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Ose NJ, Campitelli P, Modi T, Kazan IC, Kumar S, Ozkan SB. Some mechanistic underpinnings of molecular adaptations of SARS-COV-2 spike protein by integrating candidate adaptive polymorphisms with protein dynamics. eLife 2024; 12:RP92063. [PMID: 38713502 PMCID: PMC11076047 DOI: 10.7554/elife.92063] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/08/2024] Open
Abstract
We integrate evolutionary predictions based on the neutral theory of molecular evolution with protein dynamics to generate mechanistic insight into the molecular adaptations of the SARS-COV-2 spike (S) protein. With this approach, we first identified candidate adaptive polymorphisms (CAPs) of the SARS-CoV-2 S protein and assessed the impact of these CAPs through dynamics analysis. Not only have we found that CAPs frequently overlap with well-known functional sites, but also, using several different dynamics-based metrics, we reveal the critical allosteric interplay between SARS-CoV-2 CAPs and the S protein binding sites with the human ACE2 (hACE2) protein. CAPs interact far differently with the hACE2 binding site residues in the open conformation of the S protein compared to the closed form. In particular, the CAP sites control the dynamics of binding residues in the open state, suggesting an allosteric control of hACE2 binding. We also explored the characteristic mutations of different SARS-CoV-2 strains to find dynamic hallmarks and potential effects of future mutations. Our analyses reveal that Delta strain-specific variants have non-additive (i.e., epistatic) interactions with CAP sites, whereas the less pathogenic Omicron strains have mostly additive mutations. Finally, our dynamics-based analysis suggests that the novel mutations observed in the Omicron strain epistatically interact with the CAP sites to help escape antibody binding.
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Affiliation(s)
- Nicholas James Ose
- Department of Physics and Center for Biological Physics, Arizona State UniversityTempeUnited States
| | - Paul Campitelli
- Department of Physics and Center for Biological Physics, Arizona State UniversityTempeUnited States
| | - Tushar Modi
- Department of Physics and Center for Biological Physics, Arizona State UniversityTempeUnited States
| | - I Can Kazan
- Department of Physics and Center for Biological Physics, Arizona State UniversityTempeUnited States
| | - Sudhir Kumar
- Institute for Genomics and Evolutionary Medicine, Temple UniversityPhiladelphiaUnited States
- Department of Biology, Temple UniversityPhiladelphiaUnited States
- Center for Genomic Medicine Research, King Abdulaziz UniversityJeddahSaudi Arabia
| | - Sefika Banu Ozkan
- Department of Physics and Center for Biological Physics, Arizona State UniversityTempeUnited States
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Bastidas OH, Sevarac Z. Time dependent dihedral angle oscillations of the spike protein of SARS-CoV-2 reveal favored frequencies of dihedral angle rotations. Sci Rep 2024; 14:3323. [PMID: 38336854 PMCID: PMC10858279 DOI: 10.1038/s41598-024-53954-9] [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: 04/06/2023] [Accepted: 02/07/2024] [Indexed: 02/12/2024] Open
Abstract
The spike protein of SARS-CoV-2 is critical to viral infection of human host cells which ultimately results in COVID-19. In this study we analyzed the behavior of dihedral angles (phi and psi) of the wild-type spike protein over time from molecular dynamics and identified that their oscillations are dominated by a few discrete, relatively low frequencies in the 23-63 MHz range with 42.969 MHz being the most prevalent frequency sampled by the oscillations. We thus observed the spike protein to favor certain frequencies more than others. Gaps in the tally of all observed frequencies for low-abundance amino acids also suggests that the frequency components of dihedral angle oscillations may be a function of position in the primary structure since relatively more abundant amino acids lacked gaps. Lastly, certain residues identified in the literature as constituting the inside of a druggable pocket, as well as others identified as allosteric sites, are observed in our data to have distinctive time domain profiles. This motivated us to propose additional residues with similar time domain profiles, which may be of potential interest to the vaccine and drug design communities for further investigation. Thus these findings indicate that there is a particular frequency domain profile for the spike protein hidden within the time domain data and this information, perhaps with the suggested residues, might provide additional insight into therapeutic development strategies for COVID-19 and beyond.
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Ose NJ, Campitelli P, Modi T, Can Kazan I, Kumar S, Banu Ozkan S. Some mechanistic underpinnings of molecular adaptations of SARS-COV-2 spike protein by integrating candidate adaptive polymorphisms with protein dynamics. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2023.09.14.557827. [PMID: 37745560 PMCID: PMC10515954 DOI: 10.1101/2023.09.14.557827] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 09/26/2023]
Abstract
We integrate evolutionary predictions based on the neutral theory of molecular evolution with protein dynamics to generate mechanistic insight into the molecular adaptations of the SARS-COV-2 Spike (S) protein. With this approach, we first identified Candidate Adaptive Polymorphisms (CAPs) of the SARS-CoV-2 Spike protein and assessed the impact of these CAPs through dynamics analysis. Not only have we found that CAPs frequently overlap with well-known functional sites, but also, using several different dynamics-based metrics, we reveal the critical allosteric interplay between SARS-CoV-2 CAPs and the S protein binding sites with the human ACE2 (hACE2) protein. CAPs interact far differently with the hACE2 binding site residues in the open conformation of the S protein compared to the closed form. In particular, the CAP sites control the dynamics of binding residues in the open state, suggesting an allosteric control of hACE2 binding. We also explored the characteristic mutations of different SARS-CoV-2 strains to find dynamic hallmarks and potential effects of future mutations. Our analyses reveal that Delta strain-specific variants have non-additive (i.e., epistatic) interactions with CAP sites, whereas the less pathogenic Omicron strains have mostly additive mutations. Finally, our dynamics-based analysis suggests that the novel mutations observed in the Omicron strain epistatically interact with the CAP sites to help escape antibody binding.
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Affiliation(s)
- Nicholas J. Ose
- Department of Physics and Center for Biological Physics, Arizona State University, Tempe, Arizona, United States of America
| | - Paul Campitelli
- Department of Physics and Center for Biological Physics, Arizona State University, Tempe, Arizona, United States of America
| | - Tushar Modi
- Department of Physics and Center for Biological Physics, Arizona State University, Tempe, Arizona, United States of America
| | - I. Can Kazan
- Department of Physics and Center for Biological Physics, Arizona State University, Tempe, Arizona, United States of America
| | - Sudhir Kumar
- Institute for Genomics and Evolutionary Medicine, Temple University, Philadelphia, Pennsylvania, United States of America
- Department of Biology, Temple University, Philadelphia, Pennsylvania, United States of America
- Center for Genomic Medicine Research, King Abdulaziz University, Jeddah, Saudi Arabia
| | - S. Banu Ozkan
- Department of Physics and Center for Biological Physics, Arizona State University, Tempe, Arizona, United States of America
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Barozi V, Edkins AL, Tastan Bishop Ö. Evolutionary progression of collective mutations in Omicron sub-lineages towards efficient RBD-hACE2: Allosteric communications between and within viral and human proteins. Comput Struct Biotechnol J 2022; 20:4562-4578. [PMID: 35989699 PMCID: PMC9384468 DOI: 10.1016/j.csbj.2022.08.015] [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: 07/05/2022] [Revised: 08/06/2022] [Accepted: 08/07/2022] [Indexed: 11/23/2022] Open
Abstract
The interaction between the Spike (S) protein of SARS-CoV-2 and the human angiotensin converting enzyme 2 (hACE2) is essential for infection, and is a target for neutralizing antibodies. Consequently, selection of mutations in the S protein is expected to be driven by the impact on the interaction with hACE2 and antibody escape. Here, for the first time, we systematically characterized the collective effects of mutations in each of the Omicron sub-lineages (BA.1, BA.2, BA.3 and BA.4) on both the viral S protein receptor binding domain (RBD) and the hACE2 protein using post molecular dynamics studies and dynamic residue network (DRN) analysis. Our analysis suggested that Omicron sub-lineage mutations result in altered physicochemical properties that change conformational flexibility compared to the reference structure, and may contribute to antibody escape. We also observed changes in the hACE2 substrate binding groove in some sub-lineages. Notably, we identified unique allosteric communication paths in the reference protein complex formed by the DRN metrics betweenness centrality and eigencentrality hubs, originating from the RBD core traversing the receptor binding motif of the S protein and the N-terminal domain of the hACE2 to the active site. We showed allosteric changes in residue network paths in both the RBD and hACE2 proteins due to Omicron sub-lineage mutations. Taken together, these data suggest progressive evolution of the Omicron S protein RBD in sub-lineages towards a more efficient interaction with the hACE2 receptor which may account for the increased transmissibility of Omicron variants.
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Affiliation(s)
- Victor Barozi
- Research Unit in Bioinformatics (RUBi), Department of Biochemistry and Microbiology, Rhodes University, Makhanda/Grahamstown 6139, South Africa
| | - Adrienne L. Edkins
- The Biomedical Biotechnology Research Unit (BioBRU), Department of Biochemistry and Microbiology, Rhodes University, Makhanda/Grahamstown 6139, South Africa
| | - Özlem Tastan Bishop
- Research Unit in Bioinformatics (RUBi), Department of Biochemistry and Microbiology, Rhodes University, Makhanda/Grahamstown 6139, South Africa
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Gao K, Wang R, Chen J, Cheng L, Frishcosy J, Huzumi Y, Qiu Y, Schluckbier T, Wei X, Wei GW. Methodology-Centered Review of Molecular Modeling, Simulation, and Prediction of SARS-CoV-2. Chem Rev 2022; 122:11287-11368. [PMID: 35594413 PMCID: PMC9159519 DOI: 10.1021/acs.chemrev.1c00965] [Citation(s) in RCA: 33] [Impact Index Per Article: 16.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/06/2023]
Abstract
Despite tremendous efforts in the past two years, our understanding of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), virus-host interactions, immune response, virulence, transmission, and evolution is still very limited. This limitation calls for further in-depth investigation. Computational studies have become an indispensable component in combating coronavirus disease 2019 (COVID-19) due to their low cost, their efficiency, and the fact that they are free from safety and ethical constraints. Additionally, the mechanism that governs the global evolution and transmission of SARS-CoV-2 cannot be revealed from individual experiments and was discovered by integrating genotyping of massive viral sequences, biophysical modeling of protein-protein interactions, deep mutational data, deep learning, and advanced mathematics. There exists a tsunami of literature on the molecular modeling, simulations, and predictions of SARS-CoV-2 and related developments of drugs, vaccines, antibodies, and diagnostics. To provide readers with a quick update about this literature, we present a comprehensive and systematic methodology-centered review. Aspects such as molecular biophysics, bioinformatics, cheminformatics, machine learning, and mathematics are discussed. This review will be beneficial to researchers who are looking for ways to contribute to SARS-CoV-2 studies and those who are interested in the status of the field.
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Affiliation(s)
- Kaifu Gao
- Department
of Mathematics, Michigan State University, East Lansing, Michigan 48824, United States
| | - Rui Wang
- Department
of Mathematics, Michigan State University, East Lansing, Michigan 48824, United States
| | - Jiahui Chen
- Department
of Mathematics, Michigan State University, East Lansing, Michigan 48824, United States
| | - Limei Cheng
- Clinical
Pharmacology and Pharmacometrics, Bristol
Myers Squibb, Princeton, New Jersey 08536, United States
| | - Jaclyn Frishcosy
- Department
of Mathematics, Michigan State University, East Lansing, Michigan 48824, United States
| | - Yuta Huzumi
- Department
of Mathematics, Michigan State University, East Lansing, Michigan 48824, United States
| | - Yuchi Qiu
- Department
of Mathematics, Michigan State University, East Lansing, Michigan 48824, United States
| | - Tom Schluckbier
- Department
of Mathematics, Michigan State University, East Lansing, Michigan 48824, United States
| | - Xiaoqi Wei
- Department
of Mathematics, Michigan State University, East Lansing, Michigan 48824, United States
| | - Guo-Wei Wei
- Department
of Mathematics, Michigan State University, East Lansing, Michigan 48824, United States
- Department
of Electrical and Computer Engineering, Michigan State University, East Lansing, Michigan 48824, United States
- Department
of Biochemistry and Molecular Biology, Michigan
State University, East Lansing, Michigan 48824, United States
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