@article { ISI:000360934400007, title = {Design and development of cheminfocloud: an integrated cloud enabled platform for virtual screening}, journal = {Combinatorial Chemistry \& High Throughput Screening}, volume = {18}, number = {6}, year = {2015}, month = {JAN}, pages = {604-619}, publisher = {BENTHAM SCIENCE PUBL LTD}, address = {EXECUTIVE STE Y-2, PO BOX 7917, SAIF ZONE, 1200 BR SHARJAH, U ARAB EMIRATES}, abstract = {

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.

}, keywords = {Chemoinformatics, cloud computing, machine learning, Molecular docking, OpenVz, sequence alignment, spectra prediction, text mining, virtual screening}, issn = {1386-2073}, doi = {10.2174/1386207318666150703113656}, author = {Karthikeyan, Muthukumarasamy and Pandit, Deepak and Bhavasar, Arvind and Vyas, Renu} } @article {48370, title = {BESFA: bioinformatics based evolutionary, structural \& functional analysis of prostate, Placenta, Ovary, Testis, and Embryo (POTE) paralogs}, journal = {Heliyon}, volume = {8}, year = {2022}, month = {SEP}, pages = {e10476}, type = {Article}, abstract = {

The POTE family comprises 14 paralogues and is primarily expressed in Prostate, Placenta, Ovary, Testis, Embryo (POTE), and cancerous cells. The prospective function of the POTE protein family under physiological conditions is less understood. We systematically analyzed their cellular localization and molecular docking analysis to elucidate POTE proteins{\textquoteright} structure, function, and Adaptive Divergence. Our results suggest that group three POTE paralogs (POTEE, POTEF, POTEI, POTEJ, and POTEKP (a pseudogene)) exhibits significant variation among other members could be because of their Adaptive Divergence. Furthermore, our molecular docking studies on POTE protein revealed the highest binding affinity with NCI-approved anticancer compounds. Additionally, POTEE, POTEF, POTEI, and POTEJ were subject to an explicit molecular dynamic simulation for 50ns. MM-GBSA and other essential electrostatics were calculated that showcased that only POTEE and POTEF have absolute binding affinities with minimum energy exploitation. Thus, this study{\textquoteright}s outcomes are expected to drive cancer research to successful utilization of POTE genes family as a new biomarker, which could pave the way for the discovery of new therapies.

}, keywords = {(MMGBSA), Adaptive divergence, Evolution, generalized born surface area, Homology, Mechanics, Molecular docking, Molecular dynamic simulation molecular, POTE paralogs}, doi = {10.1016/j.heliyon.2022.e10476}, author = {Qazi, Sahar and Jit, Bimal Prasad and Das, Abhishek and Karthikeyan, Muthukumarasamy and Saxena, Amit and Ray, M. D. and Singh, Angel Rajan and Raza, Khalid and Jayaram, B. and Sharma, Ashok} } @article {49130, title = {Comprehensive molecular docking and dynamic simulations for drug repurposing of clinical drugs against multiple cancer kinase targets}, journal = {Journal of Biomolecular Structure and Dynamics}, volume = {41}, year = {2023}, month = {NOV }, pages = {7735-7743}, type = {Article}, abstract = {

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

}, keywords = {chemotherapeutic drugs, Drug repurposing, Molecular docking, molecular simulation (MD), structure-based drug designing (SBDD), virtual screening}, issn = {0739-1102}, doi = {10.1080/07391102.2022.2124453}, author = {Shaikh, Nilofer and Linthoi, R. K. and Swamy, V, K. and Karthikeyan, Muthukumarasamy and Vyas, Renu} }