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In Journal of computational chemistry ; h5-index 0.0

Protein structure determination has long been one of the most challenging problems in molecular biology for the past 60 years. Here we present an ab initio protein tertiary-structure prediction method assisted by predicted contact maps from SPOT-Contact and predicted dihedral angles from SPIDER 3. These predicted properties were then fed to the crystallography and NMR system (CNS) for restrained structure modeling. The resulted structures are first evaluated by the potential energy calculated by CNS, followed by dDFIRE energy function for model selections. The method called SPOT-Fold has been tested on 241 CASP targets between 67 and 670 amino acid residues, 60 randomly selected globular proteins under 100 amino acids. The method has a comparable accuracy to other contact-map-based modeling techniques. © 2019 Wiley Periodicals, Inc.

Cai Yufeng, Li Xiongjun, Sun Zhe, Lu Yutong, Zhao Huiying, Hanson Jack, Paliwal Kuldip, Litfin Thomas, Zhou Yaoqi, Yang Yuedong


contact map, deep learning, molecular dynamics, protein structure prediction, template-free modeling