Sequence Co-Evolutionary Information is a Natural Partner to Minimally-Frustrated Models of Biomolecular Dynamics

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Sequence Co-Evolutionary Information is a Natural Partner to Minimally-Frustrated Models of Biomolecular Dynamics

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Title: Sequence Co-Evolutionary Information is a Natural Partner to Minimally-Frustrated Models of Biomolecular Dynamics
Author(s):
Noel, Jeffrey K.;
Morcos, Faruck;
Onuchic, Jose N.
Date Created: 2016-01-26
Item Type: article
Keywords: Show Keywords
Abstract: Experimentally derived structural constraints have been crucial to the implementation of computational models of biomolecular dynamics. For example, not only does crystallography provide essential starting points for molecular simulations but also high-resolution structures permit for parameterization of simplified models. Since the energy landscapes for proteins and other biomolecules have been shown to be minimally frustrated and therefore funneled, these structure-based models have played a major role in understanding the mechanisms governing folding and many functions of these systems. Structural information, however, may be limited in many interesting cases. Recently, the statistical analysis of residue co-evolution in families of protein sequences has provided a complementary method of discovering residue-residue contact interactions involved in functional configurations. These functional configurations are often transient and difficult to capture experimentally. Thus, co-evolutionary information can be merged with that available for experimentally characterized low free-energy structures, in order to more fully capture the true underlying biomolecular energy landscape.;
Publisher: F1000 Research Ltd
ISSN: 2046-1402
Source: F1000research
Link to Related Resource: http://dx.doi.org/10.12688/f1000research.7186.1
Persistent Link: http://hdl.handle.net/10735.1/5822
Bibliographic Citation: Noel, Jeffrey K., Faruck Morcos, and Jose N. Onuchic. 2016. "Sequence co-evolutionary information is a natural partner to minimally-frustrated models of biomolecular dynamics." F1000research 5(106), doi:10.12688/f1000research.7186.1
Terms of Use: CC BY 4.0 (Attribution)
©2016 The Authors. All Rights Reserved.
Sponsors: Center for Theoretical Biological Physics sponsored by the National Science Foundation (grants PHY-1427654 and NSF-MCB-1214457); Welch Foundation (grant C-1792).

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CC BY 4.0 (Attribution) Except where otherwise noted, this item's license is described as CC BY 4.0 (Attribution)