Focused On-demand Library for Tumor suppressor candidate 3

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.

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.

We use our state-of-the-art dedicated workflow for designing focused 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

Q13454

UPID:

TUSC3_HUMAN

Alternative names:

Dolichyl-diphosphooligosaccharide--protein glycosyltransferase subunit TUSC3; Magnesium uptake/transporter TUSC3; Protein N33

Alternative UPACC:

Q13454; A8MSM0; D3DSP2; Q14911; Q14912; Q96FW0

Background:

Tumor suppressor candidate 3 (TUSC3) plays a crucial role in protein glycosylation, acting as an accessory component of the N-oligosaccharyl transferase (OST) complex. This complex is pivotal for transferring high mannose oligosaccharides to nascent polypeptide chains, a process essential for proper protein folding and stability. TUSC3 is also known for its function in magnesium transport, highlighting its multifaceted role in cellular physiology.

Therapeutic significance:

The association of TUSC3 with Intellectual developmental disorder, autosomal recessive 7, underscores its potential as a therapeutic target. Understanding the role of TUSC3 could open doors to potential therapeutic strategies, offering hope for interventions in genetic disorders linked to protein glycosylation defects.