AI-ACCELERATED DRUG DISCOVERY

Focused On-demand Library for Proto-oncogene Wnt-3

Available from Reaxense
Predicted by Alphafold

Focused On-demand Libraries - Reaxense 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.

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.

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

Reaxense

upacc

P56703

UPID:

WNT3_HUMAN

Alternative names:

Proto-oncogene Int-4 homolog

Alternative UPACC:

P56703; Q2M237; Q9H1J9

Background:

Proto-oncogene Wnt-3, also known as Int-4 homolog, plays a pivotal role in the canonical Wnt signaling pathway, activating TCF/LEF family transcription factors. Essential for early embryogenesis, it orchestrates gastrulation, primitive streak formation, and mesoderm development. It's crucial for limb formation and the development of the apical ectodermal ridge.

Therapeutic significance:

Linked to Tetraamelia syndrome 1, characterized by limb agenesis and various organ anomalies, Wnt-3's involvement suggests potential therapeutic targets. Understanding the role of Proto-oncogene Wnt-3 could open doors to potential therapeutic strategies for this autosomal recessive disease.

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