Focused On-demand Library for RNA-binding region-containing protein 3

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.


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.


The library includes a list of the most effective modulators, each annotated with 38 ADME-Tox and 32 physicochemical and drug-likeness parameters. Furthermore, each compound is shown with its optimal docking poses, affinity scores, and activity scores, offering a detailed summary.


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 stands out due to several important features:


  • The Receptor.AI platform compiles comprehensive data on the target protein, encompassing previous experiments, literature, known ligands, structural details, and more, leading to a higher chance of selecting the most relevant compounds.

  • Advanced molecular simulations on the platform help pinpoint potential binding sites, making the compounds in our focused library ideal for finding allosteric inhibitors and targeting cryptic pockets.

  • Receptor.AI boasts over 50 tailor-made AI models, rigorously tested and proven in various drug discovery projects and research initiatives. They are crafted for efficacy, dependability, and precision, all of which are key in creating our focused libraries.

  • Beyond creating focused libraries, Receptor.AI offers comprehensive services and complete solutions throughout the preclinical drug discovery phase. Our success-based pricing model minimises risk and maximises the mutual benefits of the project's success.

PARTNER
Receptor.AI
 
UPACC
Q96LT9

UPID:
RNPC3_HUMAN

ALTERNATIVE NAMES:
RNA-binding motif protein 40; U11/U12 small nuclear ribonucleoprotein 65 kDa protein

ALTERNATIVE UPACC:
Q96LT9; A8K1C9; D3DT74; Q5TZ87; Q96FK7; Q96JI8; Q9NSU7; Q9NXX2

BACKGROUND:
The RNA-binding region-containing protein 3, with alternative names RNA-binding motif protein 40 and U11/U12 small nuclear ribonucleoprotein 65 kDa protein, is integral to the minor spliceosome's function of excising U12-type introns from pre-mRNA. These introns, though rare, are critical for the proper functioning of certain genes. The protein's specific interaction with the 3'-stem-loop of m(7)G-capped U12 snRNA is a key aspect of its role in RNA splicing.

THERAPEUTIC SIGNIFICANCE:
Understanding the role of RNA-binding region-containing protein 3 could open doors to potential therapeutic strategies, especially considering its involvement in Pituitary hormone deficiency, combined or isolated, 7. This disease's link to the protein offers a promising avenue for exploring treatments aimed at correcting growth hormone deficiencies.

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