Explore the Potential with AI-Driven Innovation
The specialised, focused library is developed on demand with the most recent virtual screening and parameter assessment technology, guided by the Receptor.AI drug discovery platform. This approach exceeds the capabilities of traditional methods and offers compounds with higher activity, selectivity, and safety.
We carefully select specific compounds from a vast collection of over 60 billion molecules in virtual chemical space. Our partner Reaxense helps in synthesizing and delivering these compounds.
The library features a range of promising modulators, each detailed with 38 ADME-Tox and 32 physicochemical and drug-likeness parameters. Plus, each compound is presented with its ideal docking poses, affinity scores, and activity scores, ensuring a thorough insight.
We use our state-of-the-art dedicated workflow for designing focused libraries for enzymes.
Fig. 1. The sreening workflow of Receptor.AI
The procedure entails thorough molecular simulations of the catalytic and allosteric binding pockets, accompanied by ensemble virtual screening that factors in their conformational flexibility. When developing modulators, the structural modifications brought about by reaction intermediates are factored in to optimize activity and selectivity.
Key features that set our library apart include:
partner
Reaxense
upacc
P06737
UPID:
PYGL_HUMAN
Alternative names:
-
Alternative UPACC:
P06737; A6NDQ4; B4DUB7; F5H816; O60567; O60752; O60913; Q501V9; Q641R5; Q96G82
Background:
The Glycogen phosphorylase, liver form, encoded by the gene with accession number P06737, is an allosteric enzyme pivotal in glycogen catabolism. It catalyzes the phosphorolytic cleavage of glycogen, producing glucose-1-phosphate, a critical step in maintaining glucose homeostasis at both cellular and organismal levels.
Therapeutic significance:
Glycogen storage disease 6, linked to mutations affecting this enzyme, manifests as hypoglycemia, ketosis, growth retardation, and hepatomegaly, sparing heart and skeletal muscle. Understanding the enzyme's role could unveil novel therapeutic strategies for this metabolic disorder.