D-I-TASSER (Distance-guided Iterative Threading ASSEmbly Refinement) is a new method extended from I-TASSER for high-accuracy protein structure and function predictions. Starting from a query sequence, D-I-TASSER first generates inter-residue contact maps, distance maps and hydrogen-bond networks using multiple deep neural-network predictors, including DeepPotential, NeBcon, ResPRE, ResTriplet, and TripletRes. It then identifies structural templates from the PDB by multiple threading approach LOMETS3, with full-length atomic models assembled by contact/distance/hydrogen bond- guided replica-exchange Monte Carlo simulations. Biological functions of the query protein are finally derived from the structure model by COFACTOR. The large-scale benchmark tests showed that D-I-TASSER generates significantly more accurate models than I-TASSER, especially for the sequences that do not have homologous templates in the PDB. Please report problems and questions at our Discussion Board.
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