AI-ACCELERATED DRUG DISCOVERY

Focused On-demand Library for Nuclear factor NF-kappa-B p100 subunit

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.

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.

The library features a range of promising modulators, each detailed with 38 ADME-Tox and 32 physicochemical and drug-likeness parameters. Plus, each compound is presented with its ideal docking poses, affinity scores, and activity scores, ensuring a thorough insight.

We utilise our cutting-edge, exclusive workflow to develop 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.

Key features that set our library apart include:

  • The Receptor.AI platform integrates extensive information about the target protein, such as historical experiments, academic research, known ligands, and structural insights, thereby increasing the likelihood of identifying highly relevant compounds.
  • The platform’s sophisticated molecular simulations are designed to discover potential binding sites, ensuring that our focused library is optimal for the discovery of allosteric inhibitors and binders for cryptic pockets.
  • With over 50 customisable AI models, verified through extensive testing in commercial drug discovery and research, Receptor.AI is efficient, reliable, and precise. These models are essential in the production of our focused libraries.
  • Receptor.AI not only produces focused libraries but also provides full services and solutions at every stage of preclinical drug discovery, with a success-based pricing structure that aligns our interests with the success of your project.

partner

Reaxense

upacc

Q00653

UPID:

NFKB2_HUMAN

Alternative names:

DNA-binding factor KBF2; H2TF1; Lymphocyte translocation chromosome 10 protein; Nuclear factor of kappa light polypeptide gene enhancer in B-cells 2; Oncogene Lyt-10

Alternative UPACC:

Q00653; A8K9D9; D3DR83; Q04860; Q9BU75; Q9H471; Q9H472

Background:

The Nuclear factor NF-kappa-B p100 subunit, known by alternative names such as DNA-binding factor KBF2 and Oncogene Lyt-10, plays a pivotal role in immune response, inflammation, and cell differentiation. It is part of the NF-kappa-B family, which acts as a transcription factor involved in various biological processes. The protein exists in different forms, including p100 and its processed form p52, each binding to specific DNA sequences to regulate gene expression.

Therapeutic significance:

Given its crucial role in immune response and inflammation, the Nuclear factor NF-kappa-B p100 subunit is implicated in Immunodeficiency, common variable, 10, a disease characterized by recurrent infections and autoimmune features. Targeting this protein could offer novel therapeutic approaches for managing this immunodeficiency and potentially other related autoimmune disorders.

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