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 Granulocyte colony-stimulating factor receptor 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 Granulocyte colony-stimulating factor receptor 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 Granulocyte colony-stimulating factor receptor, 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 Granulocyte colony-stimulating factor receptor. 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 Granulocyte colony-stimulating factor receptor. 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 Granulocyte colony-stimulating factor receptor 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.
Granulocyte colony-stimulating factor receptor
partner:
Reaxense
upacc:
Q99062
UPID:
CSF3R_HUMAN
Alternative names:
-
Alternative UPACC:
Q99062
Background:
The Granulocyte colony-stimulating factor receptor (G-CSFR), encoded by the gene with accession number Q99062, is pivotal in hematopoiesis. It serves as a receptor for CSF3, playing an essential role in the maturation and differentiation of cells within the neutrophil lineage. Its functions extend to promoting cell proliferation, differentiation, and survival, and it may also participate in cell surface adhesion or recognition processes.
Therapeutic significance:
G-CSFR is directly implicated in hereditary neutrophilia and severe congenital neutropenia 7, autosomal recessive, conditions marked by abnormal neutrophil counts and susceptibility to infections. Targeting G-CSFR pathways offers a promising avenue for developing treatments for these hematopoietic disorders, highlighting the receptor's therapeutic potential.
