Evidence map›Paper›PMID 37745560›Full record

ArticlebioRxiv : the preprint server for biology2024

Some mechanistic underpinnings of molecular adaptations of SARS-COV-2 spike protein by integrating candidate adaptive polymorphisms with protein dynamics.

Nicholas J Ose, Paul Campitelli, Tushar Modi, I Can Kazan, Sudhir Kumar, S Banu Ozkan

Abstract readPreprint
In one paragraph

Article in bioRxiv : the preprint server for biology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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1 · What the graph read from it

What it found

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

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3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

6 authors.

Nicholas J OseDepartment of Physics and Center for Biological Physics, Arizona State University, Tempe, Arizona, United States of America.ORCID 0000-0002-2194-5199
Paul CampitelliDepartment of Physics and Center for Biological Physics, Arizona State University, Tempe, Arizona, United States of America.
Tushar ModiDepartment of Physics and Center for Biological Physics, Arizona State University, Tempe, Arizona, United States of America.
I Can KazanDepartment of Physics and Center for Biological Physics, Arizona State University, Tempe, Arizona, United States of America.ORCID 0000-0003-2593-4179
Sudhir KumarInstitute for Genomics and Evolutionary Medicine, Temple University, Philadelphia, Pennsylvania, United States of America.ORCID 0000-0002-9918-8212
S Banu OzkanDepartment of Physics and Center for Biological Physics, Arizona State University, Tempe, Arizona, United States of America.

Funding

Methods For Evolutionary Genomics AnalysisR35GM139540 · NIGMS · TEMPLE UNIV OF THE COMMONWEALTH · PI Sudhir Kumar · 2021 to 2026
$2.9M
Using dynamic network models to quantitatively predict changes in binding affinity/specificity that arise from long-range amino acid substitutionsR01GM147635 · NIGMS · ARIZONA STATE UNIVERSITY-TEMPE CAMPUS · PI OZKAN, SEFIKA BANU, SWINT-KRUSE, LISKIN · 2022 to 2025
$1.8M
NIGMS NIH HHS R01 GM147635NIGMS NIH HHS R35 GM139540
6 · The paper itself

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.

Identifiers

PMID37745560
PMCPMC10515954

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