Focused On-demand Library for Protein SLFN14

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.

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 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

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

P0C7P3

UPID:

SLN14_HUMAN

Alternative names:

Alternative UPACC:

P0C7P3; B2RTW9

Background:

Protein SLFN14, devoid of ribosome-associated and endoribonuclease activities, exhibits a unique role in RNA surveillance pathways. It is known for its polysome-associated endoribonuclease activity, crucial for the cleavage of aberrant mRNAs and rRNAs, facilitating RNA quality control in a magnesium- and manganese-dependent manner. This protein is pivotal in the maturation of megakaryocytes, essential for proplatelet extension.

Therapeutic significance:

SLFN14's mutation is linked to Bleeding disorder, platelet-type, 20, characterized by thrombocytopenia and platelet secretion defects. Understanding the role of Protein SLFN14 could open doors to potential therapeutic strategies for managing bleeding disorders by targeting the underlying genetic and molecular pathways.