SoSe 23: Estimating pH-dependent rates by machine learning techniques
Luca Donati
Comments
Molecular Dynamics (MD) simulations are a powerful tool to study the behavior of molecules at
the atomic level. A wide range of computational methods have been developed to analyze MD simulations
and to extract meaningful information such as transition rates. The purpose of the seminar is to study
and extend these methods to determine how transition rates of molecular systems are affected by the pH of
the environment [1,2]. The results of this project will be relevant in studying the μ-opioid receptor system,
whose activation and the emergence of adverse effects by opioids depend on the pH of the cell membrane
within which it resides [3].
The project is highly interdisciplinary and students from physics, chemistry, and mathematics are encouraged
to participate.
Website https://www.zib.de/userpage/donati/
Suggested reading
1. L. Donati, and M. Weber. In: J. Chem. Phys. 157.22 (2022), p. 224103.
2. R. J. Rabben, S. Ray, and M. Weber. In: J. Chem. Phys. 153.11 (2020), p. 114109.
3. G. Del Vecchio, et al. In: Sci. Rep. 9 (2019), p. 19344.
13 Class schedule
Regular appointments