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    Maintaining and Enhancing Diversity of Sampled Protein Conformations in Robotics-Inspired Methods

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    Author
    Abella, Jayvee R.; Moll, Mark; Kavraki, Lydia E.
    Date
    2018
    Abstract
    The ability to efficiently sample structurally diverse protein conformations allows one to gain a high-level view of a protein's energy landscape. Algorithms from robot motion planning have been used for conformational sampling, and several of these algorithms promote diversity by keeping track of "coverage" in conformational space based on the local sampling density. However, large proteins present special challenges. In particular, larger systems require running many concurrent instances of these algorithms, but these algorithms can quickly become memory intensive because they typically keep previously sampled conformations in memory to maintain coverage estimates. In addition, robotics-inspired algorithms depend on defining useful perturbation strategies for exploring the conformational space, which is a difficult task for large proteins because such systems are typically more constrained and exhibit complex motions. In this article, we introduce two methodologies for maintaining and enhancing diversity in robotics-inspired conformational sampling. The first method addresses algorithms based on coverage estimates and leverages the use of a low-dimensional projection to define a global coverage grid that maintains coverage across concurrent runs of sampling. The second method is an automatic definition of a perturbation strategy through readily available flexibility information derived from B-factors, secondary structure, and rigidity analysis. Our results show a significant increase in the diversity of the conformations sampled for proteins consisting of up to 500 residues when applied to a specific robotics-inspired algorithm for conformational sampling. The methodologies presented in this article may be vital components for the scalability of robotics-inspired approaches.
    Citation
    Abella, Jayvee R., Moll, Mark and Kavraki, Lydia E.. "Maintaining and Enhancing Diversity of Sampled Protein Conformations in Robotics-Inspired Methods." Journal of Computional Biology, 25, no. 1 (2018) Mary Ann Liebert, Inc.: https://doi.org/10.1089/cmb.2017.0164.
    Published Version
    https://doi.org/10.1089/cmb.2017.0164
    Keyword
    concurrent sampling; perturbation strategies; protein conformational sampling; robotics-inspired sampling
    Type
    Journal article
    Publisher
    Mary Ann Liebert, Inc.
    Citable link to this page
    https://hdl.handle.net/1911/102294
    Rights
    This is an author's peer-reviewed final manuscript, as accepted by the publisher. The published article is copyrighted by Mary Ann Liebert, Inc.
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    • Computer Science Publications [142]
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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