Focused On-demand Libraries - Receptor.AI Collaboration


Explore the Potential with AI-Driven Innovation

The focused library is created on demand with the latest virtual screening and parameter assessment technology, supported by the Receptor.AI drug discovery platform. This method is more effective than traditional methods and results in higher-quality compounds with better activity, selectivity, and safety.


The compounds are cherry-picked from the vast virtual chemical space of over 60B molecules. The synthesis and delivery of compounds is facilitated by Reaxense.


In the library, a selection of top modulators is provided, each marked with 38 ADME-Tox and 32 parameters related to physicochemical properties and drug-likeness. Also, every compound comes with its best docking poses, affinity scores, and activity scores, providing a comprehensive overview.


Our top-notch dedicated system is used to design specialised 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.


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
Q9UHB7

UPID:
AFF4_HUMAN

ALTERNATIVE NAMES:
ALL1-fused gene from chromosome 5q31 protein; Major CDK9 elongation factor-associated protein

ALTERNATIVE UPACC:
Q9UHB7; B2RP19; B7WPD2; Q498B2; Q59FB3; Q6P592; Q8TDR1; Q9P0E4

BACKGROUND:
The protein AF4/FMR2 family member 4, known for its alternative names such as Major CDK9 elongation factor-associated protein, is a key component of the SEC. It boosts the RNA polymerase II transcription process by reducing pausing at DNA sites. AFF4's role as a scaffold in the SEC is crucial for the assembly of ELL proteins and the P-TEFb complex, which is further exploited by HIV-1 to enhance viral gene expression.

THERAPEUTIC SIGNIFICANCE:
Given its link to CHOPS syndrome, a disorder marked by a spectrum of physical and cognitive impairments, the study of AFF4 is of paramount importance. Understanding the role of AFF4 could open doors to potential therapeutic strategies, offering hope for advancements in treatment options.

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