<HashMap><database>biostudies-literature</database><scores><citationCount>0</citationCount><reanalysisCount>0</reanalysisCount><viewCount>44</viewCount><searchCount>0</searchCount></scores><additional><submitter>Groban ES</submitter><funding>NIGMS NIH HHS</funding><pagination>e32</pagination><full_dataset_link>https://www.ebi.ac.uk/biostudies/studies/S-EPMC1440919</full_dataset_link><repository>biostudies-literature</repository><omics_type>Unknown</omics_type><volume>2(4)</volume><pubmed_abstract>Post-translational phosphorylation is a ubiquitous mechanism for modulating protein activity and protein-protein interactions. In this work, we examine how phosphorylation can modulate the conformation of a protein by changing the energy landscape. We present a molecular mechanics method in which we phosphorylate proteins in silico and then predict how the conformation of the protein will change in response to phosphorylation. We apply this method to a test set comprised of proteins with both phosphorylated and non-phosphorylated crystal structures, and demonstrate that it is possible to predict localized phosphorylation-induced conformational changes, or the absence of conformational changes, with near-atomic accuracy in most cases. Examples of proteins used for testing our methods include kinases and prokaryotic response regulators. Through a detailed case study of cyclin-dependent kinase 2, we also illustrate how the computational methods can be used to provide new understanding of how phosphorylation drives conformational change, why substituting Glu or Asp for a phosphorylated amino acid does not always mimic the effects of phosphorylation, and how a phosphatase can "capture" a phosphorylated amino acid. This work illustrates how computational methods can be used to elucidate principles and mechanisms of post-translational phosphorylation, which can ultimately help to bridge the gap between the number of known sites of phosphorylation and the number of structures of phosphorylated proteins.</pubmed_abstract><journal>PLoS computational biology</journal><pubmed_title>Conformational changes in protein loops and helices induced by post-translational phosphorylation.</pubmed_title><pmcid>PMC1440919</pmcid><funding_grant_id>T32 GM008284</funding_grant_id><funding_grant_id>GM08284</funding_grant_id><pubmed_authors>Narayanan A</pubmed_authors><pubmed_authors>Jacobson MP</pubmed_authors><pubmed_authors>Groban ES</pubmed_authors><view_count>44</view_count></additional><is_claimable>false</is_claimable><name>Conformational changes in protein loops and helices induced by post-translational phosphorylation.</name><description>Post-translational phosphorylation is a ubiquitous mechanism for modulating protein activity and protein-protein interactions. In this work, we examine how phosphorylation can modulate the conformation of a protein by changing the energy landscape. We present a molecular mechanics method in which we phosphorylate proteins in silico and then predict how the conformation of the protein will change in response to phosphorylation. We apply this method to a test set comprised of proteins with both phosphorylated and non-phosphorylated crystal structures, and demonstrate that it is possible to predict localized phosphorylation-induced conformational changes, or the absence of conformational changes, with near-atomic accuracy in most cases. Examples of proteins used for testing our methods include kinases and prokaryotic response regulators. Through a detailed case study of cyclin-dependent kinase 2, we also illustrate how the computational methods can be used to provide new understanding of how phosphorylation drives conformational change, why substituting Glu or Asp for a phosphorylated amino acid does not always mimic the effects of phosphorylation, and how a phosphatase can "capture" a phosphorylated amino acid. This work illustrates how computational methods can be used to elucidate principles and mechanisms of post-translational phosphorylation, which can ultimately help to bridge the gap between the number of known sites of phosphorylation and the number of structures of phosphorylated proteins.</description><dates><release>2006-01-01T00:00:00Z</release><publication>2006 Apr</publication><modification>2022-02-11T10:19:58.865Z</modification><creation>2019-03-27T01:26:16Z</creation></dates><accession>S-EPMC1440919</accession><cross_references><pubmed>16628247</pubmed><doi>10.1371/journal.pcbi.0020032</doi></cross_references></HashMap>