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 Protein canopy homolog 3 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 Protein canopy homolog 3 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 Protein canopy homolog 3, 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 Protein canopy homolog 3. 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 Protein canopy homolog 3. 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 Protein canopy homolog 3 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.
Protein canopy homolog 3
partner:
Reaxense
upacc:
Q9BT09
UPID:
CNPY3_HUMAN
Alternative names:
CTG repeat protein 4a; Expanded repeat-domain protein CAG/CTG 5; Protein associated with TLR4; Trinucleotide repeat-containing gene 5 protein
Alternative UPACC:
Q9BT09; O15412; Q0P6I2; Q8NF54; Q8WTU8; Q9P0F2
Background:
Protein canopy homolog 3, also known as CTG repeat protein 4a, Expanded repeat-domain protein CAG/CTG 5, and Protein associated with TLR4, plays a crucial role in the immune system. It acts as a Toll-like receptor (TLR)-specific co-chaperone for HSP90B1, essential for proper TLR folding, excluding TLR3, facilitating TLR's exit from the endoplasmic reticulum. This process is vital for initiating both innate and adaptive immune responses.
Therapeutic significance:
The protein is linked to Developmental and epileptic encephalopathy 60, a severe condition characterized by early-onset epilepsies, neurodevelopmental impairment, and a poor prognosis. Understanding the role of Protein canopy homolog 3 in this disease could pave the way for innovative therapeutic strategies targeting the underlying genetic variants.
