Explore the Potential with AI-Driven Innovation
The focused library is created on demand with the latest virtual screening and parameter assessment technology, supported by the Receptor.AI drug discovery platform. This method is more effective than traditional methods and results in higher-quality compounds with better activity, selectivity, and safety.
Our selection of compounds is from a large virtual library of over 60 billion molecules. The production and distribution of these compounds are managed by our partner Reaxense.
In the library, a selection of top modulators is provided, each marked with 38 ADME-Tox and 32 parameters related to physicochemical properties and drug-likeness. Also, every compound comes with its best docking poses, affinity scores, and activity scores, providing a comprehensive overview.
Our top-notch dedicated system is used to design specialised libraries for receptors.
Fig. 1. The sreening workflow of Receptor.AI
It features thorough molecular simulations of the receptor within its native membrane environment, complemented by ensemble virtual screening that considers its conformational mobility. For dimeric or oligomeric receptors, the full functional complex is constructed, and tentative binding sites are determined on and between the subunits to cover the entire spectrum of potential mechanisms of action.
Key features that set our library apart include:
partner
Reaxense
upacc
P43220
UPID:
GLP1R_HUMAN
Alternative names:
-
Alternative UPACC:
P43220; Q2M229; Q99669
Background:
The Glucagon-like peptide 1 receptor (GLP-1R) is a pivotal G-protein coupled receptor that plays a crucial role in glucose metabolism by mediating the effects of glucagon-like peptide 1 (GLP-1). It activates signaling pathways that lead to increased levels of intracellular cAMP, which in turn facilitates insulin secretion in response to elevated blood glucose levels.
Therapeutic significance:
Understanding the role of Glucagon-like peptide 1 receptor could open doors to potential therapeutic strategies. Its involvement in insulin secretion positions it as a key target in the development of treatments for diabetes and related metabolic disorders.