Focused On-demand Library for Cytokine-like nuclear factor N-PAC

Available from Reaxense
Predicted by Alphafold

Focused On-demand Libraries - Reaxense Collaboration

Explore the Potential with AI-Driven Innovation

This comprehensive focused library is produced on demand with state-of-the-art virtual screening and parameter assessment technology driven by Receptor.AI drug discovery platform. This approach outperforms traditional methods and provides higher-quality compounds with superior activity, selectivity and safety.

From a virtual chemical space containing more than 60 billion molecules, we precisely choose certain compounds. Our collaborator, Reaxense, aids in their synthesis and provision.

In the library, a selection of top modulators is provided, each marked with 38 ADME-Tox and 32 parameters related to physicochemical properties and drug-likeness. Also, every compound comes with its best docking poses, affinity scores, and activity scores, providing a comprehensive overview.

Our top-notch dedicated system is used to design specialised libraries.

 Fig. 1. The sreening workflow of Receptor.AI

Our methodology leverages molecular simulations to examine a vast array of proteins, capturing their dynamics in both isolated forms and in complexes with other proteins. Through ensemble virtual screening, we thoroughly account for the protein's conformational mobility, identifying critical binding sites within functional regions and distant allosteric locations. This detailed exploration ensures that we comprehensively assess every possible mechanism of action, with the objective of identifying novel therapeutic targets and lead compounds that span a wide 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.







Alternative names:

3-hydroxyisobutyrate dehydrogenase-like protein; Glyoxylate reductase 1 homolog; Nuclear protein NP60; Nuclear protein of 60 kDa; Nucleosome-destabilizing factor; Putative oxidoreductase GLYR1

Alternative UPACC:

Q49A26; B4DL47; C9JJ40; C9JJ60; Q5U632; Q6P1Q2; Q6V3W7; Q9BTI1; Q9BXK2


Cytokine-like nuclear factor N-PAC, known for its diverse roles in chromatin modification and gene expression regulation, is a pivotal player in cellular biology. This protein, also referred to as 3-hydroxyisobutyrate dehydrogenase-like protein, Glyoxylate reductase 1 homolog, and several other names, exhibits a unique ability to bind histone H3 and DNA, facilitating transcriptional activation. Its interaction with KDM1B enhances histone demethylase activity, crucial for chromatin remodeling and efficient transcription through nucleosomes. N-PAC's role in heart development and stress response via MAPK14/p38alpha regulation underscores its multifunctional nature.

Therapeutic significance:

Understanding the role of Cytokine-like nuclear factor N-PAC could open doors to potential therapeutic strategies.

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