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Protein structure modeling and refinement by global optimization in CASP12
Author(s) -
Hong Seung Hwan,
Joung InSuk,
FloresCanales Jose C.,
Manavalan Balachandran,
Cheng Qianyi,
Heo Seungryong,
Kim Jong Yun,
Lee Sun Young,
Nam Mikyung,
Joo Keehyoung,
Lee InHo,
Lee Sung Jong,
Lee Jooyoung
Publication year - 2018
Publication title -
proteins: structure, function, and bioinformatics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.699
H-Index - 191
eISSN - 1097-0134
pISSN - 0887-3585
DOI - 10.1002/prot.25426
Subject(s) - computer science , casp , protein structure prediction , simulated annealing , force field (fiction) , global optimization , molecular dynamics , protocol (science) , energy minimization , algorithm , biological system , protein structure , artificial intelligence , computational chemistry , physics , chemistry , medicine , alternative medicine , nuclear magnetic resonance , pathology , biology
For protein structure modeling in the CASP12 experiment, we have developed a new protocol based on our previous CASP11 approach. The global optimization method of conformational space annealing (CSA) was applied to 3 stages of modeling: multiple sequence‐structure alignment, three‐dimensional (3D) chain building, and side‐chain re‐modeling. For better template selection and model selection, we updated our model quality assessment (QA) method with the newly developed SVMQA (support vector machine for quality assessment). For 3D chain building, we updated our energy function by including restraints generated from predicted residue‐residue contacts. New energy terms for the predicted secondary structure and predicted solvent accessible surface area were also introduced. For difficult targets, we proposed a new method, LEEab, where the template term played a less significant role than it did in LEE, complemented by increased contributions from other terms such as the predicted contact term. For TBM (template‐based modeling) targets, LEE performed better than LEEab, but for FM targets, LEEab was better. For model refinement, we modified our CASP11 molecular dynamics (MD) based protocol by using explicit solvents and tuning down restraint weights. Refinement results from MD simulations that used a new augmented statistical energy term in the force field were quite promising. Finally, when using inaccurate information (such as the predicted contacts), it was important to use the Lorentzian function for which the maximal penalty arising from wrong information is always bounded.