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 Regenerating islet-derived protein 3-alpha 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 Regenerating islet-derived protein 3-alpha 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 Regenerating islet-derived protein 3-alpha, 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 Regenerating islet-derived protein 3-alpha. 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 Regenerating islet-derived protein 3-alpha. 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 Regenerating islet-derived protein 3-alpha 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.
Regenerating islet-derived protein 3-alpha
partner:
Reaxense
upacc:
Q06141
UPID:
REG3A_HUMAN
Alternative names:
Hepatointestinal pancreatic protein; Human proislet peptide; Pancreatitis-associated protein 1; Regenerating islet-derived protein III-alpha
Alternative UPACC:
Q06141
Background:
Regenerating islet-derived protein 3-alpha, known by alternative names such as Hepatointestinal pancreatic protein and Pancreatitis-associated protein 1, plays a crucial role in the body's defense against Gram-positive bacteria. It achieves this by binding to carbohydrate moieties of peptidoglycan and forming a hexameric pore in bacterial membranes. Additionally, it functions as a hormone, influencing cell proliferation, differentiation, and inflammatory responses through various signaling pathways.
Therapeutic significance:
Understanding the role of Regenerating islet-derived protein 3-alpha could open doors to potential therapeutic strategies. Its ability to modulate immune responses and influence cell proliferation makes it a promising target for developing treatments for skin injuries and possibly enhancing pancreatic beta-cell function.
