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

Focused On-demand Libraries - Receptor.AI 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. Reaxense aids in their synthesis and provision.


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.


Our high-tech, dedicated method is applied to construct targeted libraries for enzymes.


 

Fig. 1. The screening 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 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
Receptor.AI
 
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:
Nuclear factor NF-kappa-B p100 subunit, also referred to as Lymphocyte translocation chromosome 10 protein, is integral to the NF-kappa-B signaling pathway. This pathway's activation leads to the transcription of genes involved in immunity, inflammation, and cell survival. The protein's function is regulated through its conversion from p100 to p52, influencing the transcriptional activity of NF-kappa-B target genes.

THERAPEUTIC SIGNIFICANCE:
Understanding the role of the Nuclear factor NF-kappa-B p100 subunit could open doors to potential therapeutic strategies. Its involvement in Immunodeficiency, common variable, 10, highlights its potential as a target for developing treatments aimed at enhancing immune function and correcting immunodeficiency disorders.

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