Focused On-demand Library for Tumor necrosis factor ligand superfamily member 15

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.

Our selection of compounds is from a large virtual library of over 60 billion molecules. The production and distribution of these compounds are managed by our partner 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 employ our advanced, specialised process to create targeted libraries for enzymes.

 Fig. 1. The sreening workflow of Receptor.AI

This approach involves comprehensive molecular simulations of the catalytic and allosteric binding pockets and ensemble virtual screening that accounts for their conformational flexibility. In the case of designing modulators, the structural adjustments caused by reaction intermediates are considered to improve activity and selectivity.

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.







Alternative names:

TNF ligand-related molecule 1; Vascular endothelial cell growth inhibitor

Alternative UPACC:

O95150; Q3SX69; Q5VJK8; Q5VWH1; Q8NFE9


Tumor necrosis factor ligand superfamily member 15, also known as TNF ligand-related molecule 1 and Vascular endothelial cell growth inhibitor, is identified by the accession number O95150. This protein serves as a receptor for TNFRSF25 and TNFRSF6B, playing a crucial role in mediating the activation of NF-kappa-B. It is known for its ability to inhibit vascular endothelial growth and angiogenesis in vitro, alongside promoting the activation of caspases and apoptosis.

Therapeutic significance:

Understanding the role of Tumor necrosis factor ligand superfamily member 15 could open doors to potential therapeutic strategies. Its involvement in inhibiting angiogenesis and promoting apoptosis highlights its potential as a target in cancer therapy and diseases characterized by abnormal cell growth.

Looking for more information on this library or underlying technology? Fill out the form below and we'll be in touch with all the details you need.
Thank you! Your submission has been received!
Oops! Something went wrong while submitting the form.