Focused On-demand Libraries - Receptor.AI Collaboration


Explore the Potential with AI-Driven Innovation

This extensive focused library is tailor-made using the latest virtual screening and parameter assessment technology, operated by the Receptor.AI drug discovery platform. This technique is more effective than traditional methods, offering compounds with improved activity, selectivity, and safety.


The compounds are cherry-picked from the vast virtual chemical space of over 60B molecules. The synthesis and delivery of compounds is 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 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
P23771

UPID:
GATA3_HUMAN

ALTERNATIVE NAMES:
GATA-binding factor 3

ALTERNATIVE UPACC:
P23771; Q5VWG7; Q5VWG8; Q96J16

BACKGROUND:
The protein Trans-acting T-cell-specific transcription factor GATA-3, alternatively named GATA-binding factor 3, is crucial for immune and inflammatory responses. It binds to specific DNA sequences to regulate the expression of genes involved in T-cell receptor signaling and Th2 cell differentiation. Additionally, GATA-3 coordinates the activation of macrophages and their metabolic pathways in response to interleukin-33, playing a key role in tissue repair processes.

THERAPEUTIC SIGNIFICANCE:
Involvement of GATA-3 in Hypoparathyroidism, sensorineural deafness, and renal disease highlights its potential as a target for therapeutic intervention. The protein's essential role in immune regulation and tissue repair mechanisms underscores the importance of exploring GATA-3-targeted therapies for treating complex diseases.

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