Focused On-demand Library for Zinc finger C4H2 domain-containing protein

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.


Contained in the library are leading modulators, each labelled with 38 ADME-Tox and 32 physicochemical and drug-likeness qualities. In addition, each compound is illustrated with its optimal docking poses, affinity scores, and activity scores, giving a complete picture.


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


 

Fig. 1. The screening workflow of Receptor.AI

By deploying molecular simulations, our approach comprehensively covers a broad array of proteins, tracking their flexibility and dynamics individually and within complexes. Ensemble virtual screening is utilised to take into account conformational dynamics, identifying pivotal binding sites located within functional regions and at allosteric locations. This thorough exploration ensures that every conceivable mechanism of action is considered, aiming to identify new therapeutic targets and advance lead compounds throughout a vast spectrum of biological functions.


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
Q9NQZ6

UPID:
ZC4H2_HUMAN

ALTERNATIVE NAMES:
Hepatocellular carcinoma-associated antigen 127

ALTERNATIVE UPACC:
Q9NQZ6; B2RDC2; B3KVZ5; B4DED0; E7EM74; G3V1L3; Q53H73; Q5JTF9; Q9H9C3; Q9H9H7; Q9ULQ4

BACKGROUND:
Hepatocellular carcinoma-associated antigen 127, with its alternative name Zinc finger C4H2 domain-containing protein, is instrumental in interneurons differentiation and plays a significant role in the development of neurons and the formation of neuromuscular junctions. This protein's function is vital for the proper functioning of both the central and peripheral nervous systems.

THERAPEUTIC SIGNIFICANCE:
Given its association with Wieacker-Wolf syndrome and the female-restricted variant of Wieacker-Wolff syndrome, the Zinc finger C4H2 domain-containing protein is a key target for research into neurodevelopmental disorders. These diseases, marked by early-onset muscle weakness and developmental challenges, underscore the therapeutic potential of targeting this protein.

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