Quantum Semiempirical Energy Based (SEEB) Descriptors Performance with Benzamidine Inhibitors of Trypsin

• Tipo: Artigo em Revista Científica Internacional
• Data: 2010

Autores

Alexandre R F Carvalho (Autor) Outra; Andre Melo (Autor) FCUP

Revista

Título: Molecular Informatics

Vol. 29 Nº 3

Páginas: 525-531

ISSN: 1868-1743

Editora: Wiley-Blackwell

Indexação

ISI Web of Knowledge - 1 Citação

Scopus - 1 Citação

Classificação Científica

FOS: Ciências exactas e naturais > Matemática

Outras Informações

ID Authenticus: P-003-5DZ

DOI: 10.1002/minf.201000024

Abstract (EN): MLR is a classical approach to regression problems in QSARs. In this study, the behaviour of SEEB descriptors was analysed with a MLR model. For this purpose a SEEB/MLR 3D-QSAR model was developed to evaluate the efficiency of benzamide trypsin inhibitors. The development of inhibitors of trypsin-like serine proteases has been an active area of research. They are involved in many bio-logical processes like protein digestion and blood coagulation and also serve as a useful model system to study protein-ligand interaction. The regression coefficients, obtained by this procedure, have an intuitively simple and therefore appealing meaning for the relative influence of each amino acid residue to the predictive model. The predictive capability of SEEB is shown to be comparable to those of other QSAR methods.

Idioma: Inglês

Tipo (Avaliação Docente): Científica

Nº de páginas: 7