ChemRxiv
These are preliminary reports that have not been peer-reviewed. They should not be regarded as conclusive, guide clinical practice/health-related behavior, or be reported in news media as established information. For more information, please see our FAQs.
Optimizing_electrostatic_potential_CHEMRXIV.pdf (3.99 MB)
0/0

Optimizing Electrostatic Similarity for Virtual Screening: A New Methodology

preprint
submitted on 26.10.2019 and posted on 30.10.2019 by Savíns Puertas Martín, Juana Lopez Redondo, Horacio Pérez-Sánchez, Pilar Martínez Ortigosa
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.

Funding

Spanish Ministry of Economy and Competitiveness (RTI2018-095993-B-100, CTQ2017-87974-R)

Junta de Andalucía (P12-TIC301, UAL18-TIC-A020-B)

Fundación Séneca--Agencia de Ciencia y Tecnología de la Región de Murcia(Projects 20988/PI/18, 20817/PI/18

History

Email Address of Submitting Author

savinspm@ual.es

Institution

University of Almeria

Country

Spain

ORCID For Submitting Author

0000-0001-8956-1733

Declaration of Conflict of Interest

The authors declare no conflict of interest.

Version Notes

Initial version.

Exports