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 Fructose-2,6-bisphosphatase TIGAR 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 Fructose-2,6-bisphosphatase TIGAR 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 Fructose-2,6-bisphosphatase TIGAR, 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 Fructose-2,6-bisphosphatase TIGAR. 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 Fructose-2,6-bisphosphatase TIGAR. 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 Fructose-2,6-bisphosphatase TIGAR 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.
Fructose-2,6-bisphosphatase TIGAR
partner:
Reaxense
upacc:
Q9NQ88
UPID:
TIGAR_HUMAN
Alternative names:
TP53-induced glycolysis and apoptosis regulator; TP53-induced glycolysis regulatory phosphatase
Alternative UPACC:
Q9NQ88; B2R840
Background:
Fructose-2,6-bisphosphatase TIGAR, identified by its alternative names TP53-induced glycolysis and apoptosis regulator and TP53-induced glycolysis regulatory phosphatase, plays a pivotal role in cellular metabolism. It hydrolyzes fructose-2,6-bisphosphate and fructose-1,6-bisphosphate, acting as a negative regulator of glycolysis. This action facilitates the activation of the pentose phosphate pathway (PPP), leading to NADPH production and a reduction in intracellular reactive oxygen species (ROS). TIGAR's function extends to protecting cells from oxidative or metabolic stress-induced cell death, promoting survival during hypoxia, and supporting adult intestinal regeneration and neuroprotection against ischemic brain damage.
Therapeutic significance:
Understanding the role of Fructose-2,6-bisphosphatase TIGAR could open doors to potential therapeutic strategies. Its involvement in reducing intracellular ROS levels, protecting against cell death, and promoting DNA repair highlights its potential as a target in treating oxidative stress-related conditions, ischemic injuries, and enhancing cancer cell survival through metabolic modulation.
