Introduction & Background

Inflammatory diseases are a significant global health threat and rank among the leading causes of mortality and disability worldwide. According to the World Health Organization, chronic conditions such as rheumatoid arthritis, inflammatory bowel disease, and systemic autoimmune disorders affect hundreds of millions of people globally. These conditions not only reduce patients’ quality of life but also impose substantial burdens on healthcare systems. One promising target for anti-inflammatory therapy is tyrosine kinase 2 (TYK2), a protein crucial for regulating immune responses. Dysfunction in TYK2 is closely linked to the development and progression of chronic inflammatory and autoimmune diseases, with its pseudokinase domain (JH2) playing a key regulatory role over its kinase domain (JH1).

Challenge / Objective

The project was designed with the following objectives:

• Identify Compounds with Selectivity: Discover chemical compounds that selectively bind to the JH2 pseudokinase domain of TYK2 while avoiding interaction with the JH1 kinase domain to enhance therapeutic specificity.

• Confirm Selectivity Across the JAK Family: Evaluate these compounds against other proteins in the Janus kinase family to eliminate off-target interactions that could compromise safety and efficacy.

• Optimize Pharmacokinetic Properties: Refine the selection based on ADMET analysis to ensure optimal pharmacokinetic and drug-like characteristics.

Approach

• Virtual Screening:

A virtual screening was conducted on the ZINC database, which contains approximately 900 million chemical compounds. This extensive screening aimed to identify candidates with the potential to selectively bind to the JH2 pseudokinase domain of TYK2.

• Selectivity Evaluation:

After the initial screening, the compounds were further evaluated for their ability to interact with other Janus kinase proteins. This step was critical to confirm their selectivity for the TYK2 JH2 domain.

• Collaboration with Toxometris.AI:

The most promising compounds were then assessed in collaboration with Toxometris.AI, where their ADMET properties were analyzed. This collaboration helped refine the candidate list to include compounds with optimal pharmacokinetic and drug-like characteristics.

Results

• Diverse and Potent Candidates:

The study uncovered potential chemical compounds spanning a wide range of chemical classes, exhibiting remarkable structural diversity and high affinity for TYK2.

• Superior Binding Affinity:

Notably, some compounds demonstrated even greater binding affinity than Deucravacitinib, the first-in-class selective inhibitor developed by BMS.

• Novel Structural Insights:

Conformational and chemical analyses revealed novel substructures and scaffolds that could facilitate strong binding within the JH2 pseudokinase domain pocket.

Impact and Next Steps

This study highlights a promising strategy for developing selective TYK2 inhibitors, which could lead to innovative therapeutic approaches for chronic inflammatory and autoimmune diseases. The integration of a large-scale virtual screening, rigorous selectivity evaluation, and ADMET analysis ensures that only the most promising compounds are advanced. Future work will focus on further optimization of these compounds and exploring their potential in preclinical studies.