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 Amiloride-sensitive sodium channel subunit gamma 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 Amiloride-sensitive sodium channel subunit gamma 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 Amiloride-sensitive sodium channel subunit gamma, 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 Amiloride-sensitive sodium channel subunit gamma. 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 Amiloride-sensitive sodium channel subunit gamma. 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 Amiloride-sensitive sodium channel subunit gamma 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.
Amiloride-sensitive sodium channel subunit gamma
partner:
Reaxense
upacc:
P51170
UPID:
SCNNG_HUMAN
Alternative names:
Epithelial Na(+) channel subunit gamma; Gamma-NaCH; Nonvoltage-gated sodium channel 1 subunit gamma; SCNEG
Alternative UPACC:
P51170; P78437; Q6PCC2; Q93023; Q93024; Q93025; Q93026; Q93027; Q96TD2
Background:
The Amiloride-sensitive sodium channel subunit gamma, known alternatively as Epithelial Na(+) channel subunit gamma, Gamma-NaCH, Nonvoltage-gated sodium channel 1 subunit gamma, or SCNEG, plays a pivotal role in the regulation of sodium permeability across epithelial cells. This protein facilitates the electrodiffusion of sodium, crucial for maintaining electrolyte balance, blood pressure homeostasis, and airway surface liquid homeostasis, which is essential for mucus clearance. It is instrumental in sodium reabsorption in various organs including the kidneys, colon, lungs, and sweat glands, and is also involved in taste perception.
Therapeutic significance:
Mutations in the Amiloride-sensitive sodium channel subunit gamma are linked to Liddle syndrome 2, Bronchiectasis with or without elevated sweat chloride 3, and Pseudohypoaldosteronism 1B3, autosomal recessive. These conditions underscore the protein's critical role in fluid and electrolyte homeostasis. Understanding its function and the impact of its genetic variants offers a pathway to targeted treatments for these disorders, highlighting its therapeutic significance.
