03538nas a2200289   4500008004100000022001400041245013400055210006900189260000800258300001400266490000700280520258100287653001002868653002102878653001602899653001402915653001602929653002202945653002202967100001802989700002803007700002003035700001503055700001803070700003303088856012703121       2020                        eng d  a1386-207300aDesign of novel drug-like molecules using informatics rich secondary metabolites analysis of Indian medicinal and aromatic plants0 aDesign of novel druglike molecules using informatics rich second  cJAN  a1113-11310 v233 a<p>Background: Several medicinal plants are being used in Indian medicine systems from ancient times. However, in most cases, the specific molecules or the active ingredients responsible for the medicinal or therapeutic properties are not yet known. Objective: This study aimed to report a computational protocol as well as a tool for generating novel potential drug candidates from the bioactive molecules of Indian medicinal and aromatic plants through the chemoinformatics approach. Methods: We built a database of the Indian medicinal and aromatic plants coupled with associated information (plant families, plant parts used for the medicinal purpose, structural information, therapeutic properties, etc.) We also developed a Java-based chemoinformatics open-source tool called DoMINE (Database of Medicinally Important Natural products from plantaE) for the generation of virtual library and screening of novel molecules from known medicinal plant molecules. We employed chemoinformatics approaches to in-silico screened metabolites from 104 Indian medicinal and aromatic plants and designed novel drug-like bioactive molecules. For this purpose, 1665 ring containing molecules were identified by text mining of literature related to the medicinal plant species, which were later used to extract 209 molecular scaffolds. Different scaffolds were further used to build a focused virtual library. Virtual screening was performed with cluster analysis to predict drug-like and lead-like molecules from these plant molecules in the context of drug discovery. The predicted drug-like and lead-like molecules were evaluated using chemoinformatics approaches and statistical parameters, and only the most significant molecules were proposed as the candidate molecules to develop new drugs. Results and Conclusion: The supra network of molecules and scaffolds identifies the relationship between the plant molecules and drugs. Cluster analysis of virtual library molecules showed that novel molecules had more pharmacophoric properties than toxicophoric and chemophoric properties. We also developed the DoMINE toolkit for the advancement of natural product-based drug discovery through chemoinformatics approaches. This study will be useful in developing new drug molecules from the known medicinal plant molecules. Hence, this work will encourage experimental organic chemists to synthesize these molecules based on the predicted values. These synthesized molecules need to be subjected to biological screening to identify potential molecules for drug discovery research.</p>
10aDrugs10amedicinal plants10aMetabolites10ascaffolds10atext mining10avirtual libraries10avirtual screening1 aKarade, Divya1 aVijayasarathi, Durairaj1 aKadoo, Narendra1 aVyas, Renu1 aIngle, P., K.1 aKarthikeyan, Muthukumarasamy  uhttp://library.ncl.res.in/content/design-novel-drug-molecules-using-informatics-rich-secondary-metabolites-analysis-indian02676nas a2200265   4500008004100000022001400041245016300055210006900218260000800287300001400295490000700309520173600316653000902052653002502061653001202086653001902098653001302117653002202130100002402152700002802176700002202204700002102226700003402247856012902281       2021                        eng d  a0739-110200aPharmacore maping based on docking, ADME/toxicity, virtual screening on 3,5-dimethyl-1,3,4-hexanetriol and dodecanoic acid derivates for anticancer inhibitors0 aPharmacore maping based on docking ADMEtoxicity virtual screenin  cJAN  a4490-45000 v393 a<p>Plants produced natural generating products play a significant role in drug discovery of new bioactive compounds and these are used for advancement of innovative curative drugs for specific target health diseases. In this study Docking and ADME/T virtual screening method are apply for in drug discovery and can be divided into ligand- and target structure-based. The aim of this study was to analyze theDecalepis hamiltoniiisolated compounds by using the evaluation of molecular docking and virtual screening of anticancer drugs. MOE docking ADME/Toxicity and virtual screening approaches. A docking energy -12.97 kcal/mol; -9.93- kcal/mol on cancer responsible protein was targeted. Further, the compounds were filtered through the rule of five, ADME/Toxicity risk and synthetic accessibility. The active compound were then docked to recognize the possible target binding pocket to obtain a set of a ligand poses and to prioritize the predicted active compounds. The scrutinize compounds, as well as their metabolites were evaluated for different pharmacokinetics parameter such as ADME/Toxicity. Therefore, the result shows that a large number of compounds were found to be ADME/toxicity positive to be a positive drug molecule against cancer, selected compounds under study satisfies parameters for ADME and Toxicity properties. The present study demonstrate to identifying the novel structures which are having similar structural feature with like activity with respect to the compounds 3,5-Dimethyl-1,3,4-Hexanetriol and Dodecanoic acid that are shown best binding energy with the receptors 4igk and 4b3z respectively. This study may provide significant clues for discovery novel drug inhibitors for cancer properties.</p>10aADME10aDecalepis hamiltonii10adocking10adrug discovery10aToxicity10avirtual screening1 aPrakash, Palanisamy1 aVijayasarathi, Durairaj1 aSelvam, Kuppusamy1 aKarthi, Sengodan1 aManivasagaperumal, Rengarajan  uhttp://library.ncl.res.in/content/pharmacore-maping-based-docking-admetoxicity-virtual-screening-35-dimethyl-134-hexanetriol