Evolution leads to considerable changes in the sequence of biomolecules, while their overall structure and function remain quite conserved. The wealth of genomic sequences, the ‘Biological Big Data’, modern sequencing techniques provide allows us to investigate biomolecular evolution with unprecedented detail. Sophisticated statistical models can infer residue pair mutations resulting from spatial proximity. The introduction of predicted spatial adjacencies as constraints in biomolecular structure prediction workflows has transformed the field of protein and RNA structure prediction toward accuracies approaching the experimental resolution limit. Going beyond structure prediction, the same mathematical framework allows mimicking evolutionary fitness landscapes to infer signaling interactions, epistasis, or mutational landscapes.
Biomolecular coevolution and its applications: Going from structure prediction toward signaling, epistasis, and function
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Mehari B. Zerihun, Alexander Schug; Biomolecular coevolution and its applications: Going from structure prediction toward signaling, epistasis, and function. Biochem Soc Trans 15 December 2017; 45 (6): 1253–1261. doi: https://doi.org/10.1042/BST20170063
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