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 Iron-responsive element-binding protein 2 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 Iron-responsive element-binding protein 2 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 Iron-responsive element-binding protein 2, 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 Iron-responsive element-binding protein 2. 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 Iron-responsive element-binding protein 2. 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 Iron-responsive element-binding protein 2 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.
Iron-responsive element-binding protein 2
partner:
Reaxense
upacc:
P48200
UPID:
IREB2_HUMAN
Alternative names:
Iron regulatory protein 2
Alternative UPACC:
P48200; A0A0A6YY96; A8KAC7; E1CJT9; H0YKU0; Q13095; Q1HE21; Q59FQ7; Q8WVK6; Q9UF17
Background:
Iron-responsive element-binding protein 2 (IREB2), also known as Iron regulatory protein 2, plays a crucial role in iron metabolism. It binds to iron-responsive elements (IREs) in the mRNA of key iron metabolism genes, regulating their expression in response to iron levels. This protein's interaction with IREs in ferritin and transferrin receptor mRNA modulates iron storage and transport.
Therapeutic significance:
IREB2's involvement in Neurodegeneration, early-onset, with choreoathetoid movements and microcytic anemia highlights its potential as a therapeutic target. Understanding IREB2's function could pave the way for novel treatments for this severe disorder, emphasizing the importance of research into its regulatory mechanisms and genetic variants.
