AI-ACCELERATED DRUG DISCOVERY

Doublecortin domain-containing protein 2

Explore its Potential with AI-Driven Innovation
Predicted by Alphafold

Doublecortin domain-containing protein 2 - 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 Doublecortin domain-containing protein 2 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 Doublecortin domain-containing protein 2 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 Doublecortin domain-containing protein 2, 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 Doublecortin domain-containing protein 2. 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 Doublecortin domain-containing protein 2. 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 Doublecortin domain-containing protein 2 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.

Doublecortin domain-containing protein 2

partner:

Reaxense

upacc:

Q9UHG0

UPID:

DCDC2_HUMAN

Alternative names:

Protein RU2S

Alternative UPACC:

Q9UHG0; Q5VTR8; Q5VTR9; Q86W35; Q9UFD1; Q9UHG1; Q9ULR6

Background:

Doublecortin domain-containing protein 2, also known as Protein RU2S, plays a pivotal role in the inhibition of the canonical Wnt signaling pathway, crucial for cell fate determination, migration, and organogenesis. This protein is also implicated in neuronal migration during cerebral neocortex development and is vital for ciliogenesis and maintaining ciliary length, essential for cellular signaling and homeostasis.

Therapeutic significance:

Protein RU2S is associated with a spectrum of diseases, including Dyslexia 2, Nephronophthisis 19, autosomal recessive Deafness 66, and neonatal Sclerosing cholangitis. These associations highlight its potential as a therapeutic target for cognitive disorders, kidney and liver diseases, and hearing loss. Understanding the role of Protein RU2S could open doors to potential therapeutic strategies.

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