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Optimizing Electrostatic Similarity for Virtual Screening: A New Methodology
Volume 31, Issue 4 (2020), pp. 821–839
Pub. online: 29 July 2020      Type: Research Article      Open accessOpen Access
Received
1 March 2020
Accepted
1 July 2020
Published
29 July 2020

Abstract

Ligand Based Virtual Screening methods are widely used in drug discovery as filters for subsequent in-vitro and in-vivo characterization. Since the databases processed are enormously large, this pre-selection process requires the use of fast and precise methodologies. In this work, the similarity between compounds is measured in terms of electrostatic potential. To do so, we propose a new and alternative methodology, called LBVS-Electrostatic. Accordingly to the obtained results, we are able to conclude that many of the compounds proposed with our novel approach could not be discovered with the classical one.

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Biographies

Puertas-Martín Savíns
savinspm@ual.es

S. Puertas-Martín is a predoctoral researcher at the Informatics Department at University of Almería, Spain. He studied the degree and master in computer engineering at the University of Almería. He is currently doing his PhD thanks to the Spanish FPU program. His publications and more information about him can be found on https://www.scopus.com/authid/detail.uri?authorId=57201417677. His research interests are drug discovery, global optimization and high performance computing.

L. Redondo Juana
jlredondo@ual.es

J.L. Redondo is a professor at the Informatics Department at University of Almería, Spain. She obtained her PhD from the University of Almería. Her publications can be found on https://www.scopus.com/authid/detail.uri?authorId=35206862500. Her research interests include high performance computing, global optimization and applications.

Pérez-Sánchez Horacio
hperez@ucam.edu

P.M. Ortigosa is a full professor at the Informatics Department at University of Almería, Spain. She obtained her PhD from the University of Málaga. Her publications can be found on https://www.scopus.com/authid/detail.uri?authorId=6602759441. Her research interests include high performance computing, global optimization and applications.

M. Ortigosa Pilar
ortigosa@ual.es

H. Pérez-Sánchez is principal investigator of the Structural Bioinformatics and High Performance Computing (BIO-HPC) research group at Universidad Católica de Murcia (UCAM), Spain. He obtained his PhD from the University of Murcia. His publications can be found on https://www.scopus.com/authid/detail.uri?authorId=12767397700. His research interests include high performance computing, structural bioinformatics and physical chemistry.


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© 2020 Vilnius University
Open access article under the CC BY license.

Keywords
virtual screening shape similarity electrostatic similarity

Funding
This work was supported by the Spanish Ministry of Economy and Competitiveness through the CTQ2017-87974-R and RTI2018-095993-B-100 grants; by the Programa Regional de Fomento de la Investigación (Plan de Actuación 2018, Región de Murcia, Spain) through the: ‘Ayudas a la realización de proyectos para el desarrollo de investigación científica y técnica por grupos competitivos (20988/PI/18)’ grant; by the Junta de Andalucía through the grant Proyectos de excelencia (P18-RT-1193), and by the University of Almería through the grant: “Ayudas a proyectos de investigación I+D+I en el marco del Programa Operativo FEDER 2014-20 “(UAL18-TIC-A020-B); and by Fundación Séneca (The Agency of Science and Technology of the Region of Murcia, 20817/PI/18). Savíns Puertas Martín is a fellow of the Spanish ‘Formación del Profesorado Universitario’ program (FPU15/02912), financed by the Spanish Ministry of Education, Culture and Sport.

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