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 computing configurational entropy changes due to correlated motions from molecular simulations. Here, we present the first application of the MIE method to protein-ligand binding, using multiple molecular dynamics simulations (MMDSs) to study association of the UEV domain of the protein Tsg101 and an HIV-derived nonapeptide. The current investigation utilizes the second-order MIE approximation, which treats correlations between all pairs of degrees of freedom. The computed change in configurational entropy is large and is found to have 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.

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Molecular dynamics simulations have been used to assess the conformational behaviour of seven disaccharides in aqueous solution. Solvation decreased the overall conformational fluctuations of the sugars, compared to in vacuo simulations using a high dielectric constant. The most significant finding was a linear correlation between the experimental chromatographic retention parameter K´ and a molecular modelling parameter based on the next-nearest oxygen–oxygen distances in the disaccharides. The results support previous proposals for a stereospecific hydration model for carbohydrates and demonstrate the utility of a combined experimental/molecular modelling approach to its study.

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