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 H/ACA ribonucleoprotein complex subunit DKC1 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 H/ACA ribonucleoprotein complex subunit DKC1 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 H/ACA ribonucleoprotein complex subunit DKC1, 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 H/ACA ribonucleoprotein complex subunit DKC1. 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 H/ACA ribonucleoprotein complex subunit DKC1. 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 H/ACA ribonucleoprotein complex subunit DKC1 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.
H/ACA ribonucleoprotein complex subunit DKC1
partner:
Reaxense
upacc:
O60832
UPID:
DKC1_HUMAN
Alternative names:
CBF5 homolog; Dyskerin; Nopp140-associated protein of 57 kDa; Nucleolar protein NAP57; Nucleolar protein family A member 4; snoRNP protein DKC1
Alternative UPACC:
O60832; F5BSB3; O43845; Q96G67; Q9Y505
Background:
H/ACA ribonucleoprotein complex subunit DKC1, also known as Dyskerin, plays a pivotal role in cellular processes, including ribosome biogenesis and telomere maintenance. It catalyzes the pseudouridylation of rRNA, a modification crucial for stabilizing rRNA structure and function. Dyskerin's involvement in cell adhesion and proliferation further underscores its multifaceted biological significance.
Therapeutic significance:
Dyskerin's mutation is directly linked to Dyskeratosis congenita and Hoyeraal-Hreidarsson syndrome, diseases characterized by bone marrow failure and developmental anomalies. Understanding Dyskerin's role could pave the way for innovative treatments targeting these genetic disorders, highlighting its therapeutic potential.
