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Basu S, Subedi U, Tonelli M, Afshinpour M, Tiwari N, Fuentes EJ, Chakravarty S. Assessing the functional roles of coevolving PHD finger residues. Protein Sci 2024; 33:e5065. [PMID: 38923615 PMCID: PMC11201814 DOI: 10.1002/pro.5065] [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: 10/31/2023] [Revised: 04/21/2024] [Accepted: 05/16/2024] [Indexed: 06/28/2024]
Abstract
Although in silico folding based on coevolving residue constraints in the deep-learning era has transformed protein structure prediction, the contributions of coevolving residues to protein folding, stability, and other functions in physical contexts remain to be clarified and experimentally validated. Herein, the PHD finger module, a well-known histone reader with distinct subtypes containing subtype-specific coevolving residues, was used as a model to experimentally assess the contributions of coevolving residues and to clarify their specific roles. The results of the assessment, including proteolysis and thermal unfolding of wildtype and mutant proteins, suggested that coevolving residues have varying contributions, despite their large in silico constraints. Residue positions with large constraints were found to contribute to stability in one subtype but not others. Computational sequence design and generative model-based energy estimates of individual structures were also implemented to complement the experimental assessment. Sequence design and energy estimates distinguish coevolving residues that contribute to folding from those that do not. The results of proteolytic analysis of mutations at positions contributing to folding were consistent with those suggested by sequence design and energy estimation. Thus, we report a comprehensive assessment of the contributions of coevolving residues, as well as a strategy based on a combination of approaches that should enable detailed understanding of the residue contributions in other large protein families.
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Affiliation(s)
- Shraddha Basu
- Department of Chemistry & BiochemistrySouth Dakota State UniversityBrookingsSouth DakotaUSA
| | - Ujwal Subedi
- Department of Chemistry & BiochemistrySouth Dakota State UniversityBrookingsSouth DakotaUSA
| | - Marco Tonelli
- National Magnetic Resonance Facility at Madison (NMRFAM), University of Wisconsin‐MadisonMadisonWisconsinUSA
| | - Maral Afshinpour
- Department of Chemistry & BiochemistrySouth Dakota State UniversityBrookingsSouth DakotaUSA
| | - Nitija Tiwari
- Department of Biochemistry & Molecular BiologyUniversity of IowaIowa CityIowaUSA
| | - Ernesto J. Fuentes
- Department of Biochemistry & Molecular BiologyUniversity of IowaIowa CityIowaUSA
| | - Suvobrata Chakravarty
- Department of Chemistry & BiochemistrySouth Dakota State UniversityBrookingsSouth DakotaUSA
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Gupta MN, Uversky VN. Protein structure-function continuum model: Emerging nexuses between specificity, evolution, and structure. Protein Sci 2024; 33:e4968. [PMID: 38532700 DOI: 10.1002/pro.4968] [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: 12/02/2023] [Revised: 02/18/2024] [Accepted: 03/05/2024] [Indexed: 03/28/2024]
Abstract
The rationale for replacing the old binary of structure-function with the trinity of structure, disorder, and function has gained considerable ground in recent years. A continuum model based on the expanded form of the existing paradigm can now subsume importance of both conformational flexibility and intrinsic disorder in protein function. The disorder is actually critical for understanding the protein-protein interactions in many regulatory processes, formation of membrane-less organelles, and our revised notions of specificity as amply illustrated by moonlighting proteins. While its importance in formation of amyloids and function of prions is often discussed, the roles of intrinsic disorder in infectious diseases and protein function under extreme conditions are also becoming clear. This review is an attempt to discuss how our current understanding of protein function, specificity, and evolution fit better with the continuum model. This integration of structure and disorder under a single model may bring greater clarity in our continuing quest for understanding proteins and molecular mechanisms of their functionality.
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Affiliation(s)
- Munishwar Nath Gupta
- Department of Biochemical Engineering and Biotechnology, Indian Institute of Technology, New Delhi, India
| | - Vladimir N Uversky
- Department of Molecular Medicine and USF Health Byrd Alzheimer's Research Institute, Morsani College of Medicine, University of South Florida, Tampa, Florida, USA
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Nussinov R, Zhang M, Maloney R, Tsai CJ, Yavuz BR, Tuncbag N, Jang H. Mechanism of activation and the rewired network: New drug design concepts. Med Res Rev 2021; 42:770-799. [PMID: 34693559 PMCID: PMC8837674 DOI: 10.1002/med.21863] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/29/2021] [Revised: 07/06/2021] [Accepted: 10/07/2021] [Indexed: 12/13/2022]
Abstract
Precision oncology benefits from effective early phase drug discovery decisions. Recently, drugging inactive protein conformations has shown impressive successes, raising the cardinal questions of which targets can profit and what are the principles of the active/inactive protein pharmacology. Cancer driver mutations have been established to mimic the protein activation mechanism. We suggest that the decision whether to target an inactive (or active) conformation should largely rest on the protein mechanism of activation. We next discuss the recent identification of double (multiple) same-allele driver mutations and their impact on cell proliferation and suggest that like single driver mutations, double drivers also mimic the mechanism of activation. We further suggest that the structural perturbations of double (multiple) in cis mutations may reveal new surfaces/pockets for drug design. Finally, we underscore the preeminent role of the cellular network which is deregulated in cancer. Our structure-based review and outlook updates the traditional Mechanism of Action, informs decisions, and calls attention to the intrinsic activation mechanism of the target protein and the rewired tumor-specific network, ushering innovative considerations in precision medicine.
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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, Maryland, USA.,Department of Human Molecular Genetics and Biochemistry, Sackler School of Medicine, Tel Aviv University, Tel Aviv, Israel
| | - Mingzhen Zhang
- Computational Structural Biology Section, Frederick National Laboratory for Cancer Research in the Laboratory of Cancer Immunometabolism, National Cancer Institute, Frederick, Maryland, USA
| | - Ryan Maloney
- Computational Structural Biology Section, Frederick National Laboratory for Cancer Research in the Laboratory of Cancer Immunometabolism, National Cancer Institute, Frederick, Maryland, USA
| | - Chung-Jung Tsai
- Computational Structural Biology Section, Frederick National Laboratory for Cancer Research in the Laboratory of Cancer Immunometabolism, National Cancer Institute, Frederick, Maryland, USA
| | - Bengi Ruken Yavuz
- Department of Health Informatics, Graduate School of Informatics, Middle East Technical University, Ankara, Turkey
| | - Nurcan Tuncbag
- Department of Health Informatics, Graduate School of Informatics, Middle East Technical University, Ankara, Turkey.,Department of Chemical and Biological Engineering, College of Engineering, Koc University, Istanbul, Turkey.,Koc University Research Center for Translational Medicine, School of Medicine, Koc University, Istanbul, Turkey
| | - Hyunbum Jang
- Computational Structural Biology Section, Frederick National Laboratory for Cancer Research in the Laboratory of Cancer Immunometabolism, National Cancer Institute, Frederick, Maryland, USA
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