DeepCDpred: Inter-residue distance and contact prediction for improved prediction of protein structure.

ABSTRACT: Rapid, accurate prediction of protein structure from amino acid sequence would accelerate fields as diverse as drug discovery, synthetic biology and disease diagnosis. Massively improved prediction of protein structures has been driven by improving the prediction of the amino acid residues that contact in their 3D structure. For an average globular protein, around 92% of all residue pairs are non-contacting, therefore accurate prediction of only a small percentage of inter-amino acid distances could increase the number of constraints to guide structure determination. We have trained deep neural networks to predict inter-residue contacts and distances. Distances are predicted with an accuracy better than most contact prediction techniques. Addition of distance constraints improved de novo s

SUBMITTER: Ji S 

PROVIDER: S-EPMC6324825 | biostudies-literature | 2019

REPOSITORIES: biostudies-literature