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 Arginase-2, mitochondrial 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 Arginase-2, mitochondrial 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 Arginase-2, mitochondrial, 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 Arginase-2, mitochondrial. 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 Arginase-2, mitochondrial. 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 Arginase-2, mitochondrial 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.
Arginase-2, mitochondrial
partner:
Reaxense
upacc:
P78540
UPID:
ARGI2_HUMAN
Alternative names:
Arginase II; Kidney-type arginase; Non-hepatic arginase; Type II arginase
Alternative UPACC:
P78540; B2R690; Q6FHY8
Background:
Arginase-2, a mitochondrial enzyme also known as Kidney-type arginase, Non-hepatic arginase, and Type II arginase, plays a pivotal role in arginine metabolism, impacting nitric oxide synthesis and immune responses. Its activities extend to regulating L-arginine availability, influencing T cell survival, and modulating inflammation in various tissues. This protein's involvement in endothelial cell senescence, vascular smooth muscle cell apoptosis, and autophagy underscores its significance in cellular and vascular health.
Therapeutic significance:
Understanding the role of Arginase-2 could open doors to potential therapeutic strategies, particularly in conditions where arginine metabolism, immune response modulation, and vascular health are compromised. Its multifaceted functions offer a promising avenue for developing interventions aimed at enhancing immune resilience, mitigating inflammation, and promoting vascular integrity.
