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 Solute carrier family 12 member 5 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 Solute carrier family 12 member 5 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 Solute carrier family 12 member 5, 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 Solute carrier family 12 member 5. 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 Solute carrier family 12 member 5. 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 Solute carrier family 12 member 5 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.
Solute carrier family 12 member 5
partner:
Reaxense
upacc:
Q9H2X9
UPID:
S12A5_HUMAN
Alternative names:
Electroneutral potassium-chloride cotransporter 2; K-Cl cotransporter 2; Neuronal K-Cl cotransporter
Alternative UPACC:
Q9H2X9; A2RTX2; Q5VZ41; Q9H4Z0; Q9ULP4
Background:
Solute carrier family 12 member 5, also known as the electroneutral potassium-chloride cotransporter 2 (K-Cl cotransporter 2), plays a pivotal role in neuronal Cl(-) homeostasis. It mediates potassium-chloride cotransport in mature neurons, essential for maintaining low neuronal Cl(-) levels. This function is crucial for the hyperpolarization and inhibition of neurons following GABA-A and glycine receptor activation. Additionally, it contributes to dendritic spine formation and maturation, highlighting its significance in neural architecture and function.
Therapeutic significance:
The protein is implicated in severe neurological disorders, including Developmental and epileptic encephalopathy 34 and Epilepsy, idiopathic generalized 14. These conditions are characterized by refractory seizures and cognitive impairments, linked to mutations affecting the gene encoding this cotransporter. Understanding its role could lead to novel therapeutic strategies targeting these debilitating epilepsies, offering hope for improved treatments and outcomes.
