AI-ACCELERATED DRUG DISCOVERY
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 catalytic subunit A 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 catalytic subunit A 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 catalytic subunit A, 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 catalytic subunit A. 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 catalytic subunit A. 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 catalytic subunit A 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 catalytic subunit A
partner:
Reaxense
upacc:
P38606
UPID:
VATA_HUMAN
Alternative names:
V-ATPase 69 kDa subunit; Vacuolar ATPase isoform VA68; Vacuolar proton pump subunit alpha
Alternative UPACC:
P38606; B2RBR8; B7Z1R5; D3DN75; Q53YD9; Q96DY6; Q9UHY3
Background:
The V-type proton ATPase catalytic subunit A, also known as V-ATPase 69 kDa subunit, plays a crucial role in acidifying intracellular compartments and the extracellular environment in certain cell types. This protein is integral to various physiological processes, including iron homeostasis and neurite development. Its involvement in synaptic connectivity and virion uncoating during Rabies virus replication highlights its multifaceted role in biological systems.
Therapeutic significance:
Given its association with Cutis laxa, autosomal recessive, 2D, and Epileptic encephalopathy, infantile or early childhood, 3, understanding the V-type proton ATPase catalytic subunit A's function could pave the way for novel therapeutic strategies targeting these conditions. Its role in disease mechanisms offers a promising avenue for drug discovery.
