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• W2801362520 abstract "Abstract A revolutionary change in conventional methods of testing bioactivity of plant materials has taken place with the intervention of computing. The computer-aided tools have significantly reduced the time necessary for bioactivity assessments. Quick and cost-effective prediction of biological activity of plant materials is now possible based on physicochemical properties. Although Computer-Aided Drug Discovery (CADD) has emerged as a broad subject in the field of medicinal plants research, computational molecular docking and computational target fishing are the specific techniques applied in this field. Above all, Artificial Neural Networks (ANNs) have become one of the latest techniques for direct prediction of a specific property of specific bio-molecules. This chapter, utilizing a specific example, describes how ANNs could be used to predict possible biological activity of a few drug molecules using computational tools. Results obtained from ANNs have been cross-validated using molecular docking technique. Six gossypol derivatives, whose biological activities have not been studied before, were taken for the study. Their physicochemical properties were considered as input and biological activities as output. Chemical descriptors and their respective biological activities of a number of compounds were recorded from NCBI PubChem compound database. The data were divided into 70% and 30% as training set and test set, respectively. On successful validation of the training by adjusting different layers and nodes of ANNs and after setting out final networks, descriptors of six unknown gossypol derivatives were used as experimental set for prediction of their bioactivity. Based on ANNs prediction, out of the six, three derivatives, whose predicted biological activities were the same, were taken for finding their activity using BiosolveIT FlexX 1.3.0 software to cross validate the prediction of ANNs. It was observed that ANN prediction for contraceptive activity of gossylic lactone, gossypol tetra acetic acid, and gossypol-6,6'-dimethyl ether matched with cross validation result obtained from BiosolveIT FlexX 1.3.0. The cross validation study also suggested that by inhibiting acrosin and hyaluronidase enzymes, these three derivatives might exert contraceptive activity." @default.
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• W2801362520 date "2018-01-01" @default.
• W2801362520 modified "2023-09-23" @default.
• W2801362520 title "Virtual Screening of Phytochemicals" @default.
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• W2801362520 doi "https://doi.org/10.1016/b978-0-12-812364-5.00011-0" @default.
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