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 Translation initiation factor eIF-2B subunit epsilon 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 Translation initiation factor eIF-2B subunit epsilon 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 Translation initiation factor eIF-2B subunit epsilon, 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 Translation initiation factor eIF-2B subunit epsilon. 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 Translation initiation factor eIF-2B subunit epsilon. 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 Translation initiation factor eIF-2B subunit epsilon 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.
Translation initiation factor eIF-2B subunit epsilon
partner:
Reaxense
upacc:
Q13144
UPID:
EI2BE_HUMAN
Alternative names:
eIF-2B GDP-GTP exchange factor subunit epsilon
Alternative UPACC:
Q13144; Q541Z1; Q96D04
Background:
The Translation initiation factor eIF-2B subunit epsilon, also known as eIF-2B GDP-GTP exchange factor subunit epsilon, plays a pivotal role in protein synthesis. It catalyzes the exchange of eukaryotic initiation factor 2-bound GDP for GTP, a critical step in the initiation of translation. This protein's function is essential for the regulation of protein synthesis, impacting cellular growth and response to stress.
Therapeutic significance:
Leukoencephalopathy with vanishing white matter 5, a devastating brain disease, is directly linked to mutations in the gene encoding this protein. The disease manifests with progressive cerebellar ataxia, spasticity, cognitive deficits, and in severe cases, ovarian dysfunction in females. Understanding the role of Translation initiation factor eIF-2B subunit epsilon could open doors to potential therapeutic strategies for this and related neurological disorders.
