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.


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.


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
O43593

UPID:
HAIR_HUMAN

ALTERNATIVE NAMES:
[histone H3]-dimethyl-L-lysine(9) demethylase hairless

ALTERNATIVE UPACC:
O43593; Q6GS30; Q96H33; Q9NPE1

BACKGROUND:
Lysine-specific demethylase hairless, alternatively named [histone H3]-dimethyl-L-lysine(9) demethylase hairless, is crucial for histone H3 'Lys-9' demethylation. This activity is essential for regulating transcription, hair follicle biology, neural functions, and cell proliferation.

THERAPEUTIC SIGNIFICANCE:
Given its association with conditions like Alopecia universalis congenita, Atrichia with papular lesions, and Hypotrichosis 4, exploring the function of Lysine-specific demethylase hairless presents a promising avenue for developing treatments for these genetic hair loss conditions.

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