AI-ACCELERATED DRUG DISCOVERY

Deoxyribonuclease-2-alpha

Explore its Potential with AI-Driven Innovation
Predicted by Alphafold

Deoxyribonuclease-2-alpha - Focused Library Design

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 Deoxyribonuclease-2-alpha 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 Deoxyribonuclease-2-alpha 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 Deoxyribonuclease-2-alpha, 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 Deoxyribonuclease-2-alpha. 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 Deoxyribonuclease-2-alpha. 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 Deoxyribonuclease-2-alpha 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.

Deoxyribonuclease-2-alpha

partner:

Reaxense

upacc:

O00115

UPID:

DNS2A_HUMAN

Alternative names:

Acid DNase; Deoxyribonuclease II alpha; Lysosomal DNase II; R31240_2

Alternative UPACC:

O00115; B2RD06; B7Z4K6; O43910

Background:

Deoxyribonuclease-2-alpha, also known as Acid DNase, Lysosomal DNase II, and R31240_2, is pivotal in DNA hydrolysis under acidic conditions, favoring double-stranded DNA. It plays a crucial role in clearing nucleic acids generated through apoptosis, thus preventing autoinflammation. This protein is essential for fetal development and definitive erythropoiesis in fetal liver and bone marrow by degrading nuclear DNA expelled from erythroid precursor cells.

Therapeutic significance:

Deoxyribonuclease-2-alpha is linked to Autoinflammatory-pancytopenia syndrome, a disorder characterized by severe anemia, thrombocytopenia, and a hyperinflammatory state. Understanding the role of Deoxyribonuclease-2-alpha could open doors to potential therapeutic strategies for this syndrome.

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