This was the first CCPBioSim Special Seminar. Richard Henchman (University of Manchester) spoke about Entropy Analysis of Molecular Systems over Every Degree of Freedom. In case you missed it, want to watch it again, or want to share with friends, the recording is now available to view at

Abstract: The stability and flexibility of biomolecules are inherent to their properties and function. Entropy is central to both these quantities, first because it is a key component of the free energy, which governs stability, and second because it expresses the probability distribution over all degrees of freedom in a single number. While there are methods to evaluate entropy for specific cases and while there are many partial measures of molecular
flexibility, a general way to evaluate the entropy and full probability distribution is lacking for systems of biomolecular interest. To address this, we present the Multiscale Cell Correlation (MCC) method [1-2] which calculates entropy in a multiscale fashion in terms of cells of correlated units. We apply it to two cases: host-guest complexes [3] and proteins [4]. Binding free energies in the recent SAMP8 Challenge give a 1 kcal mol−1 error, and protein entropies closely match values from normal mode analysis. MCC explains how entropy is distributed over all degrees of freedom in each system. For binding, as expected, the entropy loss of the binding guest is offset by the gain in the released water. In proteins, entropy in the polymer chain is found to be comparable to that within the residues, and the residue entropy is largely independent of solvent exposure due to a compensation between conformational and vibrational entropy.
[1] J. Higham, S. Chou, F. Gräter, R. H. Henchman, Mol. Phys., 2018, 116, 1965.
[2] H. S. Ali, J. Higham, R. H. Henchman, Entropy, 2020, 21, 750.
[3] H. S. Ali, A. Chakravorty, J. Kalayan, S. P. de Visser, R. H. Henchman, submitted.
[4] A. Chakravorty, J. Higham, R. H. Henchman, J. Chem. Inf. Model., 2020, 60, 5540.