Conformational Ensembles from Experimental Data and Computer Simulations

Conformational Ensembles from Experimental Data and Computer Simulations

Poster Abstracts

36-POS Board 36 From Sequence to Function: Coevolving Amino Acids Encode Structural and Dynamical Domains Daniele Granata 1,2 , Luca Ponzoni 3 , Kresten Lindorff-Larsen 1 , Cristian Micheletti 3 , Vincenzo Carnevale 2 . 1 University of Copenhagen, Kobenhavn, Denmark, 2 Temple University, Philadelphia, PA, USA, 3 SISSA, Trieste, Italy. Amino acids interactions within protein families are so optimized that the sole analysis of evolutionary co-mutations can pinpoint pairs of contacting residues. It is also known that evolution conserves functional dynamics, i.e., the concerted motion or displacement of large protein regions or domains. Is it, therefore, possible to use a pure sequence-based analysis to identify these dynamical domains? We introduce a general co-evolutionary coupling analysis strategy and apply it to a curated sequence database of 800 protein families. As soon as few hundreds of sequence are available for the coupling inference, the sequence-based method partitions amino acids into clusters spatially separated but individually compact, when represented on the relative native structure. Remarkably, these "Evolutionary Domains" are also highly correlated with proteins dynamical domains, encoding their structural dynamics. Finally we discuss relevant applications to comparative analysis within ion channels family and to the identification of allosteric communication between domains in specific enzymes.

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