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 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.


We employ our advanced, specialised process to create targeted libraries for enzymes.


 

Fig. 1. The screening workflow of Receptor.AI

It includes in-depth molecular simulations of both the catalytic and allosteric binding pockets, with ensemble virtual screening focusing on their conformational flexibility. For modulators, the process includes considering the structural shifts due to reaction intermediates to boost 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.


PARTNER
Receptor.AI
 
UPACC
Q16236

UPID:
NF2L2_HUMAN

ALTERNATIVE NAMES:
HEBP1; Nuclear factor, erythroid derived 2, like 2

ALTERNATIVE UPACC:
Q16236; B2RBU2; B4E338; E9PGJ7; Q53RW6; Q59HH2; Q96F71

BACKGROUND:
The protein Nuclear factor erythroid 2-related factor 2, also known as NFE2L2 or NRF2, acts as a master regulator of the antioxidant response. It enhances the expression of genes involved in detoxification and cellular defense mechanisms against oxidative damage. NRF2's activity is modulated through its interaction with KEAP1, which in the absence of stress signals targets NRF2 for degradation.

THERAPEUTIC SIGNIFICANCE:
Given its central role in managing oxidative stress and inflammation, NFE2L2/NRF2 is implicated in the pathogenesis of Immunodeficiency, developmental delay, and hypohomocysteinemia (IMDDHH). Targeting NFE2L2/NRF2 signaling could offer novel therapeutic avenues for treating diseases associated with oxidative stress.

Looking for more information on this library or underlying technology? Fill out the form below and we will be in touch with all the details you need.