Focused On-demand Libraries - Receptor.AI Collaboration


Explore the Potential with AI-Driven Innovation

This extensive focused library is tailor-made using the latest virtual screening and parameter assessment technology, operated by the Receptor.AI drug discovery platform. This technique is more effective than traditional methods, offering compounds with improved activity, selectivity, and safety.


We carefully select specific compounds from a vast collection of over 60 billion molecules in virtual chemical space. Reaxense helps in synthesizing and delivering these compounds.


The library features a range of promising modulators, each detailed with 38 ADME-Tox and 32 physicochemical and drug-likeness parameters. Plus, each compound is presented with its ideal docking poses, affinity scores, and activity scores, ensuring a thorough insight.


Our high-tech, dedicated method is applied to construct targeted libraries for receptors.


 

Fig. 1. The screening 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.


Key features that set our library apart include:


  • The Receptor.AI platform integrates extensive information about the target protein, such as historical experiments, academic research, known ligands, and structural insights, thereby increasing the likelihood of identifying highly relevant compounds.

  • The platform’s sophisticated molecular simulations are designed to discover potential binding sites, ensuring that our focused library is optimal for the discovery of allosteric inhibitors and binders for cryptic pockets.

  • With over 50 customisable AI models, verified through extensive testing in commercial drug discovery and research, Receptor.AI is efficient, reliable, and precise. These models are essential in the production of our focused libraries.

  • Receptor.AI not only produces focused libraries but also provides full services and solutions at every stage of preclinical drug discovery, with a success-based pricing structure that aligns our interests with the success of your project.


PARTNER
Receptor.AI
 
UPACC
O00253

UPID:
AGRP_HUMAN

ALTERNATIVE NAMES:
-

ALTERNATIVE UPACC:
O00253; O15459; Q2TBD9

BACKGROUND:
Agouti-related protein plays a significant role in weight homeostasis, controlling feeding behavior through its interaction with the central melanocortin system. It inhibits cAMP production by acting as an antagonist to melanocortin receptors, affecting energy balance and fat storage.

THERAPEUTIC SIGNIFICANCE:
The involvement of Agouti-related protein in obesity underscores its potential as a therapeutic target. By modulating AGRP activity, novel treatments for obesity and related metabolic disorders could be developed, offering hope for effective management.

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