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Published on: June 8, 2022
Structural Basis for How Biologic Medicines Bind their Targets in Psoriasis Therapy.
Sherif A Eldirany1, Minh Ho1, Christopher G Bunick1,2
1Department of Dermatology, Yale University, New Haven, CT.
Understanding the molecular differences between biologic therapies for inflammatory disorders is crucial for physicians. Analyzing structural biology reveals key differences in tumor necrosis factor alpha (TNFα), interleukin-17 (IL-17), and interleukin-23 (IL-23) inhibitors, impacting treatment decisions.
Area of Science:
- Immunology
- Structural Biology
- Dermatology
Background:
- Biologic therapies are now first-line treatments for many inflammatory disorders.
- Physician familiarity with molecular mechanisms of biologics is essential for informed therapeutic decisions and patient understanding.
- Molecular differences among biologics are critical for patient safety and clinical response.
Purpose of the Study:
- To analyze structural biology information of biologics used for psoriasis treatment.
- To compare molecular differences in inhibitors of tumor necrosis factor alpha (TNFα), interleukin-17 (IL-17), and interleukin-23 (IL-23).
- To correlate structural differences with clinical data and identify needs for further research.
Main Methods:
- Review and analysis of existing structural biology data for psoriasis biologics.
- Characterization of molecular surface properties of binding epitopes.
- Comparison of epitope location, hydrophobicity, and charge across different drug classes.
Main Results:
- Significant molecular differences were identified in the binding epitopes of TNFα, IL-17, and IL-23 inhibitors.
- Variations in epitope location, hydrophobicity, and charge were observed.
- Some structural differences showed potential correlation with clinical data.
Conclusions:
- Molecular variations among biologic therapies for psoriasis are substantial.
- Further structural information is needed to fully elucidate structure-function relationships.
- Understanding these molecular differences can optimize prescribing practices and improve patient outcomes.
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