Catalysis and Electron Transfer in De Novo Designed Helical Scaffolds

The relationship between protein structure and function is one of the greatest puzzles within biochemistry. De novo metalloprotein design is a way to wipe the board clean and determine what is required to build in function from the ground up in an unrelated structure. This Review focuses on protein design efforts to create de novo metalloproteins within alpha‐helical scaffolds. Examples of successful designs include those with carbonic anhydrase or nitrite reductase activity by incorporating a ZnHis₃ or CuHis₃ site, or that recapitulate the spectroscopic properties of unique electron‐transfer sites in cupredoxins (CuHis₂Cys) or rubredoxins (FeCys₄). This work showcases the versatility of alpha helices as scaffolds for metalloprotein design and the progress that is possible through careful rational design. Our studies cover the invariance of carbonic anhydrase activity with different site positions and scaffolds, refinement of our cupredoxin models, and enhancement of nitrite reductase activity up to 1000‐fold.     

Photobodies: Light‐Activatable Single‐Domain Antibody Fragments

Photocaged antibody fragments, termed photobodies, have been developed that are impaired in their antigen‐binding capacity and can be activated by irradiation with UV light (365 nm). This rational design concept builds on the selective photocaging of a single tyrosine in a nanobody (a single‐domain antibody fragment). Tyrosine is a frequently occurring residue in central positions of the paratope region. o‐Nitrobenzyl‐protected tyrosine variants were incorporated into four nanobodies, including examples directed against EGFR and HER2, and photodeprotection restores the native sequence. An anti‐GFP photobody exhibited an at least 10 000‐fold impaired binding affinity before photodeprotection compared with the parent nanobody. A bispecific nanobody–photobody fusion protein was generated to trigger protein heterodimerization by light. Photoactivatable antibodies are expected to become versatile protein reagents and to enable novel approaches in diagnostic and therapeutic applications.     

In-situ copolymerization of aniline with alkyl amine by APS： Kinetics and application

The kinetic study of in-situ eopolymerization of aniline with o- and p-methylaniline by ammonium persulfate （APS） has been carried out. UV-vis spectroscopic method was used to investigate the course of copolymerization. Structural characterization was studied by PT-IR spectral analysis. The electronic spectra of the copolymers poly（aniline-co-p-toluidine） and poly（aniline-co-o- toluidine） show blue shift. The shift has been observed in the bands corresponding to π→π^＊ transition as well as in the exciton transition. The increase in absorbance recorded during the reaction for different concentration of aniline, o- and p-toluidine at various intervals of time of polymerization reaction indicates a growth in the polymer formation. The resulting first-order rate constant was used to calculate the rate of copolymer formation using the rate equation -d[A]/dt = kc^n.     

纺锤体驱动蛋白抑制剂的设计、合成与生物活性研究

纺锤体驱动蛋白(kinesin spindle protein, KSP/Eg5)作为潜在的肿瘤治疗靶点, 使发现KSP抑制剂成为热点. 设计并合成了4-氧基-β-四氢咔啉衍生物作为新型的KSP抑制剂, 并测定了其对KSP的抑制活性, 均优于阳性对照物. 其中化合物9c抑制KSP的IC50＝0.065 μmol•L－1, 优于阳性对照物Monastro l100多倍. 生物活性研究表明为抗肿瘤药物提供了新结构类型的候选化合物.     

Effect of PLGA as a polymeric emulsifier on preparation of hydrophilic protein-loaded solid lipid nanoparticles

Most proteins are hydrophilic and poorly encapsulated into the hydrophobic matrix of solid lipid nanoparticles (SLN). To solve this problem, poly (lactic-co-glycolic acid) (PLGA) was utilized as a lipophilic polymeric emulsifier to prepare hydrophilic protein-loaded SLN by w/o/w double emulsion and solvent evaporation techniques. Hydrogenated castor oil (HCO) was used as a lipid matrix and bovine serum albumin (BSA), lysozyme and insulin were used as model proteins to investigate the effect of PLGA on the formulation of the SLN. The results showed that PLGA was essential for the primary w/o emulsification. In addition, the stability of the w/o emulsion, the encapsulation efficiency and loading capacity of the nanoparticles were enhanced with the increase of PLGA concentration. Furthermore, increasing PLGA concentration decreased zeta potential significantly but had no influence on particle size of the SLN. In vitro release study showed that PLGA significantly affected the initial burst release, i.e. the higher the content of PLGA, the lower the burst release. The released proteins maintained their integrity and bioactivity as confirmed by sodium dodecyl sulphate-polyacrylamide gel electrophoresis (SDS-PAGE) and biological assay. These results demonstrated that PLGA was an effective emulsifier for the preparation of hydrophilic protein-loaded SLN.     

Dynamic adsorption and characterization of phospholipid and mixed phospholipid/protein layers at liquid/liquid interfaces

Drop profile analysis tensiometry is applied to study the adsorption dynamics of phospholipids, proteins and phospholipid/protein mixtures at liquid/liquid interfaces. Measurements of the dynamic interfacial tension of phospholipid layers give information on the adsorption mechanism and the structure of the adsorption layer. The equilibrium and dynamic adsorption of pure protein solutions, i.e. human serum album (HSA), beta-lactoglobulin (beta-LG), beta-casein (beta-CA), can be explained well by the thermodynamic model of Frumkin and the diffusion-controlled adsorption theory. The adsorption behavior from mixed phospholipid/protein solutions was also investigated in terms of dynamic interfacial tensions. Interestingly, a "skin-like" folded film of pure protein or phospholipid/protein complex layers can be observed at curved surfaces at the water/oil interfaces. The addition of phospholipids accelerates the formation of the folded structure at the drop surface through co-adsorption of proteins.     

缓蚀膜电化学行为与微观粘附力特征

采用传统电化学测试技术及原子力显微镜(AFM)力曲线分析法对十二烷基硫醇/金电极以及十二烷基磺酸钠(SDS)/铝电极表面缓蚀吸附膜的吸附行为进行了研究. 结果表明, 随缓蚀剂浓度改变, 电极电化学行为与缓蚀膜的微观粘附力特征呈现出关联性的变化趋势, 表明AFM力曲线技术可成功应用于缓蚀膜吸附行为的研究.     

双偏振干涉测量技术在生物分析方面研究应用进展

双偏振干涉测量(dual-polarization interferometry,DPI)技术是2000年以后出现的一种灵敏、实时、无需标记的新型表面状态分析方法,它能够在亚秒尺度精确测量界面层厚度、密度和质量的绝对值.所以,DPI在固/液界面上蛋白质结构、功能表征,蛋白质之间或与其它分子间的相互作用研究,核酸固定化及杂交检测研究,模拟生物膜研究以及表面超微结构表征等方面都有着广泛的应用.本文介绍了DPI的测量原理和特点,着重评述了近年来DPI在生物分析方面的应用进展.     

Q-Dock: Low-resolution flexible ligand docking with pocket-specific threading restraints

The rapidly growing number of theoretically predicted protein structures requires robust methods that can utilize low-quality receptor structures as targets for ligand docking. Typically, docking accuracy falls off dramatically when apo or modeled receptors are used in docking experiments. Low-resolution ligand docking techniques have been developed to deal with structural inaccuracies in predicted receptor models. In this spirit, we describe the development and optimization of a knowledge-based potential implemented in Q-Dock, a low-resolution flexible ligand docking approach. Self-docking experiments using crystal structures reveals satisfactory accuracy, comparable with all-atom docking. All-atom models reconstructed from Q-Dock's low-resolution models can be further refined by even a simple all-atom energy minimization. In decoy-docking against distorted receptor models with a root-mean-square deviation, RMSD, from native of approximately 3 A, Q-Dock recovers on average 15-20% more specific contacts and 25-35% more binding residues than all-atom methods. To further improve docking accuracy against low-quality protein models, we propose a pocket-specific protein-ligand interaction potential derived from weakly homologous threading holo-templates. The success rate of Q-Dock employing a pocket-specific potential is 6.3 times higher than that previously reported for the Dolores method, another low-resolution docking approach.     

Prediction of protein structural class using novel evolutionary collocation-based sequence representation

Knowledge of structural classes is useful in understanding of folding patterns in proteins. Although existing structural class prediction methods applied virtually all state-of-the-art classifiers, many of them use a relatively simple protein sequence representation that often includes amino acid (AA) composition. To this end, we propose a novel sequence representation that incorporates evolutionary information encoded using PSI-BLAST profile-based collocation of AA pairs. We used six benchmark datasets and five representative classifiers to quantify and compare the quality of the structural class prediction with the proposed representation. The best, classifier support vector machine achieved 61-96% accuracy on the six datasets. These predictions were comprehensively compared with a wide range of recently proposed methods for prediction of structural classes. Our comprehensive comparison shows superiority of the proposed representation, which results in error rate reductions that range between 14% and 26% when compared with predictions of the best-performing, previously published classifiers on the considered datasets. The study also shows that, for the benchmark dataset that includes sequences characterized by low identity (i.e., 25%, 30%, and 40%), the prediction accuracies are 20-35% lower than for the other three datasets that include sequences with a higher degree of similarity. In conclusion, the proposed representation is shown to substantially improve the accuracy of the structural class prediction. A web server that implements the presented prediction method is freely available at http://biomine.ece.ualberta.ca/Structural_Class/SCEC.html.