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.


We pick out particular compounds from an extensive virtual database of more than 60 billion molecules. The preparation and shipment of these compounds are facilitated by Reaxense.


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 use our state-of-the-art dedicated workflow for designing focused libraries for enzymes.


 

Fig. 1. The screening workflow of Receptor.AI

It includes in-depth molecular simulations of both the catalytic and allosteric binding pockets, with ensemble virtual screening focusing on their conformational flexibility. For modulators, the process includes considering the structural shifts due to reaction intermediates to boost activity and selectivity.


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
Receptor.AI
 
UPACC
Q96HD1

UPID:
CREL1_HUMAN

ALTERNATIVE NAMES:
Cysteine-rich with EGF-like domain protein 1

ALTERNATIVE UPACC:
Q96HD1; A8MX90; B2RAA9; Q6I9X5; Q8NFT4; Q9Y409

BACKGROUND:
The protein CRELD1, bearing the alternative name Cysteine-rich with EGF-like domain protein 1, is instrumental in the proper folding of proteins and the efficient localization of acetylcholine receptors to the plasma membrane. Its function is critical for cellular processes and signaling.

THERAPEUTIC SIGNIFICANCE:
Given CRELD1's involvement in Atrioventricular septal defect 2, a complex congenital heart condition, the protein emerges as a key target for drug discovery efforts. Unlocking the therapeutic potential of CRELD1 could lead to breakthroughs in the management of heart malformations.

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