AI-ACCELERATED DRUG DISCOVERY

Vacuolar protein sorting-associated protein 29

Explore its Potential with AI-Driven Innovation
Predicted by Alphafold

Vacuolar protein sorting-associated protein 29 - Focused Library Design

Available from Reaxense

This protein is integrated into the Receptor.AI ecosystem as a prospective target with high therapeutic potential. We performed a comprehensive characterization of Vacuolar protein sorting-associated protein 29 including:

1. LLM-powered literature research

Our custom-tailored LLM extracted and formalized all relevant information about the protein from a large set of structured and unstructured data sources and stored it in the form of a Knowledge Graph. This comprehensive analysis allowed us to gain insight into Vacuolar protein sorting-associated protein 29 therapeutic significance, existing small molecule ligands, relevant off-targets, and protein-protein interactions.

 Fig. 1. Preliminary target research workflow

2. AI-Driven Conformational Ensemble Generation

Starting from the initial protein structure, we employed advanced AI algorithms to predict alternative functional states of Vacuolar protein sorting-associated protein 29, including large-scale conformational changes along "soft" collective coordinates. Through molecular simulations with AI-enhanced sampling and trajectory clustering, we explored the broad conformational space of the protein and identified its representative structures. Utilizing diffusion-based AI models and active learning AutoML, we generated a statistically robust ensemble of equilibrium protein conformations that capture the receptor's full dynamic behavior, providing a robust foundation for accurate structure-based drug design.

 Fig. 2. AI-powered molecular dynamics simulations workflow

3. Binding pockets identification and characterization

We employed the AI-based pocket prediction module to discover orthosteric, allosteric, hidden, and cryptic binding pockets on the protein’s surface. Our technique integrates the LLM-driven literature search and structure-aware ensemble-based pocket detection algorithm that utilizes previously established protein dynamics. Tentative pockets are then subject to AI scoring and ranking with simultaneous detection of false positives. In the final step, the AI model assesses the druggability of each pocket enabling a comprehensive selection of the most promising pockets for further targeting.

 Fig. 3. AI-based binding pocket detection workflow

4. AI-Powered Virtual Screening

Our ecosystem is equipped to perform AI-driven virtual screening on Vacuolar protein sorting-associated protein 29. With access to a vast chemical space and cutting-edge AI docking algorithms, we can rapidly and reliably predict the most promising, novel, diverse, potent, and safe small molecule ligands of Vacuolar protein sorting-associated protein 29. This approach allows us to achieve an excellent hit rate and to identify compounds ready for advanced lead discovery and optimization.

 Fig. 4. The screening workflow of Receptor.AI

Receptor.AI, in partnership with Reaxense, developed a next-generation technology for on-demand focused library design to enable extensive target exploration.

The focused library for Vacuolar protein sorting-associated protein 29 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.

Vacuolar protein sorting-associated protein 29

partner:

Reaxense

upacc:

Q9UBQ0

UPID:

VPS29_HUMAN

Alternative names:

PEP11 homolog; Vesicle protein sorting 29

Alternative UPACC:

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

Background:

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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