Volkamer Lab
Data Driven Drug Design
At Volkamer Lab, we develop methods at the interface between structural bioinformatics and cheminformatics, mostly applied in the context of computer-aided drug design with a focus on machine learning methods.
On one hand, we investigate structure-based methods for active site assessment, including binding site comparison, pharmacophore elucidation and off-target prediction; pocket-centric fragment-based design as well as deep learning enhanced virtual screening pipelines. Besides target-independent approaches, we focus our developments on kinases, one of the major classes of therapeutic targets. Recently, we started to extend our portfolio to identify novel anti-infectives.
On the other hand, we study ligand-based methods, including machine learning methods for activity and toxicity prediction and apply them in translational projects. Special focus is set on integrating novel techniques taking the applicability and reliability into account, and the interpretability of deep learning methods. Besides revolutionizing drug design, our goal is the establishment of alternative in silico methods to determine the risk of compounds and their harmful effects on humans, animals, plants and environment (see BB3R platform).
Additionally, we continuously work on the integration of the two research areas of structure- and ligand-centered projects, i.e., focusing on structure-informed machine learning approaches applied primarily to kinases. In this attempt, we are integrating the physical aspects into molecular modelling (e.g. molecular dynamics simulations and free energy calculations) to better sample the drug target interactions. The OpenKinome initiative is an ongoing collaboration with the lab of Prof. John Chodera, our Einstein BIH Visiting Fellow.
We are also working together on campus to advance the field of rational drug discovery through the development of neuro-explicit AI models, find out more about NextAID here.
Latest news
- 2023.09.15: Floriane and Paula attended Europin Summer School on Drug Design
- 2023.05.29: TeachOpenCADD goes Deep Learning!
- 2023.05.04: Group retreat: Exploring Saarbrücken with our Berlin teammates!
- 2023.04.20: New paper presenting hurdles and signposts on the road to virtual control groups!
- 2023.04.03: Our collaboration on a chemical language model is out !
- 2023.02.01: Floriane Odje joins Volkamer’s lab
- 2023.01.05: ML for small molecule DD paper out!
- 2022.12.01: Paula joins Volkamer lab
- 2022.12.01: Michael Backenköhler joins Volkamer’s lab
- 2022.08.01: Volkamer lab moved to Saarbrücken!!!
