{"database":"biostudies-literature","file_versions":[],"scores":null,"additional":{"submitter":["Clausen R"],"funding":["CCR NIH HHS","Intramural NIH HHS","NCI NIH HHS"],"pagination":["e1004470"],"full_dataset_link":["https://www.ebi.ac.uk/biostudies/studies/S-EPMC4556523"],"repository":["biostudies-literature"],"omics_type":["Unknown"],"volume":["11(9)"],"pubmed_abstract":["An important goal in molecular biology is to understand functional changes upon single-point mutations in proteins. Doing so through a detailed characterization of structure spaces and underlying energy landscapes is desirable but continues to challenge methods based on Molecular Dynamics. In this paper we propose a novel algorithm, SIfTER, which is based instead on stochastic optimization to circumvent the computational challenge of exploring the breadth of a protein's structure space. SIfTER is a data-driven evolutionary algorithm, leveraging experimentally-available structures of wildtype and variant sequences of a protein to define a reduced search space from where to efficiently draw samples corresponding to novel structures not directly observed in the wet laboratory. The main advant"],"journal":["PLoS computational biology"],"pubmed_title":["Mapping the Conformation Space of Wildtype and Mutant H-Ras with a Memetic, Cellular, and Multiscale Evolutionary Algorithm."],"pmcid":["PMC4556523"],"funding_grant_id":["HHSN261200800001E","HHSN261200800001C"],"pubmed_authors":["Ma B","Shehu A","Clausen R","Nussinov R"],"additional_accession":[]},"is_claimable":false,"name":"Mapping the Conformation Space of Wildtype and Mutant H-Ras with a Memetic, Cellular, and Multiscale Evolutionary Algorithm.","description":"An important goal in molecular biology is to understand functional changes upon single-point mutations in proteins. Doing so through a detailed characterization of structure spaces and underlying energy landscapes is desirable but continues to challenge methods based on Molecular Dynamics. In this paper we propose a novel algorithm, SIfTER, which is based instead on stochastic optimization to circumvent the computational challenge of exploring the breadth of a protein's structure space. SIfTER is a data-driven evolutionary algorithm, leveraging experimentally-available structures of wildtype and variant sequences of a protein to define a reduced search space from where to efficiently draw samples corresponding to novel structures not directly observed in the wet laboratory. The main advant","dates":{"release":"2015-01-01T00:00:00Z","publication":"2015 Sep","modification":"2026-05-30T04:19:24.612Z","creation":"2019-03-26T22:42:26Z"},"accession":"S-EPMC4556523","cross_references":{"pubmed":["26325505"],"doi":["10.1371/journal.pcbi.1004470"]}}