AI-ACCELERATED DRUG DISCOVERY

Focused On-demand Library for UL16-binding protein 3

Available from Reaxense
Predicted by Alphafold

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 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.

In the library, a selection of top modulators is provided, each marked with 38 ADME-Tox and 32 parameters related to physicochemical properties and drug-likeness. Also, every compound comes with its best docking poses, affinity scores, and activity scores, providing a comprehensive overview.

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

Q9BZM4

UPID:

ULBP3_HUMAN

Alternative names:

ALCAN-gamma; NKG2D ligand 3; Retinoic acid early transcript 1N

Alternative UPACC:

Q9BZM4; Q5VY82; Q8IZX5; Q8TE75

Background:

UL16-binding protein 3, also known as ALCAN-gamma, NKG2D ligand 3, and Retinoic acid early transcript 1N, plays a pivotal role in immune surveillance. It binds and activates the KLRK1/NKG2D receptor, a critical component in mediating natural killer cell cytotoxicity. This interaction is fundamental in the immune system's ability to recognize and eliminate malignant cells.

Therapeutic significance:

Understanding the role of UL16-binding protein 3 could open doors to potential therapeutic strategies. Its involvement in activating natural killer cells suggests its potential in cancer immunotherapy, offering a promising avenue for research and development in targeted cancer treatments.

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