Programs
- M. Tech. in Automotive Engineering -
- Clinical Fellowship in Laboratory Genetics & Genomics - Fellowship
Publication Type : Journal Article
Thematic Areas : Nanosciences and Molecular Medicine
Publisher : Molecular Informatics
Source : Molecular Informatics, Volume 30, Number 8, p.689-706 (2011)
Url : https://onlinelibrary.wiley.com/doi/abs/10.1002/minf.201100029
Keywords : AChE, ANN, Docking, G/PLS, GFA, QSAR, SVM
Campus : Kochi
School : Center for Nanosciences
Center : Amrita Center for Nanosciences and Molecular Medicine Move, Nanosciences
Department : Nanosciences and Molecular Medicine
Year : 2011
Abstract : Recently discovered 42 AChE inhibitors binding at the catalytic and peripheral anionic site were identified on the basis of molecular docking approach, and its comparative quantitative structure–activity relationship (QSAR) models were developed. These structurally diverse inhibitors were obtained by our previously reported high-throughput in vitro screening technique using 384-well plate’s assay based on colorimetric method of Ellman. QSAR models were developed using (i) genetic function algorithm, (ii) genetic partial least squares, (iii) support vector machine and (iv) artificial neural network techniques. The QSAR model robustness and significance was critically assessed using different cross-validation techniques on test data set. The generated QSAR models using thermodynamic, electrotopological and electronic descriptors showed that nonlinear methods are more robust than linear methods, and provide insight into the structural features of compounds that are important for AChE inhibition.
Cite this Research Publication : S. Gupta, Fallarero, A., Vainio, M. J., Saravanan, P., J. Puranen, S., Järvinen, P., Johnson, M. S., Vuorela, P. M., and Dr. Gopi Mohan C., “Molecular Docking Guided Comparative GFA, G/PLS, SVM and ANN Models of Structurally Diverse Dual Binding Site Acetylcholinesterase Inhibitors”, Molecular Informatics, vol. 30, pp. 689-706, 2011.