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 Metal cation symporter ZIP8 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 Metal cation symporter ZIP8 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 Metal cation symporter ZIP8, 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 Metal cation symporter ZIP8. 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 Metal cation symporter ZIP8. 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 Metal cation symporter ZIP8 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.
Metal cation symporter ZIP8
partner:
Reaxense
upacc:
Q9C0K1
UPID:
S39A8_HUMAN
Alternative names:
BCG-induced integral membrane protein in monocyte clone 103 protein; LIV-1 subfamily of ZIP zinc transporter 6; Solute carrier family 39 member 8; Zrt- and Irt-like protein 8
Alternative UPACC:
Q9C0K1; B4E2H3; Q96SM9; Q9BVC0; Q9NSA4
Background:
The Metal cation symporter ZIP8, also known as Solute carrier family 39 member 8, plays a pivotal role in transporting divalent metal cations like zinc and manganese across the plasma membrane. These cations are crucial for various physiological processes including development, tissue homeostasis, and immunity. ZIP8 functions by transporting an electroneutral complex composed of a divalent metal cation and bicarbonate anions, contributing to the cellular uptake of essential nutrients like selenium, and also transporting non-essential, toxic metals such as cadmium.
Therapeutic significance:
ZIP8's involvement in congenital disorder of glycosylation 2N, a condition characterized by under-glycosylated serum glycoproteins leading to a wide array of clinical features, underscores its therapeutic potential. Targeting ZIP8's function could pave the way for novel treatments for this disorder and possibly other related conditions, highlighting the importance of understanding its role in disease mechanisms.
