00602nas a2200121 4500008004100000022001400041245009900055210006900154260008500223490000800308100003300316856013100349 2011 eng d a0065-772700aComputer vision based chemical information extraction from digital images and streaming videos0 aComputer vision based chemical information extraction from digit a1155 16th ST, NW, Washington, DC 20036 USAbAmerican-Chemical-Society (ACS)cAUG0 v2421 aKarthikeyan, Muthukumarasamy uhttps://library.ncl.res.in/content/computer-vision-based-chemical-information-extraction-digital-images-and-streaming-videos-000658nas a2200133 4500008004100000022001400041245012400055210006900179260007900248300003000327490000800357100003300365856012600398 2014 eng d a0065-772700aChemInfoCloud: opensource based cloud compatible chemical textmining tools for harvesting largescale medical literature0 aChemInfoCloud opensource based cloud compatible chemical textmin a1155 16th ST, NW, Washington, DC 20036 USAbAmerican Chemical SocietycAUG aMeeting Abstract: 69-CINF0 v2481 aKarthikeyan, Muthukumarasamy uhttps://library.ncl.res.in/content/cheminfocloud-opensource-based-cloud-compatible-chemical-textmining-tools-harvesting-001999nas a2200133 4500008004100000245008800041210006900129260002000198300001100218520147600229100003301705700001501738856011201753 2014 eng d00aChemoinformatics approach for the design and screening of focused virtual libraries0 aChemoinformatics approach for the design and screening of focuse aIndiabSpringer a93-1313 a

It is challenging to handle a large volume of molecular data without appropriate tools. Here, we describe the need and the approaches for the development of focussed virtual libraries to design efficient molecules and optimize them for lead generation. The experimental chemists and biologists are more interested in properties of chemicals and their response to biological system in both beneficial and adverse effects context rather than just their structures. In this chapter, the focus is to relate newly designed chemical structures to their predicted activity, property or toxicity. Property prediction tools save time, money and lives of experimental animals. They come in handy while taking informed decisions especially in certain cases involving pharmacodynamic studies of drug molecules in humans where there are inevitable ethical and safety concerns. Property prediction is an important component in virtual screening which is at the heart of drug design and the most important step where chemoinformatics plays a major role. The other fields where structure–activity relation-based principles hold good for virtual screening are agrochemicals and environmental science, specifically the toxicity and biodegradability prediction of pollutant molecules. In this chapter, we will show how to design software tools to handle generation of focussed virtual libraries from a given set of molecules with common features, fragments or bioactivity spectrum.

1 aKarthikeyan, Muthukumarasamy1 aVyas, Renu uhttps://library.ncl.res.in/content/chemoinformatics-approach-design-and-screening-focused-virtual-libraries02142nas a2200265 4500008004100000022001400041245008400055210006900139260011100208300001200319490000700331520120300338653002101541653001601562653001101578653002001589100003301609700001901642700002001661700001801681700001801699700001501717700003201732856011201764 2015 eng d a1386-207300aChemoinformatics approach for building molecular networks from marine organisms0 aChemoinformatics approach for building molecular networks from m aEXECUTIVE STE Y-2, PO BOX 7917, SAIF ZONE, 1200 BR SHARJAH, U ARAB EMIRATESbBENTHAM SCIENCE PUBL LTDcJAN a673-6840 v183 a

Natural products obtained from marine sources are considered to be a rich and diverse source of potential drugs. In the present work we demonstrate the use of chemoinformatics approach for the design of new molecules inspired by molecules from marine organisms. Accordingly we have assimilated information from two major scientific domains namely chemoinformatics and biodiversity informatics to develop an interactive marine database named MIMMO (Medicinally Important Molecules from Marine Organisms). The database can be queried for species, molecules, scaffolds, drugs, diseases and associated cumulative biological activity spectrum along with links to the literature resources. Molecular informatics analysis of the molecules obtained from MIMMO was performed to study their chemical space. The distinct skeletal features of the biologically active compounds isolated from marine species were identified. Scaffold molecules and species networks were created to identify common scaffolds from marine source and drug space. An analysis of the entire molecular data revealed a unique list of around 2000 molecules from which ten most frequently occurring distinct scaffolds were obtained.

10aChemoinformatics10aDrug design10amarine10avirtual library1 aKarthikeyan, Muthukumarasamy1 aNimje, Deepika1 aPahujani, Rakhi1 aTyagi, Kushal1 aBapat, Sanket1 aVyas, Renu1 aPadmakumar, Krishna, Pillai uhttps://library.ncl.res.in/content/chemoinformatics-approach-building-molecular-networks-marine-organisms-002120nas 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-002148nas a2200145 4500008004100000245008700041210006900128260000800197300002300205490000600228520160700234100003301841700001501874856011301889 2016 eng d00aChemEngine: harvesting 3D chemical structures of supplementary data from PDF files0 aChemEngine harvesting 3D chemical structures of supplementary da cDEC aArticle Number: 730 v83 aDigital access to chemical journals resulted in a vast array of molecular information that is now available in the supplementary material files in PDF format. However, extracting this molecular information, generally from a PDF document format is a daunting task. Here we present an approach to harvest 3D molecular data from the supporting information of scientific research articles that are normally available from publisher's resources. In order to demonstrate the feasibility of extracting truly computable molecules from PDF file formats in a fast and efficient manner, we have developed a Java based application, namely ChemEngine. This program recognizes textual patterns from the supplementary data and generates standard molecular structure data (bond matrix, atomic coordinates) that can be subjected to a multitude of computational processes automatically. The methodology has been demonstrated via several case studies on different formats of coordinates data stored in supplementary information files, wherein ChemEngine selectively harvested the atomic coordinates and interpreted them as molecules with high accuracy. The reusability of extracted molecular coordinate data was demonstrated by computing Single Point Energies that were in close agreement with the original computed data provided with the articles. It is envisaged that the methodology will enable large scale conversion of molecular information from supplementary files available in the PDF format into a collection of ready-to-compute molecular data to create an automated workflow for advanced computational processes.1 aKarthikeyan, Muthukumarasamy1 aVyas, Renu uhttps://library.ncl.res.in/content/chemengine-harvesting-3d-chemical-structures-supplementary-data-pdf-files00591nas a2200109 4500008004100000245012200041210006900163260007400232100003300306700001500339856012700354 2018 eng d00aCCCTK (Compute Cure for Cancer ToolKit) an open source drug discovery platform for design of novel anti-cancer agents0 aCCCTK Compute Cure for Cancer ToolKit an open source drug discov aNew Orleans, LAbACS, 1155 16TH ST, NW, Washington, DC 20036 USAcMAR1 aKarthikeyan, Muthukumarasamy1 aVyas, Renu uhttps://library.ncl.res.in/content/ccctk-compute-cure-cancer-toolkit-open-source-drug-discovery-platform-design-novel-anti00512nas a2200097 4500008004100000245009700041210006900138260005400207100003300261856012000294 2018 eng d00aCCCTK: High performance molecular informatics toolkit for the design of anti-cancer molecule0 aCCCTK High performance molecular informatics toolkit for the des a Boston, MAbAmerican-Chemical-Society (ACS)cAUG1 aKarthikeyan, Muthukumarasamy uhttps://library.ncl.res.in/content/ccctk-high-performance-molecular-informatics-toolkit-design-anti-cancer-molecule02768nas 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