Protein Engineering Design & Selection最新文献

Proteinase K (PRK) is a proteolytic enzyme that has been widely used in industrial applications. However, poor stability has severely limited the uses of PRK. In this work, we used two structure-guided rational design methods, Rosetta and FoldX, to modify PRK thermostability. Fifty-two single amino acid conversion mutants were constructed based on software predictions of residues that could affect protein stability. Experimental characterization revealed that 46% (21 mutants) exhibited enhanced thermostability. The top four variants, D260V, T4Y, S216Q, and S219Q, showed improved half-lives at 69°C by 12.4-, 2.6-, 2.3-, and 2.2-fold that of the parent enzyme, respectively. We also found that selecting mutations predicted by both methods could increase the predictive accuracy over that of either method alone, with 73% of the shared predicted mutations resulting in higher thermostability. In addition to providing promising new variants of PRK in industrial applications, our findings also show that combining these programs may synergistically improve their predictive accuracy.

Metalloproteins are essential to sustain life. Natural evolution optimized them for intricate structural, regulatory and catalytic functions that cannot be fulfilled by either a protein or a metal ion alone. In order to understand this synergy and the complex design principles behind the natural systems, simpler mimics were engineered from the bottom up by installing de novo metal sites in either natural or fully designed, artificial protein scaffolds. This review focuses on key challenges associated with this approach. We discuss how proteins can be equipped with binding sites that provide an optimal coordination environment for a metal cofactor of choice, which can be a single metal ion or a complex multinuclear cluster. Furthermore, we highlight recent studies in which artificial metalloproteins were engineered towards new functions, including electron transfer and catalysis. In this context, the powerful combination of de novo protein design and directed evolution is emphasized for metalloenzyme development.

Proteins catalyze the majority of chemical reactions in organisms, and harnessing this power has long been the focus of the protein engineering field. Computational protein design aims to create new proteins and functions in silico, and in doing so, accelerate the process, reduce costs and enable more sophisticated engineering goals to be accomplished. Challenges that very recently seemed impossible are now within reach thanks to several landmark advances in computational protein design methods. Here, we summarize these new methods, with a particular emphasis on de novo protein design advancements occurring within the past 5 years.

Targeted inhibition of misregulated protein-protein interactions (PPIs) has been a promising area of investigation in drug discovery and development for human diseases. However, many constraints remain, including shallow binding surfaces and dynamic conformation changes upon interaction. A particularly challenging aspect is the undesirable off-target effects caused by inherent structural similarity among the protein families. To tackle this problem, phage display has been used to engineer PPIs for high-specificity binders with improved binding affinity and greatly reduced undesirable interactions with closely related proteins. Although general steps of phage display are standardized, library design is highly variable depending on experimental contexts. Here in this review, we examined recent advances in the structure-based combinatorial library design and the advantages and limitations of different approaches. The strategies described here can be explored for other protein-protein interactions and aid in designing new libraries or improving on previous libraries.

Accumulation of plastic and subsequent microplastic is a major environmental challenge. With the discovery of potent polyethylene terephthalate (PET)-degrading enzymes, a new perspective arose for environmental decomposition as well as technical recycling. To explore the enormous diversity of potential PET-degrading enzymes in nature and also to conveniently employ techniques like protein engineering and directed evolution, a fast and reliable assay platform is needed. In this study we present our versatile solution applying a PET coating on standard lab consumables such as polymerase chain reaction tubes, 96- and 384-well microtiter plates, yielding an adjustable crystallinity of the PET. Combining the reaction vessels with either ultra-high performance liquid chromatography (UHPLC) or fluorometric readout and additional enzyme quantification offers a range of advantages. Thereby, the platform can easily be adapted to diverse needs from detailed analysis with high precision to high-throughput (HT) applications including crude lysate analysis.

Erythropoietin enhances oxygen delivery and reduces hypoxia-induced cell death, but its pro-thrombotic activity is problematic for use of erythropoietin in treating hypoxia. We constructed a fusion protein that stimulates red blood cell production and neuroprotection without triggering platelet production, a marker for thrombosis. The protein consists of an anti-glycophorin A nanobody and an erythropoietin mutant (L108A). The mutation reduces activation of erythropoietin receptor homodimers that induce erythropoiesis and thrombosis, but maintains the tissue-protective signaling. The binding of the nanobody element to glycophorin A rescues homodimeric erythropoietin receptor activation on red blood cell precursors. In a cell proliferation assay, the fusion protein is active at 10-14 M, allowing an estimate of the number of receptor-ligand complexes needed for signaling. This fusion protein stimulates erythroid cell proliferation in vitro and in mice, and shows neuroprotective activity in vitro. Our erythropoietin fusion protein presents a novel molecule for treating hypoxia.

Interest in single-domain antibodies (sdAbs) stems from their unique structural/pronounced, hence therapeutically desirable, features. From the outset-as therapeutic modalities-human antibody heavy chain variable domains (VHs) attracted a particular attention compared with 'naturally-occurring' camelid and shark heavy-chain-only antibody variable domains (VHHs and VNARs, respectively) due to their perceived lack of immunogenicity. However, they have not quite lived up to their initial promise as the VH hits, primarily mined from synthetic VH phage display libraries, have too often been plagued with aggregation tendencies, low solubility and low affinity. Largely unexplored, synthetic camelized human VH display libraries appeared to have remediated the aggregation problem, but the low affinity of the VH hits still persisted, requiring undertaking additional, laborious affinity maturation steps to render VHs therapeutically feasible. A wholesome resolution has recently emerged with the development of non-canonical transgenic rodent antibody discovery platforms that appear to facilely and profusely generate high affinity, high solubility and aggregation-resistant human VHs.

We review the background, theory and general equations for the analysis of equilibrium protein unfolding experiments, focusing on denaturant and heat-induced unfolding. The primary focus is on the thermodynamics of reversible folding/unfolding transitions and the experimental methods that are available for extracting thermodynamic parameters. We highlight the importance of modelling both how the folding equilibrium depends on a perturbing variable such as temperature or denaturant concentration, and the importance of modelling the baselines in the experimental observables.

Targeted inhibition of misregulated protein-protein interactions (PPIs) has been a promising area of investigation in drug discovery and development for human diseases. However, many constraints remain, including shallow binding surfaces and dynamic conformation changes upon interaction. A particularly challenging aspect is the undesirable off-target effects caused by inherent structural similarity among the protein families. To tackle this problem, phage display has been used to engineer PPIs for high-specificity binders with improved binding affinity and greatly reduced undesirable interactions with closely related proteins. Although general steps of phage display are standardized, library design is highly variable depending on experimental contexts. Here in this review, we examined recent advances in the structure-based combinatorial library design and the advantages and limitations of different approaches. The strategies described here can be explored for other protein-protein interactions and aid in designing new libraries or improving on previous libraries.

Proteins are dynamic molecules whose structures consist of an ensemble of conformational states. Dynamics contribute to protein function and a link to protein evolution has begun to emerge. This increased appreciation for the evolutionary impact of conformational sampling has grown from our developing structural biology capabilities and the exploration of directed evolution approaches, which have allowed evolutionary trajectories to be mapped. Recent studies have provided empirical examples of how proteins can evolve via conformational landscape alterations. Moreover, minor conformational substates have been shown to be involved in the emergence of new enzyme functions as they can become enriched through evolution. The role of remote mutations in stabilizing new active site geometries has also granted insight into the molecular basis underpinning poorly understood epistatic effects that guide protein evolution. Finally, we discuss how the growth of our understanding of remote mutations is beginning to refine our approach to engineering enzymes.