Fast and Accurate Estimation of Gas-Phase Entropy from the Molecular Surface Curvature

Abstract

Estimating entropy is crucial for understanding and modifying biological systems, such as protein-ligand binding. Current computational methods to estimate entropy require extensive, or at times prohibitively extensive, computational resources. This article presents SHAPE (SHape-based Accurate Predictor of Entropy), a new method that estimates the gas-phase entropy of small molecules purely from their surface geometry. Using SHAPE, the gas-phase entropy of small molecules can be computed in ~ 0.01 CPU hours with run time complexity of Ω(√(Na), where Na is the number of atoms. The accuracy of The method is within 1-2% of computationally expensive quantum mechanical or molecular mechanics calculations. We further show that the inclusion of gas-phase entropy, estimated using SHAPE, improves the rank-order correlation between binding affinity and the binding score from 0.18 to 0.40. The speed and accuracy of SHAPE make it well-suited for use in molecular docking studies as well as in the analysis of structure-activity relationships.