Protein structure prediction and AI in virtual screening
Title: Protein structure prediction and AI in virtual screening
SNIC Project: Berzelius-2021-85
Project Type: LiU Berzelius
Principal Investigator: Jens Carlsson <jens.carlsson.lab@gmail.com>
Affiliation: Uppsala universitet
Duration: 2021-11-19 – 2022-06-01
Classification: 10601
Homepage: http://www.carlssonlab.org/
Keywords:

Abstract

Our research focuses on computational studies of G protein-coupled receptors (GPCRs), which constitute the largest family of eukaryotic membrane proteins and are involved in essential physiological processes. GPCRs are also important therapeutic targets 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. All our projects are driven by computational chemistry and carried out in collaboration with leading experimentalists in the field. In 2022, we will focus on protein structure prediction and virtual screening using artificial intelligence.