AI-ACCELERATED DRUG DISCOVERY

V-type proton ATPase subunit S1

Explore its Potential with AI-Driven Innovation
Predicted by Alphafold

V-type proton ATPase subunit S1 - 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 V-type proton ATPase subunit S1 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 V-type proton ATPase subunit S1 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 V-type proton ATPase subunit S1, 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 V-type proton ATPase subunit S1. 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 V-type proton ATPase subunit S1. 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 V-type proton ATPase subunit S1 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.

V-type proton ATPase subunit S1

partner:

Reaxense

upacc:

Q15904

UPID:

VAS1_HUMAN

Alternative names:

Protein XAP-3; V-ATPase Ac45 subunit; V-ATPase S1 accessory protein; Vacuolar proton pump subunit S1

Alternative UPACC:

Q15904; A6ZKI4; Q8NBT4; Q9H0C7

Background:

The V-type proton ATPase subunit S1, known by alternative names such as Protein XAP-3, V-ATPase Ac45 subunit, and Vacuolar proton pump subunit S1, plays a crucial role in cellular processes. It functions as an accessory subunit of the proton-transporting vacuolar (V)-ATPase protein pump, essential for the acidification of secretory vesicles. This protein is involved in membrane trafficking, Ca(2+)-dependent membrane fusion, and plays a probable role in the assembly of the V-type ATPase complex. Additionally, it is implicated in intracellular iron homeostasis and the regulation of dense-core secretory granules' acidification in islets of Langerhans cells.

Therapeutic significance:

Immunodeficiency 47, a complex syndrome characterized by hypogammaglobulinemia, recurrent bacterial infections, and liver disease, is linked to variants affecting the V-type proton ATPase subunit S1 gene. Understanding the role of this protein could pave the way for innovative therapeutic strategies targeting this immunodeficiency.

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