Focused On-demand Libraries - Receptor.AI Collaboration


Explore the Potential with AI-Driven Innovation

The specialised, focused library is developed on demand with the most recent virtual screening and parameter assessment technology, guided by the Receptor.AI drug discovery platform. This approach exceeds the capabilities of traditional methods and offers compounds with higher 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 includes a list of the most promising modulators annotated with 38 ADME-Tox and 32 physicochemical and drug-likeness parameters. Also, each compound is presented with its optimal docking poses, affinity scores, and activity scores, providing a comprehensive overview.


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


 

Fig. 1. The screening 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
Receptor.AI
 
UPACC
P04150

UPID:
GCR_HUMAN

ALTERNATIVE NAMES:
Nuclear receptor subfamily 3 group C member 1

ALTERNATIVE UPACC:
P04150; A0ZXF9; B0LPG8; D3DQF4; F5ATB7; P04151; Q53EP5; Q6N0A4

BACKGROUND:
Nuclear receptor subfamily 3 group C member 1, also known as the Glucocorticoid Receptor, is integral to glucocorticoid hormone action. It modulates gene expression, affecting processes from inflammation to cell growth, and is involved in glucose metabolism and apoptosis. Its activity varies across different isoforms, indicating a complex regulatory mechanism.

THERAPEUTIC SIGNIFICANCE:
Given its involvement in Glucocorticoid resistance, generalized, the Glucocorticoid Receptor presents a critical target for drug discovery. Understanding the role of this receptor could open doors to potential therapeutic strategies, particularly in managing disorders of cortisol imbalance and enhancing patient outcomes.

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