Focused On-demand Libraries - Receptor.AI Collaboration


Explore the Potential with AI-Driven Innovation

This comprehensive focused library is produced on demand with state-of-the-art virtual screening and parameter assessment technology driven by Receptor.AI drug discovery platform. This approach outperforms traditional methods and provides higher-quality compounds with superior activity, selectivity and safety.


From a virtual chemical space containing more than 60 billion molecules, we precisely choose certain compounds. Reaxense aids in their synthesis and provision.


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.


 

Fig. 1. The screening 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.


Key features that set our library apart include:


  • The Receptor.AI platform integrates extensive information about the target protein, such as historical experiments, academic research, known ligands, and structural insights, thereby increasing the likelihood of identifying highly relevant compounds.

  • The platform’s sophisticated molecular simulations are designed to discover potential binding sites, ensuring that our focused library is optimal for the discovery of allosteric inhibitors and binders for cryptic pockets.

  • With over 50 customisable AI models, verified through extensive testing in commercial drug discovery and research, Receptor.AI is efficient, reliable, and precise. These models are essential in the production of our focused libraries.

  • Receptor.AI not only produces focused libraries but also provides full services and solutions at every stage of preclinical drug discovery, with a success-based pricing structure that aligns our interests with the success of your project.


PARTNER
Receptor.AI
 
UPACC
Q9Y3B4

UPID:
SF3B6_HUMAN

ALTERNATIVE NAMES:
Pre-mRNA branch site protein p14; SF3b 14 kDa subunit; Spliceosome-associated protein, 14-kDa; Splicing factor 3b, subunit 6, 14kDa

ALTERNATIVE UPACC:
Q9Y3B4; Q53TM1

BACKGROUND:
The Splicing factor 3B subunit 6, also referred to as SF3b 14 kDa subunit, is integral to the splicing factor SF3B complex, required for 'A' complex assembly in pre-mRNA splicing. It makes direct contact with the pre-mRNA branch site adenosine, a pivotal step in the splicing process, and is involved in the spliceosome's formation, facilitating the interaction of snRNP with branch sites.

THERAPEUTIC SIGNIFICANCE:
Exploring the functions of Splicing factor 3B subunit 6 unveils potential pathways for developing novel therapeutic approaches.

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