Chemoinformatics for medicinal chemistry: in silico model to enable the discovery of potent and safer anti-cocci agents

• Tipo: Artigo em Revista Científica Internacional
• Data: 2014

Autores

Alejandro Planche (Autor) FCUP; Maria Natália Cordeiro (Autor) FCUP

Revista

Título: Future Medicinal Chemistry

Vol. 6

Páginas: 2013-2028

ISSN: 1756-8919

Editora: Future Medicine Ltd.

Indexação

ISI Web of Knowledge - 23 Citações

Scopus - 19 Citações

Classificação Científica

CORDIS: Ciências Físicas > Química > Química computacional

FOS: Ciências exactas e naturais > Química

Outras Informações

ID Authenticus: P-00A-378

DOI: 10.4155/fmc.14.136

Abstract (EN): Background: Gram-positive cocci are increasingly antibiotic-resistant bacteria responsible for causing serious diseases. Chemoinformatics can help to rationalize the discovery of more potent and safer antibacterial drugs. We have developed a chemoinformatic model for simultaneous prediction of anti-cocci activities, and profiles involving absorption, distribution, metabolism, elimination and toxicity (ADMET). Results: A dataset containing 48,874 cases from many different chemicals assayed under dissimilar experimental conditions was created. The best model displayed accuracies around 93% in both training and prediction (test) sets. Quantitative contributions of several fragments to the biological effects were calculated and analyzed. Multiple biological effects of the investigational drug JNJ-Q2 were correctly predicted. Conclusion: Our chemoinformatic model can be used as powerful tool for virtual screening of promising anti-cocci agents.

Idioma: Inglês

Tipo (Avaliação Docente): Científica

Nº de páginas: 16