Computational design of IL-37b variants to disrupt dimerization and enhance monomer stability

Interleukin-37b (IL-37b) has emerged as a potential therapeutic agent for inflammatory diseases. However, IL-37b tends to self-assemble into a dimeric form, which compromises its anti-inflammatory efficacy. Furthermore, the currently active monomeric variants of IL-37b are unstable, limiting their clinical utility. To address these challenges, we employed a series of in silico protein engineering strategies to design IL-37b variants with reduced dimerization propensity and enhanced monomeric stability. We identified and analyzed hot-spot residues critical for dimer formation using a double-alanine scanning approach, and subsequently mutated these residues in search of optimal mutations to block self-dimerization. Further, we expanded computational site-saturation mutagenesis to non-binding-site residues and evaluated their impact on monomer stability. Molecular dynamics (MD) simulations and structural analyses were performed to interpret the effects of these variants on stability. In total, we identified 36 mutations that block IL-37b dimer formation and 10 mutations that enhance monomer stability. The mutational effects of the two lists of mutations were independent, enabling potential multi-mutant combinations into dual-functional variants. The systematic in silico design approach presented for IL-37b in this work also provides a generalizable framework for the rational design of other cytokines and proteins.