Personal profile

Research Interests

Dr Shubham Vishnoi is a Postdoctoral Researcher at the University of Limerick, specialising in computational drug design and molecular modelling. He holds a PhD in computational biophysics from UL where his research focused on the structure-based design of peptide therapeutics and the modelling of membrane proteins, including GPCRs. His work combines molecular dynamics simulations, quantum mechanical methods and machine learning to investigate drug, target interactions, protein crystallography and bioassay data analysis.

Dr Vishnoi contributed to the development of tools and databases such as CrystalDFTand MOFPrime aimed at predicting crystal properties from fisrst principles, and the Physicochemical n-Grams Tool which enables the encoding of sequence-based protein descriptors. He also worked with the innovation team at APC Ltd., Dublin, during his SSPC co-op PhD placement, where he contributed to the development of data visualisation and machine learning tools to enhance insights into drug and material properties. His interdisciplinary expertise bridges pharmaceutical sciences, structural bioinformatics and digital health.

He actively collaborates with academic and industry partners and is passionate about translational research that accelerates the discovery and development of next-generation biopharmaceuticals.

Expertise related to UN Sustainable Development Goals

In 2015, UN member states agreed to 17 global Sustainable Development Goals (SDGs) to end poverty, protect the planet and ensure prosperity for all. This person’s work contributes towards the following SDG(s):

  • SDG 3 - Good Health and Well-being
  • SDG 7 - Affordable and Clean Energy
  • SDG 9 - Industry, Innovation, and Infrastructure

Related documents

Education/Academic qualification

PhD, Predictive modelling of peptide-based therapeutics: a way to accelerate biopharmaceutical design and formulation development

2 Sep 20199 Jun 2023

Award Date: 24 Jan 2024

Masters, PREDICTION OF CYCLIN-DEPENDENT KINASE INHIBITOR PROTEINS USING MACHINE LEARNING APPROACH, National Institute of Pharmaceutical Education and Research, Mohali

20172019

External positions

Member of the Early Careers Committee, Biophysical Society

Associate Member of the Royal Society of Chemistry (AMRSC), Royal Society of Chemistry

Keywords

  • QC Physics
  • Piezoelectricity
  • Computational Biophysics
  • Physics-based Simulation
  • Machine Learning
  • Sustainable Energy
  • QD Chemistry
  • Drug Design
  • Biomolecular Modelling
  • Protein Modelling
  • Biomaterials
  • Density Functional Theory
  • MD Simulations
  • Classical MD
  • Chemoinformatics
  • Crystal Property Prediction
  • peptide
  • protein

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Collaborations and top research areas from the last five years

Recent external collaboration on country/territory level. Dive into details by clicking on the dots or
  • Open Access
  • Discovering chemical structure: general discussion

    Aspuru-Guzik, A., Bechtel, T., Bernales, V., Biggin, P. C., Bigi, F., Borges, I., Briling, K. R., Cheung, J., Collins, C. M., Darmawan, K. K., David, N., Day, G. M., Deringer, V. L., Draxl, C., Dyer, M., Eardley-Brunt, A., Evans, R., Fairlamb, I., Franklin, B. A. & George, J. & 32 others, Goulding, M., Grundy, J., Hafizi, R., Hakkennes, M., Hickey, N., James, G., Juraskova, V., Kalikadien, A. V., Kapil, V., Kulik, H. J., Kumar, V., Kuttner, C., Lederbauer, M., Lou, Y., Mante, E., Marsh, L., Martin, J., Middleton, C., Nematiaram, T., Pare, C. W. P., Pasca, B., Pickard, C. J., Ruscic, B., Ryder, M. R., Savoie, B. M., Sun, W., Szczypiński, F. T., Taniguchi, T., Torrisi, S., Vishnoi, S., Walsh, A. & Wang, S., 12 Dec 2024, In: Faraday Discussions. 256, p. 177-220 44 p.

    Research output: Contribution to journalComment/debate

  • Discovering structure–property correlations: general discussion

    Anker, A. S., Aspuru-Guzik, A., Ben Mahmoud, C., Bennett, S., Briling, K. R., Changiarath, A., Chong, S., Collins, C. M., Cooper, A. I., Crusius, D., Darmawan, K. K., Das, B., David, N., Day, G. M., Deringer, V. L., Duarte, F., Eardley-Brunt, A., Evans, M. L., Evans, R. & Fairlamb, I. & 43 others, Franklin, B. A., Frey, J., Ganose, A. M., Goulding, M., Hafizi, R., Hakkennes, M., Hickey, N., James, G., Jelfs, K. E., Kalikadien, A. V., Kapil, V., Koczor-Benda, Z., Krammer, F., Kulik, H. J., Kumar, V., Kuttner, C., Lam, E., Lou, Y., Mante, E., Martin, J., Mroz, A. M., Nematiaram, T., Pare, C. W. P., Patra, S., Proudfoot, J., Ruscic, B., Ryder, M. R., Sakaushi, K., Saßmannshausen, J., Savoie, B. M., Schneider, N., Schwaller, P., Skjelstad, B. B., Sun, W., Szczypiński, F. T., Torrisi, S., Ueltzen, K., Vishnoi, S., Walsh, A., Wang, X., Wilson, C., Wu, R. & Zeitler, J., 13 Dec 2024, In: Faraday Discussions. 256, p. 373-412 40 p.

    Research output: Contribution to journalComment/debate

  • Discovering trends in big data: general discussion

    Albornoz, R. V., Antypov, D., Blanke, G., Borges, I., Marulanda Bran, A., Cheung, J., Collins, C. M., David, N., Day, G. M., Deringer, V. L., Draxl, C., Eardley-Brunt, A., Evans, M. L., Fairlamb, I., Fieseler, K., Franklin, B. A., George, J., Grundy, J., Johal, J. & Kalikadien, A. V. & 23 others, Kapil, V., Kotopanov, L., Kumar, V., Kuttner, C., Lederbauer, M., Ojeda-Porras, A. C., Pang, J., Parkes, M., Pemberton, M., Ruscic, B., Ryder, M. R., Sakaushi, K., Saleh, G., Savoie, B. M., Schwaller, P., Skjelstad, B. B., Sun, W., Taniguchi, T., Taylor, C. R., Torrisi, S., Vishnoi, S., Walsh, A. & Wu, R., 18 Dec 2024, In: Faraday Discussions. 256, p. 520-550 31 p.

    Research output: Contribution to journalComment/debate

  • Computational Peptide Design Cotargeting Glucagon and Glucagon-like Peptide-1 Receptors

    Vishnoi, S., Bhattacharya, S., Walsh, E. M., Okoh, G. I. & Thompson, D., 14 Aug 2023, In: Journal of Chemical Information and Modeling. 63, 15, p. 4934-4947 14 p.

    Research output: Contribution to journalArticlepeer-review

    Open Access