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 Eukaryotic translation initiation factor 4E type 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 Eukaryotic translation initiation factor 4E type 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 Eukaryotic translation initiation factor 4E type 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 Eukaryotic translation initiation factor 4E type 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 Eukaryotic translation initiation factor 4E type 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 Eukaryotic translation initiation factor 4E type 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.
Eukaryotic translation initiation factor 4E type 2
partner:
Reaxense
upacc:
O60573
UPID:
IF4E2_HUMAN
Alternative names:
Eukaryotic translation initiation factor 4E homologous protein; Eukaryotic translation initiation factor 4E-like 3; eIF4E-like protein 4E-LP; mRNA cap-binding protein 4EHP; mRNA cap-binding protein type 3
Alternative UPACC:
O60573; B8ZZJ9; O75349
Background:
Eukaryotic translation initiation factor 4E type 2 (EIF4E2) is a pivotal protein in cellular mechanisms, primarily recognized for its role in binding the 7-methylguanosine-containing mRNA cap, a crucial step in the initiation of translation. Unlike EIF4E, EIF4E2 does not bind to eIF4G, indicating its unique function in competing with EIF4E to inhibit the assembly of the eIF4F complex at the mRNA cap. Additionally, EIF4E2 is a key player in miRNA-mediated translational repression and is involved in the cellular response to viral infections, including SARS-CoV-2, by modulating the translation initiation of genes critical to the antiviral immune response.
Therapeutic significance:
Understanding the role of Eukaryotic translation initiation factor 4E type 2 could open doors to potential therapeutic strategies, especially in the context of viral infections and the regulation of immune response genes.
