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

The specialised, focused library is developed on demand with the most recent virtual screening and parameter assessment technology, guided by the Receptor.AI drug discovery platform. This approach exceeds the capabilities of traditional methods and offers compounds with higher 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 our partner Reaxense.

Contained in the library are leading modulators, each labelled with 38 ADME-Tox and 32 physicochemical and drug-likeness qualities. In addition, each compound is illustrated with its optimal docking poses, affinity scores, and activity scores, giving a complete picture.

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

 Fig. 1. The sreening 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.

Several key aspects differentiate our library:

  • Receptor.AI compiles an all-encompassing dataset on the target protein, including historical experiments, literature data, known ligands, and structural insights, maximising the chances of prioritising the most pertinent compounds.
  • The platform employs state-of-the-art molecular simulations to identify potential binding sites, ensuring the focused library is primed for discovering allosteric inhibitors and binders of concealed pockets.
  • Over 50 customisable AI models, thoroughly evaluated in various drug discovery endeavours and research projects, make Receptor.AI both efficient and accurate. This technology is integral to the development of our focused libraries.
  • In addition to generating focused libraries, Receptor.AI offers a full range of services and solutions for every step of preclinical drug discovery, with a pricing model based on success, thereby reducing risk and promoting joint project success.

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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