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

Alexandre R F Carvalho; André Melo

doi:10.1002/minf.201000024

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

Mol Inform. 2010 Jul 12;29(6-7):525-31. doi: 10.1002/minf.201000024. Epub 2010 Jul 6.

Authors

Alexandre R F Carvalho¹, André Melo²

Affiliations

¹ REQUIMTE/Chemistry Departament, Faculty of Science, University of Porto. Rua do campo Alegre 867, 4169-007 Porto, Portugal phone/fax: +351 220402503/+351 220402659.
² REQUIMTE/Chemistry Departament, Faculty of Science, University of Porto. Rua do campo Alegre 867, 4169-007 Porto, Portugal phone/fax: +351 220402503/+351 220402659. asmelo@fc.up.pt.

PMID: 27463330
DOI: 10.1002/minf.201000024

Abstract

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 biological 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.

Keywords: 3D-QSAR; Medicinal chemistry; SEEB descriptors; Structure-activity relationships; Trypsin inhibitors.