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 Cyclic nucleotide-gated cation channel beta-1 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 Cyclic nucleotide-gated cation channel beta-1 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 Cyclic nucleotide-gated cation channel beta-1, 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 Cyclic nucleotide-gated cation channel beta-1. 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 Cyclic nucleotide-gated cation channel beta-1. 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 Cyclic nucleotide-gated cation channel beta-1 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.
Cyclic nucleotide-gated cation channel beta-1
partner:
Reaxense
upacc:
Q14028
UPID:
CNGB1_HUMAN
Alternative names:
Cyclic nucleotide-gated cation channel 4; Cyclic nucleotide-gated cation channel gamma; Cyclic nucleotide-gated cation channel modulatory subunit; Cyclic nucleotide-gated channel beta-1; Glutamic acid-rich protein
Alternative UPACC:
Q14028; H3BN09; O43636; Q13059; Q14029; Q9UMG2
Background:
Cyclic nucleotide-gated cation channel beta-1, also known as CNG channel beta-1, plays a pivotal role in visual and olfactory signal transduction. It forms a crucial part of cyclic nucleotide-gated (CNG) channels, facilitating the regulation of ion flow into rod photoreceptor outer segments in response to changes in intracellular cGMP levels. This protein's functionality is enhanced by its isoform GARP2, which modulates rod photoreceptor phosphodiesterase activity, crucial for minimizing 'dark noise' and enabling photon detection.
Therapeutic significance:
Given its critical role in visual processes, Cyclic nucleotide-gated cation channel beta-1 is directly implicated in Retinitis pigmentosa 45, a retinal dystrophy characterized by night vision blindness and progressive loss of visual field. Understanding the protein's function and its genetic variants could pave the way for innovative treatments targeting the underlying mechanisms of this and potentially other related visual disorders.
