title: Fast de novo discovery of low-energy protein loop conformations.
abstract: In the prediction of protein structure from amino acid sequence, loops are challenging regions for computational methods. Since loops are often located on the protein surface, they can have significant roles in determining protein functions and binding properties. Loop prediction without the aid of a structural template requires extensive conformational sampling and energy minimization, which are computationally difficult. In this article we present a new de novo loop sampling method, the Parallely filtered Energy Targeted All-atom Loop Sampler (PETALS) to rapidly locate low energy conformations. PETALS explores both backbone and side-chain positions of the loop region simultaneously according to the energy function selected by the user, and constructs a nonredundant ensemble of low energy loop conformations using filtering criteria. The method is illustrated with the DFIRE potential and DiSGro energy function for loops, and shown to be highly effective at discovering conformations with near-native (or better) energy. Using the same energy function as the DiSGro algorithm, PETALS samples conformations with both lower RMSDs and lower energies. PETALS is also useful for assessing the accuracy of different energy functions. PETALS runs rapidly, requiring an average time cost of 10 minutes for a length 12 loop on a single 3.2 GHz processor core, comparable to the fastest existing de novo methods for generating an ensemble of conformations. Proteins 2017; 85:1402-1412. © 2017 Wiley Periodicals, Inc.
authors.affiliation: Department of Statistics, University of Florida, Gainesville, Florida, 32611.
authors.forename: Samuel W K
authors.initials: SWK
authors.lastname: Wong
authors.affiliation: Department of Statistics, Harvard University, Cambridge, Massachusetts, 02138.
authors.forename: Jun S
authors.initials: JS
authors.lastname: Liu
authors.affiliation: Department of Statistics, Harvard University, Cambridge, Massachusetts, 02138.
authors.forename: S C
authors.identifier: http://orcid.org/0000-0002-1774-3316
authors.initials: SC
authors.lastname: Kou
mesh_terms: D000465:Algorithms; D000595:Amino Acid Sequence; D000596:Amino Acids / Q000737:chemistry*; D019295:Computational Biology / Q000379:methods*; D003198:Computer Simulation; D008958:Models, Molecular; D000072756:Protein Conformation, alpha-Helical; D054730:Protein Interaction Domains and Motifs; D011506:Proteins / Q000737:chemistry*; D013816:Thermodynamics
chemical_list: D000596:Amino Acids; D011506:Proteins
keywords: loop sampling methods; particle filtering; protein structure prediction