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.
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.
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 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 distinguishes itself through several key aspects:
partner
Reaxense
upacc
Q9H857
UPID:
NT5D2_HUMAN
Alternative names:
-
Alternative UPACC:
Q9H857; C9JTZ6; E9PAL9; O95888; Q96C80; Q9H9Z8
Background:
The 5'-nucleotidase domain-containing protein 2 plays a crucial role in nucleotide metabolism, impacting various cellular processes. Its specific functions and interactions within the cell remain to be fully elucidated, making it a subject of significant scientific interest.
Therapeutic significance:
Understanding the role of 5'-nucleotidase domain-containing protein 2 could open doors to potential therapeutic strategies. Its involvement in nucleotide metabolism suggests it may influence conditions related to cellular energy balance and signaling.