Focused On-demand Libraries - Receptor.AI Collaboration


Explore the Potential with AI-Driven Innovation

The specialised, focused library is developed on demand with the most recent virtual screening and parameter assessment technology, guided by the Receptor.AI drug discovery platform. This approach exceeds the capabilities of traditional methods and offers compounds with higher 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 Reaxense.


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.


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


 

Fig. 1. The screening 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.


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
Q9UNE2

UPID:
RPH3L_HUMAN

ALTERNATIVE NAMES:
No C2 domains protein; Rabphilin-3A-like protein

ALTERNATIVE UPACC:
Q9UNE2; D3DTG7; Q9BSB3

BACKGROUND:
The protein Rab effector Noc2, known alternatively as No C2 domains protein and Rabphilin-3A-like protein, is implicated in the regulation of exocytosis, serving critical functions in both endocrine and exocrine cells. With the UniProt accession Q9UNE2, it is suggested to function as a RAB3B effector in epithelial cells, underscoring its significance in the secretion mechanisms of cells.

THERAPEUTIC SIGNIFICANCE:
Exploring the functions of Rab effector Noc2 holds promise for unveiling new therapeutic avenues. Given its key role in the mechanisms of regulated exocytosis, targeting Noc2 could lead to innovative treatments for disorders associated with secretion abnormalities.

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