Predicted IL-18/IL-18R Binding Improvement Through Protein Interface Modification with Computer-aided Design

Abstract

Cytokine-mediated immunotherapy has rapidly emerged as an effective alternative approach for cancer treatment by modulating the anti-tumor response. Interleukin-18 (IL-18) has considered as a promising cancer therapeutic agent due to the ability of cytokine to inhibit cancer by enhancing natural killer (NK) cell and cytotoxic T cell responses. Since the activity of IL-18 required the specific binding to IL-18 receptors, the modification of binding residue at the interface of proteins is an attractive strategy for IL-18 activity enhancement. An aim of this study was thus to design and predict mutations increasing the activity of IL-18 through the integration of computational structure-based energy calculation and molecular dynamic simulations, using a crystal structure of human IL-18 in complex with the receptor as a template. We performed in silico saturation mutagenesis by mutating each of the unfavorable interface binding residues of IL-18. The relative free energy changes upon mutation (ΔΔG) were computed using FoldX algorithm. An interested mutation was selected based on two criteria: (1) the most favorable free energy contribution, and (2) the structural conservation. From total 227 possible mutations, four potential mutations were finally obtained. The selected four candidate mutations were E6M, E6M+N111S+R131G, E6M+K129M+R131G, and E6M+N111S+K129M+R131G could increase the receptor binding affinity and stability compared to the wild-type. The main interaction was due to the electrostatic interaction. These in silico acquired mutations were further investigated their impact on the overall structure and dynamic behavior using molecular dynamics simulation at 310 K and 1 atm. MD simulations demonstrated that the predicted mutation on IL-18 had no influence on the overall conformation stability, but increased flexibility in the β8-β9 hairpin loop. Furthermore, the dynamic behavior suggested that four mutation candidates could alter the biological activity of IL-18. In summary, this study offered a computer-aided design strategy, which was a beneficial use of the design and development of IL-18 for increasing its cytokine potency and efficiency.