Literature DB >> 21455286

"Fluctuograms" reveal the intermittent intra-protein communication in subtilisin Carlsberg and correlate mechanical coupling with co-evolution.

Jordi Silvestre-Ryan1, Yuchun Lin, Jhih-Wei Chu.   

Abstract

The mechanism of intra-protein communication and allosteric coupling is key to understanding the structure-property relationship of protein function. For subtilisin Carlsberg, the Ca²+-binding loop is distal to substrate-binding and active sites, yet the serine protease function depends on Ca²+ binding. The atomic molecular dynamics (MD) simulations of apo and Ca²+-bound subtilisin show similar structures and there is no direct evidence that subtilisin has alternative conformations. To model the intra-protein communication due to Ca²+ binding, we transform the sequential segments of an atomic MD trajectory into separate elastic network models to represent anharmonicity and nonlinearity effectively as the temporal and spatial variation of the mechanical coupling network. In analogy to the spectrogram of sound waves, this transformation is termed the "fluctuogram" of protein dynamics. We illustrate that the Ca²+-bound and apo states of subtilisin have different fluctuograms and that intra-protein communication proceeds intermittently both in space and in time. We found that residues with large mechanical coupling variation due to Ca²+ binding correlate with the reported mutation sites selected by directed evolution for improving the stability of subtilisin and its activity in a non-aqueous environment. Furthermore, we utilize the fluctuograms calculated from MD to capture the highly correlated residues in a multiple sequence alignment. We show that in addition to the magnitude, the variance of coupling strength is also an indicative property for the sequence correlation observed in a statistical coupling analysis. The results of this work illustrate that the mechanical coupling networks calculated from atomic details can be used to correlate with functionally important mutation sites and co-evolution.

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Year:  2011        PMID: 21455286      PMCID: PMC3063751          DOI: 10.1371/journal.pcbi.1002023

Source DB:  PubMed          Journal:  PLoS Comput Biol        ISSN: 1553-734X            Impact factor:   4.475


  76 in total

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5.  Systematic multiscale parameterization of heterogeneous elastic network models of proteins.

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Authors:  W G Noid; Jhih-Wei Chu; Gary S Ayton; Vinod Krishna; Sergei Izvekov; Gregory A Voth; Avisek Das; Hans C Andersen
Journal:  J Chem Phys       Date:  2008-06-28       Impact factor: 3.488

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