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 E3 ubiquitin-protein ligase RING2 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 E3 ubiquitin-protein ligase RING2 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 E3 ubiquitin-protein ligase RING2, 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 E3 ubiquitin-protein ligase RING2. 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 E3 ubiquitin-protein ligase RING2. 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 E3 ubiquitin-protein ligase RING2 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.
E3 ubiquitin-protein ligase RING2
partner:
Reaxense
upacc:
Q99496
UPID:
RING2_HUMAN
Alternative names:
Huntingtin-interacting protein 2-interacting protein 3; Protein DinG; RING finger protein 1B; RING finger protein 2; RING finger protein BAP-1; RING-type E3 ubiquitin transferase RING2
Alternative UPACC:
Q99496; B2RBS7; B3KRH1; Q5TEN1; Q5TEN2
Background:
E3 ubiquitin-protein ligase RING2, also known as RING finger protein 2, plays a pivotal role in histone code and gene regulation by mediating monoubiquitination of 'Lys-119' of histone H2A. This modification is crucial for epigenetic transcriptional repression, including X chromosome inactivation in females. RING2 is a key component of the Polycomb group (PcG) PRC1-like complex, essential for maintaining genes in a transcriptionally repressive state throughout development.
Therapeutic significance:
RING2's involvement in Luo-Schoch-Yamamoto syndrome, characterized by growth retardation, intellectual disability, and seizures, underscores its potential as a therapeutic target. Understanding RING2's role could open doors to novel strategies for treating this disorder.
