AI-ACCELERATED DRUG DISCOVERY

Focused On-demand Library for Cell adhesion molecule-related/down-regulated by oncogenes

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.

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.

We utilise our cutting-edge, exclusive workflow to develop focused 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.

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

Q4KMG0

UPID:

CDON_HUMAN

Alternative names:

-

Alternative UPACC:

Q4KMG0; O14631

Background:

The Cell adhesion molecule-related/down-regulated by oncogenes (CAM-related/DRO) protein, encoded by the gene with accession number Q4KMG0, plays a pivotal role in cell-cell interactions essential for the differentiation of myogenic cells. This protein is a key component of a cell-surface receptor complex that orchestrates the precise communication between muscle precursor cells, facilitating their proper differentiation.

Therapeutic significance:

Given its involvement in Holoprosencephaly 11, a brain development disorder resulting from the failure of the forebrain to correctly separate into hemispheres, understanding the role of CAM-related/DRO could open doors to potential therapeutic strategies. Its genetic association with this condition underscores its potential as a target for therapeutic intervention.

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