Fragment-based QSAR model toward the selection of versatile anti-sarcoma leads

• Tipo: Artigo em Revista Científica Internacional
• Data: 2011

Autores

Alejandro Speck Planche (Autor) Outra; Valeria V Kleandrova (Autor) Outra; Feng Luan (Autor) Outra; Natalia N D S Cordeiro (Autor) FCUP

Revista

Título: European Journal of Medicinal Chemistry

Vol. 46 Nº 1

Páginas: 5910-5916

ISSN: 0223-5234

Editora: Elsevier

Indexação

ISI Web of Knowledge - 49 Citações

Scopus - 50 Citações

Classificação Científica

FOS: Ciências médicas e da saúde > Medicina básica

Outras Informações

ID Authenticus: P-002-J76

DOI: 10.1016/j.ejmech.2011.09.055

Abstract (EN): A sarcoma is a type of cancer which is originated from the connective tissue cells. With the time, several sarcomas have become resistant to the current anti-tumoral drugs. Many works have been reported in order to explain some mechanisms of resistance in different types of sarcomas and around 2000 compounds have been tested as anti-sarcoma agents against several sarcoma cell lines. However, there is no an available methodology for the rational design of compounds with anti-sarcoma activity. The present work develops a unified fragment-based approach by employing a multi-target QSAR model for the efficient search and design of new anti-sarcoma agents against 12 sarcoma cell lines. The model was obtained with the use of a heterogeneous database of compounds and it was based on substructural descriptors. The percentages of correct classification of active and inactive compounds were higher than 85% in both cases. Also, the present approach provided the rapid extraction of substructural alerts responsible of anti-sarcoma profile by calculating the quantitative contributions of fragments to anti-sarcoma activity. To our knowledge, this is the first attempt to calculate the probabilities of anti-sarcoma activity of compounds against several sarcoma cell lines simultaneously, using a unified fragment-based QSAR model.

Idioma: Inglês

Tipo (Avaliação Docente): Científica

Nº de páginas: 7