Configurational Entropy in Protein-Peptide Binding:. Computational Study of Tsg101 Ubiquitin E2 Variant Domain with an HIV-Derived PTAP Nonapeptide

Benjamin J. Killian, Joslyn Yudenfreund Kravitz, Sandeep Somani, Paramita Dasgupta, Yuan Ping Pang, Michael K. Gilson

Research output: Contribution to journalArticlepeer-review

69 Scopus citations

Abstract

Configurational entropy is thought to influence biomolecular processes, but there are still many open questions about this quantity, including its magnitude, its relationship to molecular structure, and the importance of correlation. The mutual information expansion (MIE) provides a novel and systematic approach to extracting configurational entropy changes due to correlated motions from molecular simulations. We present the first application of the MIE method to protein-ligand binding using multiple molecular dynamics simulations to study the association of the ubiquitin E2 variant domain of the protein Tsg101 and an HIV-derived nonapeptide. This investigation utilizes the second-order MIE approximation, which accounts for correlations between all pairs of degrees of freedom. The computed change in configurational entropy is large and has a major contribution from changes in pairwise correlation. The results also reveal intricate structure-entropy relationships. Thus, the present analysis suggests that in order for a model of binding to be accurate, it must include a careful accounting of configurational entropy changes.

Original languageEnglish (US)
Pages (from-to)315-335
Number of pages21
JournalJournal of Molecular Biology
Volume389
Issue number2
DOIs
StatePublished - Jun 5 2009

Keywords

  • correlation
  • multiple molecular dynamics simulation (MMDS)
  • mutual information expansion (MIE)
  • thermodynamics
  • translational/rotational entropy

ASJC Scopus subject areas

  • Biophysics
  • Structural Biology
  • Molecular Biology

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