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Structure-based Computer-aided Drug Design and Analyses against Disease Target: Cytokine IL-6/IL-6R/GP130 Complex

Shi, Guqin
http://rave.ohiolink.edu/etdc/view?acc_num=osu151197172881965

Abstract Details

2017, Doctor of Philosophy, Ohio State University, Pharmaceutical Sciences.
IL-6 is a pleiotropic cytokine that participates in various cellular processes such as acute-phase response, immune response, and hematopoiesis. It is also involved in cell proliferation, survival, and apoptosis. Excessive IL-6 signaling leads to chronic inflammation and promotes malignancies. Blockade of IL-6 is therefore a potential strategy for developing cancer therapeutics. Most current successful anti-IL-6 signaling drugs are antibodies with very few small molecule drugs reported. More importantly, a structure-based rationale for IL-6/gp130 protein-protein interaction (PPI) inhibitor design was absent. Small molecule inhibitor design targeting PPI interfaces is very challenging. Lack of success against shallow PPI interfaces, as present in IL-6/gp130, suggests that more effective approaches are needed to tackle the problem. Computational modeling techniques are especially valuable in PPI inhibitor design. In this dissertation, varied computational methods were used to facilitate the rational design of small molecule inhibitors against the shallow IL-6/gp130 interface. We started from a natural product, Madindoline A (MDL-A), which was reported as a highly selective IL-6 inhibitor by binding to gp130 extracellular domains albeit with relatively weak binding affinity (288 µM) and limited inhibitory efficacy in cancer cellular assays. Through dynamics simulations and extensive free energy analyses, we identified two hot spots at the IL-6 site III/gp130 D1 domain interface and characterized the MDL-A binding mode on the D1 domain of gp130 (gp130-D1). Based on these findings, we optimized the MDL-A scaffold and designed several generations of inhibitors with three different strategies through structure-based approaches and ensemble molecular dockings. As compared to MDL-A, the latest generation of inhibitors (LLM-4x series) have 15-fold improved affinities, which were determined by surface plasmon resonance (SPR). Furthermore, we correlated our computed energy models with experimental binding data and illustrated the potential binding mechanisms of the inhibitors. This, in turn, not only provides guidance for the next cycle of inhibitor optimizations, but also offers insights and suggestions for shallow PPI interface inhibitor design especially when computational techniques are applied.
Chenglong Li (Advisor)
Werner Tjarks (Committee Chair)
Karl Werbovetz (Committee Member)
141 p.
Pharmacy Sciences
drug design; structure-based; computer-aided; IL-6; GP130

Recommended Citations

Citations

  • Shi, G. (2017). Structure-based Computer-aided Drug Design and Analyses against Disease Target: Cytokine IL-6/IL-6R/GP130 Complex [Doctoral dissertation, Ohio State University]. OhioLINK Electronic Theses and Dissertations Center. http://rave.ohiolink.edu/etdc/view?acc_num=osu151197172881965

    APA Style (7th edition)

  • Shi, Guqin. Structure-based Computer-aided Drug Design and Analyses against Disease Target: Cytokine IL-6/IL-6R/GP130 Complex. 2017. Ohio State University, Doctoral dissertation. OhioLINK Electronic Theses and Dissertations Center, http://rave.ohiolink.edu/etdc/view?acc_num=osu151197172881965.

    MLA Style (8th edition)

  • Shi, Guqin. "Structure-based Computer-aided Drug Design and Analyses against Disease Target: Cytokine IL-6/IL-6R/GP130 Complex." Doctoral dissertation, Ohio State University, 2017. http://rave.ohiolink.edu/etdc/view?acc_num=osu151197172881965

    Chicago Manual of Style (17th edition)

osu151197172881965
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© 2017, all rights reserved.
This open access ETD is published by The Ohio State University and OhioLINK.