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 RanBP-type and C3HC4-type zinc finger-containing protein 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 RanBP-type and C3HC4-type zinc finger-containing protein 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 RanBP-type and C3HC4-type zinc finger-containing protein 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 RanBP-type and C3HC4-type zinc finger-containing protein 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 RanBP-type and C3HC4-type zinc finger-containing protein 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 RanBP-type and C3HC4-type zinc finger-containing protein 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.
RanBP-type and C3HC4-type zinc finger-containing protein 1
partner:
Reaxense
upacc:
Q9BYM8
UPID:
HOIL1_HUMAN
Alternative names:
HBV-associated factor 4; Heme-oxidized IRP2 ubiquitin ligase 1; Hepatitis B virus X-associated protein 4; RING finger protein 54; RING-type E3 ubiquitin transferase HOIL-1; Ubiquitin-conjugating enzyme 7-interacting protein 3
Alternative UPACC:
Q9BYM8; O95623; Q86SL2; Q96BS3; Q9BYM9
Background:
RanBP-type and C3HC4-type zinc finger-containing protein 1, also known as HOIL-1, plays a pivotal role in the immune response and inflammation regulation through its involvement in the LUBAC complex. This complex is crucial for NF-kappa-B activation, JNK signaling pathways, and the formation of a ubiquitin coat on invading bacteria, signaling them for destruction. HOIL-1's ability to ubiquitinate substrates like IREB2 and IRF3 underscores its significance in cellular signaling and immune defense mechanisms.
Therapeutic significance:
Given its central role in inflammation and immune response, targeting HOIL-1 could offer new avenues for treating Polyglucosan body myopathy 1, a severe condition marked by muscle weakness and cardiomyopathy. Understanding HOIL-1's functions could pave the way for innovative therapies, potentially transforming patient outcomes in diseases characterized by inflammation and immune dysregulation.
