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 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 includes a list of the most promising modulators annotated with 38 ADME-Tox and 32 physicochemical and drug-likeness parameters. Also, each compound is presented with its optimal docking poses, affinity scores, and activity scores, providing a comprehensive overview.
We utilise our cutting-edge, exclusive workflow to develop focused 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 distinguishes itself through several key aspects:
partner
Reaxense
upacc
Q92485
UPID:
ASM3B_HUMAN
Alternative names:
-
Alternative UPACC:
Q92485; B7ZB35; Q5T0Z0; Q96CB7
Background:
Acid sphingomyelinase-like phosphodiesterase 3b (ASML3B) is a lipid-modulating enzyme with pivotal roles in macrophage and dendritic cell function. It modulates lipid composition and membrane fluidity, acting as a negative regulator of Toll-like receptor signaling. Despite its known in vitro phosphodiesterase activity, the physiological substrates of ASML3B remain to be fully elucidated.
Therapeutic significance:
Understanding the role of Acid sphingomyelinase-like phosphodiesterase 3b could open doors to potential therapeutic strategies.