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.


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.


Contained in the library are leading modulators, each labelled with 38 ADME-Tox and 32 physicochemical and drug-likeness qualities. In addition, each compound is illustrated with its optimal docking poses, affinity scores, and activity scores, giving a complete picture.


Our high-tech, dedicated method is applied to construct targeted 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
P83369

UPID:
LSM11_HUMAN

ALTERNATIVE NAMES:
-

ALTERNATIVE UPACC:
P83369; A0AVQ1; Q7Z7P0; Q8N975

BACKGROUND:
The U7 snRNA-associated Sm-like protein LSm11 is integral to the histone 3'-end pre-mRNA processing mechanism, impacting chromatin structure and gene expression. Its function in the U7 snRNP complex and specific binding to U7 snRNA's Sm-binding site are critical for transitioning cells from the G1 to S phase, highlighting its importance in cellular proliferation and maintenance.

THERAPEUTIC SIGNIFICANCE:
Given LSm11's critical role in the pathogenesis of Aicardi-Goutieres syndrome 8 through impaired histone processing and activation of autoinflammatory pathways, it represents a promising target for therapeutic intervention. Exploring LSm11's function could open doors to potential therapeutic strategies, offering new avenues for treating autoinflammatory and neurological disorders.

Looking for more information on this library or underlying technology? Fill out the form below and we will be in touch with all the details you need.