Focused On-demand Library for Pre-mRNA-processing factor 17

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.

We carefully select specific compounds from a vast collection of over 60 billion molecules in virtual chemical space. Our partner Reaxense helps in synthesizing and delivering these compounds.

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

Our methodology leverages molecular simulations to examine a vast array of proteins, capturing their dynamics in both isolated forms and in complexes with other proteins. Through ensemble virtual screening, we thoroughly account for the protein's conformational mobility, identifying critical binding sites within functional regions and distant allosteric locations. This detailed exploration ensures that we comprehensively assess every possible mechanism of action, with the objective of identifying novel therapeutic targets and lead compounds that span a wide 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

O60508

UPID:

PRP17_HUMAN

Alternative names:

Cell division cycle 40 homolog; EH-binding protein 3; PRP17 homolog

Alternative UPACC:

O60508; B2RBC5; O75471; Q5SRN0; Q9UPG1

Background:

Pre-mRNA-processing factor 17, also known as Cell division cycle 40 homolog, EH-binding protein 3, and PRP17 homolog, plays a crucial role in pre-mRNA splicing as part of the activated spliceosome. Its involvement in embryonic brain development, independent of proline isomerization, underscores its significance in cellular processes.

Therapeutic significance:

The protein's link to Pontocerebellar hypoplasia 15, characterized by severe brain structural defects and impaired intellectual development, highlights its therapeutic potential. Understanding the role of Pre-mRNA-processing factor 17 could open doors to potential therapeutic strategies for this debilitating condition.