Protein Engineering Design & Selection最新文献

Many glycosylated small molecule natural products and glycoprotein biologics are important in a broad range of therapeutic and industrial applications. The sugar moieties that decorate these compounds often show a profound impact on their biological functions, thus biocatalytic methods for controlling their glycosylation are valuable. Enzymes from nature are useful tools to tailor bioproduct glycosylation but these sometimes have limitations in their catalytic efficiency, substrate specificity, regiospecificity, stereospecificity, or stability. Enzyme engineering strategies such as directed evolution or semi-rational and rational design have addressed some of the challenges presented by these limitations. In this review, we highlight some of the recent research on engineering enzymes to tailor the glycosylation of small molecule natural products (including alkaloids, terpenoids, polyketides, and peptides), as well as the glycosylation of protein biologics (including hormones, enzyme-replacement therapies, enzyme inhibitors, vaccines, and antibodies).

Human transthyretin (TTR) is a homo-tetrameric plasma protein associated with a high percentage of β-sheet forming amyloid fibrils. It accumulates in tissues or extracellular matrices to cause amyloid diseases. Free energy simulations with thermodynamic integration based on all-atom molecular dynamics simulations have been carried out to analyze the effects of the His88 → Ala and Ser mutations on the stability of human TTR. The calculated free energy change differences (ΔΔG) caused by the His88 → Ala and His88 → Ser mutations are -1.84 ± 0.86 and 7.56 ± 0.55 kcal/mol, respectively, which are in excellent agreement with prior reported experimental values. The simulation results show that the H88A mutant is more stable than the wild type, whereas the H88S mutant is less stable than the wild type. The free energy component analysis shows that the contribution to the free energy change difference (ΔΔG) for the His88 → Ala and His88 → Ser mutations mainly arise from electrostatic and van der Waals interactions, respectively. The electrostatic term stabilizes the H88A mutant more than the wild type, but the van der Waals interaction destabilizes the H88S mutant relative to the wild type. Individual residue contributions to the free energy change show neighboring residues exert stabilizing and destabilizing influence on the mutants. The implications of the simulation results for understanding the stabilizing and destabilizing effect and its contribution to protein stability are discussed.

Enzyme design and engineering strategies are typically constrained by the limited size of nature's genetic alphabet, comprised of only 20 canonical amino acids. In recent years, site-selective incorporation of non-canonical amino acids (ncAAs) via an expanded genetic code has emerged as a powerful means of inserting new functional components into proteins, with hundreds of structurally diverse ncAAs now available. Here, we highlight how the emergence of an expanded repertoire of amino acids has opened new avenues in enzyme design and engineering. ncAAs have been used to probe complex biological mechanisms, augment enzyme function and, most ambitiously, embed new catalytic mechanisms into protein active sites that would be challenging to access within the constraints of nature's genetic code. We predict that the studies reviewed in this article, along with further advances in genetic code expansion technology, will establish ncAA incorporation as an increasingly important tool for biocatalysis in the coming years.

The Fv region of the antibody (comprising VH and VL domains) is the area responsible for target binding and thus the antibody's specificity. The orientation, or packing, of these two domains relative to each other influences the topography of the Fv region, and therefore can influence the antibody's binding affinity. We present abYpap, an improved method for predicting the packing angle between the VH and VL domains. With the large data set now available, we were able to expand greatly the number of features that could be used compared with our previous work. The machine-learning model was tuned for improved performance using 37 selected residues (previously 13) and also by including the lengths of the most variable 'complementarity determining regions' (CDR-L1, CDR-L2 and CDR-H3). Our method shows large improvements from the previous version, and also against other modeling approaches, when predicting the packing angle.

Lignocellulosic biomass is a renewable source of energy, chemicals and materials. Many applications of this resource require the depolymerization of one or more of its polymeric constituents. Efficient enzymatic depolymerization of cellulose to glucose by cellulases and accessory enzymes such as lytic polysaccharide monooxygenases is a prerequisite for economically viable exploitation of this biomass. Microbes produce a remarkably diverse range of cellulases, which consist of glycoside hydrolase (GH) catalytic domains and, although not in all cases, substrate-binding carbohydrate-binding modules (CBMs). As enzymes are a considerable cost factor, there is great interest in finding or engineering improved and robust cellulases, with higher activity and stability, easy expression, and minimal product inhibition. This review addresses relevant engineering targets for cellulases, discusses a few notable cellulase engineering studies of the past decades and provides an overview of recent work in the field.

Oxidoreductases catalyze essential redox reactions, and many require a diffusible cofactor for electron transport, such as NAD(H). Non-canonical cofactor analogs have been explored as a means to create enzymatic reactions that operate orthogonally to existing metabolism. Here, we aimed to engineer the formate dehydrogenase from Candid boidinii (CbFDH) for activity with the non-canonical cofactor nicotinamide adenine dinucleotide 3'-phosphate (3'-NADP(H)). We used PyRosetta, the Cofactor Specificity Reversal Structural Analysis and Library Design (CSR-SALAD), and structure-guided saturation mutagenesis to identify mutations that enable CbFDH to use 3'-NADP+. Two single mutants, D195A and D195G, had the highest activities with 3'-NADP+, while the double mutant D195G/Y196S exhibited the highest cofactor selectivity reversal behavior. Steady state kinetic analyses were performed; the D195A mutant exhibited the highest KTS value with 3'-NADP+. This work compares the utility of computational approaches for cofactor specificity engineering while demonstrating the engineering of an important enzyme for novel non-canonical cofactor selectivity.

Self-supervised pretraining on protein sequences has led to state-of-the art performance on protein function and fitness prediction. However, sequence-only methods ignore the rich information contained in experimental and predicted protein structures. Meanwhile, inverse folding methods reconstruct a protein's amino-acid sequence given its structure, but do not take advantage of sequences that do not have known structures. In this study, we train a masked inverse folding protein masked language model parameterized as a structured graph neural network. During pretraining, this model learns to reconstruct corrupted sequences conditioned on the backbone structure. We then show that using the outputs from a pretrained sequence-only protein masked language model as input to the inverse folding model further improves pretraining perplexity. We evaluate both of these models on downstream protein engineering tasks and analyze the effect of using information from experimental or predicted structures on performance.

Organophosphorus (OP) pesticides are still widely applied but pose a severe toxicological threat if misused. For in vivo detoxification, the application of hydrolytic enzymes potentially offers a promising treatment. A well-studied example is the phosphotriesterase of Brevundimonas diminuta (BdPTE). Whereas wild-type BdPTE can hydrolyse pesticides like paraoxon, chlorpyrifos-oxon and mevinphos with high catalytic efficiencies, kcat/KM >2 × 107 M-1 min-1, degradation of malaoxon is unsatisfactory (kcat/KM ≈ 1 × 104 M-1 min-1). Here, we report the rational engineering of BdPTE mutants with improved properties and their efficient production in Escherichia coli. As result, the mutant BdPTE(VRNVVLARY) exhibits 37-fold faster malaoxon hydrolysis (kcat/KM = 4.6 × 105 M-1 min-1), together with enhanced expression yield, improved thermal stability and reduced susceptibility to oxidation. Therefore, this BdPTE mutant constitutes a powerful candidate to develop a biocatalytic antidote for the detoxification of this common pesticide metabolite as well as related OP compounds.

Biocatalysis has become a powerful alternative for green chemistry. Expanding the range of amino acids used in protein biosynthesis can improve industrially appealing properties such as enantioselectivity, activity and stability. This review will specifically delve into the thermal stability improvements that non-canonical amino acids (ncAAs) can confer to enzymes. Methods to achieve this end, such as the use of halogenated ncAAs, selective immobilization and rational design, will be discussed. Additionally, specific enzyme design considerations using ncAAs are discussed along with the benefits and limitations of the various approaches available to enhance the thermal stability of enzymes.