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MolPredictX: Online Biological Activity Predictions by Machine Learning Models.

Marcus Tullius Scotti1, Chonny Herrera-Acevedo1,2, Renata Priscila Barros de Menezes1

  • 1Programa de Pós-Graduação de Produtos Naturais e Sintéticos Bioativos, Universidade Federal da Paraíba, 58051-900, João Pessoa-PB, Brazil.

Molecular Informatics
|August 12, 2022
PubMed
Summary

MolPredictX is a new, free web tool that predicts molecule bioactivity. It uses QSAR models for 27 predictions against diseases like malaria, dengue, and Alzheimer's, aiding drug discovery.

Keywords:
Drug developmentMolPredictXOnline web-based toolQualitative predictionbiological activity

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Area of Science:

  • Computational chemistry
  • Drug discovery
  • Bioinformatics

Background:

  • Developing novel therapeutics requires efficient prediction of molecular bioactivity.
  • Existing tools may lack comprehensive coverage or accessibility for diverse disease targets.

Purpose of the Study:

  • To introduce MolPredictX, a freely accessible web interface for predicting the biological activity of molecules.
  • To provide a versatile platform for assessing drug-likeness against a range of pathogens and diseases.

Main Methods:

  • Development of an in-house Quantitative Structure-Activity Relationship (QSAR) modeling suite.
  • Integration of QSAR models into a user-friendly web interface (MolPredictX).
  • Validation of predictive accuracy for qualitative (active/inactive) and quantitative (probability) outputs.

Main Results:

  • MolPredictX offers 27 distinct bioactivity predictions.
  • Predictions cover parasitic, viral, fungal, bacterial, and neurodegenerative disease targets.
  • The tool provides both qualitative and quantitative (probability) bioactivity assessments.

Conclusions:

  • MolPredictX serves as a valuable, accessible resource for drug discovery research.
  • The platform facilitates the identification of potential drug candidates against various diseases.
  • Continuous development ensures MolPredictX remains a relevant tool in medicinal chemistry.