Protein Engineering Design & Selection最新文献

To combat the enduring and dangerous spread of COVID-19, many innovations to rapid diagnostics have been developed based on proteinprotein interactions of the SARS-CoV-2 spike and nucleocapsid proteins to increase testing accessibility. These antigen tests have most prominently been developed using the lateral flow assay (LFA) test platform which has the benefit of administration at point-of-care, delivering quick results, lower cost, and does not require skilled personnel. However, they have gained criticism for an inferior sensitivity. In the last year, much attention has been given to creating a rapid LFA test for detection of COVID-19 antigens that can address its high limit of detection while retaining the advantages of rapid antibodyantigen interaction. In this review, a summary of these proteinprotein interactions as well as the challenges, benefits, and recent improvements to protein based LFA for detection of COVID-19 are discussed.

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.

Diaminopimelate decarboxylases (DAPDCs) are highly selective enzymes that catalyze the common final step in different lysine biosynthetic pathways, i.e. the conversion of meso-diaminopimelate (DAP) to L-lysine. We examined the modification of the substrate specificity of the thermostable decarboxylase from Thermotoga maritima with the aim to introduce activity with 2-aminopimelic acid (2-APA) since its decarboxylation leads to 6-aminocaproic acid (6-ACA), a building block for the synthesis of nylon-6. Structure-based mutagenesis of the distal carboxylate binding site resulted in a set of enzyme variants with new activities toward different D-amino acids. One of the mutants (E315T) had lost most of its activity toward DAP and primarily acted as a 2-APA decarboxylase. We next used computational modeling to explain the observed shift in catalytic activities of the mutants. The results suggest that predictive computational protocols can support the redesign of the catalytic properties of this class of decarboxylating PLP-dependent enzymes.

Generating combinatorial libraries of specific sets of mutations are essential for addressing protein engineering questions involving contingency in molecular evolution, epistatic relationships between mutations, as well as functional antibody and enzyme engineering. Here we present optimization of a combinatorial mutagenesis method involving template-based nicking mutagenesis, which allows for the generation of libraries with >99% coverage for tens of thousands of user-defined variants. The non-optimized method resulted in low library coverage, which could be rationalized by a model of oligonucleotide annealing bias resulting from the nucleotide mismatch free-energy difference between mutagenic oligo and template. The optimized method mitigated this thermodynamic bias using longer primer sets and faster annealing conditions. Our updated method, applied to two antibody fragments, delivered between 99.0% (32451/32768 library members) to >99.9% coverage (32757/32768) for our desired libraries in 2 days and at an approximate 140-fold sequencing depth of coverage.

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.

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.

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.

Protein-based binders have become increasingly more attractive candidates for drug and imaging agent development. Such binders could be evolved from a number of different scaffolds, including antibodies, natural protein effectors and unrelated small protein domains of different geometries. While both computational and experimental approaches could be utilized for protein binder engineering, in this review we focus on various computational approaches for protein binder design and demonstrate how experimental selection could be applied to subsequently optimize computationally-designed molecules. Recent studies report a number of designed protein binders with pM affinities and high specificities for their targets. These binders usually characterized with high stability, solubility, and low production cost. Such attractive molecules are bound to become more common in various biotechnological and biomedical applications in the near future.