多特征融合的蛋白质相互作用位点预测

蛋白质相互作用位点预测为蛋白质功能和药物设计的理解提供重要线索。而蛋白质的各种特征为蛋白质相互作用位点预测提供了大量有用信息,特别是进化信息、残基序列邻近和空间邻近性。不同的蛋白质特征对蛋白质间的相互作用的贡献也不一样。通过提取蛋白质序列谱、保守性和残基熵,提出了特征融合技术对蛋白质相互作用位点进行研究,采用SVM构建三种预测器,分别对各种不同的特征加以验证,实验结果表明了基于特征融合方法的有效性和正确性。     

HClO对贻贝粘附单元DOPA氧化的理论研究

采用量子化学密度泛函理论(DFT)研究贻贝粘附单元DOPA(3,4-二羟基苯丙氨酸)的结构与性质,得分子的几何构型、原子电荷分布、反应活性及热力学等参数,表明:DOPA苯环易与HClO(次氯酸)发生亲电取代反应(1),生成3-氯4,5-二羟基苯丙氨酸,阻碍生成贻贝内超强粘附单元DOPA二联体,降低粘附蛋白间粘性;DOPA侧链易与HClO发生亲电亲核反应(2),促使DOPA侧链的断裂,降低粘附蛋白内粘性;在相同温度下,反应(1)和反应(2)的△G<0,且△G(1)<△G(2),反应(1)较易发生.     

基于长周期光纤光栅的生物传感器设计及仿真

利用生物活性物质高效、专一的催化特性,通过生化反应中生成的复合物对包层折射率和半径的直接调制,提出了基于长周期光纤光栅的、可用于蛋白质等生物物质鉴别与分析的传感方案,并用数值计算方法对检测中所生成复合物薄膜层的折射率和厚度变化对耦合波长偏移和衰减的影响进行了仿真研究,为新型高灵敏度生物传感器的研发提供了理论依据。     

Protien side-chain conformational entropy derived from fusion data-comparison with other empirical scales

The loss of conformational entropy of protein side-chains isa major effect in the energetics of folding. The simplest approachis to enumerate the number of freely rotatable bonds. Recently,two scales of side-chain conformational entropy have been proposedbased on the definition of entropy as the Boltzmann samplingover all accessible states (S –Rp_iInp_i, where p_i is theprobability of being in a rotameric state). In one scale, derivedonly for aliphatic and aromatic side-chains, the values of p_iwere obtained from Monte Carlo simulations. In the other scale,the observed frequencies of different rotameric states in adatabase of protein crystal structures yielded an estimate forp_i. Here an empirical estimation of the fusion entropy of theside-chains is used to derive a third scale. The fusion entropyis obtained as a sum of empirically derived contributions fromcomponent hydrocarbon and functional groups. There is a goodagreement between the fusion scale and the other two scales.This suggests that the magnitude of conformational entropy isbeing correctly established     

Protein stability for single substitution mutants and the extent of local compactness in the denatured state

The stability changes caused by single amino acid substitutionsare studied by a simple, empirical method which takes accountof the free energy change in the compact denatured state aswell as in the native state. The conformational free energyis estimated from effective inter-residue contact energies,as evaluated in our previous study. When this method is applied,with a simple assumption about the compactness of the denaturedstate, for single amino acid replacements at Glu49 of the tryptophansynthase subunit and at Ile3 of bacteriophage T4 lysozyme,the estimates of the unfolding Gibbs free energy changes correlatewell with observed values, especially for hydrophobic aminoacids, and it also yields the same magnitudes of energy as theobserved values for both proteins. When it is also applied foramino acid replacements at various positions to estimate theaverage number of contacts at each position in the denaturedstate from the observed value of unfolding free energy change,those values for replacements with Gly and Ala at the same residueposition in staphylococcal nuclease correlate well with eachother. The estimated numbers of contacts indicate that the proteinis not fully expanded in the denatured state and also that thecompact denatured state may have a substantially native-liketopology, like the molten globule state, in that there is aweak correlation between the estimated average number of contactsat each residue position in the denatured state and the numberof contacts in the native structure. These results provide somefurther evidence that the inter-residue contact energies asapplied here (i) properly reflect actual inter-residue interactionsand (ii) can be considered to be a pairwise hydrophobicity scale.Also, the results indicate that characterization of the denaturedstate is critical to understanding the folding process.     

Solvent interactions with n ring systems in proteins

The interaction of water molecules with apolar amino acids isan important aspect of the hydrophobic effect and hence of proteinfolding. Our distributed multipole electrostatic model for waterinteracting with phenylalanine dipeptides shows that minimumenergy sites exist above the aromatic ring such that a solventmolecule can interact with the electrons, but only when thissite is not blocked by mainchain atoms or disturbed by main-chainpolar atoms. This is consistent with the experimental evidenceof others that water can hydrogen bond to aromatic n electrons.In contrast, our analysis of solvent interactions with phenylalanineresidues based on 48 high-resolution, well-refined protein structuresshows that the dominant interaction of solvent molecules iswith the edge of the ring and not with the 7i electrons. Asthe faces of phenylalanine rings tend to be buried, and solventinteractions with neighbouring polar atoms are more favourable,the interaction of water molecules with the faces of aromatic rings appears not to occur frequently in proteins     

过敏原肌质钙结合蛋白在毕赤酵母中的表达、优化及免疫反应性研究

目的 探究天然肌质钙结合蛋白(sarcoplasmic calcium binding protein, SCP)的可替代物,为蟹类过敏原的检测提供基础材料,本研究首次利用毕赤酵母(Pichia pastoris, P. pastoris)高效表达表达三疣梭子蟹(Portunus trituberculatus)重要过敏原SCP,并检验其免疫反应性。方法 根据毕赤酵母的密码子偏好性优化SCP基因并构建重组质粒。将其热激转化至P. pastoris GS115菌株后经遗传霉素(Geneticin, G418)筛选获得阳性高拷贝子。最后通过甲醇诱导表达重组SCP并结合免疫印记(Western blotting, WB)和间接酶联免疫吸附实验(enzyme-linked immunosorbent assay, ELISA)验证其免疫反应性。结果 SCP在P. pastoris GS115中实现了可溶性高效表达,其表观分子量约为28 kDa。在摇瓶水平下,最佳诱导条件为pH为6.0、每24 h添加1.0%(v/v)甲醇,于28℃发酵144 h,在此条件下,纯度为91.6%的SCP产量可达15 mg/L。WB和间接ELISA结果表明,重组SCP具有IgG结合能力。结论 毕赤酵母表达系统可以得到纯度较高且免疫反应性良好的重组SCP。本研究为SCP的理化研究及产业化应用奠定了基础,并有望促进特异性甲壳类过敏原检测的发展。     

BP神经网络结合变量选择方法在牛奶蛋白质含量检测中的应用北大核心CSCD

牛奶中的蛋白质含量会影响牛奶的品质,利用高光谱图像的光谱特征信息研究对牛奶蛋白质含量预测的可行性。本文提出一种基于竞争性自适应重加权算法(competitive adaptive reweighted sampling, CARS)和连续投影算法(successive projections algorithm, SPA)结合多层前馈神经网络(back propagation, BP)的预测建模方法,实验以含有不同浓度蛋白质的牛奶为对象,利用可见光/近红外高光谱成像系统共采集到5种牛奶共计250组高光谱数据,通过实验对比选择采用标准化方法对获取到的吸收光谱预处理,然后采用CARS结合SPA筛选特征波长,得到18个特征波长,建立CARS-SPA-BP模型,经过试验,CARS-SPA-BP模型的训练集决定系数和测试集决定系数R;和R;分别达到0.971和0.968,训练集均方根误差(root mean square error of calibration,RMSEC)和测试集均方根误差(root mean square error of prediction,RMSEP)达到了0.033和0.034。研究发现,采用CARS结合SPA筛选的牛奶特征波长建立的多层前馈神经网络模型,其模型预测结果与全波长建模相比并没有明显降低,因此将CARS结合SPA用于波长筛选并且结合BP神经网络基本可以完成对牛奶蛋白质含量的预测。为验证CARS-SPA-BP模型的预测能力,在相同数据环境下,使用较为传统的偏最小二乘回归(partial least squares regression, PLSR)进行建模,实验结果表明,CARS-SPA-BP相较于PLSR,R;和RMSEP均有明显提升。研究表明,CARS-SPA-BP可充分利用牛奶光谱特征信息实现较高精度的牛奶蛋白质含量检测。