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.


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


In the library, a selection of top modulators is provided, each marked with 38 ADME-Tox and 32 parameters related to physicochemical properties and drug-likeness. Also, every compound comes with its best docking poses, affinity scores, and activity scores, providing a comprehensive overview.


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


 

Fig. 1. The screening workflow of Receptor.AI

Our methodology leverages molecular simulations to examine a vast array of proteins, capturing their dynamics in both isolated forms and in complexes with other proteins. Through ensemble virtual screening, we thoroughly account for the protein's conformational mobility, identifying critical binding sites within functional regions and distant allosteric locations. This detailed exploration ensures that we comprehensively assess every possible mechanism of action, with the objective of identifying novel therapeutic targets and lead compounds that span a wide spectrum of biological functions.


Our library is unique due to several crucial aspects:


  • Receptor.AI compiles all relevant data on the target protein, such as past experimental results, literature findings, known ligands, and structural data, thereby enhancing the likelihood of focusing on the most significant compounds.

  • By utilizing advanced molecular simulations, the platform is adept at locating potential binding sites, rendering the compounds in the focused library well-suited for unearthing allosteric inhibitors and binders for hidden pockets.

  • The platform is supported by more than 50 highly specialized AI models, all of which have been rigorously tested and validated in diverse drug discovery and research programs. Its design emphasizes efficiency, reliability, and accuracy, crucial for producing focused libraries.

  • Receptor.AI extends beyond just creating focused libraries; it offers a complete spectrum of services and solutions during the preclinical drug discovery phase, with a success-dependent pricing strategy that reduces risk and fosters shared success in the project.


PARTNER
Receptor.AI
 
UPACC
P17302

UPID:
CXA1_HUMAN

ALTERNATIVE NAMES:
Connexin-43; Gap junction 43 kDa heart protein

ALTERNATIVE UPACC:
P17302; B2R5U9; Q6FHU1; Q9Y5I8

BACKGROUND:
The Gap junction alpha-1 protein, or Connexin-43, is integral to cellular communication, forming channels that allow for the exchange of crucial ions and molecules. This protein's role extends to the regulation of bladder capacity and cell growth inhibition, demonstrating its broad impact on physiological functions.

THERAPEUTIC SIGNIFICANCE:
Given its involvement in a spectrum of genetic conditions, including Oculodentodigital dysplasia and Craniometaphyseal dysplasia, autosomal recessive, Connexin-43 emerges as a key target for drug discovery. Its multifaceted role in biological systems makes it an intriguing subject for scientific inquiry, with the potential to revolutionize treatments for diseases linked to cellular communication and growth regulation.

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