2014
DOI: 10.1073/pnas.1322352111
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Control of catalytic efficiency by a coevolving network of catalytic and noncatalytic residues

Abstract: The active sites of enzymes consist of residues necessary for catalysis and structurally important noncatalytic residues that together maintain the architecture and function of the active site. Examples of evolutionary interactions between catalytic and noncatalytic residues have been difficult to define and experimentally validate due to a general intolerance of these residues to substitution. Here, using computational methods to predict coevolving residues, we identify a network of positions consisting of tw… Show more

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Cited by 33 publications
(50 citation statements)
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“…This loop includes the critical 361-HRD-363 motif that is involved in kinase activity and regulation. The catalytic loop sequence 363-DLAARN-368 is also highly conserved throughout the majority of protein tyrosine kinases and includes a critically important for kinase activity R367 [131,132]. A strong correspondence between coevolving residue positions and conserved residues in the catalytic and substrate binding sites is consistent with the previous studies [112123].…”
Section: Resultssupporting
confidence: 82%
“…This loop includes the critical 361-HRD-363 motif that is involved in kinase activity and regulation. The catalytic loop sequence 363-DLAARN-368 is also highly conserved throughout the majority of protein tyrosine kinases and includes a critically important for kinase activity R367 [131,132]. A strong correspondence between coevolving residue positions and conserved residues in the catalytic and substrate binding sites is consistent with the previous studies [112123].…”
Section: Resultssupporting
confidence: 82%
“…In contrast the clr transformation in combination with Dirichlet sampling indicated that only a minority of the variant combinations were under strong positive selection, a result that was in agreement with the biochemical characterization of the variants [35]. …”
Section: Resultsmentioning
confidence: 69%
“…Compositional datasets from HTS can be analyzed in a rigorous manner by adapting tools from other fields (Van den Boogaart and Tolosana-Delgado, 2013 ; Pawlowsky-Glahn et al, 2015 ) and using new tools based on the same underlying foundations (Fernandes et al, 2013 ; Erb and Notredame, 2016 ; Silverman et al, 2017 ; Quinn et al, 2017 ). There are now examples in the literature that provide guidance on how to do some or all of these analyses on HTS datasets, including meta-transcriptomics (Macklaim et al, 2013 ) and tag-sequencing (McMurrough et al, 2014 ; Bian et al, 2017 ). We briefly review the approaches below.…”
Section: Analysis Of Hts Using Coda Methodsmentioning
confidence: 99%