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 Transient receptor potential cation channel subfamily V member 4 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 Transient receptor potential cation channel subfamily V member 4 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 Transient receptor potential cation channel subfamily V member 4, 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 Transient receptor potential cation channel subfamily V member 4. 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 Transient receptor potential cation channel subfamily V member 4. 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 Transient receptor potential cation channel subfamily V member 4 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.
Transient receptor potential cation channel subfamily V member 4
partner:
Reaxense
upacc:
Q9HBA0
UPID:
TRPV4_HUMAN
Alternative names:
Osm-9-like TRP channel 4; Transient receptor potential protein 12; Vanilloid receptor-like channel 2; Vanilloid receptor-like protein 2; Vanilloid receptor-related osmotically-activated channel
Alternative UPACC:
Q9HBA0; B7ZKQ6; Q17R79; Q2Y122; Q2Y123; Q2Y124; Q86YZ6; Q8NDY7; Q8NG64; Q96Q92; Q96RS7; Q9HBC0
Background:
Transient receptor potential cation channel subfamily V member 4 (TRPV4) is a versatile protein involved in osmotic sensitivity, mechanosensitivity, and plays a pivotal role in calcium ion permeability across cell membranes. Its activation is influenced by various stimuli including hypotonicity, heat, and phorbol esters, contributing to diverse cellular functions from cell-cell junction formation to bone and cartilage development.
Therapeutic significance:
TRPV4's involvement in a wide array of diseases, from skeletal dysplasias like Brachyolmia 3 and Metatropic dysplasia to neuromuscular disorders such as Charcot-Marie-Tooth disease, underscores its potential as a therapeutic target. Understanding the role of TRPV4 could open doors to potential therapeutic strategies for these conditions.
