Focused On-demand Library for Pre-mRNA-splicing factor RBM22

Focused On-demand Libraries - Reaxense 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.

From a virtual chemical space containing more than 60 billion molecules, we precisely choose certain compounds. Our collaborator, Reaxense, aids in their synthesis and provision.

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

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.

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

Reaxense

upacc

Q9NW64

UPID:

RBM22_HUMAN

Alternative names:

RNA-binding motif protein 22; Zinc finger CCCH domain-containing protein 16

Alternative UPACC:

Q9NW64; A6NDM5; B4DLI9; O95607

Background:

Pre-mRNA-splicing factor RBM22, also known as RNA-binding motif protein 22 and Zinc finger CCCH domain-containing protein 16, plays a crucial role in pre-mRNA splicing as part of the activated spliceosome. It is essential for the first step of pre-mRNA splicing, binding directly to the U6 snRNA's internal stem-loop domain and the pre-mRNA intron near the 5' splice site. This protein is involved in key cellular stress responses, facilitating the translocation of nuclear and cytosolic proteins.

Therapeutic significance:

Understanding the role of Pre-mRNA-splicing factor RBM22 could open doors to potential therapeutic strategies.