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M.  Karthikeyan, Pandit, D., and Vyas, R., ?ChemScreener: a distributed computing tool for scaffold based virtual screening?, Combinatorial Chemistry & High Throughput Screening, vol. 18, no. 6, pp. 544-561, 2015.\par \par M.  Karthikeyan, Pandit, D., Bhavasar, A., and Vyas, R., ?Design and development of cheminfocloud: an integrated cloud enabled platform for virtual screening?, Combinatorial Chemistry & High Throughput Screening, vol. 18, no. 6, pp. 604-619, 2015.\par \par M.  Karthikeyan, Pandit, Y., Pandit, D., and Vyas, R., ?MegaMiner: a tool for lead identification through text mining using chemoinformatics tools and cloud computing environment?, Combinatorial Chemistry & High Throughput Screening, vol. 18, no. 6, pp. 591-603, 2015.\par \par M.  Karthikeyan, Rajamohanan, P. Ramanpilla, and Vyas, R., ?Prediction of bioactive compounds using computed NMR chemical shifts?, Combinatorial Chemistry & High Throughput Screening, vol. 18, no. 6, pp. 562-576, 2015.\par \par M.  Karthikeyan, Pandit, D., and Vyas, R., ?Protein ligand complex guided approach for virtual screening?, Combinatorial Chemistry & High Throughput Screening, vol. 18, no. 6, pp. 577-590, 2015.\par \par M.  Karthikeyan, Vyas, R., Tambe, S. S., Radhamohan, D., and Kulkarni, B. D., ?Role of chemical reactivity and transition state modeling for virtual screening?, Combinatorial Chemistry & High Throughput Screening, vol. 18, no. 7, pp. 638-657, 2015.\par \par M.  Karthikeyan and Vyas, R., ?Role of open source tools and resources in virtual screening for drug discovery?, Combinatorial Chemistry & High Throughput Screening, vol. 18, no. 6, pp. 528-543, 2015.\par \par I. G.  Shibi, Aswathy, L., Jisha, R. S., Masand, V. H., and Gajbhiye, J. M., ?Virtual screening techniques to probe the antimalarial activity of some traditionally used phytochemicals?, Combinatorial Chemistry & High Throughput Screening, vol. 19, no. 7, pp. 572-591, 2016.\par \par D.  Karade, Vijayasarathi, D., Kadoo, N., Vyas, R., Ingle, P. K., and Karthikeyan, M., ?Design of novel drug-like molecules using informatics rich secondary metabolites analysis of Indian medicinal and aromatic plants?, Combinatorial Chemistry & High Throughput Screening, vol. 23, no. 10, pp. 1113-1131, 2020.\par \par N. K.  Gaur, Goyal, V. Durani, Kulkarni, K., and Makde, R. D., ?Machine learning classifiers aid virtual screening for efficient design of mini-protein therapeutics?, Bioorganic & Medicinal Chemistry Letters, vol. 38, p. 127852, 2021.\par \par R. Balasaheb Aher and Sarkar, D., ?Pharmacophore modeling of pretomanid (PA-824) derivatives for antitubercular potency against replicating and non-replicating Mycobacterium tuberculosis?, Journal of Biomolecular Structure & Dynamics, vol. 39, no. 3, pp. 889-900, 2021.\par \par P.  Prakash, Vijayasarathi, D., Selvam, K., Karthi, S., and Manivasagaperumal, R., ?Pharmacore maping based on docking, ADME/toxicity, virtual screening on 3,5-dimethyl-1,3,4-hexanetriol and dodecanoic acid derivates for anticancer inhibitors?, Journal of Biomolecular Structure & Dynamics, vol. 39, no. 12, pp. 4490-4500, 2021.\par \par D.  Karade and Karade, V., ?AIDrugApp: artificial intelligence-based Web-App for virtual screening of inhibitors against SARS-COV-2?, Journal  of Experimental & Thereotical  Artificial  Intelligence , vol. 35, no. 3, pp. 395-443, 2023.\par \par N.  Shaikh, Linthoi, R. K., ,, Karthikeyan, M., and Vyas, R., ?Comprehensive molecular docking and dynamic simulations for drug repurposing of clinical drugs against multiple cancer kinase targets?, Journal of Biomolecular Structure and Dynamics, vol. 41, no. 16, pp. 7735-7743, 2023.\par \par }