AI-ACCELERATED DRUG DISCOVERY

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

Available from Reaxense
Predicted by Alphafold

Focused On-demand Libraries - Reaxense 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 our partner 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.

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

 Fig. 1. The sreening workflow of Receptor.AI

Our methodology employs molecular simulations to explore a wide array of proteins, capturing their dynamic states both individually and within complexes. Through ensemble virtual screening, we address conformational mobility, uncovering binding sites within functional regions and remote allosteric locations. This thorough exploration ensures no potential mechanism of action is overlooked, aiming to discover novel therapeutic targets and lead compounds across an extensive 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

Reaxense

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:

RNA-binding region-containing protein 3, also known as RNA-binding motif protein 40 and U11/U12 small nuclear ribonucleoprotein 65 kDa protein, plays a crucial role in pre-mRNA U12-dependent splicing. This process, carried out by the minor spliceosome, is essential for removing U12-type introns, which, although comprising less than 1% of all non-coding sequences, are vital for the correct expression of certain genes. The protein's ability to bind to the 3'-stem-loop of m(7)G-capped U12 snRNA underscores its significance in RNA processing.

Therapeutic significance:

RNA-binding region-containing protein 3 is implicated in Pituitary hormone deficiency, combined or isolated, 7, a condition characterized by severe postnatal growth failure and hypoplasia of the anterior pituitary. This association highlights the protein's potential as a target for therapeutic intervention in growth hormone deficiencies.

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