Focused On-demand Libraries - Receptor.AI 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.


From a virtual chemical space containing more than 60 billion molecules, we precisely choose certain compounds. Reaxense aids in their synthesis and provision.


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.


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


 

Fig. 1. The screening 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.


PARTNER
Receptor.AI
 
UPACC
Q2M1K9

UPID:
ZN423_HUMAN

ALTERNATIVE NAMES:
Olf1/EBF-associated zinc finger protein; Smad- and Olf-interacting zinc finger protein

ALTERNATIVE UPACC:
Q2M1K9; O94860; Q76N04; Q9NZ13

BACKGROUND:
The Zinc finger protein 423, with alternative names Olf1/EBF-associated zinc finger protein and Smad- and Olf-interacting zinc finger protein, is integral to BMP signaling and olfactory neuron development. It associates with SMADs in response to BMP2, activating transcription of target genes, and plays a role in cerebellar vermis development.

THERAPEUTIC SIGNIFICANCE:
Implicated in the pathogenesis of Nephronophthisis 14 and Joubert syndrome 19, Zinc finger protein 423's involvement in these genetic disorders highlights its potential as a target for therapeutic intervention. Understanding its role could lead to novel treatments for these diseases.

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