cells is unknown. In this work, a protein monomer-dimer equilibrium system was built with the allosteric effect on the binding characterized using NMR spectroscopy through mutations away from the dimer interface. A chemical shift linear fitting method was developed that enabled us to accurately determine the dissociation constant. A total of 28 allosteric mutations were prepared and grouped to negative allosteric, nonallosteric, and positive allosteric modulators. ∼ 50% of mutations displayed the allosteric-state changes when moving from a buffered solution into cells. For example, there were no positive allosteric modulators in the buffered solution but eight in cells. The change in protein allostery is correlated with the interactions between the protein and the cellular environment. These interactions presumably drive the surrounding macromolecules in cells to transiently bind to the monomer and dimer mutational sites and change the free energies of the two species differently which generate new allosteric effects. These surrounding macromolecules create a new protein allostery pathway that is only present in cells.
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Affiliation(s)
- Xiaoxu Chen
- Qingdao Institute of Bioenergy and Bioprocess Technology, Chinese Academy of Sciences, Qingdao 266101, China
- Shandong Energy Institute, Qingdao 266101, China
- Qingdao New Energy Shandong Laboratory, Qingdao 266101, China
| | - Xueying Zhang
- Qingdao Institute of Bioenergy and Bioprocess Technology, Chinese Academy of Sciences, Qingdao 266101, China
- Shandong Energy Institute, Qingdao 266101, China
- Qingdao New Energy Shandong Laboratory, Qingdao 266101, China
- University of Chinese Academy of Sciences, Beijing 100049, China
| | - Mingming Qin
- Qingdao Institute of Bioenergy and Bioprocess Technology, Chinese Academy of Sciences, Qingdao 266101, China
- Shandong Energy Institute, Qingdao 266101, China
- Qingdao New Energy Shandong Laboratory, Qingdao 266101, China
| | - Jingfei Chen
- Qingdao Institute of Bioenergy and Bioprocess Technology, Chinese Academy of Sciences, Qingdao 266101, China
- Shandong Energy Institute, Qingdao 266101, China
- Qingdao New Energy Shandong Laboratory, Qingdao 266101, China
| | - Mengting Wang
- Qingdao Institute of Bioenergy and Bioprocess Technology, Chinese Academy of Sciences, Qingdao 266101, China
- Shandong Energy Institute, Qingdao 266101, China
- Qingdao New Energy Shandong Laboratory, Qingdao 266101, China
| | - Zhijun Liu
- National Facility for Protein Science, Shanghai Advanced Research Institute, Chinese Academy of Sciences, Shanghai 201210, China
| | - Liaoyuan An
- Qingdao Institute of Bioenergy and Bioprocess Technology, Chinese Academy of Sciences, Qingdao 266101, China
- Shandong Energy Institute, Qingdao 266101, China
- Qingdao New Energy Shandong Laboratory, Qingdao 266101, China
| | - Xiangfei Song
- Qingdao Institute of Bioenergy and Bioprocess Technology, Chinese Academy of Sciences, Qingdao 266101, China
- Shandong Energy Institute, Qingdao 266101, China
- Qingdao New Energy Shandong Laboratory, Qingdao 266101, China
| | - Lishan Yao
- Qingdao Institute of Bioenergy and Bioprocess Technology, Chinese Academy of Sciences, Qingdao 266101, China
- Shandong Energy Institute, Qingdao 266101, China
- Qingdao New Energy Shandong Laboratory, Qingdao 266101, China
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10
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Li Z, Xi Y, Tu L, Zhang X, Huang Y, Nie H, Peng C, Chai H, Zeng S, Zheng X, Cheng L. Investigation of the mechanism of USP28-mediated IFITM3 elevation in BCR-ABL-dependent imatinib resistance in CML. Biomed Pharmacother 2024; 173:116315. [PMID: 38394852 DOI: 10.1016/j.biopha.2024.116315] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/21/2023] [Revised: 02/07/2024] [Accepted: 02/17/2024] [Indexed: 02/25/2024] Open
Abstract
Due to resistance and BCR-ABLT315I-mutated, CML remains a clinical challenge. It needs new potential therapeutic targets to overcome CML resistance related to BCR-ABL. Our research revealed that the deubiquitinating enzyme USP28 was highly expressed in BCR-ABL-dependent CML patients. Similarly, a high expression of USP28 was found in the K562 cell line, particularly in the imatinib-resistant strains. Notably, USP28 directly interacted with BCR-ABL. Furthermore, when BCR-ABL and its mutant BCR-ABLT315I were overexpressed in K562-IMR, they promoted the expression of IFITM3. However, when small molecule inhibitors targeting USP28 and small molecule degraders targeting BCR-ABL were combined, they significantly inhibited the expression of IFITM3. The experiments conducted on tumor-bearing animals revealed that co-treated mice showed a significant reduction in tumor size, effectively inhibiting the progression of CML tumors. In summary, USP28 promoted the proliferation and invasion of tumor cells in BCR-ABL-dependent CML by enhancing the expression of IFITM3. Moreover, imatinib resistance might be triggered by the activation of the USP28-BCR-ABL-IFITM3 pathway. Thus, the combined inhibition of USP28 and BCR-ABL could be a promising approach to overcome CML resistance dependent on BCR-ABL.
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Affiliation(s)
- Zilin Li
- School of Laboratory Medicine and Bioengineering, Hangzhou Medical College, Hangzhou, Zhejiang, China
| | - Yiling Xi
- School of Laboratory Medicine and Bioengineering, Hangzhou Medical College, Hangzhou, Zhejiang, China
| | - Linglan Tu
- School of Laboratory Medicine and Bioengineering, Hangzhou Medical College, Hangzhou, Zhejiang, China
| | - Xu Zhang
- School of Laboratory Medicine and Bioengineering, Hangzhou Medical College, Hangzhou, Zhejiang, China
| | - Yue Huang
- School of Laboratory Medicine and Bioengineering, Hangzhou Medical College, Hangzhou, Zhejiang, China
| | - Huizong Nie
- School of Laboratory Medicine and Bioengineering, Hangzhou Medical College, Hangzhou, Zhejiang, China
| | - Cheng Peng
- School of Laboratory Medicine and Bioengineering, Hangzhou Medical College, Hangzhou, Zhejiang, China
| | - Haohuan Chai
- School of Laboratory Medicine and Bioengineering, Hangzhou Medical College, Hangzhou, Zhejiang, China
| | - Shenxin Zeng
- School of Pharmacy, Hangzhou Medical College, Hangzhou, Zhejiang, China
| | - Xiaoliang Zheng
- School of Laboratory Medicine and Bioengineering, Hangzhou Medical College, Hangzhou, Zhejiang, China.
| | - Liyan Cheng
- School of Laboratory Medicine and Bioengineering, Hangzhou Medical College, Hangzhou, Zhejiang, China.
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11
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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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12
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Deng J, Yuan Y, Cui Q. Modulation of Allostery with Multiple Mechanisms by Hotspot Mutations in TetR. J Am Chem Soc 2024; 146:2757-2768. [PMID: 38231868 PMCID: PMC10843641 DOI: 10.1021/jacs.3c12494] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/19/2024]
Abstract
Modulating allosteric coupling offers unique opportunities for biomedical applications. Such efforts can benefit from efficient prediction and evaluation of allostery hotspot residues that dictate the degree of cooperativity between distant sites. We demonstrate that effects of allostery hotspot mutations can be evaluated qualitatively and semiquantitatively by molecular dynamics simulations in a bacterial tetracycline repressor (TetR). The simulations recapitulate the effects of these mutations on abolishing the induction function of TetR and provide a rationale for the different rescuabilities observed to restore allosteric coupling of the hotspot mutations. We demonstrate that the same noninducible phenotype could be the result of perturbations in distinct structural and energetic properties of TetR. Our work underscores the value of explicitly computing the functional free energy landscapes to effectively evaluate and rank hotspot mutations despite the prevalence of compensatory interactions and therefore provides quantitative guidance to allostery modulation for therapeutic and engineering applications.
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Affiliation(s)
- Jiahua Deng
- Department of Chemistry, Boston University, 590 Commonwealth Avenue, Boston, Massachusetts 02215, United States
| | - Yuchen Yuan
- Department of Chemistry, Boston University, 590 Commonwealth Avenue, Boston, Massachusetts 02215, United States
| | - Qiang Cui
- Department of Chemistry, Boston University, 590 Commonwealth Avenue, Boston, Massachusetts 02215, United States
- Department of Physics, Boston University, 590 Commonwealth Avenue, Boston, Massachusetts 02215, United States
- Department of Biomedical Engineering, Boston University, 44 Cummington Mall, Boston, Massachusetts 02215, United States
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13
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Deng J, Yuan Y, Cui Q. Modulation of Allostery with Multiple Mechanisms by Hotspot Mutations in TetR. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.08.29.555381. [PMID: 37905112 PMCID: PMC10614727 DOI: 10.1101/2023.08.29.555381] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/02/2023]
Abstract
Modulating allosteric coupling offers unique opportunities for biomedical applications. Such efforts can benefit from efficient prediction and evaluation of allostery hotspot residues that dictate the degree of co-operativity between distant sites. We demonstrate that effects of allostery hotspot mutations can be evaluated qualitatively and semi-quantitatively by molecular dynamics simulations in a bacterial tetracycline repressor (TetR). The simulations recapitulate the effects of these mutations on abolishing the induction function of TetR and provide a rationale for the different degrees of rescuability observed to restore allosteric coupling of the hotspot mutations. We demonstrate that the same non-inducible phenotype could be the result of perturbations in distinct structural and energetic properties of TetR. Our work underscore the value of explicitly computing the functional free energy landscapes to effectively evaluate and rank hotspot mutations despite the prevalence of compensatory interactions, and therefore provide quantitative guidance to allostery modulation for therapeutic and engineering applications.
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Affiliation(s)
- Jiahua Deng
- Department of Chemistry, Boston University, 590 Commonwealth Avenue, Boston, Massachusetts 02215, United States
| | - Yuchen Yuan
- Department of Chemistry, Boston University, 590 Commonwealth Avenue, Boston, Massachusetts 02215, United States
| | - Qiang Cui
- Department of Chemistry, Boston University, 590 Commonwealth Avenue, Boston, Massachusetts 02215, United States
- Department of Physics, Boston University, 590 Commonwealth Avenue, Boston, Massachusetts 02215, United States
- Department of Biomedical Engineering, Boston University, 44 Cummington Mall, Boston, Massachusetts 02215, United States
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14
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Zha J, He J, Wu C, Zhang M, Liu X, Zhang J. Designing drugs and chemical probes with the dualsteric approach. Chem Soc Rev 2023; 52:8651-8677. [PMID: 37990599 DOI: 10.1039/d3cs00650f] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/23/2023]
Abstract
Traditionally, drugs are monovalent, targeting only one site on the protein surface. This includes orthosteric and allosteric drugs, which bind the protein at orthosteric and allosteric sites, respectively. Orthosteric drugs are good in potency, whereas allosteric drugs have better selectivity and are solutions to classically undruggable targets. However, it would be difficult to simultaneously reach high potency and selectivity when targeting only one site. Also, both kinds of monovalent drugs suffer from mutation-caused drug resistance. To overcome these obstacles, dualsteric modulators have been proposed in the past twenty years. Compared to orthosteric or allosteric drugs, dualsteric modulators are bivalent (or bitopic) with two pharmacophores. Each of the two pharmacophores bind the protein at the orthosteric and an allosteric site, which could bring the modulator with special properties beyond monovalent drugs. In this study, we comprehensively review the current development of dualsteric modulators. Our main effort reason and illustrate the aims to apply the dualsteric approach, including a "double win" of potency and selectivity, overcoming mutation-caused drug resistance, developments of function-biased modulators, and design of partial agonists. Moreover, the strengths of the dualsteric technique also led to its application outside pharmacy, including the design of highly sensitive fluorescent tracers and usage as molecular rulers. Besides, we also introduced drug targets, designing strategies, and validation methods of dualsteric modulators. Finally, we detail the conclusions and perspectives.
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Affiliation(s)
- Jinyin Zha
- College of Pharmacy, Ningxia Medical University, Yinchuan, Ningxia Hui 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
| | - Jixiao He
- 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
| | - Chengwei Wu
- 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
| | - Mingyang Zhang
- 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
| | - Xinyi Liu
- College of Pharmacy, Ningxia Medical University, Yinchuan, Ningxia Hui 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
| | - Jian Zhang
- College of Pharmacy, Ningxia Medical University, Yinchuan, Ningxia Hui 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, China
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15
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Lu X, Lan X, Lu S, Zhang J. Progressive computational approaches to facilitate decryption of allosteric mechanism and drug discovery. Curr Opin Struct Biol 2023; 83:102701. [PMID: 37716092 DOI: 10.1016/j.sbi.2023.102701] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/12/2023] [Revised: 08/17/2023] [Accepted: 08/21/2023] [Indexed: 09/18/2023]
Abstract
Allostery is a ubiquitous biological phenomenon where perturbation at topologically distal areas of a protein serves as a trigger to fine-tune the orthosteric site and thus regulate protein function. The investigation of allosteric regulation greatly enhances our understanding of human diseases and broadens avenue for drug discovery. For decades, owing to the difficulty in allostery characterization through serendipitous experimental screening, researchers have developed several innovative computational approaches, which proves to accelerate the elucidation of allostery. Herein, we review the state-of-the-art advance of computational methodologies for allostery study, with particular emphasis on promising trends emerging over the past two years. We expect this review will outline the latest landscape of allostery study and inspire researchers to further facilitate this field.
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Affiliation(s)
- Xun Lu
- School of Pharmacy, Ningxia Medical University, Yinchuan 750004, 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 200025, China; Medicinal Chemistry and Bioinformatics Center, Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China
| | - Xiaobing Lan
- School of Pharmacy, Ningxia Medical University, Yinchuan 750004, China
| | - Shaoyong Lu
- School of Pharmacy, Ningxia Medical University, Yinchuan 750004, 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 200025, China; Medicinal Chemistry and Bioinformatics Center, Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China
| | - Jian Zhang
- School of Pharmacy, Ningxia Medical University, Yinchuan 750004, 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 200025, China; Medicinal Chemistry and Bioinformatics Center, Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China; School of Pharmaceutical Sciences, Zhengzhou University, Zhengzhou, China.
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16
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Colombo G. Computing allostery: from the understanding of biomolecular regulation and the discovery of cryptic sites to molecular design. Curr Opin Struct Biol 2023; 83:102702. [PMID: 37716095 DOI: 10.1016/j.sbi.2023.102702] [Citation(s) in RCA: 10] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/10/2023] [Revised: 08/22/2023] [Accepted: 08/22/2023] [Indexed: 09/18/2023]
Abstract
The concept of allostery has become a central tenet in the study of biological systems. In parallel, the discovery of allosteric drugs is generating new opportunities to selectively modulate difficult targets involved in pathologic mechanisms. Molecular simulations can provide atomistically detailed insight into the processes involved in allosteric regulation and signaling, and at the same time, they have the potential to unveil regulatory hotspots or cryptic sites that are not immediately evident from the analysis of static structures. In this context, computational approaches should be able to connect the study of allosteric regulation at different scales to the possibility of leveraging this knowledge to expand the chemical space of new, active drugs. Here, we will discuss recent advances in the study of allosteric regulation via computational methods and connect the mechanistic knowledge generated to the possibility of designing new small molecules that can tweak the functions of their receptors.
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Affiliation(s)
- Giorgio Colombo
- Department of Chemistry, University of Pavia, Via Taramelli 12, 27100 Pavia, Italy.
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17
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Liu X, Yang B, Huang X, Yan W, Zhang Y, Hu G. Identifying Lymph Node Metastasis-Related Factors in Breast Cancer Using Differential Modular and Mutational Structural Analysis. Interdiscip Sci 2023; 15:525-541. [PMID: 37115388 DOI: 10.1007/s12539-023-00568-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/25/2023] [Revised: 04/13/2023] [Accepted: 04/13/2023] [Indexed: 04/29/2023]
Abstract
Complex diseases are generally caused by disorders of biological networks and/or mutations in multiple genes. Comparisons of network topologies between different disease states can highlight key factors in their dynamic processes. Here, we propose a differential modular analysis approach that integrates protein-protein interactions with gene expression profiles for modular analysis, and introduces inter-modular edges and date hubs to identify the "core network module" that quantifies the significant phenotypic variation. Then, based on this core network module, key factors, including functional protein-protein interactions, pathways, and driver mutations, are predicted by the topological-functional connection score and structural modeling. We applied this approach to analyze the lymph node metastasis (LNM) process in breast cancer. The functional enrichment analysis showed that both inter-modular edges and date hubs play important roles in cancer metastasis and invasion, and in metastasis hallmarks. The structural mutation analysis suggested that the LNM of breast cancer may be the outcome of the dysfunction of rearranged during transfection (RET) proto-oncogene-related interactions and the non-canonical calcium signaling pathway via an allosteric mutation of RET. We believe that the proposed method can provide new insights into disease progression such as cancer metastasis.
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Affiliation(s)
- Xingyi Liu
- Center for Systems Biology, Department of Bioinformatics, School of Biology and Basic Medical Sciences, Soochow University, Suzhou, 215123, Jiangsu, China
| | - Bin Yang
- Center for Systems Biology, Department of Bioinformatics, School of Biology and Basic Medical Sciences, Soochow University, Suzhou, 215123, Jiangsu, China
| | - Xinpeng Huang
- Center for Systems Biology, Department of Bioinformatics, School of Biology and Basic Medical Sciences, Soochow University, Suzhou, 215123, Jiangsu, China
| | - Wenying Yan
- Center for Systems Biology, Department of Bioinformatics, School of Biology and Basic Medical Sciences, Soochow University, Suzhou, 215123, Jiangsu, China.
- Jiangsu Province Engineering Research Center of Precision Diagnostics and Therapeutics Development, Suzhou, 215123, Jiangsu, China.
| | - Yujuan Zhang
- Experimental Center of Suzhou Medical College, Soochow University, Suzhou, 215123, Jiangsu, China.
| | - Guang Hu
- Center for Systems Biology, Department of Bioinformatics, School of Biology and Basic Medical Sciences, Soochow University, Suzhou, 215123, Jiangsu, China.
- Jiangsu Province Engineering Research Center of Precision Diagnostics and Therapeutics Development, Suzhou, 215123, Jiangsu, China.
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18
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Nussinov R, Liu Y, Zhang W, Jang H. Protein conformational ensembles in function: roles and mechanisms. RSC Chem Biol 2023; 4:850-864. [PMID: 37920394 PMCID: PMC10619138 DOI: 10.1039/d3cb00114h] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/30/2023] [Accepted: 09/02/2023] [Indexed: 11/04/2023] Open
Abstract
The sequence-structure-function paradigm has dominated twentieth century molecular biology. The paradigm tacitly stipulated that for each sequence there exists a single, well-organized protein structure. Yet, to sustain cell life, function requires (i) that there be more than a single structure, (ii) that there be switching between the structures, and (iii) that the structures be incompletely organized. These fundamental tenets called for an updated sequence-conformational ensemble-function paradigm. The powerful energy landscape idea, which is the foundation of modernized molecular biology, imported the conformational ensemble framework from physics and chemistry. This framework embraces the recognition that proteins are dynamic and are always interconverting between conformational states with varying energies. The more stable the conformation the more populated it is. The changes in the populations of the states are required for cell life. As an example, in vivo, under physiological conditions, wild type kinases commonly populate their more stable "closed", inactive, conformations. However, there are minor populations of the "open", ligand-free states. Upon their stabilization, e.g., by high affinity interactions or mutations, their ensembles shift to occupy the active states. Here we discuss the role of conformational propensities in function. We provide multiple examples of diverse systems, including protein kinases, lipid kinases, and Ras GTPases, discuss diverse conformational mechanisms, and provide a broad outlook on protein ensembles in the cell. We propose that the number of molecules in the active state (inactive for repressors), determine protein function, and that the dynamic, relative conformational propensities, rather than the rigid structures, are the hallmark of cell life.
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Affiliation(s)
- Ruth Nussinov
- Computational Structural Biology Section, 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
- Cancer Innovation Laboratory, National Cancer Institute Frederick MD 21702 USA
| | - Yonglan Liu
- Cancer Innovation Laboratory, National Cancer Institute Frederick MD 21702 USA
| | - Wengang Zhang
- Cancer Innovation Laboratory, National Cancer Institute Frederick MD 21702 USA
| | - Hyunbum Jang
- Computational Structural Biology Section, Frederick National Laboratory for Cancer Research Frederick MD 21702 USA
- Cancer Innovation Laboratory, National Cancer Institute Frederick MD 21702 USA
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19
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de Buhr S, Gräter F. Myristoyl's dual role in allosterically regulating and localizing Abl kinase. eLife 2023; 12:e85216. [PMID: 37843155 PMCID: PMC10619977 DOI: 10.7554/elife.85216] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/28/2022] [Accepted: 10/15/2023] [Indexed: 10/17/2023] Open
Abstract
c-Abl kinase, a key signaling hub in many biological processes ranging from cell development to proliferation, is tightly regulated by two inhibitory Src homology domains. An N-terminal myristoyl modification can bind to a hydrophobic pocket in the kinase C-lobe, which stabilizes the autoinhibitory assembly. Activation is triggered by myristoyl release. We used molecular dynamics simulations to show how both myristoyl and the Src homology domains are required to impose the full inhibitory effect on the kinase domain and reveal the allosteric transmission pathway at residue-level resolution. Importantly, we find myristoyl insertion into a membrane to thermodynamically compete with binding to c-Abl. Myristoyl thus not only localizes the protein to the cellular membrane, but membrane attachment at the same time enhances activation of c-Abl by stabilizing its preactivated state. Our data put forward a model in which lipidation tightly couples kinase localization and regulation, a scheme that currently appears to be unique for this non-receptor tyrosine kinase.
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Affiliation(s)
- Svenja de Buhr
- Heidelberg Institute for Theoretical Studies (HITS), Heidelberg UniversityHeidelbergGermany
| | - Frauke Gräter
- Heidelberg Institute for Theoretical Studies (HITS), Heidelberg UniversityHeidelbergGermany
- Institute for Scientific Computing (IWR), Heidelberg UniversityHeidelbergGermany
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20
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Gianni S, Jemth P. Allostery Frustrates the Experimentalist. J Mol Biol 2023; 435:167934. [PMID: 36586463 DOI: 10.1016/j.jmb.2022.167934] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/21/2022] [Revised: 12/20/2022] [Accepted: 12/22/2022] [Indexed: 12/29/2022]
Abstract
Proteins interact with other proteins, with nucleic acids, lipids, carbohydrates and various small molecules in the living cell. These interactions have been quantified and structurally characterized in numerous studies such that we today have a comprehensive picture of protein structure and function. However, proteins are dynamic and even folded proteins are likely more heterogeneous than they appear in most descriptions. One property of proteins that relies on dynamics and heterogeneity is allostery, the ability of a protein to change structure and function upon ligand binding to an allosteric site. Over the last decades the concept of allostery was broadened to embrace all types of long-range interactions across a protein including purely entropic changes without a conformational change in single protein domains. But with this re-definition came a problem: How do we measure allostery? In this opinion, we discuss some caveats arising from the quantitative description of single-domain allostery from an experimental perspective and how the limitations cannot be separated from the definition of allostery per se. Furthermore, we attempt to tie together allostery with the concept of frustration in an effort to investigate the links between these two complex, and yet general, properties of proteins. We arrive at the conclusion that the sensitivity to perturbation of allosteric networks in single protein domains is too large for the networks to be of significant biological relevance.
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Affiliation(s)
- Stefano Gianni
- Istituto Pasteur-Fondazione Cenci Bolognetti and Istituto di Biologia e Patologia Molecolari del CNR, Dipartimento di Scienze Biochimiche "A. Rossi Fanelli," Sapienza Università di Roma, 00185 Rome, Italy.
| | - Per Jemth
- Department of Medical Biochemistry and Microbiology, Uppsala University, BMC Box 582, SE-75123 Uppsala, Sweden.
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21
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Fabry J, Thayer KM. Network Analysis of Molecular Dynamics Sectors in the p53 Protein. ACS OMEGA 2023; 8:571-587. [PMID: 36643471 PMCID: PMC9835189 DOI: 10.1021/acsomega.2c05635] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 08/31/2022] [Accepted: 12/05/2022] [Indexed: 06/17/2023]
Abstract
Design of allosteric regulators is an emergent field in the area of drug discovery holding promise for currently untreated diseases. Allosteric regulators bind to a protein in one location and affect a distant site. The ubiquitous presence of allosteric effectors in biology and the success of serendipitously identified allosteric compounds point to the potential they hold. Although the mechanism of transmission of an allosteric signal is not unequivocally determined, one hypothesis suggests that groups of evolutionarily covarying residues within a protein, termed sectors, are conduits. A long-term goal of our lab is to allosterically modulate the activity of proteins by binding small molecules at points of allosteric control. However, methods to consistently identify such points remain unclear. Sector residues on the surfaces of proteins are a promising source of allosteric targets. Recently, we introduced molecular dynamics (MD)-based sectors; MD sectors capitalize on covariance of motion, in place of evolutionary covariance. By focusing on motional covariance, MD sectors tap into the framework of statistical mechanics afforded by the Boltzmann ensemble of structural conformations comprising the underlying data set. We hypothesized that the method of MD sectors can be used to identify a cohesive network of motionally covarying residues capable of transmitting an allosteric signal in a protein. While our initial qualitative results showed promise for the method to predict sectors, that a network of cohesively covarying residues had been produced remained an untested assumption. In this work, we apply network theory to rigorously analyze MD sectors, allowing us to quantitatively assess the biologically relevant property of network cohesiveness of sectors in the context of the tumor suppressor protein, p53. We revised the methodology for assessing and improving MD sectors. Specifically, we introduce a metric to calculate the cohesive properties of the network. Our new approach separates residues into two categories: sector residues and non-sector residues. The relatedness within each respective group is computed with a distance metric. Cohesive sector networks are identified as those that have high relatedness among the sector residues which exceeds the relatedness of the residues to the non-sector residues in terms of the correlation of motions. Our major finding was that the revised means of obtaining sectors was more efficacious than previous iterations, as evidenced by the greater cohesion of the networks. These results are discussed in the context of the development of allosteric regulators of p53 in particular and the expected applicability of the method to the drug design field in general.
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Affiliation(s)
- Jonathan
D. Fabry
- Department
of Mathematics and Computer Science, Wesleyan
University, Middletown, Connecticut06457United States
- Department
of Chemistry, Wesleyan University, Middletown, Connecticut06457, United States
| | - Kelly M. Thayer
- Department
of Mathematics and Computer Science, Wesleyan
University, Middletown, Connecticut06457United States
- Department
of Chemistry, Wesleyan University, Middletown, Connecticut06457, United States
- College
of Integrative Sciences, Wesleyan University, Middletown, Connecticut06457, United States
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22
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Ozdemir ES, Nussinov R. Pathogen-driven cancers from a structural perspective: Targeting host-pathogen protein-protein interactions. Front Oncol 2023; 13:1061595. [PMID: 36910650 PMCID: PMC9997845 DOI: 10.3389/fonc.2023.1061595] [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: 10/04/2022] [Accepted: 02/06/2023] [Indexed: 02/25/2023] Open
Abstract
Host-pathogen interactions (HPIs) affect and involve multiple mechanisms in both the pathogen and the host. Pathogen interactions disrupt homeostasis in host cells, with their toxins interfering with host mechanisms, resulting in infections, diseases, and disorders, extending from AIDS and COVID-19, to cancer. Studies of the three-dimensional (3D) structures of host-pathogen complexes aim to understand how pathogens interact with their hosts. They also aim to contribute to the development of rational therapeutics, as well as preventive measures. However, structural studies are fraught with challenges toward these aims. This review describes the state-of-the-art in protein-protein interactions (PPIs) between the host and pathogens from the structural standpoint. It discusses computational aspects of predicting these PPIs, including machine learning (ML) and artificial intelligence (AI)-driven, and overviews available computational methods and their challenges. It concludes with examples of how theoretical computational approaches can result in a therapeutic agent with a potential of being used in the clinics, as well as future directions.
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Affiliation(s)
- Emine Sila Ozdemir
- Cancer Early Detection Advanced Research Center, Knight Cancer Institute, Oregon Health & Science University, Portland, OR, United States
| | - Ruth Nussinov
- Cancer Innovation Laboratory, Frederick National Laboratory for Cancer Research, National Cancer Institute at Frederick, Frederick, MD, United States.,Department of Human Molecular Genetics and Biochemistry, Sackler School of Medicine, Tel Aviv University, Tel Aviv, Israel
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23
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Liu Y, Zhang M, Jang H, Nussinov R. Higher-order interactions of Bcr-Abl can broaden chronic myeloid leukemia (CML) drug repertoire. Protein Sci 2023; 32:e4504. [PMID: 36369657 PMCID: PMC9795542 DOI: 10.1002/pro.4504] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/30/2022] [Revised: 10/31/2022] [Accepted: 11/06/2022] [Indexed: 11/14/2022]
Abstract
Bcr-Abl, a nonreceptor tyrosine kinase, is associated with leukemias, especially chronic myeloid leukemia (CML). Deletion of Abl's N-terminal region, to which myristoyl is linked, renders the Bcr-Abl fusion oncoprotein constitutively active. The substitution of Abl's N-terminal region by Bcr enables Bcr-Abl oligomerization. Oligomerization is critical: it promotes clustering on the membrane, which is essential for potent MAPK signaling and cell proliferation. Here we decipher the Bcr-Abl specific, step-by-step oligomerization process, identify a specific packing surface, determine exactly how the process is structured and identify its key elements. Bcr's coiled coil (CC) domain at the N-terminal controls Bcr-Abl oligomerization. Crystallography validated oligomerization via Bcr-Abl dimerization between two Bcr CC domains, with tetramerization via tight packing between two binary assemblies. However, the structural principles guiding Bcr CC domain oligomerization are unknown, hindering mechanistic understanding and drugs exploiting it. Using molecular dynamics (MD) simulations, we determine that the binary complex of the Bcr CC domain serves as a basic unit in the quaternary complex providing a specific surface for dimer-dimer packing and higher-order oligomerization. We discover that the small α1-helix is the key. In the binary assembly, the helix forms interchain aromatic dimeric packing, and in the quaternary assembly, it contributes to the specific dimer-dimer packing. Our mechanism is supported by the experimental literature. It offers the key elements controlling this process which can expand the drug discovery strategy, including by Bcr CC-derived peptides, and candidate residues for small covalent drugs, toward quenching oligomerization, supplementing competitive and allosteric tyrosine kinase inhibitors.
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Affiliation(s)
- Yonglan Liu
- Cancer Innovation LaboratoryNational Cancer InstituteFrederickMarylandUSA
| | - Mingzhen Zhang
- Computational Structural Biology SectionFrederick National Laboratory for Cancer ResearchFrederickMarylandUSA
| | - Hyunbum Jang
- Computational Structural Biology SectionFrederick National Laboratory for Cancer ResearchFrederickMarylandUSA
| | - Ruth Nussinov
- Computational Structural Biology SectionFrederick National Laboratory for Cancer ResearchFrederickMarylandUSA,Department of Human Molecular Genetics and BiochemistrySackler School of Medicine, Tel Aviv UniversityTel AvivIsrael
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24
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Armour-Garb I, Han ISM, Cowan BS, Thayer KM. Variable Regions of p53 Isoforms Allosterically Hard Code DNA Interaction. J Phys Chem B 2022; 126:8495-8507. [PMID: 36245142 PMCID: PMC9623584 DOI: 10.1021/acs.jpcb.2c06229] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/05/2022]
Abstract
Allosteric regulation of protein activity pervades biology as the "second secret of life." We have been examining the allosteric regulation and mutant reactivation of the tumor suppressor protein p53. We have found that generalizing the definition of allosteric effector to include entire proteins and expanding the meaning of binding site to include the interface of a transcription factor with its DNA to be useful in understanding the modulation of protein activity. Here, we cast the variable regions of p53 isoforms as allosteric regulators of p53 interactions with its consensus DNA. We implemented molecular dynamics simulations and our lab's new techniques of molecular dynamics (MD) sectors and MD-Markov state models to investigate the effects of nine naturally occurring splice variant isoforms of p53. We find that all of the isoforms differ from wild type in their dynamic properties and how they interact with the DNA. We consider the implications of these findings on allostery and cancer treatment.
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Affiliation(s)
- Isabel Armour-Garb
- †Department
of Mathematics and Computer Science, ‡Department of Chemistry, and §College of Integrative
Sciences, Wesleyan University, Middletown, Connecticut 06457, United States
| | - In Sub Mark Han
- †Department
of Mathematics and Computer Science, ‡Department of Chemistry, and §College of Integrative
Sciences, Wesleyan University, Middletown, Connecticut 06457, United States
| | - Benjamin S. Cowan
- †Department
of Mathematics and Computer Science, ‡Department of Chemistry, and §College of Integrative
Sciences, Wesleyan University, Middletown, Connecticut 06457, United States
| | - Kelly M. Thayer
- †Department
of Mathematics and Computer Science, ‡Department of Chemistry, and §College of Integrative
Sciences, Wesleyan University, Middletown, Connecticut 06457, United States,
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25
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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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Nussinov R, Zhang M, Liu Y, Jang H. AlphaFold, Artificial Intelligence (AI), and Allostery. J Phys Chem B 2022; 126:6372-6383. [PMID: 35976160 PMCID: PMC9442638 DOI: 10.1021/acs.jpcb.2c04346] [Citation(s) in RCA: 49] [Impact Index Per Article: 24.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/22/2022] [Revised: 08/03/2022] [Indexed: 02/08/2023]
Abstract
AlphaFold has burst into our lives. A powerful algorithm that underscores the strength of biological sequence data and artificial intelligence (AI). AlphaFold has appended projects and research directions. The database it has been creating promises an untold number of applications with vast potential impacts that are still difficult to surmise. AI approaches can revolutionize personalized treatments and usher in better-informed clinical trials. They promise to make giant leaps toward reshaping and revamping drug discovery strategies, selecting and prioritizing combinations of drug targets. Here, we briefly overview AI in structural biology, including in molecular dynamics simulations and prediction of microbiota-human protein-protein interactions. We highlight the advancements accomplished by the deep-learning-powered AlphaFold in protein structure prediction and their powerful impact on the life sciences. At the same time, AlphaFold does not resolve the decades-long protein folding challenge, nor does it identify the folding pathways. The models that AlphaFold provides do not capture conformational mechanisms like frustration and allostery, which are rooted in ensembles, and controlled by their dynamic distributions. Allostery and signaling are properties of populations. AlphaFold also does not generate ensembles of intrinsically disordered proteins and regions, instead describing them by their low structural probabilities. Since AlphaFold generates single ranked structures, rather than conformational ensembles, it cannot elucidate the mechanisms of allosteric activating driver hotspot mutations nor of allosteric drug resistance. However, by capturing key features, deep learning techniques can use the single predicted conformation as the basis for generating a diverse ensemble.
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Affiliation(s)
- Ruth Nussinov
- Computational
Structural Biology Section, Frederick National
Laboratory for Cancer Research, Frederick, Maryland 21702, United States
- 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, Frederick, Maryland 21702, United States
| | - Yonglan Liu
- Cancer
Innovation Laboratory, National Cancer Institute, Frederick, Maryland 21702, United States
| | - Hyunbum Jang
- Computational
Structural Biology Section, Frederick National
Laboratory for Cancer Research, Frederick, Maryland 21702, United States
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Liu Y, Zhang M, Tsai CJ, Jang H, Nussinov R. Allosteric regulation of autoinhibition and activation of c-Abl. Comput Struct Biotechnol J 2022; 20:4257-4270. [PMID: 36051879 PMCID: PMC9399898 DOI: 10.1016/j.csbj.2022.08.014] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/22/2022] [Revised: 08/07/2022] [Accepted: 08/07/2022] [Indexed: 11/23/2022] Open
Abstract
c-Abl, a non-receptor tyrosine kinase, regulates cell growth and survival in healthy cells and causes chronic myeloid leukemia (CML) when fused by Bcr. Its activity is blocked in the assembled inactive state, where the SH3 and SH2 domains dock into the kinase domain, reducing its conformational flexibility, resulting in the autoinhibited state. It is active in an extended 'open' conformation. Allostery governs the transitions between the autoinhibited and active states. Even though experiments revealed the structural hallmarks of the two states, a detailed grasp of the determinants of c-Abl autoinhibition and activation at the atomic level, which may help innovative drug discovery, is still lacking. Here, using extensive molecular dynamics simulations, we decipher exactly how these determinants regulate it. Our simulations confirm and extend experimental data that the myristoyl group serves as the switch for c-Abl inhibition/activation. Its dissociation from the kinase domain promotes the SH2-SH3 release, initiating c-Abl activation. We show that the precise SH2/N-lobe interaction is required for full activation of c-Abl. It stabilizes a catalysis-favored conformation, priming it for catalytic action. Bcr-Abl allosteric drugs elegantly mimic the endogenous myristoyl-mediated autoinhibition state of c-Abl 1b. Allosteric activating mutations shift the ensemble to the active state, blocking ATP-competitive drugs. Allosteric drugs alter the active-site conformation, shifting the ensemble to re-favor ATP-competitive drugs. Our work provides a complete mechanism of c-Abl activation and insights into critical parameters controlling at the atomic level c-Abl inactivation, leading us to propose possible strategies to counter reemergence of drug resistance.
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Affiliation(s)
- Yonglan Liu
- Cancer Innovation Laboratory, National Cancer Institute, Frederick, MD 21702, USA
| | - Mingzhen Zhang
- Computational Structural Biology Section, Frederick National Laboratory for Cancer Research, Frederick, MD 21702, USA
| | - Chung-Jung Tsai
- Computational Structural Biology Section, Frederick National Laboratory for Cancer Research, Frederick, MD 21702, USA
| | - Hyunbum Jang
- Computational Structural Biology Section, Frederick National Laboratory for Cancer Research, Frederick, MD 21702, USA
| | - Ruth Nussinov
- Computational Structural Biology Section, 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
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Berezovsky IN, Nussinov R. Multiscale Allostery: Basic Mechanisms and Versatility in Diagnostics and Drug Design. J Mol Biol 2022; 434:167751. [PMID: 35863488 DOI: 10.1016/j.jmb.2022.167751] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/17/2023]
Affiliation(s)
- Igor N Berezovsky
- Bioinformatics Institute (BII), Agency for Science, Technology and Research (A*STAR), 30 Biopolis Street, #07-01, Matrix, Singapore 138671, Singapore; Department of Biological Sciences (DBS), National University of Singapore (NUS), 8 Medical Drive, 117579, Singapore.
| | - Ruth Nussinov
- Computational Structural Biology Section, Frederick National Laboratory for Cancer Research in the Cancer Innovation Laboraory, 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.
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Alexandar SP, Yennamalli RM, Ulaganathan V. Coarse grained modelling highlights the binding differences in the two different allosteric sites of the Human Kinesin EG5 and its implications in inhibitor design. Comput Biol Chem 2022; 99:107708. [PMID: 35717732 DOI: 10.1016/j.compbiolchem.2022.107708] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/26/2022] [Revised: 05/26/2022] [Accepted: 05/27/2022] [Indexed: 11/03/2022]
Abstract
Kinesins involved in mitotic cell division have gained prominence as promising chemotherapy targets. One such kinesin, EG5, a motor protein responsible for cell division, is a validated chemotherapy target with several compounds at various stages of clinical trials. EG5 has an active site and two different allosteric sites that are known to have ligand specificity. Upon ligand binding, EG5's motor domain will no longer undergo nucleotide-dependent conformational changes required to complete the catalytic cycle. However, there is a lack of in-depth knowledge on the mechanism of inhibitor binding to the two different allosteric sites. To understand the EG5's inhibition mechanism and interactions at allosteric sites and other functionally important regions, we generated two coarse-grained models, Gaussian Network Model (GNM) and Anisotropic Network Model (ANM), to identify the dynamics and its correlation to EG5's function. The first three slowest modes of GNM showed marked differences between the various models of EG5. In the first mode, when the inhibitor is bound at allosteric site 1, there is a presence of a hinge region around residue 166, which is not found when the inhibitor is bound at allosteric site 2 or allosteric sites 1 and 2. The third slowest mode showed a distinctive positively correlated region when the inhibitor is bound at allosteric site 2. These differences indicated that the mechanism of binding at allosteric site 1 and allosteric site 2 are unique. Further, it was observed that the simultaneous ligand binding at allosteric sites 1 and 2 shares structural dynamics and interactions that were found while ligand binds at allosteric sites 1 and 2 independently, leading to a new mechanism. Taken together, our observations suggest that there are different mechanisms at play in each inhibitor bound system considered.
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Affiliation(s)
- Soundarya Priya Alexandar
- Molecular Motors Lab, Department of Biotechnology, School of Chemical & Biotechnology, SASTRA Deemed to be University, Tirumalaisamudram, Thanjavur, Tamil Nadu 613401, India
| | - Ragothaman M Yennamalli
- Department of Bioinformatics, School of Chemical & Biotechnology, SASTRA Deemed to be University, Tirumalaisamudram, Thanjavur, Tamil Nadu 613401, India
| | - Venkatasubramanian Ulaganathan
- Molecular Motors Lab, Department of Biotechnology, School of Chemical & Biotechnology, SASTRA Deemed to be University, Tirumalaisamudram, Thanjavur, Tamil Nadu 613401, India.
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