MolPredictX: A Pioneer Mobile App Version for Online Biological Activity Predictions by Machine Learning Models

Marcus Tullius Scotti; Emmanuella Faustino Albuquerque; Ciro Gomes da Silva Junior; Renata P B Menezes; Chonny Herrera-Acevedo; Natália F Sousa; Lucas Ferreira Calado; Eduardo Henrique Pessoa Alves; Luciana Scotti

doi:10.1007/978-1-0716-4003-6_17

MolPredictX: A Pioneer Mobile App Version for Online Biological Activity Predictions by Machine Learning Models

Methods Mol Biol. 2025:2834:351-371. doi: 10.1007/978-1-0716-4003-6_17.

Authors

Marcus Tullius Scotti¹, Emmanuella Faustino Albuquerque¹, Ciro Gomes da Silva Junior¹, Renata P B Menezes¹, Chonny Herrera-Acevedo^{1

2}, Natália F Sousa¹, Lucas Ferreira Calado¹, Eduardo Henrique Pessoa Alves¹, Luciana Scotti¹

Affiliations

¹ Post-Graduate Program in Natural and Synthetic Bioactive Products, Federal University of Paraíba, João Pessoa, PB, Brazil.
² Department of Chemical Engineering, Universidad ECCI, Bogotá, Distrito Capital, Colombia.

PMID: 39312174
DOI: 10.1007/978-1-0716-4003-6_17

Abstract

MolPredictX is a free-access web tool in which it is possible to analyze the prediction of biological activity of chemical molecules. MolPredictX has been available online to the general public for just over a year and has now gone through its first update. We also developed its version for android, being the first free app capable of predicting biological activities. MolPredictX is available for free at https://www.molpredictX.ufpb.br/ , and its mobile application version can be obtained from Google Play.

Keywords: Computer-aided drug design; Quantitative structure activity relationships.

MeSH terms

Computational Biology / methods
Humans
Internet
Machine Learning*
Mobile Applications*
Software*