Explore the Potential with AI-Driven Innovation
This comprehensive focused library is produced on demand with state-of-the-art virtual screening and parameter assessment technology driven by Receptor.AI drug discovery platform. This approach outperforms traditional methods and provides higher-quality compounds with superior activity, selectivity and safety.
The compounds are cherry-picked from the vast virtual chemical space of over 60B molecules. The synthesis and delivery of compounds is facilitated by our partner Reaxense.
The library includes a list of the most effective modulators, each annotated with 38 ADME-Tox and 32 physicochemical and drug-likeness parameters. Furthermore, each compound is shown with its optimal docking poses, affinity scores, and activity scores, offering a detailed summary.
We employ our advanced, specialised process to create targeted libraries for enzymes.
Fig. 1. The sreening workflow of Receptor.AI
This approach involves comprehensive molecular simulations of the catalytic and allosteric binding pockets and ensemble virtual screening that accounts for their conformational flexibility. In the case of designing modulators, the structural adjustments caused by reaction intermediates are considered to improve activity and selectivity.
Our library is unique due to several crucial aspects:
partner
Reaxense
upacc
P13807
UPID:
GYS1_HUMAN
Alternative names:
-
Alternative UPACC:
P13807; Q9BTT9
Background:
Glycogen [starch] synthase, muscle (P13807), plays a pivotal role in glycogen synthesis, transferring glycosyl residues to form alpha-1,4-glucan chains. This enzyme's activity is crucial for energy storage in muscle tissues.
Therapeutic significance:
Muscle glycogen storage disease 0, linked to mutations in P13807, underscores the enzyme's critical role in energy metabolism. Targeting this pathway could offer novel treatments for metabolic disorders.