AI-ACCELERATED DRUG DISCOVERY

Focused On-demand Library for Trans-acting T-cell-specific transcription factor GATA-3

Available from Reaxense
Predicted by Alphafold

Focused On-demand Libraries - Reaxense 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.

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 our associate Reaxense.

The library includes a list of the most effective modulators, each annotated with 38 ADME-Tox and 32 physicochemical and drug-likeness parameters. Furthermore, each compound is shown with its optimal docking poses, affinity scores, and activity scores, offering a detailed summary.

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

 Fig. 1. The sreening 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.

Our library stands out due to several important features:

  • The Receptor.AI platform compiles comprehensive data on the target protein, encompassing previous experiments, literature, known ligands, structural details, and more, leading to a higher chance of selecting the most relevant compounds.
  • Advanced molecular simulations on the platform help pinpoint potential binding sites, making the compounds in our focused library ideal for finding allosteric inhibitors and targeting cryptic pockets.
  • Receptor.AI boasts over 50 tailor-made AI models, rigorously tested and proven in various drug discovery projects and research initiatives. They are crafted for efficacy, dependability, and precision, all of which are key in creating our focused libraries.
  • Beyond creating focused libraries, Receptor.AI offers comprehensive services and complete solutions throughout the preclinical drug discovery phase. Our success-based pricing model minimises risk and maximises the mutual benefits of the project's success.

partner

Reaxense

upacc

P23771

UPID:

GATA3_HUMAN

Alternative names:

GATA-binding factor 3

Alternative UPACC:

P23771; Q5VWG7; Q5VWG8; Q96J16

Background:

Trans-acting T-cell-specific transcription factor GATA-3, also known as GATA-binding factor 3, plays a pivotal role in immune responses. It acts as a transcriptional activator, binding to the enhancer of the T-cell receptor alpha and delta genes, and is essential for the T-helper 2 (Th2) differentiation process. GATA-3 is also involved in macrophage transcriptional activation and metabolic reprogramming in response to IL33, facilitating the differentiation of inflammation-resolving macrophages upon tissue injury.

Therapeutic significance:

GATA-3 is linked to Hypoparathyroidism, sensorineural deafness, and renal disease, a condition characterized by steroid-resistant nephrosis with progressive renal failure. Understanding the role of GATA-3 could open doors to potential therapeutic strategies for this multifaceted disease.

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