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 Golgi reassembly-stacking protein 1 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 Golgi reassembly-stacking protein 1 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 Golgi reassembly-stacking protein 1, 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 Golgi reassembly-stacking protein 1. 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 Golgi reassembly-stacking protein 1. 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 Golgi reassembly-stacking protein 1 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.
Golgi reassembly-stacking protein 1
partner:
Reaxense
upacc:
Q9BQQ3
UPID:
GORS1_HUMAN
Alternative names:
Golgi peripheral membrane protein p65; Golgi phosphoprotein 5; Golgi reassembly-stacking protein of 65 kDa
Alternative UPACC:
Q9BQQ3; B3KWC8; Q3SYG7; Q8N272; Q96H42
Background:
Golgi reassembly-stacking protein 1, also known as Golgi peripheral membrane protein p65, Golgi phosphoprotein 5, and Golgi reassembly-stacking protein of 65 kDa, plays a pivotal role in the structure and function of the Golgi apparatus. It ensures the adhesion of membrane cisternae to form stacks, which align to create the Golgi ribbon. This protein, in concert with GORASP2/GRASP55, is essential for Golgi ribbon formation and maintenance, and is involved in the assembly and membrane stacking of the cisternae. It also plays a role in the reassembly of Golgi stacks post-mitosis and mediates the docking of transport vesicles with Golgi membranes.
Therapeutic significance:
Understanding the role of Golgi reassembly-stacking protein 1 could open doors to potential therapeutic strategies.
