HT_PREDICT: a machine learning-based computational open-source tool for screening HDAC6 inhibitors.
SAR QSAR Environ Res
; 35(6): 505-530, 2024 Jun.
Article
em En
| MEDLINE
| ID: mdl-39007781
ABSTRACT
Histone deacetylase 6 (HDAC6) is a promising drug target for the treatment of human diseases such as cancer, neurodegenerative diseases (in particular, Alzheimer's disease), and multiple sclerosis. Considerable attention is paid to the development of selective non-toxic HDAC6 inhibitors. To this end, we successfully form a set of 3854 compounds and proposed adequate regression QSAR models for HDAC6 inhibitors. The models have been developed using the PubChem, Klekota-Roth, 2D atom pair fingerprints, and RDkit descriptors and the gradient boosting, support vector machines, neural network, and k-nearest neighbours methods. The models are integrated into the developed HT_PREDICT application, which is freely available at https//htpredict.streamlit.app/. In vitro studies have confirmed the predictive ability of the proposed QSAR models integrated into the HT_PREDICT web application. In addition, the virtual screening performed with the HT_PREDICT web application allowed us to propose two promising inhibitors for further investigations.
Palavras-chave
Texto completo:
1
Coleções:
01-internacional
Base de dados:
MEDLINE
Assunto principal:
Relação Quantitativa Estrutura-Atividade
/
Inibidores de Histona Desacetilases
/
Aprendizado de Máquina
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Desacetilase 6 de Histona
Limite:
Humans
Idioma:
En
Revista:
SAR QSAR Environ Res
Assunto da revista:
SAUDE AMBIENTAL
Ano de publicação:
2024
Tipo de documento:
Article
País de afiliação:
Moldávia