Use of restrained molecular dynamics to predict the conformations of phosphorylated receiver domains in two-component signaling systems.
Two-component signaling (TCS) is the primary means by which bacteria, as well as certain plants and fungi, respond to external stimuli. Signal transduction involves stimulus-dependent autophosphorylation of a sensor histidine kinase and phosphoryl transfer to the receiver domain of a downstream response regulator. Phosphorylation acts as an allosteric switch, inducing structural and functional changes in the pathway's components. Due to their transient nature, phosphorylated receiver domains are challenging to characterize structurally. In this work, we provide a methodology for simulating receiver domain phosphorylation to predict conformations that are nearly identical to experimental structures. Using restrained molecular dynamics, phosphorylated conformations of receiver domains can be reliably sampled on nanosecond timescales. These simulations also provide data on conformational dynamics that can be used to identify regions of functional significance related to phosphorylation. We first validated this approach on several well-characterized receiver domains and then used it to compare the upstream and downstream components of the fungal Sln1 phosphorelay. Our results demonstrate that this technique provides structural insight, obtained in the absence of crystallographic or NMR information, regarding phosphorylation-induced conformational changes in receiver domains that regulate the output of their associated signaling pathway. To our knowledge, this is the first time such a protocol has been described that can be broadly applied to TCS proteins for predictive purposes. Proteins 2016; 85:155-176. © 2016 Wiley Periodicals, Inc.
Department of Chemistry and Biochemistry, University of Oklahoma, Norman, Oklahoma.
Clay A
CA
Foster
Department of Chemistry and Biochemistry, University of Oklahoma, Norman, Oklahoma.
Ann H
AH
West
D001412:Bacillus subtilis / Q000235:genetics / Q000378:metabolism; D001426:Bacterial Proteins / Q000737:chemistry* / Q000378:metabolism; D001665:Binding Sites; D004926:Escherichia coli / Q000235:genetics / Q000378:metabolism; D029968:Escherichia coli Proteins / Q000737:chemistry* / Q000378:metabolism; D015870:Gene Expression; D047908:Intracellular Signaling Peptides and Proteins / Q000737:chemistry* / Q000378:metabolism; D000072236:Methyl-Accepting Chemotaxis Proteins / Q000737:chemistry* / Q000378:metabolism; D015233:Models, Statistical; D056004:Molecular Dynamics Simulation; D010766:Phosphorylation; D011485:Protein Binding; D054730:Protein Interaction Domains and Motifs; D011494:Protein Kinases / Q000737:chemistry* / Q000378:metabolism; D017433:Protein Structure, Secondary; D012441:Saccharomyces cerevisiae / Q000235:genetics / Q000378:metabolism; D029701:Saccharomyces cerevisiae Proteins / Q000737:chemistry* / Q000378:metabolism; D015398:Signal Transduction; D016962:Sinorhizobium meliloti / Q000235:genetics / Q000378:metabolism; D013816:Thermodynamics
D001426:Bacterial Proteins; D029968:Escherichia coli Proteins; D047908:Intracellular Signaling Peptides and Proteins; D000072236:Methyl-Accepting Chemotaxis Proteins; C465562:PhoP protein, E coli; D029701:Saccharomyces cerevisiae Proteins; C080951:Spo0F protein, Bacillus subtilis; C000607606:cheY protein, E coli; C069289:FixJ protein, Bacteria; D011494:Protein Kinases; C083749:SLN1 protein, S cerevisiae
molecular dynamics; phosphorelay; phosphotransfer; post-translational modifications; response regulator; two-component signaling systems