Barreling Forward: Advancements in De Novo Protein Design

Abstract

Natural evolution and protein redesign have only explored a tiny fraction of theoretically possible protein structures. However, de novo protein design will prove powerful in engineering novel proteins with specific functions by comprehensively sampling the protein space using computational methods guided by protein folding principles. De novo protein design involves working backwards from a desired protein with special structure and function to derive an amino acid sequence capable of folding into such a conformation—a challenging approach due to the vast number of protein conformations to evaluate. Here, we present a review of the latest advancements in de novo protein design methods and applications in conjunction with a physical model of a de novo fluorescence‐activating β‐barrel protein. Approaches to de novo protein design include: (1) simulating the folding of a fixed amino acid sequence to determine each residue’s most stable conformation, (2) determining the amino acid sequence that folds into a desired protein conformation, and (3) performing comprehensive rapid evaluations of each possible conformation. This novel protein is then synthesized and validated through in vitro or in vivo assays. In one recent breakthrough by Baker et. al., a de novo approach was used to design a β‐barrel protein comprised of a cylindrical pleated β‐sheet which binds the fluorogenic compound DFHBI. This study is the first instance of a de novo protein designed to bind to a small molecule of interest, with applications in visualizing cell movement, gene expression, DNA replication, protein translation, and tumor progression. In designing this fluorescence activating β‐barrel protein, structural irregularities were introduced to stabilize the structure and enlarge the β‐barrel cavity. Subsequently, the optimal sequences for β‐barrels with reasonable binding site and affinity for DFHBI were designed by computationally adjusting individual residue conformations. Finally, this optimized protein was synthesized, which had greater affinity with DFHBI and increased fluorescence in in vitro and in vivo experiments. Support or Funding Information This is a SMART Team project supported through the contributions of Dr. Jinan Wang of the University of Kansas Center for Computational Biology, the Milwaukee School of Engineering, and the Olathe Medical Professions 21st Century Academy.