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 Abscission/NoCut checkpoint regulator 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 Abscission/NoCut checkpoint regulator 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 Abscission/NoCut checkpoint regulator, 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 Abscission/NoCut checkpoint regulator. 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 Abscission/NoCut checkpoint regulator. 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 Abscission/NoCut checkpoint regulator 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.
Abscission/NoCut checkpoint regulator
partner:
Reaxense
upacc:
Q96K21
UPID:
ANCHR_HUMAN
Alternative names:
MLL partner containing FYVE domain; Zinc finger FYVE domain-containing protein 19
Alternative UPACC:
Q96K21; B3KVB2; C9JNF4; H3BUF9; Q86WC2; Q8WU96
Background:
The Abscission/NoCut checkpoint regulator, also known as Zinc finger FYVE domain-containing protein 19, plays a pivotal role in cytokinesis. It ensures the proper timing of abscission, preventing premature resolution of intercellular chromosome bridges and DNA damage accumulation. This protein, alongside CHMP4C, maintains VPS4 at the midbody ring until the abscission checkpoint signaling concludes.
Therapeutic significance:
Linked to Cholestasis, progressive familial intrahepatic, 9 (PFIC9), a severe liver disorder, understanding the Abscission/NoCut checkpoint regulator's role could unveil new therapeutic avenues. The PFIC9-associated variant p.M76V suggests a direct impact on protein function, highlighting its potential as a therapeutic target.
