Periodic Reporting for period 4 - FRAGMENT2DRUG (Jigsaw puzzles at atomic resolution: Computational design of GPCR drugs from fragments)
Okres sprawozdawczy: 2022-05-01 do 2023-04-30
The objective of this project was to develop a computational platform to accelerate the early drug discovery process for G protein-coupled receptors (GPCRs), which are a class of important therapeutic targets. Computational modeling based on atomic-level models of GPCRs, combined with extensive experimental testing, enabled discovery of GPCR ligands. The conclusion of the action is that fragment-based lead discovery and structure-based modeling can be a powerful strategy to identify starting points for development of novel drugs. The results of the project are important for society as they can lead to novel therapeutic drugs of neurodegenerative diseases and accelerate the drug discovery process, which could improve human health.
A combination of different computational techniques was first used to improve understanding of how to GPCRs bind ligands and to develop computational fragment-based strategies for efficient drug design. We then applied the developed techniques to identify ligands of therapeutically relevant GPCRs and enzymes using fragment-based lead discovery. In the applied projects, we explored strategies to design drugs that modulate several targets (polypharmacology) and successfully identified novel starting points for development of drugs for treatment of Parkinson’s disease. We also accomplished our goal to discover ligands of peptide-binding GPCRs using a fragment-based approach and identified ligands of Neurotensin receptors. The results of the action have been disseminated in 13 scientific publications and via presentations at conferences.
This project progressed beyond the state of the art by developing techniques that enable very efficient fragment-based discovery of GPCR ligands by performing structure-based virtual screening of large chemical libraries. In the applied part of the project, the rational design of polypharmacology is the most significant achievement. A common property of drugs (e.g. antipsychotics) is that such compounds interact with multiple targets, which is essential for their therapeutic effect. However, the fact that multi-target interactions may be required for treatment of complex diseases contrasts with the philosophy of modern drug discovery, which focuses on ligands with selectivity for a one target. Although potential of polypharmacology is clear, progress has been limited by difficulties to rationally design such compounds. We undertook the challenge to design ligand polypharmacology relevant for Parkinson’s disease. The project successfully used structure-based modelling to design a single compound with the ability to modulate the activity of two GPCRs. The most potent dual-target compounds display high potency at both targets and one scaffold was demonstrated to be active in a rat model of parkinsonism.