Novel molecular inhibitor design for Plasmodium falciparum Lactate dehydrogenase enzyme using machine learning generated library of diverse compounds.
Mol Divers
; 2024 Aug 20.
Article
em En
| MEDLINE
| ID: mdl-39162960
ABSTRACT
Generative machine learning models offer a novel strategy for chemogenomics and de novo drug design, allowing researchers to streamline their exploration of the chemical space and concentrate on specific regions of interest. In cases with limited inhibitor data available for the target of interest, de novo drug design plays a crucial role. In this study, we utilized a package called 'mollib,' trained on ChEMBL data containing approximately 365,000 bioactive molecules. By leveraging transfer learning techniques with this package, we generated a series of compounds, starting from five initial compounds, which are potential Plasmodium falciparum (Pf) Lactate dehydrogenase inhibitors. The resulting compounds exhibit structural diversity and hold promise as potential novel Pf Lactate dehydrogenase inhibitors.
Texto completo:
1
Coleções:
01-internacional
Base de dados:
MEDLINE
Idioma:
En
Revista:
Mol Divers
Assunto da revista:
BIOLOGIA MOLECULAR
Ano de publicação:
2024
Tipo de documento:
Article
País de afiliação:
Índia