Computational studies of GPCRs and viral enzymes
||Computational studies of GPCRs and viral enzymes|
||SNIC Large Storage|
||Jens Carlsson <email@example.com>|
||2023-01-01 – 2024-01-01|
||10601 10407 30103|
Our research focuses on computational studies of G protein-coupled receptors (GPCRs) and viral 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, 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 detailed understanding of how neurotransmitters interact with GPCRs and modulate their function. In 2023, we will focus on discovery of allosteric modulators of GPCRs, understanding the molecular basis of signalling, the evolution of ligand specificity, and development of novel methods for structure-based drug discovery. Since the start of the COVID-19 pandemic, part of our research is also focused on the identification of inhibitors of viral proteases. By combining virtual screens, machine learning and simulations, we will predict inhibitors of SARS-CoV-2 with the goal to develop broad-spectrum antiviral drugs. All our projects are driven by computational chemistry and carried out in collaboration with leading experimentalists in the field. Our current research is funded by several major funding agencies (e.g., VR, ERC, and KAW).