LEAP: Highly accurate prediction of protein loop conformations by integrating coarse-grained sampling and optimized energy scores with all-atom refinement of backbone and side chains

Journal of Computational Chemistry

Volumn 35, Issue 4, 2014, Pages 335-341

  Liang, Shide ^a   Zhang, Chi ^b   Zhou, Yaoqi ^b,c,d,e  

^a OSAKA UNIVERSITY   (Japan)

^b UNIVERSITY OF NEBRASKA   (United States)

^c INDIANA UNIVERSITY   (United States)

^d INDIANA UNIVERSITY SCHOOL OF MEDICINE   (United States)

^e GRIFFITH UNIVERSITY   (Australia)

Author keywords

loop modeling coarse grained energy function energy minimization Monte Carlo simulation force field development

Indexed keywords

AB INITIO PREDICTION; COARSE-GRAINED; CRITICAL ASSESSMENT; INTEGRATED TECHNIQUES; ROOT MEAN SQUARE DEVIATIONS; SCORING FUNCTIONS; TEMPLATE-BASED MODELING; UNSOLVED PROBLEMS;

CHAINS; COMPUTER OPERATING SYSTEMS; FORECASTING; MONTE CARLO METHODS; OPTIMIZATION;

PROTEINS;

PROTEIN;

ARTICLE; CHEMISTRY; LOOP MODELING • COARSE-GRAINED ENERGY FUNCTION • ENERGY MINIMIZATION • MONTE CARLO SIMULATION • FORCE FIELD DEVELOPMENT; PROTEIN CONFORMATION; QUANTUM THEORY;

LOOP MODELING • COARSE-GRAINED ENERGY FUNCTION • ENERGY MINIMIZATION • MONTE CARLO SIMULATION • FORCE FIELD DEVELOPMENT;

PROTEIN CONFORMATION; PROTEINS; QUANTUM THEORY;

EID: 84891886128     PISSN: 01928651     EISSN: 1096987X     Source Type: Journal    
DOI: 10.1002/jcc.23509     Document Type: Article

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