Focused On-demand Library for NF-kappa-B inhibitor-interacting Ras-like protein 1

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.

Our selection of compounds is from a large virtual library of over 60 billion molecules. The production and distribution of these compounds are managed by our partner Reaxense.

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

 Fig. 1. The sreening workflow of Receptor.AI

Our strategy employs molecular simulations to explore an extensive range of proteins, capturing their dynamics both individually and within complexes with other proteins. Through ensemble virtual screening, we address proteins' conformational mobility, uncovering key binding sites at both functional regions and remote allosteric locations. This comprehensive investigation ensures a thorough assessment of all potential mechanisms of action, with the goal of discovering innovative therapeutic targets and lead molecules across across diverse biological functions.

Our library stands out due to several important features:

  • The Receptor.AI platform compiles comprehensive data on the target protein, encompassing previous experiments, literature, known ligands, structural details, and more, leading to a higher chance of selecting the most relevant compounds.
  • Advanced molecular simulations on the platform help pinpoint potential binding sites, making the compounds in our focused library ideal for finding allosteric inhibitors and targeting cryptic pockets.
  • Receptor.AI boasts over 50 tailor-made AI models, rigorously tested and proven in various drug discovery projects and research initiatives. They are crafted for efficacy, dependability, and precision, all of which are key in creating our focused libraries.
  • Beyond creating focused libraries, Receptor.AI offers comprehensive services and complete solutions throughout the preclinical drug discovery phase. Our success-based pricing model minimises risk and maximises the mutual benefits of the project's success.







Alternative names:

I-kappa-B-interacting Ras-like protein 1

Alternative UPACC:

Q9NYS0; Q96K18


NF-kappa-B inhibitor-interacting Ras-like protein 1, also known as I-kappa-B-interacting Ras-like protein 1, plays a crucial role in regulating NF-kappa-B activity. It achieves this by preventing the degradation of NF-kappa-B inhibitor beta (NFKBIB) through most signals, thereby ensuring NFKBIB's resistance to degradation. This protein may function by inhibiting the phosphorylation of NFKBIB and facilitating the cytoplasmic retention of the p65/RELA NF-kappa-B subunit. Its exact mechanism as a GTPase remains to be fully elucidated, with both GTP- and GDP-bound forms impacting the phosphorylation of NFKBIB.

Therapeutic significance:

Understanding the role of NF-kappa-B inhibitor-interacting Ras-like protein 1 could open doors to potential therapeutic strategies.

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