Focused On-demand Libraries - Receptor.AI 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.


The compounds are cherry-picked from the vast virtual chemical space of over 60B molecules. The synthesis and delivery of compounds is facilitated by 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 top-notch dedicated system is used to design specialised libraries.


 

Fig. 1. The screening 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
Receptor.AI
 
UPACC
P26232

UPID:
CTNA2_HUMAN

ALTERNATIVE NAMES:
Alpha N-catenin; Alpha-catenin-related protein

ALTERNATIVE UPACC:
P26232; B3KXE5; B7Z2W7; B7Z352; B7Z898; Q4ZFW1; Q53R26; Q53R33; Q53T67; Q53T71; Q53TM8; Q7Z3L1; Q7Z3Y0

BACKGROUND:
The protein Catenin alpha-2, known alternatively as Alpha N-catenin and Alpha-catenin-related protein, is integral to the regulation of cell-cell adhesion and neuronal differentiation within the nervous system. It ensures proper cortical neuronal migration and neurite growth by negatively regulating the Arp2/3 complex's activity and mediating actin polymerization. This action prevents excessive actin branching, thereby facilitating neurite stability and growth. Catenin alpha-2 also plays a role in synaptic plasticity and the development of cerebellar and hippocampal structures.

THERAPEUTIC SIGNIFICANCE:
Mutations in Catenin alpha-2 are associated with Cortical dysplasia, complex, with other brain malformations 9, highlighting its critical role in neurodevelopment. The exploration of Catenin alpha-2's function offers promising avenues for developing therapeutic interventions for neurological disorders.

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