Focused On-demand Libraries - Receptor.AI Collaboration


Explore the Potential with AI-Driven Innovation

The specialised, focused library is developed on demand with the most recent virtual screening and parameter assessment technology, guided by the Receptor.AI drug discovery platform. This approach exceeds the capabilities of traditional methods and offers compounds with higher 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.


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.


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


 

Fig. 1. The screening workflow of Receptor.AI

The procedure entails thorough molecular simulations of the catalytic and allosteric binding pockets, accompanied by ensemble virtual screening that factors in their conformational flexibility. When developing modulators, the structural modifications brought about by reaction intermediates are factored in to optimize activity and selectivity.


Our library distinguishes itself through several key aspects:


  • The Receptor.AI platform integrates all available data about the target protein, including past experiments, literature data, known ligands, structural information and more. This consolidated approach maximises the probability of prioritising highly relevant compounds.

  • The platform uses sophisticated molecular simulations to identify possible binding sites so that the compounds in the focused library are suitable for discovering allosteric inhibitors and the binders for cryptic pockets.

  • The platform integrates over 50 highly customisable AI models, which are thoroughly tested and validated on a multitude of commercial drug discovery programs and research projects. It is designed to be efficient, reliable and accurate. All this power is utilised when producing the focused libraries.

  • In addition to producing the focused libraries, Receptor.AI provides services and end-to-end solutions at every stage of preclinical drug discovery. The pricing model is success-based, which reduces your risks and leverages the mutual benefits of the project's success.


PARTNER
Receptor.AI
 
UPACC
P22087

UPID:
FBRL_HUMAN

ALTERNATIVE NAMES:
34 kDa nucleolar scleroderma antigen; Histone-glutamine methyltransferase; U6 snRNA 2'-O-methyltransferase fibrillarin

ALTERNATIVE UPACC:
P22087; B5BUE8; O75259; Q6IAT5; Q9UPI6

BACKGROUND:
The protein rRNA 2'-O-methyltransferase fibrillarin, known for its roles as Histone-glutamine methyltransferase and U6 snRNA 2'-O-methyltransferase, is integral to the methylation of 'Gln-105' of histone H2A, affecting the binding of the FACT complex. This modification is present at the 35S ribosomal DNA locus, highlighting its importance in the structural and functional integrity of the ribosome. As part of the SSU processome, fibrillarin's activity is essential for the accurate assembly of the small eukaryotic ribosomal subunit.

THERAPEUTIC SIGNIFICANCE:
Understanding the role of rRNA 2'-O-methyltransferase fibrillarin could open doors to potential therapeutic strategies.

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