Our Research

Driven by Discovery - Backed by Data

At Canhitt, science isn’t just what we do—it’s who we are. Our research fuels everything from platform innovation to real-world impact, and we’re proud to share the data, insights, and peer-reviewed publications that power our progress. Dive into our figures, explore our findings, and see how our cutting-edge work is shaping the future of preclinical drug discovery. This is where bold ideas meet rigorous science—and where breakthroughs begin.

Kalyaanamoorthy, S., Minh, B., Wong, T. et al. ModelFinder: fast model selection for accurate phylogenetic estimates. Nat Methods 14, 587–589 (2017).

https://doi.org/10.1038/nmeth.4285

Tran, N., Dasari, S., Barwell, S.A.E. et al., The H163A mutation unravels an oxidized conformation of the SARS-CoV-2 main protease. Nat Commun 14, 5625 (2023).

https://doi.org/10.1038/s41467-023-40023-4

Y. Zhao, K. Singh, R. Chowdary Karuturi, A. A. Hefny, A. Shakeri, M. A. Beazely, P. P. N. Rao, ChemMedChem2024, 19, e202400198.

https://doi.org/10.1002/cmdc.202400198

Khavandi, M., Rao, P. P. N., Beazely, M.A. Int. J. Mol. Sci. 2023, 24(2), 911

https://doi.org/10.3390/ijms24020911

Weng, Y.L., Naik, S.R., Dingelstad, N. et al. Molecular dynamics and in silico mutagenesis on the reversible inhibitor-bound SARS-CoV-2 main protease complexes reveal the role of lateral pocket in enhancing the ligand affinity. Sci Rep 11, 7429 (2021).

https://doi.org/10.1038/s41598-021-86471-0

Reeves, S., Kalyaanamoorthy, S. Zero-shot transfer of protein sequence likelihood models to thermostability prediction. Nat Mach Intell 6, 1063–1076 (2024).

https://doi.org/10.1038/s42256-024-00887-7