New computational method for more efficient drug discovery
Researchers of the University of Barcelona have developed a more efficient computational method to identify new drugs. The study, published in the scientific journal Nature Chemistry, proposes a new approach to discovering biologically active molecules. Based on a different principle, this method complements conventional tools and advances the field of rational drug design. ICREA researcher Xavier Barril, from the Faculty of Pharmacy and Food Sciences and The Institute of Biomedicine of the University of Barcelona (IBUB), has led this project, which has the participation of professor Francesc Xavier Luque and PhD student Sergio Ruiz Carmona, members of the same Faculty.
Researchers of the University of Barcelona have developed a more efficient computational method to identify new drugs. The study, published in the scientific journal Nature Chemistry, proposes a new approach to discovering biologically active molecules. Based on a different principle, this method complements conventional tools and advances the field of rational drug design. ICREA researcher Xavier Barril, from the Faculty of Pharmacy and Food Sciences and The Institute of Biomedicine of the University of Barcelona (IBUB), has led this project, which has the participation of professor Francesc Xavier Luque and PhD student Sergio Ruiz Carmona, members of the same Faculty.
Improving efficiency and effectiveness in drug discovery is a key goal in pharmaceutical research. In this process, researchers seek molecules that can bind to a target protein and modify its behaviour to meet clinical needs. “All current methods for predicting whether a molecule will bind to a target protein are based on affinity, that is, in the thermodynamic stability of the complex. We show that molecules must form structurally stable complexes, and that it is possible to distinguish between active from inactive compounds by examining which specific interactions are the hardest to break”, says Professor Xavier Barril.
This approach has been implemented in software that identifies molecules with likelihood of binding the target protein. “The method allows selecting molecules that can be starting points to create new drugs”, says Barril. “Moreover, -he continues- the process is complementary to existing methods and increases efficiency fivefold while reducing computational costs. We are successfully applying in several projects in the field of cancer and infectious diseases, among others”.
A new vision for the protein-ligand drugs
This work introduces a new perspective on the ligand-protein interaction. “We donʼt look at the balancing situation, where two molecules make the best possible interactions, but we also consider how the complex might dissociate, where the breaking points are, and how the drug can be optimized to resist separation. Now we have to focus on this phenomenon to understand it better and determine whether more complex models can further improve our predictions”, says the researcher. The UB team is already using this method, which is open to all the scientific community.
Article reference:
Ruiz-Carmona, S.; Schmidtke, P.; Luque, F. J.; Baker, L.; Matassova, N.; Davis, B.; Roughley, S.; Murray, J.; Hubbard, R., and Barril, X. “Dynamic undocking and the quasi-bound state as tools for drug discovery”. Nature Chemistry, October 2016. Doi: doi:10.1038/nchem.2660