AI-ACCELERATED DRUG DISCOVERY

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

Available from Reaxense
Predicted by Alphafold

Focused On-demand Libraries - Reaxense Collaboration

Explore the Potential with AI-Driven Innovation

The focused library is created on demand with the latest virtual screening and parameter assessment technology, supported by the Receptor.AI drug discovery platform. This method is more effective than traditional methods and results in higher-quality compounds with better activity, selectivity, and safety.

We pick out particular compounds from an extensive virtual database of more than 60 billion molecules. The preparation and shipment of these compounds are facilitated by our associate Reaxense.

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.

We use our state-of-the-art dedicated workflow for designing focused libraries for enzymes.

 Fig. 1. The sreening workflow of Receptor.AI

The procedure entails thorough molecular simulations of the catalytic and allosteric binding pockets, accompanied by ensemble virtual screening that factors in their conformational flexibility. When developing modulators, the structural modifications brought about by reaction intermediates are factored in to optimize activity and selectivity.

Our library is unique due to several crucial aspects:

  • Receptor.AI compiles all relevant data on the target protein, such as past experimental results, literature findings, known ligands, and structural data, thereby enhancing the likelihood of focusing on the most significant compounds.
  • By utilizing advanced molecular simulations, the platform is adept at locating potential binding sites, rendering the compounds in the focused library well-suited for unearthing allosteric inhibitors and binders for hidden pockets.
  • The platform is supported by more than 50 highly specialized AI models, all of which have been rigorously tested and validated in diverse drug discovery and research programs. Its design emphasizes efficiency, reliability, and accuracy, crucial for producing focused libraries.
  • Receptor.AI extends beyond just creating focused libraries; it offers a complete spectrum of services and solutions during the preclinical drug discovery phase, with a success-dependent pricing strategy that reduces risk and fosters shared success in the project.

partner

Reaxense

upacc

O15111

UPID:

IKKA_HUMAN

Alternative names:

Conserved helix-loop-helix ubiquitous kinase; I-kappa-B kinase 1; Nuclear factor NF-kappa-B inhibitor kinase alpha; Transcription factor 16

Alternative UPACC:

O15111; O14666; Q13132; Q5W0I4; Q92467

Background:

Inhibitor of nuclear factor kappa-B kinase subunit alpha (IKK-alpha) is a serine kinase pivotal in the NF-kappa-B signaling pathway, activated by various stimuli. It phosphorylates inhibitors of NF-kappa-B, facilitating their degradation, thus freeing NF-kappa-B to activate genes involved in immune response and cell survival. IKK-alpha also plays a role in the non-canonical NF-kappa-B pathway, influencing B-cell survival and lymphoid organogenesis.

Therapeutic significance:

IKK-alpha's involvement in diseases like Cocoon syndrome and Bartsocas-Papas syndrome 2, due to gene variants, highlights its potential as a therapeutic target. Understanding IKK-alpha's role could open doors to novel treatments for these and related conditions.

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