Focused On-demand Library for Small nuclear ribonucleoprotein E

Focused On-demand Libraries - Reaxense 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.

We pick out particular compounds from an extensive virtual database of more than 60 billion molecules. The preparation and shipment of these compounds are facilitated by our associate Reaxense.

The library features a range of promising modulators, each detailed with 38 ADME-Tox and 32 physicochemical and drug-likeness parameters. Plus, each compound is presented with its ideal docking poses, affinity scores, and activity scores, ensuring a thorough insight.

We employ our advanced, specialised process to create targeted libraries.

Fig. 1. The sreening workflow of Receptor.AI

Utilising molecular simulations, our approach thoroughly examines a wide array of proteins, tracking their conformational changes individually and within complexes. Ensemble virtual screening enables us to address conformational flexibility, revealing essential binding sites at functional regions and allosteric locations. Our rigorous analysis guarantees that no potential mechanism of action is overlooked, aiming to uncover new therapeutic targets and lead compounds across diverse 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

P62304

UPID:

RUXE_HUMAN

Alternative names:

Sm protein E

Alternative UPACC:

P62304; B2R5B9; P08578; Q15498; Q5BKT2

Background:

Small nuclear ribonucleoprotein E (Sm protein E) is a core component of the spliceosomal U1, U2, U4, and U5 small nuclear ribonucleoproteins (snRNPs), playing a crucial role in pre-mRNA splicing. It is involved in the building blocks of the spliceosome, participating in both the pre-catalytic spliceosome B complex and activated spliceosome C complexes. Additionally, it contributes to the splicing of U12-type introns in pre-mRNAs and is part of the U7 snRNP involved in histone 3'-end processing.

Therapeutic significance:

Sm protein E's involvement in Hypotrichosis 11, a condition characterized by reduced hair quantity and abnormal follicles, highlights its potential as a therapeutic target. Understanding the role of Small nuclear ribonucleoprotein E could open doors to potential therapeutic strategies for hair growth disorders.