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    Protein Folding and Structure Prediction from the Ground Up II: AWSEM for a/ß Proteins

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    Author
    Chen, M.; Lin, X.; Lu, W.; Onuchic, J.; Wolynes, P.G.
    Date
    2016
    Abstract
    The atomistic associative memory, water mediated, structure and energy model (AAWSEM) is an efficient coarse-grained force field with transferable tertiary interactions that incorporates local in sequence energetic biases using structural information derived from all-atom simulations of long segments of the protein. For α helical proteins, the accuracy of structure prediction using AAWSEM has been established previously. In this article, we examine the capability of AAWSEM to predict the structure of α/β proteins. We also elaborate on an iterative approach that uses the structures from a first round of AAWSEM simulation as fragment memories. This iterative scheme improves the quality of the structure prediction and makes the free energy profile more funneled toward native configurations. We explore the use of clustering analyses as a way of evaluating the confidence in various structure prediction models. Clustering using a local relative order parameter (mutual Q) of the predicted structural ensemble turns out to be optimal. The tightest cluster according to mutual Q generally has the most correctly folded structure. Since there is no bioinformatic input, AAWSEM amounts to an ab initio protein structure prediction method that combines the efficiency of coarse-grained simulations with the local structural accuracy that can be achieved from all-atom simulations.
    Citation
    Chen, M., Lin, X., Lu, W., et al.. "Protein Folding and Structure Prediction from the Ground Up II: AWSEM for a/ß Proteins." Journal of Physical Chemistry B, (2016) American Chemical Society: http://dx.doi.org/10.1021/acs.jpcb.6b09347.
    Published Version
    http://dx.doi.org/10.1021/acs.jpcb.6b09347
    Type
    Journal article
    Publisher
    American Chemical Society
    Citable link to this page
    https://hdl.handle.net/1911/93962
    Rights
    Article is made available in accordance with the publisher's policy and may be subject to US copyright law. Please refer to the publisher's site for terms of use.
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    Home | FAQ | Contact Us | Privacy Notice | Accessibility Statement
    Managed by the Digital Scholarship Services at Fondren Library, Rice University
    Physical Address: 6100 Main Street, Houston, Texas 77005
    Mailing Address: MS-44, P.O.BOX 1892, Houston, Texas 77251-1892
    Site Map