title: 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.
abstract: Prediction of protein loop conformations without any prior knowledge (ab initio prediction) is an unsolved problem. Its solution will significantly impact protein homology and template-based modeling as well as ab initio protein-structure prediction. Here, we developed a coarse-grained, optimized scoring function for initial sampling and ranking of loop decoys. The resulting decoys are then further optimized in backbone and side-chain conformations and ranked by all-atom energy scoring functions. The final integrated technique called loop prediction by energy-assisted protocol achieved a median value of 2.1 Å root mean square deviation (RMSD) for 325 12-residue test loops and 2.0 Å RMSD for 45 12-residue loops from critical assessment of structure-prediction techniques (CASP) 10 target proteins with native core structures (backbone and side chains). If all side-chain conformations in protein cores were predicted in the absence of the target loop, loop-prediction accuracy only reduces slightly (0.2 Å difference in RMSD for 12-residue loops in the CASP target proteins). The accuracy obtained is about 1 Å RMSD or more improvement over other methods we tested. The executable file for a Linux system is freely available for academic users at http://sparks-lab.org.
authors: Systems Immunology Laboratory, Immunology Frontier Research Center, Osaka University, Suita, Osaka, 565-0871, Japan.
authors: Shide
authors: S
authors: Liang
authors: Chi
authors: C
authors: Zhang
authors: Yaoqi
authors: Y
authors: Zhou
mesh_terms: D011487:Protein Conformation; D011506:Proteins / Q000737:chemistry*; D011789:Quantum Theory
chemical_list: D011506:Proteins
keywords: loop modeling • coarse-grained energy function • energy minimization • Monte Carlo simulation • force field development