02120nas a2200217 4500008004100000022001400041245008400055210006900139260011100208300001200319490000700331520128100338653002401619653002501643653003101668653002201699100003301721700001901754700001501773856011401788 2015 eng d a1386-207300aChemScreener: a distributed computing tool for scaffold based virtual screening0 aChemScreener a distributed computing tool for scaffold based vir aEXECUTIVE STE Y-2, PO BOX 7917, SAIF ZONE, 1200 BR SHARJAH, U ARAB EMIRATESbBENTHAM SCIENCE PUBL LTDcJAN a544-5610 v183 a

In this work we present ChemScreener, a Java-based application to perform virtual library generation combined with virtual screening in a platform-independent distributed computing environment. ChemScreener comprises a scaffold identifier, a distinct scaffold extractor, an interactive virtual library generator as well as a virtual screening module for subsequently selecting putative bioactive molecules. The virtual libraries are annotated with chemophore-, pharmacophore- and toxicophore-based information for compound prioritization. The hits selected can then be further processed using QSAR, docking and other in silico approaches which can all be interfaced within the ChemScreener framework. As a sample application, in this work scaffold selectivity, diversity, connectivity and promiscuity towards six important therapeutic classes have been studied. In order to illustrate the computational power of the application, 55 scaffolds extracted from 161 anti-psychotic compounds were enumerated to produce a virtual library comprising 118 million compounds (17 GB) and annotated with chemophore, pharmacophore and toxicophore based features in a single step which would be non-trivial to perform with many standard software tools today on libraries of this size.

10aScaffold extraction10atherapeutic category10avirtual library generation10avirtual screening1 aKarthikeyan, Muthukumarasamy1 aPandit, Deepak1 aVyas, Renu uhttps://library.ncl.res.in/content/chemscreener-distributed-computing-tool-scaffold-based-virtual-screening-002057nas a2200289 4500008004100000022001400041245010400055210006900159260011100228300001200339490000700351520101200358653002101370653002001391653002101411653002201432653001101454653002301465653002301488653001601511653002201527100003301549700001901582700002101601700001501622856013001637 2015 eng d a1386-207300aDesign and development of cheminfocloud: an integrated cloud enabled platform for virtual screening0 aDesign and development of cheminfocloud an integrated cloud enab aEXECUTIVE STE Y-2, PO BOX 7917, SAIF ZONE, 1200 BR SHARJAH, U ARAB EMIRATESbBENTHAM SCIENCE PUBL LTDcJAN a604-6190 v183 a

The power of cloud computing and distributed computing has been harnessed to handle vast and heterogeneous data required to be processed in any virtual screening protocol. A cloud computing platorm ChemInfoCloud was built and integrated with several chemoinformatics and bioinformatics tools. The robust engine performs the core chemoinformatics tasks of lead generation, lead optimisation and property prediction in a fast and efficient manner. It has also been provided with some of the bioinformatics functionalities including sequence alignment, active site pose prediction and protein ligand docking. Text mining, NMR chemical shift (1H, 13C) prediction and reaction fingerprint generation modules for efficient lead discovery are also implemented in this platform. We have developed an integrated problem solving cloud environment for virtual screening studies that also provides workflow management, better usability and interaction with end users using container based virtualization, OpenVz.

10aChemoinformatics10acloud computing10amachine learning10aMolecular docking10aOpenVz10asequence alignment10aspectra prediction10atext mining10avirtual screening1 aKarthikeyan, Muthukumarasamy1 aPandit, Deepak1 aBhavasar, Arvind1 aVyas, Renu uhttps://library.ncl.res.in/content/design-and-development-cheminfocloud-integrated-cloud-enabled-platform-virtual-screening-002426nas a2200241 4500008004100000022001400041245012700055210006900182260011100251300001200362490000700374520149700381653002101878653002001899653001201919653001601931653002201947100003301969700001902002700001902021700001502040856012902055 2015 eng d a1386-207300aMegaMiner: a tool for lead identification through text mining using chemoinformatics tools and cloud computing environment0 aMegaMiner a tool for lead identification through text mining usi aEXECUTIVE STE Y-2, PO BOX 7917, SAIF ZONE, 1200 BR SHARJAH, U ARAB EMIRATESbBENTHAM SCIENCE PUBL LTDcJAN a591-6030 v183 a

Virtual screening is an indispensable tool to cope with the massive amount of data being tossed by the high throughput omics technologies. With the objective of enhancing the automation capability of virtual screening process a robust portal termed MegaMiner has been built using the cloud computing platform wherein the user submits a text query and directly accesses the proposed lead molecules along with their drug-like, lead-like and docking scores. Textual chemical structural data representation is fraught with ambiguity in the absence of a global identifier. We have used a combination of statistical models, chemical dictionary and regular expression for building a disease specific dictionary. To demonstrate the effectiveness of this approach, a case study on malaria has been carried out in the present work. MegaMiner offered superior results compared to other text mining search engines, as established by F score analysis. A single query term `malaria' in the portlet led to retrieval of related PubMed records, protein classes, drug classes and 8000 scaffolds which were internally processed and filtered to suggest new molecules as potential anti-malarials. The results obtained were validated by docking the virtual molecules into relevant protein targets. It is hoped that MegaMiner will serve as an indispensable tool for not only identifying hidden relationships between various biological and chemical entities but also for building better corpus and ontologies.

10aChemoinformatics10acloud computing10amalaria10atext mining10avirtual screening1 aKarthikeyan, Muthukumarasamy1 aPandit, Yogesh1 aPandit, Deepak1 aVyas, Renu uhttps://library.ncl.res.in/content/megaminer-tool-lead-identification-through-text-mining-using-chemoinformatics-tools-and-001949nas a2200229 4500008004100000022001400041245007300055210006900128260011100197300001200308490000700320520110300327653001901430653001701449653000801466653002501474653002201499100003301521700004301554700001501597856010701612 2015 eng d a1386-207300aPrediction of bioactive compounds using computed NMR chemical shifts0 aPrediction of bioactive compounds using computed NMR chemical sh aEXECUTIVE STE Y-2, PO BOX 7917, SAIF ZONE, 1200 BR SHARJAH, U ARAB EMIRATESbBENTHAM SCIENCE PUBL LTDcJAN a562-5760 v183 a

NMR based chemical shifts are an important diagnostic parameter for structure elucidation as they capture rich information related to conformational, electronic and stereochemical arrangement of functional groups in a molecule which is responsible for its activity towards any biological target. The present work discusses the importance of computing NMR chemical shifts from molecular structures. The NMR chemical shift data (experimental or computed) was used to generate fingerprints in binary formats for mapping molecular fragments (as descriptors) and correlating with the bioactivity classes. For this study, chemical shift data derived binary fingerprints were computed for 149 classes and 4800 bioactive molecules. The sensitivity and selectivity of fingerprints in discriminating molecules belonging to different therapeutic categories was assessed using a LibSVM based classifier. An accuracy of 82% for proton and 94% for carbon NMR fingerprints were obtained for anti-psoriatic and anti-psychotic molecules demonstrating the effectiveness of this approach for virtual screening.

10aChemical shift10afingerprints10aNMR10asimilarity searching10avirtual screening1 aKarthikeyan, Muthukumarasamy1 aRajamohanan, Pattuparambil, Ramanpilla1 aVyas, Renu uhttps://library.ncl.res.in/content/prediction-bioactive-compounds-using-computed-nmr-chemical-shifts-002219nas 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

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.

10aComplexes10aligand10aprotein10ascaffolds10asequences10asimilarity score10avirtual screening1 aKarthikeyan, Muthukumarasamy1 aPandit, Deepak1 aVyas, Renu uhttps://library.ncl.res.in/content/protein-ligand-complex-guided-approach-virtual-screening-002540nas a2200301 4500008004100000022001400041245008400055210006900139260011100208300001200319490000700331520149700338653001701835653001801852653002301870653002301893653002401916653001301940653001401953653001401967653002201981100003302003700001502036700002302051700002402074700002602098856011402124 2015 eng d a1386-207300aRole of chemical reactivity and transition state modeling for virtual screening0 aRole of chemical reactivity and transition state modeling for vi aEXECUTIVE STE Y-2, PO BOX 7917, SAIF ZONE, 1200 BR SHARJAH, U ARAB EMIRATESbBENTHAM SCIENCE PUBL LTDcJAN a638-6570 v183 a

Every drug discovery research program involves synthesis of a novel and potential drug molecule utilizing atom efficient, economical and environment friendly synthetic strategies. The current work focuses on the role of the reactivity based fingerprints of compounds as filters for virtual screening using a tool ChemScore. A reactant-like (RLS) and a product-like (PLS) score can be predicted for a given compound using the binary fingerprints derived from the numerous known organic reactions which capture the molecule-molecule interactions in the form of addition, substitution, rearrangement, elimination and isomerization reactions. The reaction fingerprints were applied to large databases in biology and chemistry, namely ChEMBL, KEGG, HMDB, DSSTox, and the Drug Bank database. A large network of 1113 synthetic reactions was constructed to visualize and ascertain the reactant product mappings in the chemical reaction space. The cumulative reaction fingerprints were computed for 4000 molecules belonging to 29 therapeutic classes of compounds, and these were found capable of discriminating between the cognition disorder related and anti-allergy compounds with reasonable accuracy of 75% and AUC 0.8. In this study, the transition state based fingerprints were also developed and used effectively for virtual screening in drug related databases. The methodology presented here provides an efficient handle for the rapid scoring of molecular libraries for virtual screening.

10afingerprints10aintermediates10ametabolic pathways10aproduct-like score10areactant-like score10areaction10ascreening10asynthesis10avirtual screening1 aKarthikeyan, Muthukumarasamy1 aVyas, Renu1 aTambe, Sanjeev, S.1 aRadhamohan, Deepthi1 aKulkarni, Bhaskar, D. uhttps://library.ncl.res.in/content/role-chemical-reactivity-and-transition-state-modeling-virtual-screening-002126nas a2200217 4500008004100000022001400041245008400055210006900139260011100208300001200319490000700331520132700338653002101665653001201686653001601698653001301714653002201727100003301749700001501782856011101797 2015 eng d a1386-207300aRole of open source tools and resources in virtual screening for drug discovery0 aRole of open source tools and resources in virtual screening for aEXECUTIVE STE Y-2, PO BOX 7917, SAIF ZONE, 1200 BR SHARJAH, U ARAB EMIRATESbBENTHAM SCIENCE PUBL LTDcJUL a528-5430 v183 a

Advancement in chemoinformatics research in parallel with availability of high performance computing platform has made handling of large scale multi-dimensional scientific data for high throughput drug discovery easier. In this study we have explored publicly available molecular databases with the help of open-source based integrated in-house molecular informatics tools for virtual screening. The virtual screening literature for past decade has been extensively investigated and thoroughly analyzed to reveal interesting patterns with respect to the drug, target, scaffold and disease space. The review also focuses on the integrated chemoinformatics tools that are capable of harvesting chemical data from textual literature information and transform them into truly computable chemical structures, identification of unique fragments and scaffolds from a class of compounds, automatic generation of focused virtual libraries, computation of molecular descriptors for structure-activity relationship studies, application of conventional filters used in lead discovery along with in-house developed exhaustive PTC (Pharmacophore, Toxicophores and Chemophores) filters and machine learning tools for the design of potential disease specific inhibitors. A case study on kinase inhibitors is provided as an example.

10aChemoinformatics10akinases10aopen source10ascaffold10avirtual screening1 aKarthikeyan, Muthukumarasamy1 aVyas, Renu uhttps://library.ncl.res.in/content/role-open-source-tools-and-resources-virtual-screening-drug-discovery-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

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.

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-indian02768nas a2200265 4500008004100000022001400041245013800055210006900193260000900262300001400271490000700285520182600292653002702118653002102145653002202166653003002188653004202218653002202260100002002282700002002302700000502322700003302327700001502360856012702375 2023 eng d a0739-110200aComprehensive molecular docking and dynamic simulations for drug repurposing of clinical drugs against multiple cancer kinase targets0 aComprehensive molecular docking and dynamic simulations for drug cNOV  a7735-77430 v413 a

Drug repurposing is a method to identify novel therapeutic agents from the existing drugs and clinical compounds. In the present comprehensive work, molecular docking, virtual screening and dynamics simulations were carried out for ten cancer types viz breast, colon, central nervous system, leukaemia, melanoma, ovarian, prostate, renal and lung (non-small and small cell) against validated eighteen kinase targets. The study aims to understand the action of chemotherapy drugs mechanism through binding interactions against selected targets via comparative docking simulations with the state-art molecular modelling suits such as MOE, Cresset-Flare, AutoDock Vina, GOLD and GLIDE. Chemotherapeutic drugs (n = 112) were shortlisted from standard drug databases with appropriate chemoinformatic filters. Based on docking studies it was revealed that leucovorin, nilotinib, ellence, thalomid and carfilzomib drugs possessed potential against other cancer targets. A library was built to enumerate novel molecules based on the scaffold and functional groups extracted from known drugs and clinical compounds. Twenty novel molecules were prioritised further based on drug-like attributes. These were cross docked against 1MQ4 Aurora-A Protein Kinase for prostate cancer and 4UYA Mitogen-activated protein kinase for renal cancer. All docking programs yielded similar results but interestingly AutoDock Vina yielded the lowest RMSD with the native ligand. To further validate the final docking results at atomistic level, molecular dynamics simulations were performed to ascertain the stability of the protein-ligand complex. The study enables repurposing of drugs and lead identification by employing a host of structure and ligand based virtual screening tools and techniques. Communicated by Ramaswamy H. Sarma

10achemotherapeutic drugs10aDrug repurposing10aMolecular docking10amolecular simulation (MD)10astructure-based drug designing (SBDD)10avirtual screening1 aShaikh, Nilofer1 aLinthoi, R., K.1 a1 aKarthikeyan, Muthukumarasamy1 aVyas, Renu uhttps://library.ncl.res.in/content/comprehensive-molecular-docking-and-dynamic-simulations-drug-repurposing-clinical-drugs