Focused On-demand Library for Inhibitor of nuclear factor kappa-B kinase subunit beta

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.

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.

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.

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

 Fig. 1. The sreening 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.







Alternative names:

I-kappa-B kinase 2; Nuclear factor NF-kappa-B inhibitor kinase beta; Serine/threonine protein kinase IKBKB

Alternative UPACC:

O14920; B4DZ30; B4E0U4; O75327


Inhibitor of nuclear factor kappa-B kinase subunit beta (IKBKB) is a pivotal serine kinase in the NF-kappa-B signaling pathway, activated by various stimuli including inflammatory cytokines and cellular stresses. It phosphorylates NF-kappa-B inhibitors, leading to their degradation and the subsequent activation of NF-kappa-B, a transcription factor vital for immune response and cell survival.

Therapeutic significance:

IKBKB's role in immune response regulation is linked to diseases such as Immunodeficiency 15A and 15B, characterized by severe infections and immune system dysfunction. Targeting IKBKB could offer novel therapeutic strategies for these primary immunodeficiency disorders.

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