Virtual Screening Based on Electrostatic Similarity and Flexible Ligands

Abstract

Virtual Screening (VS) is a technique aimed at reducing the time and budget required when working on drug discovery campaigns. The idea consists of applying computational procedures to prefilter databases to a subset of potential compounds, to be characterized experimentally in later phases. The problem lies in the fact that the current VS methods make simplifications, meaning they are not exhaustive. One particular common simplification is to consider the molecules as rigid. Such an assumption greatly reduces the computational complexity of the optimization problem to be solved, but it may result in poor or inefficient predictions. In this work, we have extended the features of Optipharm, a recently developed piece of software, by applying a methodology that considers the flexibility of the molecules. The new OptiPharm has several strengths over its previous version. More precisely, (i) it includes a prefilter based on molecule descriptors, (ii) simulates molecule flexibility by computing different poses for each rotatable bond, (iii) reduces the search space dimension, and (iv) introduces circular limits for the angular variables to enhance searchability. As the results show, these improvements help OptiPharm to achieve better predictions.