Universiteit Leiden

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Research project

Prediction of binding Kinetics

Supervisor: Gerard van Westen

Contact
Gerard van Westen

Suitable for students of:  MST master

It has been hypothesized that residence time (the reciprocal of koff) is a better surrogate for in vivo efficacy than affinity. 1 Estimation of (relative) binding affinity using in silico methods has recently made several breakthroughs. 2 Therefore, the goal of this project will be to predict binding kinetics using Molecular Dynamics. More specifically, Metadynamics will be used to escape the low energy landscape of the bound state. Recently kinetics have been predicted using Metadynamics on the protein trypsin. This study will explore different techniques on the Adenosine A2A receptor for which a lot of experimental data exists. 4 Using Graphic Processing Units (GPUs) for the simulations, relatively long time scales will be simulated which will enable us to study ligand unbinding events.

Requirements

Our research is interdisciplinary and we have both life scientists and computer scientists working in our group. Accordingly, most projects advertised in the context of the group are suitable for (MSc) students with either a chemical/biological/life science or a computer science/machine learning background. No previous experience in the other field is required, but interest to either get familiar with life science data, or with computational methods, would clearly be an advantage. We strongly support students to publish their results if possible and when the project results are suitable.

  1. Guo, Dong, et al. "Drug‐Target Residence Time—A Case for G Protein Coupled Receptors." Medicinal research reviews 34.4 (2014): 856-892.
  2. Wang, Lingle, et al. "Accurate and reliable prediction of relative ligand binding potency in prospective drug discovery by way of a modern free-energy calculation protocol and force field." Journal of the American Chemical Society 137.7 (2015): 2695-2703.
  3. Tiwary, Pratyush, et al. "Kinetics of protein–ligand unbinding: Predicting pathways, rates, and rate-limiting steps." Proceedings of the National Academy of Sciences 112.5 (2015): E386-E391.
  4. Guo, Dong, et al. "Binding Kinetics of ZM241385 Derivatives at the Human Adenosine A2A Receptor." ChemMedChem 9.4 (2014): 752-761.
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