Focused On-demand Library for Nucleobindin-2

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 carefully select specific compounds from a vast collection of over 60 billion molecules in virtual chemical space. Our partner Reaxense helps in synthesizing and delivering these compounds.

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

 Fig. 1. The sreening workflow of Receptor.AI

Our methodology employs molecular simulations to explore a wide array of proteins, capturing their dynamic states both individually and within complexes. Through ensemble virtual screening, we address conformational mobility, uncovering binding sites within functional regions and remote allosteric locations. This thorough exploration ensures no potential mechanism of action is overlooked, aiming to discover novel therapeutic targets and lead compounds across an extensive spectrum of biological functions.

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.







Alternative names:

DNA-binding protein NEFA; Epididymis secretory protein Li 109; Gastric cancer antigen Zg4; Prepronesfatin

Alternative UPACC:

P80303; A8K642; D3DQX5; Q8NFT5; V9HW75


Nucleobindin-2, known by alternative names such as DNA-binding protein NEFA and Prepronesfatin, plays a crucial role in calcium homeostasis and acts as a non-receptor guanine nucleotide exchange factor. It is pivotal in activating the G-protein alpha subunit GNAI3, influencing cellular signaling pathways. Additionally, as an anorexigenic peptide, it is integral in regulating food intake and energy homeostasis through hypothalamic pathways, functioning independently of leptin.

Therapeutic significance:

Understanding the role of Nucleobindin-2 could open doors to potential therapeutic strategies. Its involvement in regulating blood pressure and energy homeostasis presents it as a target for developing treatments for hypertension and metabolic disorders.

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