AI-ACCELERATED DRUG DISCOVERY

Nucleotide-binding oligomerization domain-containing protein 2

Explore its Potential with AI-Driven Innovation
Predicted by Alphafold

Nucleotide-binding oligomerization 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 Nucleotide-binding oligomerization 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 Nucleotide-binding oligomerization 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 Nucleotide-binding oligomerization 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 Nucleotide-binding oligomerization 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 Nucleotide-binding oligomerization 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 Nucleotide-binding oligomerization 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.

Nucleotide-binding oligomerization domain-containing protein 2

partner:

Reaxense

upacc:

Q9HC29

UPID:

NOD2_HUMAN

Alternative names:

Caspase recruitment domain-containing protein 15; Inflammatory bowel disease protein 1

Alternative UPACC:

Q9HC29; E2JEQ6; Q96RH5; Q96RH6; Q96RH8

Background:

Nucleotide-binding oligomerization domain-containing protein 2 (NOD2) is a critical pattern recognition receptor (PRR) that plays a pivotal role in gastrointestinal immunity. It detects bacterial peptidoglycan fragments, activating immune responses. NOD2's interaction with various signaling molecules triggers pathways essential for maintaining intestinal microbiota balance and controlling inflammation.

Therapeutic significance:

NOD2's involvement in Blau syndrome, Inflammatory bowel disease 1, and Yao syndrome highlights its therapeutic significance. Understanding NOD2's role could lead to innovative treatments for these conditions, emphasizing the importance of targeting this protein in drug discovery efforts.

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