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 Inward rectifier potassium channel 2 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 Inward rectifier potassium channel 2 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 Inward rectifier potassium channel 2, 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 Inward rectifier potassium channel 2. 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 Inward rectifier potassium channel 2. 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 Inward rectifier potassium channel 2 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.
Inward rectifier potassium channel 2
partner:
Reaxense
upacc:
P63252
UPID:
KCNJ2_HUMAN
Alternative names:
Cardiac inward rectifier potassium channel; Inward rectifier K(+) channel Kir2.1; Potassium channel, inwardly rectifying subfamily J member 2
Alternative UPACC:
P63252; O15110; P48049
Background:
The Inward rectifier potassium channel 2, also known as Kir2.1, plays a pivotal role in establishing the action potential waveform and excitability of neuronal and muscle tissues. Characterized by its unique ability to allow more potassium flow into the cell than out, its activity is essential for maintaining the electrical stability of cells. The channel's function is modulated by extracellular potassium levels and can be inhibited by internal magnesium or extracellular barium or cesium.
Therapeutic significance:
Kir2.1 is implicated in critical cardiac conditions including Long QT syndrome 7, Short QT syndrome 3, and familial Atrial fibrillation 9. These disorders highlight the channel's significance in cardiac rhythm regulation, where dysfunction can lead to life-threatening arrhythmias. Understanding Kir2.1's role offers a pathway to novel therapeutic strategies targeting these cardiac abnormalities.
