AI-ACCELERATED DRUG DISCOVERY

Focused On-demand Library for Protocadherin-12

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 strategy employs molecular simulations to explore an extensive range of proteins, capturing their dynamics both individually and within complexes with other proteins. Through ensemble virtual screening, we address proteins' conformational mobility, uncovering key binding sites at both functional regions and remote allosteric locations. This comprehensive investigation ensures a thorough assessment of all potential mechanisms of action, with the goal of discovering innovative therapeutic targets and lead molecules across across diverse 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

Q9NPG4

UPID:

PCD12_HUMAN

Alternative names:

Vascular cadherin-2; Vascular endothelial cadherin-2

Alternative UPACC:

Q9NPG4; Q6UXB6; Q96KB8; Q9H7Y6; Q9H8E0

Background:

Protocadherin-12, also known as Vascular cadherin-2 and Vascular endothelial cadherin-2, plays a crucial role in cellular adhesion, facilitating cell-cell interactions at interendothelial junctions. It is instrumental in regulating cell migration by enhancing cell-cell adhesion and promoting homotypic calcium-dependent aggregation. Despite its weak association with the cytoskeleton, Protocadherin-12 clusters at intercellular junctions, underscoring its significance in cellular cohesion.

Therapeutic significance:

Protocadherin-12's involvement in Diencephalic-mesencephalic junction dysplasia syndrome 1, a condition marked by severe developmental delays, highlights its potential as a therapeutic target. Understanding the role of Protocadherin-12 could open doors to potential therapeutic strategies, offering hope for interventions in neurodevelopmental disorders.

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