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 pick out particular compounds from an extensive virtual database of more than 60 billion molecules. The preparation and shipment of these compounds are facilitated by our associate Reaxense.
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.
Our top-notch dedicated system is used to design specialised 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
Q9BU70
UPID:
TRMO_HUMAN
Alternative names:
tRNA methyltransferase O
Alternative UPACC:
Q9BU70; Q5T113; Q86SK0; Q9NXJ7; Q9P0Q7
Background:
tRNA (adenine(37)-N6)-methyltransferase, also known as tRNA methyltransferase O, plays a crucial role in the post-transcriptional modification of tRNA. It is responsible for the methylation of N6-methyl-N6-threonylcarbamoyladenosine at position 37 of the tRNA anticodon loop of tRNA(Ser)(GCU), a modification that enhances the decoding efficiency of tRNA.
Therapeutic significance:
Understanding the role of tRNA (adenine(37)-N6)-methyltransferase could open doors to potential therapeutic strategies.