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 Voltage-dependent R-type calcium channel subunit alpha-1E 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 Voltage-dependent R-type calcium channel subunit alpha-1E 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 Voltage-dependent R-type calcium channel subunit alpha-1E, 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 Voltage-dependent R-type calcium channel subunit alpha-1E. 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 Voltage-dependent R-type calcium channel subunit alpha-1E. 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 Voltage-dependent R-type calcium channel subunit alpha-1E 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.
Voltage-dependent R-type calcium channel subunit alpha-1E
partner:
Reaxense
upacc:
Q15878
UPID:
CAC1E_HUMAN
Alternative names:
Brain calcium channel II; Calcium channel, L type, alpha-1 polypeptide, isoform 6; Voltage-gated calcium channel subunit alpha Cav2.3
Alternative UPACC:
Q15878; B1AM12; B1AM13; B1AM14; Q14580; Q14581
Background:
The Voltage-dependent R-type calcium channel subunit alpha-1E, known alternatively as Brain calcium channel II, plays a pivotal role in mediating calcium ion entry into neurons. This process is crucial for a myriad of cellular functions including muscle contraction, neurotransmitter release, and cell division. The alpha-1E subunit is distinctive for generating R-type calcium currents, part of the high-voltage activated group, and shows insensitivity to dihydropyridines.
Therapeutic significance:
Linked to Developmental and epileptic encephalopathy 69 (DEE69), a severe neurological disorder characterized by refractory seizures and neurodevelopmental impairment, the alpha-1E subunit's modulation of neuronal firing patterns presents a potential target for therapeutic intervention. Understanding its role could lead to novel treatments for DEE69, especially considering some patients' favorable response to topiramate.
