Aravindhan Ganesan

Dr. Ganesan is passionate about computational molecular biosciences and drug discovery. His research team focuses on (i) understanding the nature and biophysical processes behind molecular recognition in biological systems; (ii) small molecule therapeutics design for neurodegeneration, cancers, and COVID-19, and (iii) development of new computational tools for in silico structural biology. His research programs on Pharmacology of cannabinoid receptors, hnRNPA1 protein aggregation in multiple sclerosis, and computational drug discovery are supported by Natural Sciences and Engineering Research Council of Canada- Discovery Grant, New Frontiers in Research Fund-Exploration Grant, and Canada First Research Excellence Fund- Transformative Quantum Technologies (CFREF-TQT)-UWaterloo funds, respectively. Dr. Ganesan has published over 35 peer-reviewed papers, submitted a patent application, and made several presentations at international conferences.

• Computational molecular biosciences and drug discovery
• Molecular pharmacology
• Development of new computational tools for structural biology analyses
• Therapeutics design for cancers and neurodegeneration
• Molecular Therapeutics and Theranostics
• Drug Discovery, Design and Delivery
• Bioinformatics, Systematics and Evolution

Molecular pharmacology of cannabinoid receptors modulated by cannabinoids. Computational drug design of inhibitors targeting neurodegeneration and cancers. Developing Augmented Reality/Virtual Reality and computational toolkits for driving next-generation drug discovery research Understanding the molecular recognition processes of integral proteins

• 2012 PhD Swinburne University of Technology, Melbourne, Australia
• 2007 MSc in Bioinformatics, Annamalai University, India

• 2014, The Endeavour Postdoctoral Research Fellowship, Australian National University, Canberra, Australia
• 2011-2012, Deutscher Akademischer Austauschdienst (DAAD) German Academic Exchange Serivces research grant, German Research School of Simulation Sciences, Juelich, Germany

• Guest Editor of a special issue on Biomolecular modelling and Simulation: a field coming of Age in the journal of Life, MDPI publications.
• Reviewer of scientific articles for peer-reviewed journals from MDPI publications and Springer Nature.

• Member of the German DAAD alumni association and the Australian Global Alumni Network.
• Member of Canadian Society for Chemistry

• Member of the Centre for Bioengineering and Biotechnology, Univeristy of Waterloo

• Weng YL, Naik SR, Dingelstad N, Lugo MR, Kalyaanamoorthy S, Ganesan A. Molecular dynamics and in silico mutagenesis on the reversible inhibitor-bound SARS-CoV-2 main protease complexes reveal the role of a lateral pocket in enhancing the ligand affinity. Scientific Reports. 2021;11(1):1-22.
• Mesbahuddin M, Ganesan A, Kalyaanamoorthy S. Engineering carbonic anhydrases for CO2 capture: A critical review. Protein Engineering, Design, and Selection. 2021;34:gzab021.
• Thibault PA, Ganesan A, Kalyaanamoorthy S, Clarke JP WE, Salapa HE, Levin MC. hnRNP A/B Proteins: An encylopedic assessment of their roles in homeostasis and diseases. Biology. 2021;10(8):721.
• Naik SR, Prashant Bharadwaj, Nadia Dingelstad*, Subha Kalyaanamoorthy, Subhash C Mandal, Aravindhan Ganesan, Debprasad Chattopadhyay, Partha Palit. Structure-based virtual screening, molecular dynamics, and binding affinity calculations of potential phytocompounds against SARS-CoV-2. Journal of Biomolecular Structure and Dynamics. 2021; DOI: 10.1080/07391102.2021.1891969.
• Chen R, Ganesan A, Arutyunova E, Lemieux JM, Barakat K. Targeting B7-1 in Immunotherapy. Medicinal Research Reviews. 2020;40(2): 654-682.
• Ganesan A, Ahmed M, Okoye I, et al. Comprehensive in vitro characterization of PD-L1 inhibitors. Scientific Reports. 2020;9(1):2054-2322.
• Ganesan A, Chul T, Barakat K. Revealing the atomistic details behind the binding of B7-1 to CD28 and CTLA-4: A comprehensive protein-protein modelling study. Biochemica et Biophysica Acta-General Subjects. 2018;1862(12):2764-2778. DOI: 10.1016/j.bbagen.2018.08.010
• Ganesan A, Arulraj T, Choulli T, Barakat K. 2018. A mathematical modelling tool for unravelling the antibody-mediated effects on CTLA-4 interactions. BMC Medical Informatics and Decision Making. 2018;18(37):1-17. https://doi.org/10.1186/s12911-018-0606-x
• Ganesan A, Coote M, Barakat K. Molecular 'time-machines' to unravel key biological events for drug design. WIREs: Computational Molecular Science. 2017;7(4).e1306:1-21. https://doi.org/10.1002/wcms.1306
• Nothling MD, Ganesan A, Condic-Jurkic K, et al. Simple design of an enzyme inspired supported catalyst based on a catalytic triad. Chem. 2017;2(5):732-745. DOI:10.1016/j.chempr.2017.04.004
• Please see Dr. Aravindhan Ganesan's Google Scholar profile for a current list of his peer-reviewed articles: https://scholar.google.com.au/citations?user=VE-8INYAAAAJ&hl=en

• Khaled Barakat, Marawan Ahmed, Aravindhan Ganesan, Michael Houghton and Lorne Tyrrell, ‘Systems and methods of selecting compounds with reduced risk of cardiotoxicity using cardiac sodium ion channel models’, US 2018/0068053 A1.