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 Protein transport protein Sec24D 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 Protein transport protein Sec24D 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 Protein transport protein Sec24D, 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 Protein transport protein Sec24D. 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 Protein transport protein Sec24D. 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 Protein transport protein Sec24D 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.
Protein transport protein Sec24D
partner:
Reaxense
upacc:
O94855
UPID:
SC24D_HUMAN
Alternative names:
SEC24-related protein D
Alternative UPACC:
O94855; Q8IYI7
Background:
Protein transport protein Sec24D, also known as SEC24-related protein D, is a crucial component of the coat protein complex II (COPII). This complex is instrumental in the formation of transport vesicles from the endoplasmic reticulum (ER), facilitating the physical deformation of the ER membrane into vesicles and the selection of cargo molecules for transport to the Golgi complex. Sec24D plays a pivotal role in cargo selection within the COPII complex, showing specificity for GPI-anchored proteins and IxM motif-containing cargos like SNAREs GOSR2 and STX5.
Therapeutic significance:
Given its involvement in Cole-Carpenter syndrome 2, a disorder characterized by severe bone fragility and craniosynostosis, understanding the role of Protein transport protein Sec24D could open doors to potential therapeutic strategies. Its specific function in cargo selection suggests a targeted approach in treating the syndrome's underlying cellular transport issues.
