Computational Intelligence in Drug Discovery
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This book spotlights on the application of computational techniques to analyze the dengue virus protein to find a potent inhibitor to block the growth of the virus. It presents a systematic approach for analyzing dengue NS2B/NS3 protease structure with a focus on the identification of lead molecule by molecular docking and molecular dynamics simulation studies. The lead molecule is further optimized using scaffold hopping studies. This study justifies the utility of novel designed library of compounds as a valuable small- molecule inhibitor for the dengue protein targets. As an extended part o...
This book spotlights on the application of computational techniques to analyze the dengue virus protein to find a potent inhibitor to block the growth of the virus. It presents a systematic approach for analyzing dengue NS2B/NS3 protease structure with a focus on the identification of lead molecule by molecular docking and molecular dynamics simulation studies. The lead molecule is further optimized using scaffold hopping studies. This study justifies the utility of novel designed library of compounds as a valuable small- molecule inhibitor for the dengue protein targets. As an extended part of this research, the dengue-human protein interaction is predicted using artificial neural network techniques to find a better drug target for the dengue protein. As a final part of this research, an analytic framework was proposed that integrates the computer-aided drug design tools, biological data sources, and machine learning algorithms within a framework. Hence it is concluded that advancement in computational approaches can contribute better and ease the drug discoveryprocess.
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