Focused On-demand Library for Probable methyltransferase TARBP1

Details

Focused On-demand Libraries - Receptor.AI Collaboration


Explore the Potential with AI-Driven Innovation

Our detailed focused library is generated on demand with advanced virtual screening and parameter assessment technology powered by the Receptor.AI drug discovery platform. This method surpasses traditional approaches, delivering compounds of better quality with enhanced 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 Reaxense.


The library features a range of promising modulators, each detailed with 38 ADME-Tox and 32 physicochemical and drug-likeness parameters. Plus, each compound is presented with its ideal docking poses, affinity scores, and activity scores, ensuring a thorough insight.


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


 

Fig. 1. The screening workflow of Receptor.AI

It includes in-depth molecular simulations of both the catalytic and allosteric binding pockets, with ensemble virtual screening focusing on their conformational flexibility. For modulators, the process includes considering the structural shifts due to reaction intermediates to boost activity and selectivity.


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
Receptor.AI
 
UPACC
Q13395

UPID:
TARB1_HUMAN

ALTERNATIVE NAMES:
TAR RNA-binding protein 1; TAR RNA-binding protein of 185 kDa

ALTERNATIVE UPACC:
Q13395; Q9H581

BACKGROUND:
The Probable methyltransferase TARBP1, known for its alternative names TAR RNA-binding protein 1 and TAR RNA-binding protein of 185 kDa, is implicated in the methylation of RNA molecules such as tRNAs. Its role in microbial infection, particularly in HIV-1, where it binds to TAR RNA and potentially affects the virus's replication by interacting with RNA polymerase II, underscores its significance in viral pathogenesis.

THERAPEUTIC SIGNIFICANCE:
Exploring the functions of Probable methyltransferase TARBP1 offers promising pathways for drug discovery. Given its critical role in RNA methylation and the HIV-1 lifecycle, targeting TARBP1 could lead to innovative treatments for HIV-1 and other RNA-based viral diseases.

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