AlphaMol has successfully predicted drug molecule kinetic property through machine learning. It has been published recently as a cover story in the ACS J. Chem. Theory Comput.

Dong, J.; Wang, S.; Cui, W.; Sun, X.; Guo, H.; Yan H.; Vogel H.; Wang Z.*; Yuan, S.*, Machine learning deciphered molecular mechanistics with accurate kinetic and thermodynamic prediction. Journal of Chemical Theory and Computation 2024.

The kinetic and thermodynamic properties play a crucial role in determining the drug activity and efficacy. Our team has developed a novel algorithm to predict these two properties through machine learning. The algorithm has been validated through biological testing, and the results have been published in the latest paper titled, "Machine Learning Deciphered Molecular Mechanistics with Accurate Kinetic and Thermodynamic Prediction."

We believe this new method could facilitate and guide rational drug design, making the drug discovery process more efficient and effective.

Check out our latest paper to learn more about this exciting work in modern drug discovery here:
https://doi.org/10.1021/acs.jctc.3c01412