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.


We pick out particular compounds from an extensive virtual database of more than 60 billion molecules. The preparation and shipment of these compounds are 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 utilise our cutting-edge, exclusive workflow to develop focused libraries for enzymes.


 

Fig. 1. The screening workflow of Receptor.AI

The method includes detailed molecular simulations of the catalytic and allosteric binding pockets, along with ensemble virtual screening that considers their conformational flexibility. In the design of modulators, structural changes induced by reaction intermediates are taken into account to enhance activity and selectivity.


Several key aspects differentiate our library:


  • Receptor.AI compiles an all-encompassing dataset on the target protein, including historical experiments, literature data, known ligands, and structural insights, maximising the chances of prioritising the most pertinent compounds.

  • The platform employs state-of-the-art molecular simulations to identify potential binding sites, ensuring the focused library is primed for discovering allosteric inhibitors and binders of concealed pockets.

  • Over 50 customisable AI models, thoroughly evaluated in various drug discovery endeavours and research projects, make Receptor.AI both efficient and accurate. This technology is integral to the development of our focused libraries.

  • In addition to generating focused libraries, Receptor.AI offers a full range of services and solutions for every step of preclinical drug discovery, with a pricing model based on success, thereby reducing risk and promoting joint project success.


PARTNER
Receptor.AI
 
UPACC
O00300

UPID:
TR11B_HUMAN

ALTERNATIVE NAMES:
Osteoclastogenesis inhibitory factor; Osteoprotegerin

ALTERNATIVE UPACC:
O00300; B2R9A8; O60236; Q53FX6; Q9UHP4

BACKGROUND:
Osteoclastogenesis inhibitory factor, or Osteoprotegerin, serves as a critical regulator in preventing arterial calcification and bone loss by binding to TNFSF11/RANKL and TNFSF10/TRAIL, blocking osteoclastogenesis and protecting against apoptosis. This balance is essential for bone and vascular health.

THERAPEUTIC SIGNIFICANCE:
Osteoprotegerin's involvement in juvenile-onset Paget disease of bone 5, through gene variants affecting its function, underscores its therapeutic potential. Targeting the pathways modulated by Osteoprotegerin could offer new avenues for treating bone remodeling disorders and preventing arterial calcification.

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