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.
Our selection of compounds is from a large virtual library of over 60 billion molecules. The production and distribution of these compounds are managed 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.
We utilise our cutting-edge, exclusive workflow to develop focused libraries for enzymes.
Fig. 1. The sreening workflow of Receptor.AI
It includes comprehensive molecular simulations of the catalytic and allosteric binding pockets and the ensemble virtual screening accounting for their conformational mobility. In the case of designing modulators, the structural changes induced by reaction intermediates are taken into account to leverage activity and selectivity.
Our library is unique due to several crucial aspects:
partner
Reaxense
upacc
Q9NQL2
UPID:
RRAGD_HUMAN
Alternative names:
-
Alternative UPACC:
Q9NQL2; A8K184; Q7L8F9; Q9NPG0
Background:
Ras-related GTP-binding protein D plays a pivotal role in amino acid-induced activation of the mTORC1 signaling cascade. It forms heterodimeric Rag complexes, cycling between active and inactive forms, crucial for mTORC1 recruitment to lysosomes and activation.
Therapeutic significance:
Linked to Hypomagnesemia 7, a renal disorder with potential cardiomyopathy, understanding Ras-related GTP-binding protein D's role could unveil new therapeutic strategies.