Prediction of Structures and Interactions from Genome Information.

INTEGRATIVE STRUCTURAL BIOLOGY WITH HYBRID METHODS(2018)

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摘要
Predicting three dimensional residue-residue contacts from evolutionary information in protein sequences was attempted already in the early 1990s. However, contact prediction accuracies of methods evaluated in CASP experiments before CASP11 remained quite low, typically with <20% true positives. Recently, contact prediction has been significantly improved to the level that an accurate three dimensional model of a large protein can be generated on the basis of predicted contacts. This improvement was attained by disentangling direct from indirect correlations in amino acid covariations or cosubstitutions between sites in protein evolution. Here, we review statistical methods for extracting causative correlations and various approaches to describe protein structure, complex, and flexibility based on predicted contacts.
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关键词
Contact prediction,Direct coupling,Amino acid covariation,Amino acid cosubstitution,Partial correlation,Maximum entropy model,Inverse Potts model,Markov random field,Boltzmann machine,Deep neural network
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