Quantum Semiempirical Energy Based (SEEB) Descriptors Performance with Benzamidine Inhibitors of Trypsin
✍ Scribed by Alexandre R. F. Carvalho; André Melo
- Publisher
- Wiley (John Wiley & Sons)
- Year
- 2010
- Tongue
- English
- Weight
- 368 KB
- Volume
- 29
- Category
- Article
- ISSN
- 1868-1743
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✦ Synopsis
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.