Prediction of Structures and Interactions from Genome Information

Abstract

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.

35 pages, 4 Tables, and 1 figures. In 2018, this manuscript with the short version of appendix has been published as the chapter 9 of a book, "Integrative Structural Biology with Hybrid Methods" edited by Haruki Nakamura as one of the book series: "Advances in Experimental Medicine and Biology 1105" from Springer Nature Singapore Pte Ltd.; https://doi.org/10.1007/978-981-13-2200-6_9

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Cited by in corpus (2)

• Prediction of Structures and Interactions from Genome Information
• Boltzmann machine learning and regularization methods for inferring evolutionary fields and couplings from a multiple sequence alignment