02219nas a2200253   4500008004100000022001400041245006500055210006500120260011100185300001200296490000700308520137700315653001401692653001101706653001201717653001401729653001401743653002101757653002201778100003301800700001901833700001501852856009801867       2015                        eng d  a1386-207300aProtein ligand complex guided approach for virtual screening0 aProtein ligand complex guided approach for virtual screening  aEXECUTIVE STE Y-2, PO BOX 7917, SAIF ZONE, 1200 BR SHARJAH, U ARAB EMIRATESbBENTHAM SCIENCE PUBL LTDcJAN  a577-5900 v183 a<p>The target ligand association data is a rich source of information which is not exploited enough for drug design efforts in virtual screening. A java based open-source toolkit for Protein Ligand Network Extraction (J-ProLiNE) focused on protein-ligand complex analysis with several features integrated in a distributed computing network has been developed. Sequence alignment and similarity search components have been automated to yield local, global alignment scores along with similarity and distance scores. 10000 proteins with co-crystallized ligands from pdb and MOAD databases were extracted and analyzed for revealing relationships between targets, ligands and scaffolds. Through this analysis, we could generate a protein ligand network to identify the promiscuous and selective scaffolds for multiple classes of proteins targets. Using J-ProLiNE we created a 507 x 507 matrix of protein targets and native ligands belonging to six enzyme classes and analyzed the results to elucidate the protein-protein, protein-ligand and ligand-ligand interactions. In yet another application of the J-ProLiNE software, we were able to process kinase related information stored in US patents to construct disease-gene-ligand-scaffold networks. It is hoped that the studies presented here will enable target ligand knowledge based virtual screening for inhibitor design.</p>10aComplexes10aligand10aprotein10ascaffolds10asequences10asimilarity score10avirtual screening1 aKarthikeyan, Muthukumarasamy1 aPandit, Deepak1 aVyas, Renu  uhttps://library.ncl.res.in/content/protein-ligand-complex-guided-approach-virtual-screening-003539nas a2200289   4500008004100000022001400041245013400055210006900189260000800258300001400266490000700280520258100287653001002868653002102878653001602899653001402915653001602929653002202945653002202967100001802989700002803007700002003035700001503055700001803070700003303088856012803121       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  uhttps://library.ncl.res.in/content/design-novel-drug-molecules-using-informatics-rich-secondary-metabolites-analysis-indian