Focused On-demand Libraries - Receptor.AI Collaboration


Explore the Potential with AI-Driven Innovation

This comprehensive focused library is produced on demand with state-of-the-art virtual screening and parameter assessment technology driven by Receptor.AI drug discovery platform. This approach outperforms traditional methods and provides higher-quality compounds with superior activity, selectivity and safety.


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


The library includes a list of the most promising modulators annotated with 38 ADME-Tox and 32 physicochemical and drug-likeness parameters. Also, each compound is presented with its optimal docking poses, affinity scores, and activity scores, providing a comprehensive overview.


Our top-notch dedicated system is used to design specialised libraries.


 

Fig. 1. The screening workflow of Receptor.AI

Utilising molecular simulations, our approach thoroughly examines a wide array of proteins, tracking their conformational changes individually and within complexes. Ensemble virtual screening enables us to address conformational flexibility, revealing essential binding sites at functional regions and allosteric locations. Our rigorous analysis guarantees that no potential mechanism of action is overlooked, aiming to uncover new therapeutic targets and lead compounds across diverse 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.


PARTNER
Receptor.AI
 
UPACC
P80303

UPID:
NUCB2_HUMAN

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

ALTERNATIVE UPACC:
P80303; A8K642; D3DQX5; Q8NFT5; V9HW75

BACKGROUND:
The protein Nucleobindin-2, with aliases such as Epididymis secretory protein Li 109 and Gastric cancer antigen Zg4, is a calcium-binding entity involved in maintaining calcium equilibrium. It serves as a guanine nucleotide exchange factor for GNAI3, essential for G-protein signaling. Beyond its role in calcium homeostasis, Nucleobindin-2 functions in appetite suppression and energy balance, acting through leptin-independent mechanisms, and may influence blood pressure regulation.

THERAPEUTIC SIGNIFICANCE:
Exploring the multifunctional roles of Nucleobindin-2 offers a promising avenue for therapeutic intervention. Its critical functions in appetite regulation and cardiovascular health highlight its potential as a novel target for addressing obesity and hypertension.

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