Focused On-demand Library for Protein transport protein Sec23A

Available from Reaxense
Predicted by Alphafold

Focused On-demand Libraries - Reaxense Collaboration

Explore the Potential with AI-Driven Innovation

This comprehensive focused library is produced on demand with state-of-the-art virtual screening and parameter assessment technology driven by Receptor.AI drug discovery platform. This approach outperforms traditional methods and provides higher-quality compounds with superior 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.

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.

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

 Fig. 1. The sreening workflow of Receptor.AI

This approach involves comprehensive molecular simulations of the catalytic and allosteric binding pockets and ensemble virtual screening that accounts for their conformational flexibility. In the case of designing modulators, the structural adjustments caused by reaction intermediates are considered to improve 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.







Alternative names:

SEC23-related protein A

Alternative UPACC:

Q15436; B2R5P4; B3KXI2; Q8NE16


Protein transport protein Sec23A, also known as SEC23-related protein A, plays a pivotal role in cellular transport mechanisms. It is a crucial component of the coat protein complex II (COPII), which is instrumental in forming transport vesicles from the endoplasmic reticulum (ER). This process is essential for the physical deformation of the ER membrane into vesicles and the selection of cargo molecules for transport to the Golgi complex. Additionally, Sec23A is required for the translocation of the insulin-induced glucose transporter SLC2A4/GLUT4 to the cell membrane, highlighting its significance in glucose metabolism.

Therapeutic significance:

Given its involvement in Craniolenticulosutural dysplasia, a syndrome characterized by late-closing fontanels, sutural cataracts, facial dysmorphisms, and skeletal defects, understanding the role of Protein transport protein Sec23A could open doors to potential therapeutic strategies. Its critical function in cellular transport and glucose metabolism makes it a promising target for addressing the underlying molecular mechanisms of this syndrome.

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