{"database":"biostudies-literature","file_versions":[],"scores":null,"additional":{"submitter":["Rynkiewicz P"],"funding":["NIGMS NIH HHS"],"pagination":["10978-10996"],"full_dataset_link":["https://www.ebi.ac.uk/biostudies/studies/S-EPMC8776918"],"repository":["biostudies-literature"],"omics_type":["Unknown"],"volume":["40(21)"],"pubmed_abstract":["Comparative functional analysis of the dynamic interactions between various <i>Betacoronavirus</i> mutant strains and broadly utilized target proteins such as ACE2 and CD26, is crucial for a more complete understanding of zoonotic spillovers of viruses that cause diseases such as COVID-19. Here, we employ machine learning to replicated sets of nanosecond scale GPU accelerated molecular dynamics simulations to statistically compare and classify atom motions of these target proteins in both the presence and absence of different endemic and emergent strains of the viral receptor binding domain (RBD) of the S spike glycoprotein. A multi-agent classifier successfully identified functional binding dynamics that are evolutionarily conserved from bat CoV-HKU4 to human endemic/emergent strains. Con"],"journal":["Journal of biomolecular structure & dynamics"],"pubmed_title":["Functional binding dynamics relevant to the evolution of zoonotic spillovers in endemic and emergent <i>Betacoronavirus</i> strains."],"pmcid":["PMC8776918"],"funding_grant_id":["R15 GM116102"],"pubmed_authors":["Hudson AO","Babbitt GA","Rynkiewicz P","Lynch ML","Cui F"],"additional_accession":[]},"is_claimable":false,"name":"Functional binding dynamics relevant to the evolution of zoonotic spillovers in endemic and emergent <i>Betacoronavirus</i> strains.","description":"Comparative functional analysis of the dynamic interactions between various <i>Betacoronavirus</i> mutant strains and broadly utilized target proteins such as ACE2 and CD26, is crucial for a more complete understanding of zoonotic spillovers of viruses that cause diseases such as COVID-19. Here, we employ machine learning to replicated sets of nanosecond scale GPU accelerated molecular dynamics simulations to statistically compare and classify atom motions of these target proteins in both the presence and absence of different endemic and emergent strains of the viral receptor binding domain (RBD) of the S spike glycoprotein. A multi-agent classifier successfully identified functional binding dynamics that are evolutionarily conserved from bat CoV-HKU4 to human endemic/emergent strains. Con","dates":{"release":"2022-01-01T00:00:00Z","publication":"2022","modification":"2026-05-08T02:10:54.765Z","creation":"2024-12-03T22:57:33.399Z"},"accession":"S-EPMC8776918","cross_references":{"pubmed":["34286673"],"doi":["10.1080/07391102.2021.1953604"]}}