Explore the Potential with AI-Driven Innovation
This extensive focused library is tailor-made using the latest virtual screening and parameter assessment technology, operated by the Receptor.AI drug discovery platform. This technique is more effective than traditional methods, offering compounds with improved activity, selectivity, and safety.
We pick out particular compounds from an extensive virtual database of more than 60 billion molecules. The preparation and shipment of these compounds are facilitated by our associate Reaxense.
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.
Our top-notch dedicated system is used to design specialised libraries for enzymes.
Fig. 1. The sreening workflow of Receptor.AI
The method includes detailed molecular simulations of the catalytic and allosteric binding pockets, along with ensemble virtual screening that considers their conformational flexibility. In the design of modulators, structural changes induced by reaction intermediates are taken into account to enhance activity and selectivity.
Our library stands out due to several important features:
partner
Reaxense
upacc
P15259
UPID:
PGAM2_HUMAN
Alternative names:
BPG-dependent PGAM 2; Muscle-specific phosphoglycerate mutase; Phosphoglycerate mutase isozyme M
Alternative UPACC:
P15259
Background:
Phosphoglycerate mutase 2 (PGAM2) plays a pivotal role in glycolysis and gluconeogenesis, facilitating the interconversion of 3- and 2-phosphoglycerate. Known by alternative names such as BPG-dependent PGAM 2 and Muscle-specific phosphoglycerate mutase, PGAM2's activity is crucial for efficient energy production in muscle tissues.
Therapeutic significance:
PGAM2's dysfunction is linked to Glycogen storage disease 10, characterized by myoglobinuria, muscle pain, and exercise intolerance. This association highlights the protein's potential as a target for therapeutic intervention in metabolic disorders.