Due to the steric effects imposed by bulky polymers, the formation of catalytically competent enzyme and substrate conformations is critical in the biodegradation of plastics. In poly­(ethylene terephthalate) (PET), the backbone adopts different conformations, gauche and trans, coexisting to different extents in amorphous and crystalline regions. However, which conformation is susceptible to biodegradation and the extent of enzyme and substrate conformational changes required for expedient catalysis remain poorly understood. To overcome this obstacle, we utilized molecular dynamics simulations, docking, and enzyme engineering in concert with high-resolution microscopy imaging and solid-state nuclear magnetic resonance (NMR) to demonstrate the importance of conformational selection in biocatalytic plastic hydrolysis. Our results demonstrate how single-amino acid substitutions in Ideonella sakaiensis PETase can alter its conformational landscape, significantly affecting the relative abundance of productive ground-state structures ready to bind discrete substrate conformers. We experimentally show how an enzyme binds to plastic and provide a model for key residues involved in the recognition of gauche and trans conformations supported by in silico simulations. We demonstrate how enzyme engineering can be used to create a trans-selective variant, resulting in higher activity when combined with an all-trans PET-derived oligomeric substrate, stemming from both increased accessibility and conformational preference. Our work cements the importance of matching enzyme and substrate conformations in plastic hydrolysis, and we show that also the noncanonical trans conformation in PET is conducive for degradation. Understanding the contribution of enzyme and substrate conformations to biocatalytic plastic degradation could facilitate the generation of designer enzymes with increased performance.

Structural information is crucial for understanding catalytic mechanisms and to guide enzyme engineering efforts of biocatalysts, such as terpene cyclases. However, low sequence similarity can impede homology modeling, and inherent protein instability presents challenges for structural studies. We hypothesized that X-ray crystallography of engineered thermostable ancestral enzymes can enable access to reliable homology models of extant biocatalysts. We have applied this concept in concert with molecular modeling and enzymatic assays to understand the structure activity relationship of spiroviolene synthase, a class I terpene cyclase, aiming to engineer its specificity. Engineering a surface patch in the reconstructed ancestor afforded a template structure for generation of a high-confidence homology model of the extant enzyme. On the basis of structural considerations, we designed and crystallized ancestral variants with single residue exchanges that exhibited tailored substrate specificity and preserved thermostability. We show how the two single amino acid alterations identified in the ancestral scaffold can be transferred to the extant enzyme, conferring a specificity switch that impacts the extant enzyme’s specificity for formation of the diterpene spiroviolene over formation of sesquiterpenes hedycaryol and farnesol by up to 25-fold. This study emphasizes the value of ancestral sequence reconstruction combined with enzyme engineering as a versatile tool in chemical biology.

The robust computational design of functional proteins has the potential to deeply impact translational research and broaden our understanding of the determinants of protein function and stability. The low success rates of computational design protocols and the extensive in vitro optimization often required, highlight the challenge of designing proteins that perform essential biochemical functions, such as binding or catalysis. One of the most simplistic approaches for the design of function is to adopt functional motifs in naturally occurring proteins and transplant them to computationally designed proteins. The structural complexity of the functional motif largely determines how readily one can find host protein structures that are “designable”, meaning that are likely to present the functional motif in the desired conformation. One promising route to enhance the “designability” of protein structures is to allow backbone flexibility. Here, we present a computational approach that couples conformational folding with sequence design to embed functional motifs into heterologous proteins—Rosetta Functional Folding and Design (FunFolDes). We performed extensive computational benchmarks, where we observed that the enforcement of functional requirements resulted in designs distant from the global energetic minimum of the protein. An observation consistent with several experimental studies that have revealed function-stability tradeoffs. To test the design capabilities of FunFolDes we transplanted two viral epitopes into distant structural templates including one de novo “functionless” fold, which represent two typical challenges where the designability problem arises. The designed proteins were experimentally characterized showing high binding affinities to monoclonal antibodies, making them valuable candidates for vaccine design endeavors. Overall, we present an accessible strategy to repurpose old protein folds for new functions. This may lead to important improvements on the computational design of proteins, with structurally complex functional sites, that can perform elaborate biochemical functions related to binding and catalysis.