Explore the Potential with AI-Driven Innovation
The focused library is created on demand with the latest virtual screening and parameter assessment technology, supported by the Receptor.AI drug discovery platform. This method is more effective than traditional methods and results in higher-quality compounds with better activity, selectivity, and safety.
From a virtual chemical space containing more than 60 billion molecules, we precisely choose certain compounds. Our collaborator, Reaxense, aids in their synthesis and provision.
In the library, a selection of top modulators is provided, each marked with 38 ADME-Tox and 32 parameters related to physicochemical properties and drug-likeness. Also, every compound comes with its best docking poses, affinity scores, and activity scores, providing a comprehensive overview.
We employ our advanced, specialised process to create targeted 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.
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.