Author

Sankaranarayanan Murugesan

Birla Institute of Technology and Science, PilaniORCID 0000-0002-3680-1577Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Bioinformatics· 2 Microbiology· 1

Signature Assays, Organisms & Methods

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Research Focus:drug response / drug discovery· 2 Approach:experimental assay· 1 Organism:human· 1 Approach:machine learning (classical)· 1 Approach:statistical model· 1

Frequent Co-Authors

A Arulmozhi· 1 shared A. ArivuchelvaniD· 1 shared A. JagadeeswaraniD· 1 shared Aditya V. VashiiD· 1 shared Alexander J. McAuleyiD· 1 shared Anupama KumariD· 1 shared Bang M. TraniD· 1 shared Carl M. J. KirkpatrickiD· 1 shared

Activity by Year

2023-2025 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 24 mutual co-author links

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1 shared paperBioinformatics

A Arulmozhi

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Author profile →

3 papers

Recent·Most cited

Machine Learning-Based Bioactivity Prediction of Potential PPAR-γ Agonists for the Management of Diabetes

Juhi Madhwani, Sankaranarayanan Murugesan

The paper uses machine learning to predict PPAR-γ agonist bioactivity, achieving an R2 score of 0.83 using molecular descriptors from ChEMBL data.

bioRxiv · Aug 9, 2025 · PreprintBioinformatics

Use of Stem Cell-Derived Cardiomyocyte and Nasal Epithelium Models to Establish a Multi-Tissue Model Platform to Validate Repurposed Drugs Against SARS-CoV-2 Infection

Nathan Gödde, Carmel O’Brien, Elizabeth Vincan, Aditya V. Vashi, Stephanie Olliff, Bang M. Tran, Shafagh A. Waters, Sarah Goldie, Petrus Jansen van Vuren, Shane Riddell, Matthew P. Bruce, Vinti Agarwal, Eugene Athan, Kim R. Blasdell, Simran Chahal, , Seshadri S. Vasan

The paper validates repurposed drugs against SARS-CoV-2 using stem cell-derived cardiomyocyte and nasal epithelium models, confirming fluvoxamine's antiviral efficacy in combination with other drugs.

bioRxiv · May 22, 2024 · PreprintMicrobiology

Computational study of Piper betle L. phytocompounds by insilico and ADMET analysis for prediction of potential xanthine oxidase inhibitory activity

P Vikrama Chakravarthi, M. Karthikeyan, L. Lakshmanan, Sankaranarayanan Murugesan, A. Arivuchelvan, K. Sukumar, A Arulmozhi, A. Jagadeeswaran

This study identifies potential xanthine oxidase inhibitors from Piper betle phytocompounds through in silico docking and ADMET analysis, showing some compounds outperform allopurinol.

bioRxiv · Jan 13, 2023 · PreprintBioinformatics