AI-ACCELERATED DRUG DISCOVERY

Focused On-demand Library for NF-kappa-B essential modulator

Available from Reaxense
Predicted by Alphafold

Focused On-demand Libraries - Reaxense 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.

The compounds are cherry-picked from the vast virtual chemical space of over 60B molecules. The synthesis and delivery of compounds is facilitated by our partner Reaxense.

The library includes a list of the most effective modulators, each annotated with 38 ADME-Tox and 32 physicochemical and drug-likeness parameters. Furthermore, each compound is shown with its optimal docking poses, affinity scores, and activity scores, offering a detailed summary.

We utilise our cutting-edge, exclusive workflow to develop focused libraries for enzymes.

 Fig. 1. The sreening workflow of Receptor.AI

The method includes detailed molecular simulations of the catalytic and allosteric binding pockets, along with ensemble virtual screening that considers their conformational flexibility. In the design of modulators, structural changes induced by reaction intermediates are taken into account to enhance 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

Reaxense

upacc

Q9Y6K9

UPID:

NEMO_HUMAN

Alternative names:

FIP-3; IkB kinase-associated protein 1; Inhibitor of nuclear factor kappa-B kinase subunit gamma; NF-kappa-B essential modifier

Alternative UPACC:

Q9Y6K9; Q7LBY6; Q7Z7F1

Background:

NF-kappa-B essential modulator (NEMO), also known as Inhibitor of nuclear factor kappa-B kinase subunit gamma, plays a pivotal role in the NF-kappa-B signaling pathway. This pathway is crucial for immune response, cell survival, and inflammation. NEMO facilitates the activation of NF-kappa-B by mediating the phosphorylation and degradation of its inhibitors. It uniquely binds to both 'Lys-63'-linked and linear polyubiquitin, with a preference for the latter, highlighting its versatile role in cellular signaling.

Therapeutic significance:

NEMO is implicated in a range of diseases, including Ectodermal dysplasia and immunodeficiency, Immunodeficiency 33, Incontinentia pigmenti, and systemic autoinflammatory disease. These conditions underscore the protein's critical role in immune regulation and development. Understanding NEMO's function could pave the way for innovative treatments targeting these genetic disorders, offering hope for affected individuals.

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