Our research focuses on computational studies of G protein-coupled receptors (GPCRs) and enzymes. GPCRs constitute the largest family of eukaryotic membrane proteins and are involved in essential physiological processes. They are also important therapeutic targets and >30% of all drugs mediate their effect by modulating members of this family. Our goals are to improve understanding of GPCR-ligand interactions at the atomic level using simulations and develop new strategies for structure-based drug discovery. By combining protein structure prediction using machine learning methods, molecular docking screening, and free energy calculations, we design ligands to therapeutic targets and test these experimentally to identify lead candidates. Using molecular dynamics (MD) simulations, we gain a detailed understanding of how neurotransmitters interact with GPCRs and modulate their function. In 2025, we will focus on the discovery of allosteric modulators of GPCRs, understanding the molecular basis of signaling, the evolution of ligand specificity, and development of novel strategies for structure-based drug discovery. Recently, we have also expanded our research projects to include computational studies of enzymes and the development of antiviral and anticancer drugs. By combining virtual screens, machine learning, and simulations, we will design novel inhibitors of enzymes involved in viral infection and cancer. All our projects are driven by computational chemistry methods and carried out in collaboration with leading experimentalists in the field.