Focused On-demand Libraries - Receptor.AI 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 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.


Our high-tech, dedicated method is applied to construct targeted libraries.


 

Fig. 1. The screening workflow of Receptor.AI

Utilising molecular simulations, our approach thoroughly examines a wide array of proteins, tracking their conformational changes individually and within complexes. Ensemble virtual screening enables us to address conformational flexibility, revealing essential binding sites at functional regions and allosteric locations. Our rigorous analysis guarantees that no potential mechanism of action is overlooked, aiming to uncover new therapeutic targets and lead compounds 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
Receptor.AI
 
UPACC
Q01081

UPID:
U2AF1_HUMAN

ALTERNATIVE NAMES:
U2 auxiliary factor 35 kDa subunit; U2 small nuclear RNA auxiliary factor 1; U2 snRNP auxiliary factor small subunit

ALTERNATIVE UPACC:
Q01081; Q701P4; Q71RF1

BACKGROUND:
The Splicing factor U2AF 35 kDa subunit, known for its essential roles in splicing by mediating crucial interactions for 3'-splice site selection, is a key player in the post-transcriptional regulation of gene expression. It acts as a bridge between U2AF2 and enhancer complexes, facilitating the recruitment of U2 snRNP to introns.

THERAPEUTIC SIGNIFICANCE:
Understanding the role of the Splicing factor U2AF 35 kDa subunit could open doors to potential therapeutic strategies, especially considering its involvement in Myelodysplastic syndrome through the disruption of normal splicing mechanisms. This insight offers a pathway to novel treatments for MDS and related hematopoietic disorders.

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