Optimizing Electrostatic Similarity for Virtual Screening: A New Methodology

30 October 2019, Version 1
This content is a preprint and has not undergone peer review at the time of posting.

Abstract

Ligand Based Virtual Screening (LBVS) methods are widely used in drug discovery as filters for subsequent in-vitro and in-vivo characterization. This means, increasing accuracy of LBVS approaches may have a huge impact on increasing chances of success. Since the databases processed in drug discovery campaigns are enormously large, this pre-selection process requires the use of fast and precise methodologies. The similarity between compounds can be measured using different descriptors such as shape, pharmacophore or electrostatic similarity. The latter is the goal of this work, i.e., we want to improve the process of obtaining the compounds most similar to a query in terms of electrostatic similarity. To do so, the current and widely proposed methodology in the literature is based on the use of ROCS to assess the similarity of compounds in terms of shape and then evaluate a small subset of them with ZAP for prioritization regarding electrostatic similarity. This paper proposes an alternative methodology that consists of directly optimizing electrostatic similarity and works with the entire database of compounds without using shape cut-offs. For this purpose, a new and improved version of the OptiPharm software has been developed. OptiPharm implements a parameterizable metaheuristic algorithm able to solve any optimization problems directly related to the involved molecular conformations. We show that our new method completely outperforms the classical proposal widely used in the literature. Accordingly, we are able to conclude that many of the compounds proposed with our novel approach could not be discovered with the classical one. As a result, this methodology opens up new horizons in Drug Discovery.

Keywords

Virtual screening
Shape similarity
Electrostatic similarity
Methodology

Comments

Comments are not moderated before they are posted, but they can be removed by the site moderators if they are found to be in contravention of our Commenting Policy [opens in a new tab] - please read this policy before you post. Comments should be used for scholarly discussion of the content in question. You can find more information about how to use the commenting feature here [opens in a new tab] .
This site is protected by reCAPTCHA and the Google Privacy Policy [opens in a new tab] and Terms of Service [opens in a new tab] apply.