AI-ACCELERATED DRUG DISCOVERY

Focused On-demand Library for Tumor necrosis factor receptor superfamily member 9

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 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 includes a list of the most promising modulators annotated with 38 ADME-Tox and 32 physicochemical and drug-likeness parameters. Also, each compound is presented with its optimal docking poses, affinity scores, and activity scores, providing a comprehensive overview.

We employ our advanced, specialised process to create targeted libraries for receptors.

 Fig. 1. The sreening workflow of Receptor.AI

This includes comprehensive molecular simulations of the receptor in its native membrane environment, paired with ensemble virtual screening that factors in its conformational mobility. In cases involving dimeric or oligomeric receptors, the entire functional complex is modelled, pinpointing potential binding pockets on and between the subunits to capture the full range of 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

Reaxense

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:

Tumor necrosis factor receptor superfamily member 9 (TNFRSF9), also known as 4-1BB ligand receptor, CDw137, T-cell antigen 4-1BB homolog, and T-cell antigen ILA, plays a pivotal role in enhancing CD8(+) T-cell survival, cytotoxicity, and mitochondrial activity. This receptor's interaction with TNFSF9/4-1BBL is crucial for promoting immunity against viruses and tumors, highlighting its significance in the immune response.

Therapeutic significance:

TNFRSF9's involvement in Immunodeficiency 109 with lymphoproliferation, a primary immune disorder characterized by recurrent infections and susceptibility to Epstein-Barr virus, underscores its therapeutic potential. Targeting TNFRSF9 could lead to innovative treatments for immune disorders and EBV-related conditions.

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