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 Interferon regulatory factor 9 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 Interferon regulatory factor 9 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 Interferon regulatory factor 9, 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 Interferon regulatory factor 9. 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 Interferon regulatory factor 9. 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 Interferon regulatory factor 9 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.
Interferon regulatory factor 9
partner:
Reaxense
upacc:
Q00978
UPID:
IRF9_HUMAN
Alternative names:
IFN-alpha-responsive transcription factor subunit; ISGF3 p48 subunit; Interferon-stimulated gene factor 3 gamma; Transcriptional regulator ISGF3 subunit gamma
Alternative UPACC:
Q00978; D3DS61
Background:
Interferon regulatory factor 9 (IRF9) serves as a critical component in the immune response against viral infections. It functions as a transcription factor essential for mediating signaling by type I interferons, including IFN-alpha and IFN-beta. Upon activation, IRF9, in conjunction with phosphorylated STAT1 and STAT2, forms the ISGF3 transcription factor complex, which enters the nucleus to activate interferon-stimulated genes, propelling the cell into an antiviral state.
Therapeutic significance:
Given its pivotal role in anti-viral immunity, IRF9's dysfunction is linked to Immunodeficiency 65, a severe disorder marked by recurrent viral infections and adverse reactions to live vaccines. Understanding the role of IRF9 could open doors to potential therapeutic strategies for enhancing viral resistance and treating immunodeficiency disorders.
