Abstract
The sequences of biomolecules such as proteins and RNA genes contain information about their three-dimensional states and functions. For over 40 years biologists have used the evolutionary conservation of this information to detect homology and predict important subsets of residues. Recent work has substantially extended this view of conservation by including the detection of evolutionary couplings , interactions, between residues, resulting in a paradigm shift in our ability to compute three-dimensional structures from sequences alone. In addition to three-dimensional structure of single proteins and RNA, this statistical analysis of evolutionary constraints can identify functional residues involved in ligand binding, biomolecule-interactions, alternative ensembles of conformations, “invisible” tertiary states of disordered proteins and allows quantitative prediction of effects of mutations. In this chapter we present an overview of the statistical inference methodologies, a survey of the resulting applications and challenges facing the field.
Parts of this chapter have been adapted from (Hopf 2016).
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Hopf, T.A., Marks, D.S. (2017). Protein Structures, Interactions and Function from Evolutionary Couplings. In: J. Rigden, D. (eds) From Protein Structure to Function with Bioinformatics. Springer, Dordrecht. https://doi.org/10.1007/978-94-024-1069-3_2
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