AI-ACCELERATED DRUG DISCOVERY

Focused On-demand Library for Frizzled-4

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.

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

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 for receptors.

 Fig. 1. The sreening workflow of Receptor.AI

The method involves detailed molecular simulations of the receptor in its native membrane environment, with ensemble virtual screening focusing on its conformational mobility. When dealing with dimeric or oligomeric receptors, the whole functional complex is modelled, and the tentative binding pockets on and between the subunits are established to address all possible mechanisms of action.

Our library distinguishes itself through several key aspects:

  • The Receptor.AI platform integrates all available data about the target protein, including past experiments, literature data, known ligands, structural information and more. This consolidated approach maximises the probability of prioritising highly relevant compounds.
  • The platform uses sophisticated molecular simulations to identify possible binding sites so that the compounds in the focused library are suitable for discovering allosteric inhibitors and the binders for cryptic pockets.
  • The platform integrates over 50 highly customisable AI models, which are thoroughly tested and validated on a multitude of commercial drug discovery programs and research projects. It is designed to be efficient, reliable and accurate. All this power is utilised when producing the focused libraries.
  • In addition to producing the focused libraries, Receptor.AI provides services and end-to-end solutions at every stage of preclinical drug discovery. The pricing model is success-based, which reduces your risks and leverages the mutual benefits of the project's success.

partner

Reaxense

upacc

Q9ULV1

UPID:

FZD4_HUMAN

Alternative names:

FzE4

Alternative UPACC:

Q9ULV1; A8K9Q3; Q14C97; Q6S9E4

Background:

Frizzled-4 (FzE4) is a key receptor for Wnt proteins, pivotal in the canonical signaling pathway leading to the activation of gene transcription via beta-catenin accumulation. It plays a crucial role in retinal vascularization, responding to Wnt proteins and norrin to stimulate vascular development and tissue morphogenesis.

Therapeutic significance:

Vitreoretinopathy, exudative 1, a disorder affecting retinal vasculature and potentially leading to blindness, is linked to mutations in the Frizzled-4 gene. Understanding the role of Frizzled-4 could open doors to potential therapeutic strategies for this and related retinal diseases.

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