MolPredictX: Online Biological Activity Predictions by Machine Learning Models.

Journal: Molecular informatics
Published Date: Sep 1, 2022

Abstract

Here we report the development of MolPredictX, an innovate and freely accessible web interface for biological activity predictions of query molecules. MolPredictX utilizes in-house QSAR models to provide 27 qualitative predictions (active or inactive), and quantitative probabilities for bioactivity against parasitic (Trypanosoma and Leishmania), viral (Dengue, Sars-CoV and Hepatitis C), pathogenic yeast (Candida albicans), bacterial (Salmonella enterica and Escherichia coli), and Alzheimer disease enzymes. In this article, we introduce the methodology and usability of this webtool, highlighting its potential role in the development of new drugs against a variety of diseases. MolPredictX is undergoing continuous development and is freely available at https://www.molpredictx.ufpb.br/.

Authors

  • Marcus Tullius Scotti
    Programa de Pós-Graduação de Produtos Naturais e Sintéticos Bioativos, Universidade Federal da Paraíba, 58051-900, João Pessoa-PB, Brazil.
  • Chonny Herrera-Acevedo
    Post-Graduate Program in Natural and Synthetic Bioactive Products, Federal University of Paraíba, João Pessoa, PB, 58051-900, Brazil.
  • Renata Priscila Barros de Menezes
    Post-Graduate Program in Natural and Synthetic Bioactive Products, Federal University of Paraíba, João Pessoa 58051-900, Brazil.
  • Holli-Joi Martin
    Laboratory for Molecular Modeling, Division of Chemical Biology and Medicinal Chemistry, UNC Eshelman School of Pharmacy, University of North Carolina, Chapel Hill, NC, 27599, USA.
  • Eugene N Muratov
    Laboratory for Molecular Modeling, UNC Eshelman School of Pharmacy, University of North Carolina, Chapel Hill, North Carolina, United States of America.
  • Ávilla Ítalo de Souza Silva
    Programa de Pós-Graduação de Produtos Naturais e Sintéticos Bioativos, Universidade Federal da Paraíba, 58051-900, João Pessoa-PB, Brazil.
  • Emmanuella Faustino Albuquerque
    Programa de Pós-Graduação de Produtos Naturais e Sintéticos Bioativos, Universidade Federal da Paraíba, 58051-900, João Pessoa-PB, Brazil.
  • Lucas Ferreira Calado
    Programa de Pós-Graduação de Produtos Naturais e Sintéticos Bioativos, Universidade Federal da Paraíba, 58051-900, João Pessoa-PB, Brazil.
  • Ericsson Coy-Barrera
    Bioorganic Chemistry Laboratory, Facultad de Ciencias Básicas y Aplicadas, Universidad Militar Nueva Granada, 250247, Cajicá, Colombia.
  • Luciana Scotti
    Health Sciences Center, Federal University of Paraiba, Campus I, 58051-970, João Pessoa, PB, Brazil. luciana.scotti@gmail.com.

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