4.8 Article

Automated identification of functional dynamic contact networks from X-ray crystallography

Journal

NATURE METHODS
Volume 10, Issue 9, Pages 896-U110

Publisher

NATURE PUBLISHING GROUP
DOI: 10.1038/NMETH.2592

Keywords

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Funding

  1. US National Institute of General Medical Sciences Protein Structure Initiative at the Joint Center for Structural Genomics [U54GM094586]
  2. SLAC National Accelerator Laboratory LDRD (Laboratory Directed Research and Development) grant [SLAC-LDRD-0014-13-2]
  3. Damon Runyon Cancer Research Foundation [DRG-2136-12]
  4. General Wang Yaowu Stanford graduate fellowship
  5. US National Institutes of Health [GM75995]
  6. US National Institutes of Health Early Independence Award [DP5OD009180]

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Protein function often depends on the exchange between conformational substates. Allosteric ligand binding or distal mutations can stabilize specific active-site conformations and consequently alter protein function. Observing alternative conformations at low levels of electron density, in addition to comparison of independently determined X-ray crystal structures, can provide mechanistic insights into conformational dynamics. Here we report a new algorithm, CONTACT, that identifies contact networks of conformationally heterogeneous residues directly from high-resolution X-ray crystallography data. Contact networks determined for Escherichia coli dihydrofolate reductase (ecDHFR) predict the observed long-range pattern of NMR chemical shift perturbations of an allosteric mutation. A comparison of contact networks in wild-type and mutant ecDHFR suggests that mutations that alter optimized contact networks of coordinated motions can impair catalytic function. CONTACT-guided mutagenesis can exploit the structure-dynamics-function relationship in protein engineering and design.

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