Directed co-evolution of interacting protein-peptide pairs by compartmentalized two-hybrid replication (C2HR)

Thermostability enhancement of polyethylene terephthalate degrading PETase using self- and nonself-ligating protein scaffolding approaches

Polyethylene terephthalate (PET) hydrolase enzymes show promise for enzymatic PET degradation and green recycling of single-use PET vessels representing a major source of global pollution. Their full potential can be unlocked with enzyme engineering to render activities on recalcitrant PET substrates commensurate with cost-effective recycling at scale. Thermostability is a highly desirable property in industrial enzymes, often imparting increased robustness and significantly reducing quantities required. To date, most engineered PET hydrolases show improved thermostability over their parental enzymes. Here, we report engineered thermostable variants of Ideonella sakaiensis PET hydrolase enzyme (IsPETase) developed using two scaffolding strategies. The first employed SpyCatcher-SpyTag technology to covalently cyclize IsPETase, resulting in increased thermostability that was concomitant with reduced turnover of PET substrates compared to native IsPETase. The second approach using a GFP-nanobody fusion protein (vGFP) as a scaffold yielded a construct with a melting temperature of 80°C. This was further increased to 85°C when a thermostable PETase variant (FAST PETase) was scaffolded into vGFP, the highest reported so far for an engineered PET hydrolase derived from IsPETase. Thermostability enhancement using the vGFP scaffold did not compromise activity on PET compared to IsPETase. These contrasting results highlight potential topological and dynamic constraints imposed by scaffold choice as determinants of enzyme activity.

Deploying synthetic coevolution and machine learning to engineer protein-protein interactions

Fine-tuning of protein-protein interactions occurs naturally through coevolution, but this process is difficult to recapitulate in the laboratory. We describe a platform for synthetic protein-protein coevolution that can isolate matched pairs of interacting muteins from complex libraries. This large dataset of coevolved complexes drove a systems-level analysis of molecular recognition between Z domain-affibody pairs spanning a wide range of structures, affinities, cross-reactivities, and orthogonalities, and captured a broad spectrum of coevolutionary networks. Furthermore, we harnessed pretrained protein language models to expand, in silico, the amino acid diversity of our coevolution screen, predicting remodeled interfaces beyond the reach of the experimental library. The integration of these approaches provides a means of simulating protein coevolution and generating protein complexes with diverse molecular recognition properties for biotechnology and synthetic biology.

Methods for the directed evolution of biomolecular interactions

Noncovalent interactions between biomolecules such as proteins and nucleic acids coordinate all cellular processes through changes in proximity. Tools that perturb these interactions are and will continue to be highly valuable for basic and translational scientific endeavors. By taking cues from natural systems, such as the adaptive immune system, we can design directed evolution platforms that can generate proteins that bind to biomolecules of interest. In recent years, the platforms used to direct the evolution of biomolecular binders have greatly expanded the range of types of interactions one can evolve. Herein, we review recent advances in methods to evolve protein-protein, protein-RNA, and protein-DNA interactions.

Directed evolution of orthogonal RNA-RBP pairs through library-vs-library in vitro selection

RNA-binding proteins (RBPs) and their RNA ligands play many critical roles in gene regulation and RNA processing in cells. They are also useful for various applications in cell biology and synthetic biology. However, re-engineering novel and orthogonal RNA-RBP pairs from natural components remains challenging while such synthetic RNA-RBP pairs could significantly expand the RNA-RBP toolbox for various applications. Here, we report a novel library-vs-library in vitro selection strategy based on Phage Display coupled with Systematic Evolution of Ligands by EXponential enrichment (PD-SELEX). Starting with pools of 1.1 × 1012 unique RNA sequences and 4.0 × 108 unique phage-displayed L7Ae-scaffold (LS) proteins, we selected RNA-RBP complexes through a two-step affinity purification process. After six rounds of library-vs-library selection, the selected RNAs and LS proteins were analyzed by next-generation sequencing (NGS). Further deconvolution of the enriched RNA and LS protein sequences revealed two synthetic and orthogonal RNA-RBP pairs that exhibit picomolar affinity and >4000-fold selectivity.