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.


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 Reaxense.


In the library, a selection of top modulators is provided, each marked with 38 ADME-Tox and 32 parameters related to physicochemical properties and drug-likeness. Also, every compound comes with its best docking poses, affinity scores, and activity scores, providing a comprehensive overview.


We employ our advanced, specialised process to create targeted libraries.


 

Fig. 1. The screening workflow of Receptor.AI

By deploying molecular simulations, our approach comprehensively covers a broad array of proteins, tracking their flexibility and dynamics individually and within complexes. Ensemble virtual screening is utilised to take into account conformational dynamics, identifying pivotal binding sites located within functional regions and at allosteric locations. This thorough exploration ensures that every conceivable mechanism of action is considered, aiming to identify new therapeutic targets and advance lead compounds throughout a vast 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.


PARTNER
Receptor.AI
 
UPACC
Q8WV99

UPID:
ZFN2B_HUMAN

ALTERNATIVE NAMES:
Arsenite-inducible RNA-associated protein-like protein

ALTERNATIVE UPACC:
Q8WV99; Q8NB98

BACKGROUND:
The AN1-type zinc finger protein 2B, known for its alternative name Arsenite-inducible RNA-associated protein-like protein, is integral to protein quality control. It oversees the proper translocation of proteins into the endoplasmic reticulum and their degradation if translocation fails, playing a key role in endoplasmic reticulum stress response and protein homeostasis. Additionally, it regulates the expression of the IGF1R receptor, affecting the insulin-like growth factor signaling pathway.

THERAPEUTIC SIGNIFICANCE:
Exploring the functions of AN1-type zinc finger protein 2B offers a promising avenue for developing novel therapeutic approaches. Its critical role in protein quality control and influence on metabolic signaling pathways highlights its potential in targeting conditions stemming from protein misfolding and metabolic imbalances.

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