Focused On-demand Libraries - Receptor.AI 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 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 for receptors.


 

Fig. 1. The screening workflow of Receptor.AI

It features thorough molecular simulations of the receptor within its native membrane environment, complemented by ensemble virtual screening that considers its conformational mobility. For dimeric or oligomeric receptors, the full functional complex is constructed, and tentative binding sites are determined on and between the subunits to cover the entire spectrum of potential mechanisms of action.


Our library distinguishes itself through several key aspects:


  • The Receptor.AI platform integrates all available data about the target protein, including past experiments, literature data, known ligands, structural information and more. This consolidated approach maximises the probability of prioritising highly relevant compounds.

  • The platform uses sophisticated molecular simulations to identify possible binding sites so that the compounds in the focused library are suitable for discovering allosteric inhibitors and the binders for cryptic pockets.

  • The platform integrates over 50 highly customisable AI models, which are thoroughly tested and validated on a multitude of commercial drug discovery programs and research projects. It is designed to be efficient, reliable and accurate. All this power is utilised when producing the focused libraries.

  • In addition to producing the focused libraries, Receptor.AI provides services and end-to-end solutions at every stage of preclinical drug discovery. The pricing model is success-based, which reduces your risks and leverages the mutual benefits of the project's success.


PARTNER
Receptor.AI
 
UPACC
Q07011

UPID:
TNR9_HUMAN

ALTERNATIVE NAMES:
4-1BB ligand receptor; CDw137; T-cell antigen 4-1BB homolog; T-cell antigen ILA

ALTERNATIVE UPACC:
Q07011

BACKGROUND:
The protein Tumor necrosis factor receptor superfamily member 9, with alternative names such as 4-1BB ligand receptor and CDw137, is integral to immune system function. It acts as a receptor for TNFSF9/4-1BBL, enhancing the survival, cytotoxicity, and mitochondrial activity of CD8(+) T-cells, which are essential for combating viral infections and tumors.

THERAPEUTIC SIGNIFICANCE:
Understanding the role of Tumor necrosis factor receptor superfamily member 9 could open doors to potential therapeutic strategies for treating Immunodeficiency 109 with lymphoproliferation and other EBV-related lymphoproliferative disorders, offering hope for patients with these challenging conditions.

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