Focused On-demand Libraries - Receptor.AI Collaboration


Explore the Potential with AI-Driven Innovation

Our detailed focused library is generated on demand with advanced virtual screening and parameter assessment technology powered by the Receptor.AI drug discovery platform. This method surpasses traditional approaches, delivering compounds of better quality with enhanced activity, selectivity, and safety.


Our selection of compounds is from a large virtual library of over 60 billion molecules. The production and distribution of these compounds are managed 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.


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


 

Fig. 1. The screening workflow of Receptor.AI

By deploying molecular simulations, our approach comprehensively covers a broad array of proteins, tracking their flexibility and dynamics individually and within complexes. Ensemble virtual screening is utilised to take into account conformational dynamics, identifying pivotal binding sites located within functional regions and at allosteric locations. This thorough exploration ensures that every conceivable mechanism of action is considered, aiming to identify new therapeutic targets and advance lead compounds throughout a vast spectrum of biological functions.


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
Q15646

UPID:
OASL_HUMAN

ALTERNATIVE NAMES:
2'-5'-OAS-related protein; 59 kDa 2'-5'-oligoadenylate synthase-like protein; Thyroid receptor-interacting protein 14; p59 OASL

ALTERNATIVE UPACC:
Q15646; B2RAZ2; I1YDD2; O75686; Q17R95; Q9Y6K6; Q9Y6K7

BACKGROUND:
2'-5'-oligoadenylate synthase-like protein, also referred to as Thyroid receptor-interacting protein 14 or p59 OASL, is distinguished by its ability to bind double-stranded RNA without exhibiting 2'-5'-OAS activity. It effectively counters viral infections such as encephalomyocarditis virus and hepatitis C virus through a distinctive antiviral pathway that does not involve RNase L.

THERAPEUTIC SIGNIFICANCE:
Exploring the function of 2'-5'-oligoadenylate synthase-like protein unveils potential avenues for therapeutic intervention. Its antiviral properties, independent of the RNase L pathway, make it a promising candidate for the development of innovative antiviral drugs.

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