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In Silico Drug-Designing Studies on Flavanoids as Anticolon Cancer Agents: Pharmacophore Mapping, Molecular Docking, and Monte Carlo Method-Based QSAR Modeling | Interdisciplinary Sciences: Computational Life Sciences
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In silico molecular modeling studies were carried out on some newly synthesized flavanoid analogues. Search for potential targets for these compounds was performed using pharmacophore-mapping algorithm employing inverse screening of some representative compounds to a large set of pharmacophore models constructed from human target proteins. Further, molecular docking studies were carried out to assess binding affinity of these compounds to proteins mediating tumor growth. In vitro anticancer studies were carried out on colon cancer cell lines (HCT116) to assess validity of this approach for target identification of the new compounds. Further important structural features of compounds for anticolon cancer activity were assessed using Monte Carlo-based SMILES and hydrogen graph-Based QSAR studies. In conclusion this study have depicted successful and stepwise application of pharmacophore mapping, molecular docking, and QSAR studies in target identification and lead optimization of flavonoids.
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headline:In Silico Drug-Designing Studies on Flavanoids as Anticolon Cancer Agents: Pharmacophore Mapping, Molecular Docking, and Monte Carlo Method-Based QSAR Modeling
description:In silico molecular modeling studies were carried out on some newly synthesized flavanoid analogues. Search for potential targets for these compounds was performed using pharmacophore-mapping algorithm employing inverse screening of some representative compounds to a large set of pharmacophore models constructed from human target proteins. Further, molecular docking studies were carried out to assess binding affinity of these compounds to proteins mediating tumor growth. In vitro anticancer studies were carried out on colon cancer cell lines (HCT116) to assess validity of this approach for target identification of the new compounds. Further important structural features of compounds for anticolon cancer activity were assessed using Monte Carlo-based SMILES and hydrogen graph-Based QSAR studies. In conclusion this study have depicted successful and stepwise application of pharmacophore mapping, molecular docking, and QSAR studies in target identification and lead optimization of flavonoids.
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description:In silico molecular modeling studies were carried out on some newly synthesized flavanoid analogues. Search for potential targets for these compounds was performed using pharmacophore-mapping algorithm employing inverse screening of some representative compounds to a large set of pharmacophore models constructed from human target proteins. Further, molecular docking studies were carried out to assess binding affinity of these compounds to proteins mediating tumor growth. In vitro anticancer studies were carried out on colon cancer cell lines (HCT116) to assess validity of this approach for target identification of the new compounds. Further important structural features of compounds for anticolon cancer activity were assessed using Monte Carlo-based SMILES and hydrogen graph-Based QSAR studies. In conclusion this study have depicted successful and stepwise application of pharmacophore mapping, molecular docking, and QSAR studies in target identification and lead optimization of flavonoids.
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