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 Double homeobox protein 4 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 Double homeobox protein 4 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 Double homeobox protein 4, 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 Double homeobox protein 4. 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 Double homeobox protein 4. 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 Double homeobox protein 4 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.
Double homeobox protein 4
partner:
Reaxense
upacc:
Q9UBX2
UPID:
DUX4_HUMAN
Alternative names:
Double homeobox protein 10
Alternative UPACC:
Q9UBX2; E2JJS1
Background:
Double homeobox protein 4 (DUX4) functions as a transcription factor, crucial during early embryogenesis. It binds to specific DNA elements, regulating gene expression by promoting or inhibiting histone acetylation. DUX4's role extends to activating essential proteins like ZSCAN4 and KDM4E, and it may also influence microRNA expression. Its involvement in transcriptional regulation underscores its significance in cellular processes.
Therapeutic significance:
DUX4's aberrant expression is linked to Facioscapulohumeral muscular dystrophy 1 (FSHD1), a degenerative muscle disease. The disease mechanism involves the reduction of D4Z4 macrosatellite repeats on chromosome 4q35, leading to DUX4 misexpression. Understanding DUX4's role could pave the way for innovative therapeutic strategies targeting its pathway to mitigate FSHD1 progression.
