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.
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.
Contained in the library are leading modulators, each labelled with 38 ADME-Tox and 32 physicochemical and drug-likeness qualities. In addition, each compound is illustrated with its optimal docking poses, affinity scores, and activity scores, giving a complete picture.
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
Q6UWU2
UPID:
GLB1L_HUMAN
Alternative names:
-
Alternative UPACC:
Q6UWU2; Q96DR0
Background:
Beta-galactosidase-1-like protein, encoded by the gene with the accession number Q6UWU2, is classified as a probable glycosyl hydrolase. This enzyme plays a crucial role in the breakdown of glycosidic bonds within beta-galactosides, facilitating various biological processes.
Therapeutic significance:
Understanding the role of Beta-galactosidase-1-like protein could open doors to potential therapeutic strategies. Its enzymatic activity suggests a pivotal function in cellular metabolism and homeostasis, making it a target of interest in drug discovery.