Focused On-demand Library for VPS35 endosomal protein-sorting factor-like

Available from Reaxense
Predicted by Alphafold

Focused On-demand Libraries - Reaxense Collaboration

Explore the Potential with AI-Driven Innovation

This extensive focused library is tailor-made using the latest virtual screening and parameter assessment technology, operated by the Receptor.AI drug discovery platform. This technique is more effective than traditional methods, offering compounds with improved 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 our associate 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.

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.







Alternative names:

Esophageal cancer-associated protein

Alternative UPACC:

Q7Z3J2; A8K2M1; O43329; Q69YI1; Q6PDA0; Q7L371; Q86W66; Q8WXA5; Q9H0L7; Q9H7C8


VPS35 endosomal protein-sorting factor-like, also known as Esophageal cancer-associated protein, plays a crucial role in cellular processes by acting as a component of the retriever complex. This complex is vital for the retrieval and recycling of various cargos, including integrin alpha-5/beta-1 and NxxY-motif-containing cargo proteins, essential for cell migration, adhesion, nutrient supply, and signaling. Additionally, it facilitates copper-dependent ATP7A trafficking, crucial for cellular copper homeostasis.

Therapeutic significance:

The involvement of VPS35 in Ritscher-Schinzel syndrome 3, characterized by a spectrum of developmental malformations, underscores its potential as a therapeutic target. Understanding the role of VPS35 could open doors to potential therapeutic strategies for treating this complex syndrome.

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