IQUIBA-NEA   25617
INSTITUTO DE QUIMICA BASICA Y APLICADA DEL NORDESTE ARGENTINO
Unidad Ejecutora - UE
congresos y reuniones científicas
Título:
Preliminary results of supervised models trained with charge density data from Cruzain-inhibitors complexes.
Autor/es:
LUCHI, ADRIANO M.; VILLAFAÑE, ROXANA; PERUCHENA, N. M.; ANGELINA, EMILIO
Lugar:
MONTEVIDEO
Reunión:
Conferencia; KHIPU Latin American Meeting in Artificial Intelligence; 2019
Institución organizadora:
KHIPU GENERAL COMMITTEE
Resumen:
Proteins are the most versatile biological molecules, with diverse functions. Recently, the AI community have developed interest in specific topics related to proteins as: protein folding, structural análisis, protein-ligand affinity estimation, among others. Cruzain is a cysteine-protease involved in Chagas disease with several Cz-inhibitor complexes deposited in the Protein Data Bank (PDB). Unfortunately, the number of structures solved up-to-date is scarce for the requirements of a machine learning optimization algorithm. Another issue is the high dimensionality of the data involved in structure-based approaches for drug design. In this work, charge density-based data was employed as input for a classification algorithm with the protein-ligand interactions as columns and ligands as rows. A support vector machine with recursive feature elimination was employed to uncover the most relevant features involved in the protein-inhibitor complexes. This approach is the first step for further analysis of topological data of Cz-ligand complexes under study. We hope that results will shed light to understand the inhibition mechanism of Cruzain.