The group research interests are at the interface between computation and biology, with an application focus on biomedicine. Specifically, we develop new computational physics methods and apply them to understand biological problems mainly at the level of protein folding and binding. This knowledge is then used to design molecules with therapeutic applications in mind.
We search new molecules to alter protein behavior with possible therapeutic implications, using new simulation-based methods for drug discovery. We develop in-silico fragment based drug discovery methods to explore the binding chemical space of a target and simulate drug-like binding events for the determination of kinetics, affinities and poses. New small molecules and peptides developped are then tested experimentally.
2. Computational Physics
We develop new codes for molecular dynamics simulations (ACEMD) running on special hardware to maximize the data throughput and extend the window of exploration of biological phenomena by simulations. We also work on distributed, volunteer computing where we perform most of our calculations with the help of people worldwide donating their computer time (GPUGRID). In order to analyze all the data generated, we actively develop new analysis techniques based on machine learning and Markov state models (HTMD) to determine equilibrium observables which can then be directly compared with experiments.
3. Protein folding and binding
We computationally investigate biological systems to understand the mechanisms of biological processes at the atomistic level. The goal is to be able to create solid, quantitative hypothesis of how proteins behaves, how chemical modifications alter binding and folding, discover hidden order in intrinsically disordered proteins and understand molecular recognition pathways between molecules. We try to confront it with experimental collaborators and to exploit this understanding to find new therapeutic solutions.