MAYA (Multiple ActivitY Analyzer): An Open Access Tool to Explore Structure‐Multiple Activity Relationships in the Chemical Universe

Herein, we introduce MAYA (Multiple Activity Analyzer), a tool designed to automatically construct a chemical multiverse, generating multiple visualizations of chemical spaces of a compound data set described by structural descriptors of different nature such as Molecular ACCess Systems (MACCS) keys, extended connectivity fingerprints with different radius, molecular descriptors with pharmaceutical relevance, and bioactivity descriptors. These representations are integrated with various data visualization techniques for the automated analysis focused on structure - multiple activity/property relationships, enabling analysis for various problems set in user-friendly source software. The source code of MAYA is freely available on GitHub at https://github.com/IsrC11/MAYA.git.

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Publication Details

Journal
Molecular Informatics
Published
2025-02-01
DOI
https://doi.org/10.1002/minf.202400306
Citations
1
Primary Topic
Computational Drug Discovery Methods
Type
article
Field-Weighted Citation Impact
1.50

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article

MAYA (Multiple ActivitY Analyzer): An Open Access Tool to Explore Structure‐Multiple Activity Relationships in the Chemical Universe

José L. Medina‐Franco, J. Israel Espinoza‐Castañeda
1 citations
Molecular Informatics
Computational Drug Discovery Methods
1.50
article

MAYA (Multiple ActivitY Analyzer): An Open Access Tool to Explore Structure‐Multiple Activity Relationships in the Chemical Universe

José L. Medina‐Franco, J. Israel Espinoza‐Castañeda
article en
1 citations

Abstract

Herein, we introduce MAYA (Multiple Activity Analyzer), a tool designed to automatically construct a chemical multiverse, generating multiple visualizations of chemical spaces of a compound data set described by structural descriptors of different nature such as Molecular ACCess Systems (MACCS) keys, extended connectivity fingerprints with different radius, molecular descriptors with pharmaceutical relevance, and bioactivity descriptors. These representations are integrated with various data visualization techniques for the automated analysis focused on structure - multiple activity/property relationships, enabling analysis for various problems set in user-friendly source software. The source code of MAYA is freely available on GitHub at https://github.com/IsrC11/MAYA.git.

Molecular InformaticsVol. 44(2)
Universidad Nacional Autónoma de México (MX)
Dirección General de Asuntos del Personal Académico, Universidad Nacional Autónoma de México
Openalex Percentile: Top 20%
Computational Drug Discovery Methods
1.50
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