Artificial intelligence-guided approach for efficient virtual screening of hits against Schistosoma mansoni.
Future Med Chem
; 15(22): 2033-2050, 2023 Nov.
Article
em En
| MEDLINE
| ID: mdl-37937522
Background: The impact of schistosomiasis, which affects over 230 million people, emphasizes the urgency of developing new antischistosomal drugs. Artificial intelligence is vital in accelerating the drug discovery process. Methodology & results: We developed classification and regression machine learning models to predict the schistosomicidal activity of compounds not experimentally tested. The prioritized compounds were tested on schistosomula and adult stages of Schistosoma mansoni. Four compounds demonstrated significant activity against schistosomula, with 50% effective concentration values ranging from 9.8 to 32.5 µM, while exhibiting no toxicity in animal and human cell lines. Conclusion: These findings represent a significant step forward in the discovery of antischistosomal drugs. Further optimization of these active compounds can pave the way for their progression into preclinical studies.
Palavras-chave
Texto completo:
1
Coleções:
01-internacional
Base de dados:
MEDLINE
Assunto principal:
Esquistossomose
/
Esquistossomicidas
Limite:
Animals
/
Humans
Idioma:
En
Revista:
Future Med Chem
Ano de publicação:
2023
Tipo de documento:
Article
País de afiliação:
Brasil
País de publicação:
Reino Unido