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 AP-4 complex subunit epsilon-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 AP-4 complex subunit epsilon-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 AP-4 complex subunit epsilon-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 AP-4 complex subunit epsilon-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 AP-4 complex subunit epsilon-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 AP-4 complex subunit epsilon-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.
AP-4 complex subunit epsilon-1
partner:
Reaxense
upacc:
Q9UPM8
UPID:
AP4E1_HUMAN
Alternative names:
AP-4 adaptor complex subunit epsilon; Adaptor-related protein complex 4 subunit epsilon-1; Epsilon subunit of AP-4; Epsilon-adaptin
Alternative UPACC:
Q9UPM8; A0AVD6; A1L4A9; A6NNX7; H0YKX4; Q68D31; Q9Y588
Background:
AP-4 complex subunit epsilon-1, known by alternative names such as AP-4 adaptor complex subunit epsilon and epsilon-adaptin, plays a crucial role in vesicular transport. It is a component of the adaptor protein complex 4 (AP-4), involved in forming vesicle coats and selecting cargo for transport. This protein is essential for the targeting of proteins from the trans-Golgi network (TGN) to the endosomal-lysosomal system, protein sorting to the basolateral membrane in epithelial cells, and the proper localization of somatodendritic proteins in neurons.
Therapeutic significance:
AP-4 complex subunit epsilon-1 is implicated in Spastic paraplegia 51 and familial persistent stuttering. Understanding its role could lead to novel therapeutic strategies for these neurodegenerative and speech disorders.
