全新设计蛋白质的折叠机制

蛋白质全新设计和折叠研究是从两个不同的方向来理解蛋白质序列-结构-功能关系这一结构生物学重要问题. 蛋白质全新设计取得的成功实例一定程度上检验了人们对蛋白质结构和相互作用理解的准确性, 但它们中多数所表现的不同于天然蛋白质的折叠动力学特征也表明, 要达到最终的功能化实现目标还面临着不少的挑战. 本文综述了蛋白质全新设计的发展过程及现状, 蛋白质折叠研究在实验、理论及模拟方面的研究进展, 以及全新设计蛋白质的折叠机制的研究现状. 阐述了深入了解全新设计蛋白质与天然蛋白质折叠机制的不同, 可以为进一步有效地合理化设计蛋白质提供有益的参考.     

模型多肽Trp-Cage折叠形成机制的研究进展

蛋白质折叠是目前结构生物学领域的核心问题之一, 理解蛋白质结构折叠机制及其与生物功能之间的相互关系一直是生命科学家非常重要的研究内容, 并且该研究受到越来越多不同学科领域研究工作者的高度重视. 蛋白质大多数在数十毫秒、微秒或几秒内完成自我折叠过程, 但其折叠过程中所发生的分子结构精细转变却在纳秒甚至更短时间尺度内完成. 由于其折叠时间分辨率的限制, 目前无论是从常规实验还是理论计算角度对其研究都存在一定的难度. 本文首先概述了蛋白质折叠研究在实验和理论模拟方面存在的一些问题,然后以结构典型且可快速折叠的人工设计多肽Trp-cage为例,主要对其折叠过渡温度、折叠形成模型及其肽链上关键氨基酸残基在折叠过程中的作用三个方面进行了详细讨论, 综述了模型多肽Trp-cage的折叠动力学行为分别在实验和理论模拟方面的研究进展. 最后就如何有效化解蛋白质残基间相互作用网络进而降低其折叠机制的复杂性提出了一些新的建议, 不仅有助于阐明该迷你蛋白Trp-cage快速折叠、稳定形成的驱动力成因, 而且也能为蛋白质折叠机制研究和多肽设计提供有益参考.     

蛋白质折叠类型的分类建模与识别

蛋白质的氨基酸序列如何决定空间结构是当今生命科学研究中的核心问题之一. 折叠类型反映了蛋白质核心结构的拓扑模式, 折叠识别是蛋白质序列-结构研究的重要内容. 我们以占Astral 1.65序列数据库中α, β和α/β三类蛋白质总量41.8%的36个无法独立建模的折叠类型为研究对象, 选取其中序列一致性小于25%的样本作为训练集, 以均方根偏差(RMSD)为指标分别进行系统聚类, 生成若干折叠子类, 并对各子类建立基于多结构比对算法(MUSTANG)结构比对的概形隐马尔科夫模型(profile-HMM). 将Astral 1.65中序列一致性小于95%的9505个样本作为检验集, 36个折叠类型的平均识别敏感性为90%, 特异性为99%, 马修斯相关系数(MCC)为0.95. 结果表明: 对于成员较多, 无法建立统一模型的折叠类型, 基于RMSD的系统分类建模均可实现较高准确率的识别, 为蛋白质折叠识别拓展了新的方法和思路, 为进一步研究奠定了基础.     

二维紧密蛋白质链折叠序列的特性研究

采用完全计数法,研究了二维紧密蛋白质链在不同HP序列时的构象性质,特别是具有唯一基态能量的折叠序列的性质.对于具有N个单体的紧密蛋白质链,发现有一定比例的序列为折叠序列.在这些折叠序列中,疏水基团(H)的数目比亲水基团(P)多20%,并同200种真实蛋白质分子的疏水基团和亲水基团的结果进行了比较.对于不同的折叠序列,根据序列中其疏水基团的数目,把具有相同疏水基团数目的序列归在同一类,发现这样的序列在总的序列中的相对含量满足高斯分布.同时还对序列中H(或者P)团族大小及其分别进行了研究,发现折叠序列与无规随机序列不同.还研究了不同折叠序列在不同链长时的比热情况,发现其相转变温度TC主要与链长有关,与折叠序列无关.     

人类朊蛋白的动力学稳定性研究（英文）

朊蛋白病是一种能在人类或者动物之间传播的致命的神经退行性疾病.尤其是人类朊蛋白疾病在近几年蔓延迅速,已经威胁到人类的健康.在本文中,我们使用分子动力学(MD)和流体分子动力学(FMD)模拟相结合的方法研究了人类朊蛋白(hPrPc)的动力学稳定性.我们通过FMD模拟产生了两个典型的hPrPc的变性结构,并进一步研究了在自然状态下这两个变性结构重折叠的过程,从关键残基、二级结构、残基-残基相互作用图等方面详细讨论了hPrPc的解折叠和重折叠路径.研究发现hPrPc的三个α-螺旋结构组成了一个疏水核心,在蛋白质的解折叠和重折叠过程中发挥了重要的作用.刚性的疏水核心就像是脚手架一般为hPrPc的重折叠提供便利.在重折叠过程中,π-螺旋和310螺旋出现几率较高,并且β-折叠的延长也更多地出现在完全解折叠的hPrPc体系中.     

Hg^2＋ -牛血清白蛋白复合体系中蛋白质微观结构的研究

研究了Hg2+在生物体内与牛血清白蛋白相互作用的毒性机理以及蛋白质的微观结构变化.测定了Hg2+与牛血清白蛋白(BSA)复合体系的红外光谱(FT-IR)和圆二色谱(CD),并对图谱进行拟合解析处理.红外光谱实验数据表明Hg2+与BSA发生作用的结合位点可能包括-SH、-OH和-NH基团,采用红外拟合技术对BSA二级结构的变化进行了研究,结果表明蛋白质α-螺旋结构含量降低,β-折叠结构含量升高.圆二色谱图也表明由于一定浓度的Hg2+与BSA结合,从而导致蛋白质的二级结构被破坏,这与拟合红外光谱得到的蛋白质二级结构数据相吻合.Hg2+与牛血清蛋白作用致使蛋白质的构象改变,形成金属离子与蛋白质作用的复合物,因而蛋白质失去活性导致生物体发生病变.     

红外光谱法分析酵母蛋白质的二级结构

采用红外光谱法分析了酵母蛋白质的二级结构。测定了不同温度下酵母酰胺Ⅲ带的一维红外光谱、二阶导数红外光谱及去卷积红外光谱。结果表明:随着测量温度的升高,酵母中的蛋白质α-螺旋结构的红外吸收强度降低;而β-转角结构、无规卷曲结构和β-折叠结构红外吸收强度均有所增加。还研究了酵母酰胺Ⅲ带的二维红外光谱,以确定酵母中蛋白质红外吸收强度的变化次序,进一步证明了酵母蛋白质的β-折叠结构的热不稳定性。     

红外光谱酰胺Ⅲ带用于蛋白质二级结构的测定研究

用甲醇对BSA和RaseA等蛋白质进行变性处理,结合蛋白质酰胺带的拟合结果对酰胺带各二级结构的谱峰进行了初步指认:1330～1290cm^-1为α-螺旋;1295～1265cm^-1为β-转角;1270～1245cm^-1为无规卷曲;1250～1220cm^-1为β-折叠.依据这些谱峰归属,对一些已知二级结构的蛋白质进行了测定,所得结果与X射线衍射数据以及酰胺带的定量结果基本一致.     

应用连续小波变换预测蛋白质的二级结构

将代码为lgca蛋白质的氨基酸序列映射为疏水值序列，在合适的尺度下，通过 连续小波变换法分别对其α螺旋,α螺旋和β折叠之间的连接多肽(即部分规则和无 规则二级结构)进行预测，准确率分别为76．5％和85．7％．从PDBsum数据库中随 机抽取100个蛋白质作为测试对象，其中全α螺旋、全β折叠、α／β以及α+β蛋 白质各25个．在100个蛋白质中共有1618个连接多肽和747个α螺旋.本法预测到的 连接多肽共有1536个，其中1308个与实际结构一致，平均预测准确率为85.2％；预 测到的α螺旋有770个，其中581个与实际结构一致，平均预测准确率为75．5％． 结果表明：该法可较好地预测蛋白质的α螺旋、连接多肽，具有极大的发展前景．     

基于药效团的三维数据库搜索

用表皮生长因子受体酪氨酸激酶抑制剂的药效团作为提问结构在三维数据库中进行了搜索.从得到的命中结构中挑选了12个化合物用柔性受体模型方法对其活性进行了预测, 发现有2个化合物具有一定的预测活性.这2个化合物可能具有酪氨酸激酶抑制剂的活性, 可能作为先导化合物进行结构优化.     

Comparative modeling: the state of the art and protein drug target structure prediction

The goal of computational protein structure prediction is to provide three-dimensional (3D) structures with resolution comparable to experimental results. Comparative modeling, which predicts the 3D structure of a protein based on its sequence similarity to homologous structures, is the most accurate computational method for structure prediction. In the last two decades, significant progress has been made on comparative modeling methods. Using the large number of protein structures deposited in the Protein Data Bank (~65,000), automatic prediction pipelines are generating a tremendous number of models (~1.9 million) for sequences whose structures have not been experimentally determined. Accurate models are suitable for a wide range of applications, such as prediction of protein binding sites, prediction of the effect of protein mutations, and structure-guided virtual screening. In particular, comparative modeling has enabled structure-based drug design against protein targets with unknown structures. In this review, we describe the theoretical basis of comparative modeling, the available automatic methods and databases, and the algorithms to evaluate the accuracy of predicted structures. Finally, we discuss relevant applications in the prediction of important drug target proteins, focusing on the G protein-coupled receptor (GPCR) and protein kinase families.     

Identification of the druggable concavity in homology models using the PLB index

Identification of the druggable concavity, in which drug-like molecules are highly inclined to bind, is an important step in structure-based drug design. We previously proposed an index named PLB (propensity for ligand binding), which is based on the amino acid composition characteristically observed at the small molecule binding sites in the X-ray structures of the complexes between proteins and drug-like small molecules. The PLB index was proven to be useful in identifying the druggable concavities in the quality X-ray structures of proteins. Here, we apply the PLB to predicting the druggable concavity in target proteins using the structures of homologous proteins constructed by homology modeling. In this study, we assembled a set of reference proteins that were accurately determined by X-ray analysis in forms of complexes with drug-like small molecules. Homology models for the reference protein were constructed using multiple homologous proteins as templates. The PLB index was then used to predict the druggable concavity. If the template protein in a complex with a drug-like small molecule was used, the druggable concavity was predicted well, with a prediction rate of 78%. When only the apo protein was available as the template, the practical prediction rate was 71%. Interestingly, even when the percent sequence identity between the reference and template proteins was lower than 30, the PLB index could successfully identify the druggable concavity in some cases. This study demonstrates the practical value of applying the PLB index to identifying the drugabble concavity in the homology model.     

Comprehensive predictions of target proteins based on protein-chemical interaction using virtual screening and experimental verifications

ABSTRACT: BACKGROUND: Identification of the target proteins of bioactive compounds is critical for elucidating the mode of action; however, target identification has been difficult in general, mostly due to the low sensitivity of detection using affinity chromatography followed by CBB staining and MS/MS analysis. RESULTS: We applied our protocol of predicting target proteins combining in silico screening and experimental verification for incednine, which inhibits the anti-apoptotic function of Bcl-xL by an unknown mechanism. One hundred eighty-two target protein candidates were computationally predicted to bind to incednine by the statistical prediction method, and the predictions were verified by in vitro binding of incednine to seven proteins, whose expression can be confirmed in our cell system. As a result, 40% accuracy of the computational predictions was achieved successfully, and we newly found 3 incednine-binding proteins. CONCLUSIONS: This study revealed that our proposed protocol of predicting target protein combining in silico screening and experimental verification is useful, and provides new insight into a strategy for identifying target proteins of small molecules.     

Antibodies to short synthetic peptides for specific recognition of partly denatured protein

On immunization with subclasses of homologous proteins, the presence of immunodominant class-specific structures often prevents the development of subclass specific antibodies. Immunization with synthetic peptides representing specific structures in such a protein can then be used instead. Sequences derived from human IgG2 and Staphylococcus aureus enterotoxin were used as a model to develop general criteria for immunization with synthetic peptides. Peptide sequences were selected on the basis of criteria such as hydrophilic property, surface probability and secondary structure, which together constitute an antigenic index. The carrier proteins keyhole limpet hemocyanin and chicken gammaglobulin were coupled by using either carbodiimide or a maleimide. Peptide-specific responses can be elicited regardless of the sequence. Some coupling conditions influenced the specificity of the antibody responses. The results of immunization with short peptides not representing a natural B-cell determinant of a protein suggest that the frequency of native protein-recognizing antibodies is considerably lower than that of antibodies that recognize the protein in a partly denatured or altered state.     

Structural analysis of inhibition mechanisms of aurintricarboxylic acid on SARS-CoV polymerase and other proteins

We recently published experimental results that indicated Aurintricarboxylic Acid (ATA) could selectively inhibit SARS-CoV replication inside host cells by greater than 1000 times. This inhibition suggested that ATA could be developed as potent anti-viral drug. Here, to extend our experimental observation, we have incorporated protein structural studies (with positive/negative controls) to investigate the potential binding modes/sites of ATA onto RNA-dependent RNA polymerase (RdRp) from SARS-CoV and other pathogenic positive-strand RNA-viruses, as well as other proteins in SARS-CoV based on the fact that ATA binds to Ca2+-activated neutral protease (m-calpain), the protein tyrosine phosphatase (PTP) and HIV integrase which have existing crystal structures. Eight regions with homologous 3D-conformation were derived for 10 proteins of interest. One of the region, Rbinding (754-766 in SARS-CoV's RdRp), located in the palm sub-domain mainly constituted of anti-parallel beta-strand-turn-beta-strand hairpin structures that covers two of the three RdRp catalytic sites (Asp 760, Asp761), was also predicted by molecular docking method (based on free energy of binding DeltaG) to be important binding motif recognized by ATA. The existence of this strictly conserved region that incorporated catalytic residues, coupled with the homologous ATA binding pockets and their consistent DeltaG values, suggested strongly ATA may be involved in an analogous inhibition mechanism of SARS-COV's RdRp in concomitant to the case in m-calpain, PTP and HIV integrase.     

质谱法分析蛇毒蛋白翻译后修饰

采用SDS-PAGE分离大连黑眉蝮蛇(Gloydius Shedaoensis)蛇毒蛋白组分, Pro-Q Emerald 488糖蛋白和Pro-Q Diamond磷酸化蛋白荧光染料用于糖蛋白和磷酸化蛋白泳带染色, 采用高效液相色谱电喷雾电离串联质谱(HPLC-nESI-MS/MS)法鉴定蛋白. SDS-PAGE胶上的8条糖蛋白带被分别鉴定为L-氨基酸氧化酶、金属蛋白酶、谷氨酰环化酶、C-端缺失L-氨基酸氧化酶、纤溶酶原激活物、磷脂酶A2(PLA2)和神经生长因子; 5条磷酸化蛋白带被分别鉴定为Stejaggregin-A、PLA2、Crisp、金属蛋白酶 P-Ⅲ和Acutolysin e precursor, 与其它蛇毒来源蛋白具有一定的同源性. 为进一步验证方法的可靠性, 采用离子交换和凝胶过滤层析技术纯化得到了PLA2, Pro-Q Diamond染色结果显示PLA2被磷酸化. 研究所得结果为进一步研究蛋白质翻译后修饰对蛇毒蛋白的生物活性、结构与功能提供了依据.     

Docking of small molecules to farnesoid X receptors using AutoDock Vina with the Convex-PL potential: lessons learned from D3R Grand Challenge 2

The 2016 D3R Grand Challenge 2 provided an opportunity to test multiple protein–ligand docking protocols on a set of ligands bound to farnesoid X receptor that has many available experimental structures. We participated in the Stage 1 of the Challenge devoted to the docking pose predictions, with the mean RMSD value of our submission poses of 2.9 Å. Here we present a thorough analysis of our docking predictions made with AutoDock Vina and the Convex-PL rescoring potential by reproducing our submission protocol and running a series of additional molecular docking experiments. We conclude that a correct receptor structure, or more precisely, the structure of the binding pocket, plays the crucial role in the success of our docking studies. We have also noticed the important role of a local ligand geometry, which seems to be not well discussed in literature. We succeed to improve our results up to the mean RMSD value of 2.15–2.33 Å  dependent on the models of the ligands, if docking these to all available homologous receptors. Overall, for docking of ligands of diverse chemical series we suggest to perform docking of each of the ligands to a set of multiple receptors that are homologous to the target.     

Bioactive Structure of Membrane Lipids and Natural Products Elucidated by a Chemistry‐Based Approach

Determining the bioactive structure of membrane lipids is a new concept, which aims to examine the functions of lipids with respect to their three‐dimensional structures. As lipids are dynamic by nature, their “structure” does not refer solely to a static picture but also to the local and global motions of the lipid molecules. We consider that interactions with lipids, which are completely defined by their structures, are controlled by the chemical, functional, and conformational matching between lipids and between lipid and protein. In this review, we describe recent advances in understanding the bioactive structures of membrane lipids bound to proteins and related molecules, including some of our recent results. By examining recent works on lipid‐raft‐related molecules, lipid–protein interactions, and membrane‐active natural products, we discuss current perspectives on membrane structural biology.     

Virtual target screening: validation using kinase inhibitors

Computational methods involving virtual screening could potentially be employed to discover new biomolecular targets for an individual molecule of interest (MOI). However, existing scoring functions may not accurately differentiate proteins to which the MOI binds from a larger set of macromolecules in a protein structural database. An MOI will most likely have varying degrees of predicted binding affinities to many protein targets. However, correctly interpreting a docking score as a hit for the MOI docked to any individual protein can be problematic. In our method, which we term "Virtual Target Screening (VTS)", a set of small drug-like molecules are docked against each structure in the protein library to produce benchmark statistics. This calibration provides a reference for each protein so that hits can be identified for an MOI. VTS can then be used as tool for: drug repositioning (repurposing), specificity and toxicity testing, identifying potential metabolites, probing protein structures for allosteric sites, and testing focused libraries (collection of MOIs with similar chemotypes) for selectivity. To validate our VTS method, twenty kinase inhibitors were docked to a collection of calibrated protein structures. Here, we report our results where VTS predicted protein kinases as hits in preference to other proteins in our database. Concurrently, a graphical interface for VTS was developed.     

Simulation of conformational changes occurring when a protein interacts with its receptor

In order to simulate the conformational changes occurring when a protein interacts with its receptor, we firstly evaluated the structural differences between the experimental unbound and bound conformations for selected proteins and created theoretical complexes by replacing, in each experimental complex, the protein-bound with the protein-unbound chain. The theoretical models were then subjected to additional modeling refinements to improve the side chain geometry. Comparing the theoretical and experimental complexes in term of structural and energetic factors is resulted that the refined theoretical complexes became more similar to the experimental ones. We applied the same procedure within an homology modeling experiment, using as templates the experimental structures of human interleukin-1beta (IL-1beta) unbound and bound with its receptor, to build models of the homologous proteins from mouse and trout in unbound and bound conformations and to simulate the interaction with the related receptors. Our results suggest that homology modeling techniques are sensitive to differences between bound and unbound conformations, and that modeling with accuracy the side chains in the complex improves the interaction and molecular recognition. Moreover, our refinement procedure could be used in protein-protein interaction studies and, also, applied in conjunction with rigid-body docking when is not available the protein-bound conformation.