Focused On-demand Library for Tumor necrosis factor ligand superfamily member 11

Available from Reaxense
Predicted by Alphafold

Focused On-demand Libraries - Reaxense Collaboration

Explore the Potential with AI-Driven Innovation

The focused library is created on demand with the latest virtual screening and parameter assessment technology, supported by the Receptor.AI drug discovery platform. This method is more effective than traditional methods and results in higher-quality compounds with better 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.

Contained in the library are leading modulators, each labelled with 38 ADME-Tox and 32 physicochemical and drug-likeness qualities. In addition, each compound is illustrated with its optimal docking poses, affinity scores, and activity scores, giving a complete picture.

We utilise our cutting-edge, exclusive workflow to develop focused libraries for enzymes.

 Fig. 1. The sreening workflow of Receptor.AI

The procedure entails thorough molecular simulations of the catalytic and allosteric binding pockets, accompanied by ensemble virtual screening that factors in their conformational flexibility. When developing modulators, the structural modifications brought about by reaction intermediates are factored in to optimize activity and selectivity.

Our library stands out due to several important features:

  • The Receptor.AI platform compiles comprehensive data on the target protein, encompassing previous experiments, literature, known ligands, structural details, and more, leading to a higher chance of selecting the most relevant compounds.
  • Advanced molecular simulations on the platform help pinpoint potential binding sites, making the compounds in our focused library ideal for finding allosteric inhibitors and targeting cryptic pockets.
  • Receptor.AI boasts over 50 tailor-made AI models, rigorously tested and proven in various drug discovery projects and research initiatives. They are crafted for efficacy, dependability, and precision, all of which are key in creating our focused libraries.
  • Beyond creating focused libraries, Receptor.AI offers comprehensive services and complete solutions throughout the preclinical drug discovery phase. Our success-based pricing model minimises risk and maximises the mutual benefits of the project's success.







Alternative names:

Osteoclast differentiation factor; Osteoprotegerin ligand; Receptor activator of nuclear factor kappa-B ligand; TNF-related activation-induced cytokine

Alternative UPACC:

O14788; O14723; Q96Q17; Q9P2Q3


Tumor necrosis factor ligand superfamily member 11, also known as Osteoclast differentiation factor, plays a pivotal role in bone metabolism. It binds to TNFRSF11B/OPG and TNFRSF11A/RANK, promoting osteoclast differentiation and activation. This protein is crucial for the regulation of T-cell-dependent immune responses and bone resorption in diseases like humoral hypercalcemia of malignancy.

Therapeutic significance:

Given its central role in osteoclastogenesis and bone metabolism, targeting Tumor necrosis factor ligand superfamily member 11 offers a promising avenue for treating Osteopetrosis, autosomal recessive 2. This rare genetic disease, characterized by defective bone resorption, highlights the therapeutic potential of modulating this protein's activity.

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.
No Spam. Cancel Anytime.