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 GRB10-interacting GYF 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 GRB10-interacting GYF 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 GRB10-interacting GYF 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 GRB10-interacting GYF 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 GRB10-interacting GYF 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 GRB10-interacting GYF 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.
GRB10-interacting GYF protein 2
partner:
Reaxense
upacc:
Q6Y7W6
UPID:
GGYF2_HUMAN
Alternative names:
PERQ amino acid-rich with GYF domain-containing protein 2; Trinucleotide repeat-containing gene 15 protein
Alternative UPACC:
Q6Y7W6; A6H8W4; B9EG55; E9PBB0; O75137; Q7Z2Z8; Q7Z3I2; Q96HU4; Q9NV82
Background:
GRB10-interacting GYF protein 2 (GIGYF2) plays a pivotal role in cellular processes by acting as a key component of the 4EHP-GYF2 complex, which represses translation initiation. It bridges EIF4E2 to ZFP36/TTP, linking translation repression with mRNA decay, and is involved in regulating tyrosine kinase receptor signaling, including IGF1 and insulin receptors. Additionally, GIGYF2 assists in ribosome-associated quality control by sequestering mRNA caps, thus blocking ribosome initiation.
Therapeutic significance:
While the direct association of GIGYF2 with Parkinson disease 11 remains uncertain, understanding its complex role in cellular signaling and protein synthesis regulation could unveil novel therapeutic strategies, particularly in neurodegenerative disorders.
