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Mishra SK, Cooper CJ, Parks JM, Mitchell JC. Hotspot Coevolution Is a Key Identifier of Near-Native Protein Complexes. J Phys Chem B 2021; 125:6058-6067. [PMID: 34077660 DOI: 10.1021/acs.jpcb.0c11525] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
Abstract
Protein-protein interactions play a key role in mediating numerous biological functions, with more than half the proteins in living organisms existing as either homo- or hetero-oligomeric assemblies. Protein subunits that form oligomers minimize the free energy of the complex, but exhaustive computational search-based docking methods have not comprehensively addressed the challenge of distinguishing a natively bound complex from non-native forms. Current protein docking approaches address this problem by sampling multiple binding modes in proteins and scoring each mode, with the lowest-energy (or highest scoring) binding mode being regarded as a near-native complex. However, high-scoring modes often match poorly with the true bound form, suggesting a need for improvement of the scoring function. In this study, we propose a scoring function, KFC-E, that accounts for both conservation and coevolution of putative binding hotspot residues at protein-protein interfaces. We tested KFC-E on four benchmark sets of unbound examples and two benchmark sets of bound examples, with the results demonstrating a clear improvement over scores that examine conservation and coevolution across the entire interface.
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Affiliation(s)
- Sambit K Mishra
- Biosciences Division, Oak Ridge National Laboratory, 1 Bethel Valley Road, Oak Ridge, Tennessee 37831-6038, United States
| | - Connor J Cooper
- Biosciences Division, Oak Ridge National Laboratory, 1 Bethel Valley Road, Oak Ridge, Tennessee 37831-6038, United States
| | - Jerry M Parks
- Biosciences Division, Oak Ridge National Laboratory, 1 Bethel Valley Road, Oak Ridge, Tennessee 37831-6038, United States
| | - Julie C Mitchell
- Biosciences Division, Oak Ridge National Laboratory, 1 Bethel Valley Road, Oak Ridge, Tennessee 37831-6038, United States
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Várnai C, Burkoff NS, Wild DL. Improving protein-protein interaction prediction using evolutionary information from low-quality MSAs. PLoS One 2017; 12:e0169356. [PMID: 28166227 PMCID: PMC5293240 DOI: 10.1371/journal.pone.0169356] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/06/2016] [Accepted: 12/15/2016] [Indexed: 01/05/2023] Open
Abstract
Evolutionary information stored in multiple sequence alignments (MSAs) has been used to identify the interaction interface of protein complexes, by measuring either co-conservation or co-mutation of amino acid residues across the interface. Recently, maximum entropy related correlated mutation measures (CMMs) such as direct information, decoupling direct from indirect interactions, have been developed to identify residue pairs interacting across the protein complex interface. These studies have focussed on carefully selected protein complexes with large, good-quality MSAs. In this work, we study protein complexes with a more typical MSA consisting of fewer than 400 sequences, using a set of 79 intramolecular protein complexes. Using a maximum entropy based CMM at the residue level, we develop an interface level CMM score to be used in re-ranking docking decoys. We demonstrate that our interface level CMM score compares favourably to the complementarity trace score, an evolutionary information-based score measuring co-conservation, when combined with the number of interface residues, a knowledge-based potential and the variability score of individual amino acid sites. We also demonstrate, that, since co-mutation and co-complementarity in the MSA contain orthogonal information, the best prediction performance using evolutionary information can be achieved by combining the co-mutation information of the CMM with co-conservation information of a complementarity trace score, predicting a near-native structure as the top prediction for 41% of the dataset. The method presented is not restricted to small MSAs, and will likely improve interface prediction also for complexes with large and good-quality MSAs.
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Affiliation(s)
- Csilla Várnai
- Systems Biology Centre, University of Warwick, Coventry, CV4 7AL, United Kingdom
| | - Nikolas S. Burkoff
- Systems Biology Centre, University of Warwick, Coventry, CV4 7AL, United Kingdom
| | - David L. Wild
- Systems Biology Centre, University of Warwick, Coventry, CV4 7AL, United Kingdom
- * E-mail:
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Zhu C, Zhang C, Zhang T, Zhang X, Shen Q, Tang B, Liang H, Lai L. Rational design of TNFα binding proteins based on the de novo designed protein DS119. Protein Sci 2016; 25:2066-2075. [PMID: 27571536 DOI: 10.1002/pro.3029] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/27/2016] [Accepted: 08/26/2016] [Indexed: 12/11/2022]
Abstract
De novo protein design offers templates for engineering tailor-made protein functions and orthogonal protein interaction networks for synthetic biology research. Various computational methods have been developed to introduce functional sites in known protein structures. De novo designed protein scaffolds provide further opportunities for functional protein design. Here we demonstrate the rational design of novel tumor necrosis factor alpha (TNFα) binding proteins using a home-made grafting program AutoMatch. We grafted three key residues from a virus 2L protein to a de novo designed small protein, DS119, with consideration of backbone flexibility. The designed proteins bind to TNFα with micromolar affinities. We further optimized the interface residues with RosettaDesign and significantly improved the binding capacity of one protein Tbab1-4. These designed proteins inhibit the activity of TNFα in cellular luciferase assays. Our work illustrates the potential application of the de novo designed protein DS119 in protein engineering, biomedical research, and protein sequence-structure-function studies.
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Affiliation(s)
- Cheng Zhu
- BNLMS, State Key Laboratory for Structural Chemistry of Unstable and Stable Species, College of Chemistry and Molecular Engineering, Peking University, Beijing, 100871, China
| | - Changsheng Zhang
- BNLMS, State Key Laboratory for Structural Chemistry of Unstable and Stable Species, College of Chemistry and Molecular Engineering, Peking University, Beijing, 100871, China
| | - Tao Zhang
- BNLMS, State Key Laboratory for Structural Chemistry of Unstable and Stable Species, College of Chemistry and Molecular Engineering, Peking University, Beijing, 100871, China
| | - Xiaoling Zhang
- Center for Quantitative Biology, Peking University, Beijing, 100871, China
| | - Qi Shen
- Center for Quantitative Biology, Peking University, Beijing, 100871, China
| | - Bo Tang
- Center for Quantitative Biology, Peking University, Beijing, 100871, China
| | - Huanhuan Liang
- National Laboratory of Biomacromolecules, Institute of Biophysics, Chinese Academy of Sciences, Beijing, 100101, China
| | - Luhua Lai
- BNLMS, State Key Laboratory for Structural Chemistry of Unstable and Stable Species, College of Chemistry and Molecular Engineering, Peking University, Beijing, 100871, China. .,Center for Quantitative Biology, Peking University, Beijing, 100871, China. .,Peking-Tsinghua Center for Life Sciences, Peking University, Beijing, 100871, China.
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Muratcioglu S, Guven-Maiorov E, Keskin Ö, Gursoy A. Advances in template-based protein docking by utilizing interfaces towards completing structural interactome. Curr Opin Struct Biol 2015; 35:87-92. [PMID: 26539658 DOI: 10.1016/j.sbi.2015.10.001] [Citation(s) in RCA: 21] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/30/2015] [Revised: 10/09/2015] [Accepted: 10/13/2015] [Indexed: 11/27/2022]
Abstract
The increase in the number of structurally determined protein complexes strengthens template-based docking (TBD) methods for modelling protein-protein interactions (PPIs). These methods utilize the known structures of protein complexes as templates to predict the quaternary structure of the target proteins. The templates may be partial or complete structures. Interface based (partial) methods have recently gained interest due in part to the observation that the interface regions are reusable. We describe how available template interfaces can be used to obtain the structural models of protein interactions. Despite the agreement that a majority of the protein complexes can be modelled using the available Protein Data Bank (PDB) structures, a handful of studies argue that we need more template proteins to increase the structural coverage of PPIs. We also discuss the performance of the interface TBD methods at large scale, and the significance of capturing multiple conformations for improving accuracy.
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Affiliation(s)
- Serena Muratcioglu
- Department of Chemical and Biological Engineering, Koc University, 34450 Istanbul, Turkey; Center for Computational Biology and Bioinformatics, Koc University, 34450 Istanbul, Turkey
| | - Emine Guven-Maiorov
- Department of Chemical and Biological Engineering, Koc University, 34450 Istanbul, Turkey; Center for Computational Biology and Bioinformatics, Koc University, 34450 Istanbul, Turkey
| | - Özlem Keskin
- Department of Chemical and Biological Engineering, Koc University, 34450 Istanbul, Turkey; Center for Computational Biology and Bioinformatics, Koc University, 34450 Istanbul, Turkey
| | - Attila Gursoy
- Department of Computer Engineering, Koc University, 34450 Istanbul, Turkey; Center for Computational Biology and Bioinformatics, Koc University, 34450 Istanbul, Turkey.
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Sánchez-Guerrero E, Hernández-Campos ME, Correa-Basurto J, López-Sánchez P, Tolentino-López LE. Three-dimensional structure and molecular dynamics studies of prorrenin/renin receptor: description of the active site. MOLECULAR BIOSYSTEMS 2015; 11:2520-8. [PMID: 26177886 DOI: 10.1039/c5mb00342c] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/21/2022]
Abstract
The recent finding of a specific receptor for prorrenin/renin (PRR) has brought new insights into the physiology of the renin-angiotensin-aldosterone system. No undoubtable role has been described for this receptor so far. Its role seems to be important in chronic illnesses such as hypertension, possibly participating in the cardiovascular remodeling process, and diabetes where participation in inflammation development has been described. It is not possible, however, to explore the PRR function using classical pharmacological approaches due to the lack of specific agonists or antagonists. Two synthetic peptides have been described to accomplish these roles, but no conclusive data have been provided. There are no X-ray crystallography studies available to describe the structure and potential sites for drug development. So, the aim of this work was to model and theoretically describe the PRR. We describe and characterize the whole receptor protein, its spatial conformation and the potential interactions of PRR with the synthetic peptides available, describing the amino acid residues responsible for these interactions. This information provides the basis for directed development of drugs, seeking to agonize or antagonize PRR activity and study its function in health and ill stages.
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Affiliation(s)
- E Sánchez-Guerrero
- Sección de Estudios de Posgrado e Investigación, Escuela Superior de Medicina del IPN, Plan de San Luis y Díaz Mirón, Casco de Santo Tomás, México D.F. 11340, Mexico
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