淀粉蔗糖酶AcAS的工作机理研究与稳定性改造

目的:对新发现的一种新型淀粉蔗糖酶AcAS的结构功能进行深入讨论。方法:用同源模建方法构建AcAS的三维结构;用高斯网络模型和各项异性网络模型,对其功能型运动和工作机理进行预测;利用迭代高斯网络模型方法对其去折叠路径进行预测;根据去折叠路径预测及折叠自由能计算结果设计突变体。结果:模建结果表明,AcAS结构与淀粉蔗糖酶NpAS的结构更相似;AcAS有扭转运动的趋势,其中AcAS的N/C结构域运动性较强,而催化核心的运动性较弱;根据去折叠路径预测,发现N、B和C结构域较易去折叠;通过自由能计算,针对上述3个结构域设计了5株突变体。结论:构建了AcAS的三维结构模型并根据模型探讨了其工作机理;根据去折叠路径预测及折叠自由能计算结果,对AcAS的稳定性改造提出了有益的建议。     

钙调蛋白的功能性运动分析

目的:研究钙调蛋白(CaM)结构的动力学行为和运动趋势。方法:利用高斯网络模型(GNM)和各向异性网络模型(ANM),分析CaM在无钙和含钙2种形式下的功能运动。结果:CaM的慢运动模式显示,CaM的构象变化主要表现为2个结构域的运动;2种形式的CaM具有共同的铰链区,铰链区位于分子的中央接头,但二者具有不同的运动趋势。交叉相关图结果显示,CaM结合钙离子后,结构域内的相互作用会增强。结论:GNM和ANM结果可以解释先前报道的实验数据。结果有助于更好地了解CaM的构象转变规律,并会提高对CaM的底物识别和调节活动机制的理解。     

水稻蒸煮品质相关QTL定位及候选基因分析

挖掘与稻米蒸煮品质相关的数量性状基因座(quantitative trait locus, QTL)，分析候选基因，并通过遗传育种手段改良稻米蒸煮品质相关性状，可有效提升稻米的口感。以籼稻华占(Huazhan, HZ)、粳稻热研2号(Nekken2)及由其构建的120个重组自交系(recombinant inbred lines, RILs)群体为实验材料，测定成熟期稻米的糊化温度(gelatinization temperature, GT)、胶稠度(gel consistency, GC)和直链淀粉含量(amylose content, AC)。结合高密度分子遗传图谱进行QTL定位，共检测到26个与稻米蒸煮品质相关的QTLs (糊化温度相关位点1个、胶稠度相关位点13个、直链淀粉含量相关位点12个)，其中最高奇数的可能性(likelihood of odd, LOD)值达30.24。通过实时荧光定量PCR (quantitative real-time polymerase chain reaction, qRT-PCR)分析定位区间内候选基因的表达量，发现6个基因在双亲间的表达量差异显著，推测LOC_Os04g20270和LOC_Os11g40100的高表达可能会极大地提高稻米的胶稠度，而LOC_Os01g04920和LOC_Os02g17500的高表达以及LOC_Os03g02650和LOC_Os05g25840的低表达有助于降低直链淀粉含量。这些结果为培育优质水稻新品种奠定了分子基础，并为揭示稻米蒸煮品质的分子调控机制提供了重要的遗传资源。     

代谢工程改造大肠杆菌合成己二酸

己二酸是一种具有重要应用价值的二元羧酸,是合成尼龙-66的关键前体。目前,生物法生产己二酸存在生产周期长、生产效率低的问题。本研究选择一株野生型高产琥珀酸菌株大肠杆菌(Escherichia coli) FMME N-2为底盘细胞,首先通过引入逆己二酸降解途径的关键酶,成功构建了可合成0.34 g/L己二酸的E. coli JL00菌株;接着,对合成路径限速酶进行表达优化,使E. coli JL01菌株在摇瓶发酵条件下产量达到0.87 g/L;随后,通过敲除sucD基因、过表达acs基因和突变lpd基因的组合策略平衡己二酸合成前体的供应,优化菌株E. coli JL12己二酸产量进一步提升至1.51 g/L;最后,在5 L发酵罐上对己二酸发酵工艺进行优化。工程菌株经72 h分批补料发酵,己二酸的产量达到22.3 g/L,转化率为0.25 g/g,生产强度为0.31 g/(L·h),具备了一定的应用潜力。本研究可为包括己二酸在内的多种二元羧酸细胞工厂的构建提供理论依据和技术基础。     

基于高斯两步移动搜索法空间可达性模型的医院布局评价

目的 探讨高斯两步移动搜索法空间可达性模型在医院布局评价中的应用。方法 借助搜狗网络地图服务应用程序接口,使用高斯两步移动搜索法测算街道/乡镇尺度下上海市三级医院空间可达性指数,评价其空间分布。结果 距离阈值为60分钟时,“5+3+1”项目实施使上海市三级医院空间可达性指数均值从1.65提升至1.98,中心城区该指标均值为3.63,郊区（县）为1.03。结论 高斯两步移动搜索法空间可达性模型评价医院布局具有方法学优越性;“5+3+1”项目改善上海市三级医院水平与布局,但地区差异依然存在。     

不同碳源诱导下牦牛瘤胃厌氧真菌Orpinomyces sp. YF3的产酶机制

为探究体外发酵牦牛瘤胃源厌氧真菌Orpinomyces sp. YF3在不同碳源诱导下的产酶机制，本研究利用厌氧培养管在10 mL基础培养基中分别添加不同碳源复杂度的葡萄糖(glucose, Glu)、滤纸(filter paper, Flp)、微晶纤维素(avicel, Avi)各8 g/L作为唯一碳源进行体外发酵，检测发酵液中的纤维降解酶活性和挥发性脂肪酸，并利用转录组学探究Orpinomyces sp. YF3的产酶机制。结果表明葡萄糖诱导下的发酵液中羧甲基纤维素酶、微晶纤维素酶、滤纸酶和木聚糖酶的活性，及乙酸的比例显著升高(P＜0.05)，丙酸、丁酸、异丁酸的比例显著降低(P＜0.05)。进一步分析发现与纤维降解酶相关的差异表达基因(differentially expressed genes, DEGs)在Glu组中显著上调。基因本体论(gene ontology, GO)功能富集显示DEGs主要集中在木聚糖酶、纤维素酶、葡萄糖和碳水化合物等的分解代谢过程及相关酶活性，京都基因和基因组百科全书(Kyoto Encyclopedia of Genes and Genomes, KEGG)通路分析富集到的纤维降解酶相关的差异通路主要是淀粉和蔗糖代谢途径、其他聚糖降解途径。以上结果表明，以葡萄糖为碳源底物的Orpinomyces sp. YF3可增加纤维素降解酶活性，提高乙酸比例，通过调控纤维降解酶基因的表达及相关代谢通路来提高对底物的降解能力，提高能量利用效率。这为Orpinomyces sp. YF3在实际生产中的应用提供了理论基础。     

绿色木霉MJ1产内切β-葡聚糖苷酶的分离纯化及酶学性质

利用KTAUPC-900快速蛋白液相色谱系统(FPLC)从绿色木霉MJ1固体发酵产物中分离纯化出内切β-葡聚糖苷酶。分离纯化后酶的比活力提高了28.6倍,回收率为19.7%。SDS-PAGE后经BIO-RAD凝胶成像系统分析该内切酶的分子量为64.7kD。酶学试验研究表明:该酶的最适反应温度53℃,最适pH为4.2,Lineweaver-Burk法求得动力学参数,K_m和V_max分别为1.230×10^{-2相似文献}   

杓兰果胶杆菌海藻糖酶的克隆表达及应用

海藻糖酶在工业发酵和食品医药等领域应用广泛,我国缺乏性能优良工业品种的海藻糖酶,同时在应用研究领域还不够深入。本研究从自然界筛选获得一株产酸性海藻糖酶的杓兰果胶杆菌(Pectobacterium cypripedii),克隆获得其海藻糖酶基因PCTre,在大肠杆菌(Escherichia coli)BL21(DE3)体系中实现了重组表达,在5L发酵罐上28h产酶达到4130U/mL。酶学性质研究显示,PCTre能特异性水解海藻糖,最适反应温度和pH分别是35℃和5.5,在pH4.0、4.5、5.0处理8h后残余酶活仍超过80%,表现出良好的耐酸性。同时该酶还显示出优良的有机溶剂耐受性,在20%(V/V)乙醇溶液中处理24h仍能保留60%的酶活。进一步在含有20%(V/V)乙醇和7.5%海藻糖的模拟发酵体系中,当添加500U/L PCTre,可在16h内完全水解海藻糖,具有良好的应用于工业乙醇发酵的潜力。     

干旱条件下外源蔗糖对高表达玉米C4型pepc水稻种子萌发的影响

为揭示外源蔗糖参与干旱胁迫下高表达转玉米C₄ 型磷酸烯醇式丙酮酸羧化酶(phosphoenolpyruvate carboxylase, PEPC)基因(C₄ pepc)水稻(简称：PC)种子萌发的生理机制,该研究以 PC及其未转基因野生型受体‘Kitaake’(简称：WT)的种子为材料,研究外施不同浓度蔗糖联合模拟干旱(10% PEG 6000)处理下,其种子发芽参数、总可溶性糖及可溶性蛋白含量、蔗糖非发酵1 (sucrose nonfermenting 1, SNF1)相关蛋白激酶(SNF1 related protein kinase 1s, SnRK1s)基因以及PEPC基因表达等参数的变化。结果表明：(1)PEG 6000模拟干旱处理均显著抑制两材料发芽,但明显促进胚根的生长;外施蔗糖则呈现浓度效应,高浓度蔗糖(>150 mmol·L^-1)进一步加剧了干旱对发芽的抑制效应,而低浓度(<30 mmol·L^-1)则可缓解干旱的抑制,但与WT(<30 mmol·L^-1)相比,促进PC水稻萌发的外施蔗糖浓度(<6 mmol·L^-1)更低,且各处理的发芽表现与其α 淀粉酶活性的动态表现一致。(2)与WT相比,外施3 mmol·L^-1蔗糖联合干旱处理下,显著提高了PC种子的发芽率,且伴随PC内源蔗糖含量、总可溶糖和可溶性蛋白含量显著增加;且外施3 mmol·L^-1蔗糖使PC中内源C₃ pepc基因表达下调,而外源导入C₄ pepc基因表达显著增加。(3)与WT相比,干旱处理下外施3 mmol·L^-1蔗糖,PC的糖信号相关基因SnRKs亚家族基因(包括SnRK1s：OsK1a OsK24 OsK35和SnRK2s:SAPK6)的表达也显著增加。研究发现,外施低浓度蔗糖通过上调PC水稻种子中可溶性糖和可溶性蛋白含量,增强SnRK1s亚家族基因和外源C₄ pepc基因的表达,提高了α 淀粉酶活性,从而缓解了干旱胁迫对PC种子萌发的抑制。     

利用degQ基因提高枯草芽孢杆菌纤溶酶表达*

从枯草芽孢杆菌(Bacillussubtilis)中通过PCR扩增得到degQ基因,将其克隆到含有枯草杆菌纤溶酶基因的蔗糖诱导表达载体pUBS中,并转化至B.subtillisDB403受体菌,得到基因工程菌DB403(pUBSD)。通过发酵表达证实degQ基因能增强枯草杆菌纤溶酶的表达,酶活提高了2.2倍。同时还对不同种类的糖、不同浓度蔗糖、不同诱导时间等发酵条件进行优化和比较研究。     

基于GNM方法研究人TDP-43-DNA相互作用动力学及关键位点

TAR DNA结合蛋白43（transactive response DNA binding protein 43，TDP-43），一种可变剪切因子，可以特异性地结合富含TG序列的DNA，涉及多种神经退行性疾病. 分子动力学模拟方法虽然是研究分子间相互作用强有力的工具，但它非常耗时，且难以对有大的构象变化的体系进行充分采样来研究其变构行为. 本工作使用粗粒化的基于弹性势的高斯网络模型（Gaussian network model，GNM）研究人TDP-43与靶标DNA间相互作用的动力学. 进一步地，利用本课题组之前提出的基于GNM的热力学循环方法识别TDP-43与DNA相互作用的关键残基，其微扰引起了大的结合自由能的变化. DNA结合后，TDP-43上富含正电残基的loop1和loop3片段有较大的柔性损失，这反映了它们在识别和结合中的诱导契合作用. 另外发现，基于热力学循环的方法不仅识别到一些与DNA特异性相互作用有关的重要残基，而且识别到一些远离结合界面但在结合引起的分子构象变化中发挥重要作用的残基. 本研究有助于理解TDP-43与DNA的特异性相互作用，可为药物设计提供重要信息，另外该方法可以很方便地拓展到其他蛋白质-核酸相互作用动力学的研究.     

Topological thermal instability and length of proteins

We present an analysis of the effects of global topology on the structural stability of folded proteins in thermal equilibrium with a heat bath. For a large class of single domain proteins, we computed the harmonic spectrum within the Gaussian Network Model (GNM) and determined their spectral dimension, a parameter describing the low frequency behavior of the density of modes. We found a surprisingly strong correlation between the spectral dimension and the number of amino acids in the protein. Considering that larger spectral dimension values relate to more topologically compact folded states, our results indicate that, for a given temperature and length of protein, the folded structure corresponds to a less compact folding, one compatible with thermodynamic stability.     

Inferring a weighted elastic network from partial unfolding with coarse‐grained simulations

A number of studies have demonstrated that simple elastic network models can reproduce experimental B‐factors, providing insights into the structure–function properties of proteins. Here, we report a study on how to improve an elastic network model and explore its performance by predicting the experimental B‐factors. Elastic network models are built on the experimental coordinates, and they only take the pairs of atoms within a given cutoff distance r_c into account. These models describe the interactions by elastic springs with the same force constant. We have developed a method based on numerical simulations with a simple coarse‐grained force field, to attribute weights to these spring constants. This method considers the time that two atoms remain connected in the network during partial unfolding, establishing a means of measuring the strength of each link. We examined two different coarse‐grained force fields and explored the computation of these weights by unfolding the native structures. Proteins 2014; 82:119–129. © 2013 Wiley Periodicals, Inc.     

Coupling of structural fluctuations to deamidation reaction in triosephosphate isomerase by Gaussian network model

We study the structural fluctuations of triosephosphate isomerase (TIM) by an elastic model, namely, the Gaussian network model (GNM), to identify a network of coupled motions in the allosteric communication between its deamidation and catalytic sites, and the promoting motions for the deamidation activity. For this, three TIM structures have been studied: one crystal structure and two model structures designed to describe different putative models for the deamidation reaction taking place at the subunit interface. The structural fluctuations have been mapped on the functional properties; then the differences in the fluctuations between the two models in relation to the deamidation reaction have been considered. The results demonstrate that the qualitative picture of the mean-square fluctuations and the correlations between the fluctuations are similar in both, but the differences may affect the observed barrier height of the deamidation reaction. The higher packing density at regions close to deamidation sites, reflected by the high-frequency fluctuating residues in the respective regions, the stronger positive correlation between the fluctuations of the deamidation sites, and enhanced positive correlation of the primary deamidation site with the extended vicinity of the catalytic region on the juxtaposed unit promote the probability of the deamidation reaction. The results in general emphasize the importance of structural fluctuations in enzyme reactions, as well as proposing the present methodology as a plausible approach for studies on the network of coupled promoting motions in protein functions.     

Association of putative concave protein-binding sites with the fluctuation behavior of residues

Here, we propose a binding site prediction method based on the high frequency end of the spectrum in the native state of the protein structural dynamics. The spectrum is obtained using an elastic network model (GNM). High frequency vibrating (HFV) residues are determined from the fastest modes dynamics. HFV residue clusters and the associated surface patch residues are tested for their likelihood to locate at the binding interfaces using two different data sets, the Benchmark Set of mainly enzymes and antigen/antibodies and the Cluster Set of more diverse structures. The binding interface is identified to be within 7.5 A of the HFV residue clusters in the Benchmark Set and Cluster Set, for 77% and 70% of the structures, respectively. The success rate increases to 88% and 84%, respectively, by using the surface patches. The results suggest that concave binding interfaces, typically those of enzyme-binding sites, are enriched by the HFV residues. Thus, we expect that the association of HFV residues with the interfaces is mostly for enzymes. If, however, a binding region has invaginations and cavities, as in some of the antigen/antibodies and in cases in the Cluster data set, we expect it would be detected there too. This implies that binding sites possess several (inter-related) properties such as cavities, high packing density, conservation, and disposition for hotspots at binding surfaces. It further suggests that the high frequency vibrating residue-based approach is a potential tool for identification of regions likely to serve as protein-binding sites. The software is available at http://www.prc.boun.edu.tr/PRC/software.html.     

vGNM: a better model for understanding the dynamics of proteins in crystals

The dynamics of proteins are important for understanding their functions. In recent years, the simple coarse-grained Gaussian Network Model (GNM) has been fairly successful in interpreting crystallographic B-factors. However, the model clearly ignores the contribution of the rigid body motions and the effect of crystal packing. The model cannot explain the fact that the same protein may have significantly different B-factors under different crystal packing conditions. In this work, we propose a new GNM, called vGNM, which takes into account both the contribution of the rigid body motions and the effect of crystal packing, by allowing the amplitude of the internal modes to be variables. It hypothesizes that the effect of crystal packing should cause some modes to be amplified and others to become less important. In doing so, vGNM is able to resolve the apparent discrepancy in experimental B-factors among structures of the same protein but with different crystal packing conditions, which GNM cannot explain. With a small number of parameters, vGNM is able to reproduce experimental B-factors for a large set of proteins with significantly better correlations (having a mean value of 0.81 as compared to 0.59 by GNM). The results of applying vGNM also show that the rigid body motions account for nearly 60% of the total fluctuations, in good agreement with previous findings.     

Propagation of dynamic changes in barnase upon binding of barstar: an NMR and computational study

NMR spectroscopy and computer simulations were used to examine changes in chemical shifts and in dynamics of the ribonuclease barnase that result upon binding to its natural inhibitor barstar. Although the spatial structures of free and bound barnase are very similar, binding results in changes of the dynamics of both fast side-chains, as revealed by (2)H relaxation measurements, and NMR chemical shifts in an extended beta-sheet that is located far from the binding interface. Both side-chain dynamics and chemical shifts are sensitive to variations in the ensemble populations of the inter-converting molecular states, which can escape direct structural observation. Molecular dynamics simulations of free barnase and barnase in complex with barstar, as well as a normal mode analysis of barnase using a Gaussian network model, reveal relatively rigid domains that are separated by the extended beta-sheet mentioned above. The observed changes in NMR parameters upon ligation can thus be rationalized in terms of changes in inter-domain dynamics and in populations of exchanging states, without measurable structural changes. This provides an alternative model for the propagation of a molecular response to ligand binding across a protein that is based exclusively on changes in dynamics.     

Dynamics of heteropentameric nicotinic acetylcholine receptor: implications of the gating mechanism

The dynamics characteristics of the currently available structure of Torpedo nicotinic acetylcholine receptor (nAChR), including the extracellular, transmembrane, and intracellular domains (ICDs), were analyzed using the Gaussian Network Model (GNM) and Anisotropic Network Model (ANM). We found that a symmetric quaternary twist motion, reported previously in the literature in a homopentameric receptor (Cheng et al. J Mol Biol 2006;355:310-324; Taly et al. Biophys J 2005;88:3954-3965), occurred also in the heteropentameric Torpedo nAChR. We believe, however, that the symmetric twist alone is not sufficient to explain a large body of experimental data indicating asymmetry and subunit nonequivalence during gating. Here we report our results supporting the hypothesis that a combination of symmetric and asymmetric motions opens the gate. We show that the asymmetric motion involves tilting of the TM2 helices. Furthermore, our study reveals three additional aspects of channel dynamics: (1) loop A serves as an allosteric mediator between the ligand binding loops and those at the domain interface, particularly the linker between TM2 and TM3; (2) the ICD can modulate the pore dynamics and thus should not be neglected in gating studies; and (3) the F loops, which are peculiarly longer and poorly-conserved in non-alpha-subunits, have important dynamical implications.     

Deriving correlated motions in proteins from X-ray structure refinement by using TLS parameters

Dynamic information in proteins may provide valuable information for understanding allosteric regulation of protein complexes or long-range effects of the mutations on enzyme activity. Experimental data such as X-ray B-factors or NMR order parameters provide a convenient estimate of atomic fluctuations (or atomic auto-correlated motions) in proteins. However, it is not as straightforward to obtain atomic cross-correlated motions in proteins — one usually resorts to more sophisticated computational methods such as Molecular Dynamics, normal mode analysis or atomic network models. In this report, we show that atomic cross-correlations can be reliably obtained directly from protein structure using X-ray refinement data. We have derived an analytic form of atomic correlated motions in terms of the original TLS parameters used to refine the B-factors of X-ray structures. The correlated maps computed using this equation are well correlated with those of the method based on a mechanical model (the correlation coefficient is 0.75) for a non-homologous dataset comprising 100 structures. We have developed an approach to compute atomic cross-correlations directly from X-ray protein structure. Being in analytic form, it is fast and provides a feasible way to compute correlated motions in proteins in a high throughput way. In addition, avoiding sophisticated computational operations; it provides a quick, reliable way, especially for non-computational biologists, to obtain dynamics information directly from protein structure relevant to its function.     

ATP binding enables broad antibiotic selectivity of aminoglycoside phosphotransferase(3')-IIIa: an elastic network analysis

The bacterial enzyme aminoglycoside phosphotransferase(3′)-IIIa (APH) confers resistance against a wide range of aminoglycoside antibiotics. In this study, we use the Gaussian network model to investigate how the binding of nucleotides and antibiotics influences the dynamics and thereby the ligand binding properties of APH. Interestingly, in NMR experiments, the dynamics differ significantly in various APH complexes, although crystallographic studies indicate that no larger conformational changes occur upon ligand binding. Isothermal titration calorimetry also shows different thermodynamic contributions to ligand binding. Formation of aminoglycoside-APH complexes is enthalpically driven, while the enthalpic change upon aminoglycoside binding to the nucleotide-APH complex is much smaller. The differential effects of nucleotide binding and antibiotic binding to APH can be explained theoretically by single-residue fluctuations and correlated motions of the enzyme. The surprising destabilization of β-sheet residues upon nucleotide binding, as seen in hydrogen/deuterium exchange experiments, shows that the number of closest neighbors does not fully explain residue flexibility. Additionally, we must consider correlated motions of dynamic protein domains, which show that not only connectivity but also the overall protein architecture is important for protein dynamics.