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-stranded RNA-specific adenosine deaminase 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-stranded RNA-specific adenosine deaminase 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-stranded RNA-specific adenosine deaminase, 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-stranded RNA-specific adenosine deaminase. 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-stranded RNA-specific adenosine deaminase. 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-stranded RNA-specific adenosine deaminase 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-stranded RNA-specific adenosine deaminase
partner:
Reaxense
upacc:
P55265
UPID:
DSRAD_HUMAN
Alternative names:
136 kDa double-stranded RNA-binding protein; Interferon-inducible protein 4; K88DSRBP
Alternative UPACC:
P55265; B1AQQ9; B1AQR0; D3DV76; O15223; O43859; O43860; Q9BYM3; Q9BYM4
Background:
The Double-stranded RNA-specific adenosine deaminase, also known as Interferon-inducible protein 4, plays a crucial role in A-to-I RNA editing. This process involves the hydrolytic deamination of adenosine to inosine in double-stranded RNA, impacting gene expression and function through various mechanisms such as mRNA translation, pre-mRNA splicing, and RNA stability. Its editing capabilities extend to both viral and cellular RNAs, influencing the functional activities of proteins and the genetic stability of RNA virus genomes.
Therapeutic significance:
Linked to diseases like Dyschromatosis symmetrica hereditaria and Aicardi-Goutieres syndrome 6, this protein's unique function in RNA editing and virus replication modulation highlights its potential as a target for therapeutic intervention. Understanding the role of Double-stranded RNA-specific adenosine deaminase could open doors to potential therapeutic strategies, especially in genetic and viral diseases.