【作者】 苏荣欣；

【导师】 何志敏；

【作者基本信息】 天津大学 ， 化学工程， 2007， 博士

【摘要】 本文组合应用色谱、质谱、光谱等测试技术,系统地研究了两个极具开发价值的水解体系:牛血红蛋白—胃蛋白酶(体系I)、牛乳酪蛋白—胰酶(体系II),并基于酶学性质和蛋白质结构知识,剖析酶解历程动态特性和多肽释放规律。1.比较体系I在两种不同水解机制下的反应行为。在pH为4.5时,牛血红蛋白保持天然结构,在胃蛋白酶作用下发生顺次水解,底物在反应过程中始终存在;在pH为2.0时,变性的牛血红蛋白在胃蛋白酶作用下发生拉链水解,底物在反应过程中快速转化为中间多肽。胃蛋白酶主要攻击α链全链和β链两端区域,而β链中部区域由于高亲水性而少有剪切。基于多肽释放动力学规律,确定活性多肽最佳制备工艺。进一步根据胃蛋白酶水解特性和牛血红蛋白结构剖析了反应行为。2.跟踪体系I活性多肽相互转化历程。在抗菌肽α107-136向血管舒缓激肽α110-125转化历程中,共涉及6个相关多肽;基于序列分析和多肽释放动力学,构建了反应网络,分析胃蛋白酶对各种肽键的亲和力;依据结构分析推断多肽生物学功能。3.利用反相色谱、离子交换色谱和体积排阻色谱对体系II酶解产物多肽进行分离。在酶解历程中,产物多肽整体上按疏水性向亲水性、多电荷向寡电荷、高分子量向低分子量转变。4.体系II的底物和产物分析。酪蛋白在胰酶作用下,胶束含量逐渐降低,但胶束尺寸和分子量却在水解10min内不断增加。反应24小时内,共释放297个多肽。胰酶攻击单体的速度从快到慢为:β-酪蛋白>αs1-酪蛋白>αs2-酪蛋白>κ-酪蛋白。5.体系II酶解历程的理论模拟和直观表征。利用2-30-30-1的BP模型对酪蛋白酶解历程分子量分布进行模拟;基于该模型完成三维图形表征,可直观分析胶束区、单体区、巨肽区、长肽区和寡肽区的含量变化。6.酪蛋白磷酸肽的特殊鉴定和释放规律。采用液质联用技术结合中性丢失扫描(SALSA自定义检索模块)和数据库搜索(Sequest蛋白数据库匹对)对酪蛋白磷酸肽(CPPs)进行鉴定;CPPs在串联质谱过程均发生明显的中性丢失现象,利用中性丢失峰,可迅速判断其价态、分子量和磷酸化个数;跟踪了CPPs的释放规律,确定了其最佳制备工艺。7.多肽反相色谱保留行为模型构建及磷酸化影响规律研究。基于365个非磷酸肽,构建了色谱保留时间预测模型;单一和多重磷酸化分别导致多肽整体亲水性的降低和增强,因此分别比非磷酸化对应体较晚和较早洗脱。更多还原

【Abstract】 In this thesis, peptic digestion of bovine hemoglobin and pancreatic digestion ofbovine casein were systematicallyinvestigated bya combination of chromatographic, massspectrometric and spectroscopic analyses. On the basis of enzyme mechanism and proteinstructure, we have extensively studied the reaction behavior of protein and release kineticsof peptides during enzymatic hydrolysis.The main aspectsand conclusions were displayedasfollows.1. Two different mechanisms of hydrolysis were compared for peptic digestion of bovinehemoglobin:“onebyone”fornativehemoglobinat pH4.5,and“zipper”fordenaturedhemoglobin at pH 2.0. The reaction mixture always contains native hemoglobin at pH4.5, whereas denatured hemoglobin were rapidly converted to intermediate peptides.For these two mechanisms, peptic cleavage sites were distributed all theα-chain andthe terminal regions ofβ-chain. Littleenzymatichydrolysisoccurredinthecenterpart ofβ-chain due mainly to their high hydrophilic nature. The reaction behavior was discussedin relation to the hydrophobicitydistribution of polypeptide chains and the mechanismofpepsin.2. The precursor cleavage of the antimicrobial peptideα107-136 into the bradykinin-potentiating peptideα110-125 were followed during peptic hydrolysis of bovinehemoglobin. A total of six peptides were identified as being involved in the cleavageprocess. Moreover, the reaction network of these peptides was developed according tothe sequence alignment and their release kinetics. The affinity of pepsin towardsdifferent peptide bonds of bovine hemoglobin was also compared based on data fromthe release kinetics of peptides. In addition, some potentially bioactive peptides werepredictedbymeansofsequenceanalysisandsecondarystructurecalculations.3. Bovine casein pancreatic hydrolysates were separated andanalyzed by reversed-phase,strong cation exchange and size exclusion chromatography. In general, the resultingpeptides were converted from hydrophobic to hydrophilic, from multiply-charged tofew-chargedandfromlargetosmallduringthecourseofhydrolysis.4. The substrate and products from pancreatic digestion of bovine casein were analyzedby size exclusion chromatography coupled with multi-angle laser light scattering(SEC-MALLS) and reversed-phase liquid chromatography coupled with tandem massspectrometry (RPLC-ESI-MS/MS), respectively. Upon limited hydrolysis, casein micelles displayed a continuous growth in their sizes and molecular weights, togetherwith the decrease in their concentration. The hydrolysis rate of micellar caseins bypancreatinwasrankedfromfasttoslowasfollows:β-casein>αs1-casein>αs2-casein>κ-casein.5. We developed a computational model to predict molecular weight distribution ofbovine casein pancreatic hydrolysates using artificial neural networks (ANN) thatcontained 2 input nodes, 1 output node and two hidden layers with 30 nodes. Based onthe prediction results from such model, a 3-D continuous surface and its correspondingcontour plot were obtained to directly and distinctly characterize the dynamic processof enzymatic hydrolysates with different molecular weight including micelles,monomers,macropeptides,polypeptidesandoligopeptides.6. In total, 52 casein phosphopeptides (CPPs) in the time-course samples were separatedand identified using liquid chromatography-tandem mass spectrometry by means ofneural loss scanning (SALSA) and database searching (Sequest). All the CPPs showedsignificant neutral loss of phosphoric acid(s) during the collision-induced dissociation(CID) process in the ion-trap mass spectrometer. Moreover, the charge states, molarmasses and number of phosphorylation sites of peptides could be determined on thebasis of these neural loss ions. In addition, a study of the release kinetics of CPPsallowed determination of the degrees of hydrolysis for the preparation of target CPPwithhighyields.7. Aprediction model as awas developed on the basis of 365non-phosphorylated peptides from casein pancreatic and peptic hydrolysates, and canbe used to accurately predict the retention times of peptides on C4 reversed-phase(300? pore size) columns with TFA as the ion pairing reagent. Singly and multiplyphosphorylations respectively reduced and increased the overall hydrophilicity ofpeptides, and thus make phosphopeptides elute after or before the non-phosphorylatedpredictivecognates,respectively.更多还原