AI-ACCELERATED DRUG DISCOVERY

Focused On-demand Library for tRNA (adenine(58)-N(1))-methyltransferase non-catalytic subunit TRM6

Available from Reaxense
Predicted by Alphafold

Focused On-demand Libraries - Reaxense Collaboration

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 effective modulators, each annotated with 38 ADME-Tox and 32 physicochemical and drug-likeness parameters. Furthermore, each compound is shown with its optimal docking poses, affinity scores, and activity scores, offering a detailed summary.

We use our state-of-the-art dedicated workflow for designing focused libraries.

 Fig. 1. The sreening workflow of Receptor.AI

Our strategy employs molecular simulations to explore an extensive range of proteins, capturing their dynamics both individually and within complexes with other proteins. Through ensemble virtual screening, we address proteins' conformational mobility, uncovering key binding sites at both functional regions and remote allosteric locations. This comprehensive investigation ensures a thorough assessment of all potential mechanisms of action, with the goal of discovering innovative therapeutic targets and lead molecules across across diverse biological functions.

Several key aspects differentiate our library:

  • Receptor.AI compiles an all-encompassing dataset on the target protein, including historical experiments, literature data, known ligands, and structural insights, maximising the chances of prioritising the most pertinent compounds.
  • The platform employs state-of-the-art molecular simulations to identify potential binding sites, ensuring the focused library is primed for discovering allosteric inhibitors and binders of concealed pockets.
  • Over 50 customisable AI models, thoroughly evaluated in various drug discovery endeavours and research projects, make Receptor.AI both efficient and accurate. This technology is integral to the development of our focused libraries.
  • In addition to generating focused libraries, Receptor.AI offers a full range of services and solutions for every step of preclinical drug discovery, with a pricing model based on success, thereby reducing risk and promoting joint project success.

partner

Reaxense

upacc

Q9UJA5

UPID:

TRM6_HUMAN

Alternative names:

mRNA methyladenosine-N(1)-methyltransferase non-catalytic subunit TRM6; tRNA(m1A58)-methyltransferase subunit TRM6

Alternative UPACC:

Q9UJA5; B4DUV6; Q76P92; Q9BQV5; Q9ULR7; Q9Y2Z8

Background:

The tRNA (adenine(58)-N(1))-methyltransferase non-catalytic subunit TRM6 plays a pivotal role in the post-transcriptional modification of RNA, specifically in the methylation of adenosine residues. This process is crucial for the proper functioning of tRNA and certain mRNAs, impacting protein synthesis and cellular function. TRM6, in collaboration with TRMT61A, facilitates the formation of N(1)-methyladenine at position 58 in initiator methionyl-tRNA, a modification essential for mRNA stability and translation efficiency.

Therapeutic significance:

Understanding the role of tRNA (adenine(58)-N(1))-methyltransferase non-catalytic subunit TRM6 could open doors to potential therapeutic strategies. Its involvement in RNA methylation presents a unique target for modulating gene expression and protein synthesis, offering avenues for the development of novel treatments in diseases where these processes are dysregulated.

Looking for more information on this library or underlying technology? Fill out the form below and we'll be in touch with all the details you need.
Thank you! Your submission has been received!
Oops! Something went wrong while submitting the form.