AI-ACCELERATED DRUG DISCOVERY

Focused On-demand Library for Tumor necrosis factor receptor superfamily member 13C

Available from Reaxense
Predicted by Alphafold

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.

From a virtual chemical space containing more than 60 billion molecules, we precisely choose certain compounds. Our collaborator, Reaxense, aids in their synthesis and provision.

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 sreening 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

Reaxense

upacc

Q96RJ3

UPID:

TR13C_HUMAN

Alternative names:

B-cell-activating factor receptor; BAFF receptor; BLyS receptor 3

Alternative UPACC:

Q96RJ3

Background:

Tumor necrosis factor receptor superfamily member 13C, also known as the B-cell-activating factor receptor (BAFF receptor), plays a pivotal role in B-cell survival and response. It specifically binds to TNFSF13B/BAFF, promoting mature B-cell survival and enhancing the B-cell response. This receptor is crucial for B-cell differentiation and immunoglobulin secretion.

Therapeutic significance:

The protein is directly linked to Immunodeficiency, common variable, 4, a disease characterized by antibody deficiency and recurrent bacterial infections due to impaired B-cell differentiation. Understanding the role of Tumor necrosis factor receptor superfamily member 13C could open doors to potential therapeutic strategies for treating immunodeficiency disorders.

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