Focused On-demand Library for Vacuolar protein sorting-associated protein 29

Available from Reaxense
Predicted by Alphafold

Focused On-demand Libraries - Reaxense Collaboration

Explore the Potential with AI-Driven Innovation

The focused library is created on demand with the latest virtual screening and parameter assessment technology, supported by the Receptor.AI drug discovery platform. This method is more effective than traditional methods and results in higher-quality compounds with better 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 our partner 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.

Our top-notch dedicated system is used to design specialised libraries.

 Fig. 1. The sreening 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.

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:

PEP11 homolog; Vesicle protein sorting 29

Alternative UPACC:

Q9UBQ0; Q502Y5; Q6FIF8; Q6IAH3; Q9H0W0; Q9NRP1; Q9NRU7


Vacuolar protein sorting-associated protein 29 (VPS29), also known as PEP11 homolog and Vesicle protein sorting 29, plays a pivotal role in the retromer cargo-selective complex (CSC). This complex is crucial for preventing the misrouting of specific transmembrane proteins to the lysosomal degradation pathway. VPS29 is involved in various transport pathways, including the retrograde transport from endosomes to the trans-Golgi network and the recycling of cargo proteins from endosomes to the plasma membrane. Its function is essential for the regulation of transcytosis of the polymeric immunoglobulin receptor and the operation of the retriever complex, which is vital for the recycling of numerous cargos such as integrin alpha-5/beta-1.

Therapeutic significance:

Understanding the role of Vacuolar protein sorting-associated protein 29 could open doors to potential therapeutic strategies.

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