R N V Krishna Deepak

Areas of Interest & Expertise

Structural Bioinformatics
Molecular Modelling and Simulations
Machine Learning
Computational Venomics

Biography

Krishna is a Computational Structural Biologist with interests in development and application of integrative structural modelling and multiscale simulation methods.

At present, he is interested in studying snake venom toxins using computational approaches to establish the structural basis of snake venom toxicity.

Before joining the University, he worked as a Senior Scientist at the Bioinformatics Institute (BII), Agency for Science, Technology and Research (A*STAR), Singapore. He obtained his PhD, specialising in Bioinformatics and Computational Biology, from the Indian Institute of Technology Kanpur (IIT Kanpur), and received his Bachelor’s degree in Agricultural Biotechnology from the Tamil Nadu Agricultural University (TNAU), Coimbatore, India.

Publications

Journal Articles

Cheng, L., Krishna Deepak, R. N. V., Wang, G., Meng, Z., Tao, L., Xie, M., Chi, W., Zhang, Y., Yang, M., Liao, Y., Chen, R., Liang, Y., Zhang, J., Huang, Y., Wang, W., Guo, Z., Wang, Y., Lin, J. D., Fan, H., & Chen, C. (2023). Hepatic mitochondrial NAD+ transporter SLC25A47 activates AMPKα mediating lipid metabolism and tumorigenesis. Hepatology, 78 (6), 1828 – 1842. https://doi.org/10.1097/HEP.0000000000000314
Liu, H., Krishna Deepak, R. N. V., Shiriaeva, A., Gati, C., Batyuk, A., Hu, H., Weierstall, U., Liu, W., Wang, W., Cherezov, V., Fan, H., & Zhang, C. (2021). Molecular basis for lipid recognition by the prostaglandin D₂ receptor CRTH2. Proceedings of the National Academy of Sciences, 118 (32) e2102813118. https://doi.org/10.1073/pnas.210281311
Yap, J., Krishna Deepak, R. N. V., Tian, Z., Ng, W. H., Goh, K. C., Foo, A., Tee, Z. H., Mohanam, M. P., Sim, Y. R. M., Degirmenci, U., Lam, P., Chen, Z., Fan, H., & Hu, J. (2021). The stability of R‑spine defines RAF inhibitor resistance: A comprehensive analysis of oncogenic BRAF mutants with in-frame insertion of αC-β4 loop. Science Advances, 7 (24), eabg0390. https://www.science.org/doi/10.1126/sciadv.abg0390