Name: investigating protein sequence-structure-dynamics relationships with bio3d-web
Uploaded: 2017-07-16T14:00:00.000+00:00
Duration: 9 min 51 s
Description: Watch this Scientific Journal Video about Investigating Protein Sequence-structure-dynamics Relationships with Bio3D-web at JoVE.com

感谢Guido Scarabelli和Hongyang Li博士在开发过程中进行广泛的测试，以及Bio3D用户社区和卑尔根大学结构生物信息学研讨会参与者的反馈和意见，从而改进了这一应用。

注意:典型的Bio3D-web会话通过五个连续和相关的步骤进行（参见图1的示意图）。每个步骤被​​实现为Web应用程序的连续导航选项卡，即SEARCH，ALIGN，FIT，PCA和eNMA。 结构搜索与选择（SEARCH） <ol><li> 输入结构 <ol><li>获得腺苷酸激酶（Adk）的PDB ID， 例如通过搜索PDB [http://www.rcsb.org/pdb]。或者，获得感兴趣的蛋白质氨基酸序列， 例如 UniProt [http://uniprot.org]。 </li><li>输入Adk的四个字符长的PDB ID（ 例如 1AKE）或将蛋白质序列粘贴到"输入结构或序列"面板的文本框中。 </li></ol></li><li> 点击选择 <ol><li>点击第一个面板中的蓝色"下一步"（击中选择）按钮，或者直接向下滚动到面板B）"点击选择"进一步分析。 </li><li>确保将"包含的结构的总数"滑块设置为其最大值，以将所有结构包括在截止值之上。 </li><li>降低"调整包含BitScore截止值"以包含更远的相关命中，或将其增加排除。 </li></ol></li><li> 可选点击过滤 <ol><li>单击第一个面板中的蓝色"下一步"（命中选择）按钮，或者简单地向下滚动到面板C）"可选过滤相关结构进行进一步分析"。 </li><li>通过检查表的细节， 例如 PDB名称，物种和结合的配体，确保所选择的命中代表相关结构。 </li><li>如果需要，通过单击表的行手动细化所选的结构子集。 注意:以蓝色突出显示的行描述了选择用于后续选项卡进一步分析的PDB ID。 </li></ol></li></ol> 2。多序列比对分析（ALIGN） <ol><li>单击ALIGN选项卡以从SEARCH选项卡执行所选结构的序列对齐。 </li><li> 对齐摘要 <ol><li>在面板A中查看对齐摘要）"对齐摘要"。确保感兴趣的区域是对齐的，并且不被一个或多个结构中的间隙掩蔽。 </li><li>如果需要，请切换"显示对齐编辑选项"并删除不需要的PDB ID， 例如缺少残留的PDB。 </li></ol></li><li> 序列比对分析 <ol><li>点击蓝色的"下一步"（分析）按钮，对收集的结构进行基于序列的聚类分析。 </li><li>选择绘图选项树状图。将集群调整为K组滑块以将结构分成k组。 </li><li>如果需要，可以通过切换"更多聚类和输出选项"复选框来更改聚类方法。 </li></oL&gt; </li><li> 残留保护分析 <ol><li>点击蓝色的"下一步"（保存）按钮计算列列残基守恒。 </li><li>选择对齐结构集合，以生成每个对齐位置处的残留守恒图。 </li><li>选择与PFAM种子对齐一致的结构，以显示关于包含家族代表成员的相关PFAM种子对齐计算的保守性。 </li></ol></li><li> 序列对齐显示 <ol><li>单击蓝色的"下一步"（对齐）按钮显示与浏览器中对齐可视化工具的完整序列对齐。 </li></ol></li></ol> 3.结构配套与分析（FIT） <ol><li>通过输入FIT选项卡执行结构叠加。 </li><li> 结构叠加 <ol><li>切换"显示PDB"复选框可视化对齐的蛋白质n结构浏览器。 </li><li>通过视觉检查确保蛋白质结构与相应的和相关的区域相叠加。单击并将鼠标拖动到要旋转的结构上，然后滚动以进行缩放。 </li><li>通过点击"颜色选项"来调整结构的着色。着色选项包括对齐位置，每位置的结构变异性，RMSD簇组，序列簇组，对准区域和二级结构。 </li><li>将叠加结构作为常规PDB文件或作为单个PyMOL会话文件下载，以便在专门的分子观察程序中进行可视化。 </li></ol></li><li> 结构分析 <ol><li>点击蓝色的"下一步"（分析）按钮，对采集的PDB结构进行基于结构的聚类。 </li><li>在"绘图选项"下拉菜单中切换RMSD热图。 </li><li>调整聚类选项，包括聚类方法本身，通过切换"更多聚类和输出选项"复选框。 注意:成对RMSD数据也可以被视为树形图，直方图或热图。 </li></ol></li><li> 残留波动 <ol><li>点击蓝色的"下一步"（RMSF）按钮查看每个残差的结构变异性（显示为RMSF图），其主要二级结构元素显示在x轴的边缘区域。 </li><li>切换显示B因子复选框以将参考结构的晶体B因子覆盖到RMSF图上。 </li></ol></li></ol>主成分分析（PCA） <ol><li>通过输入"PCA"选项卡执行主成分分析。 </li><li> 可视化主要组件 <ol><li>切换"显示PC轨迹"复选框，以使用浏览器可视化工具可视化PC所描述的动作。 </li><li>确保"打印机cipal组件1"从第一个下拉菜单中选择。 </li><li>为了可视化其他PC所描述的动作，请从"选择主要组件"下拉菜单中选择所需的PC。 </li><li>从"颜色选项"下拉菜单中更改轨迹的着色。 </li><li>从"颜色选项"中选择"每个位置的变量"，通过位移大小来选择颜色。 </li><li>单击"主组件可视化"面板中的"下载PDB轨迹"按钮，以获得由PC描述的运动的轨迹。 </li><li>点击"下载PyMOL"会话文件按钮，生成一个PyMOL会话文件，给出动作为一个向量域。 </li></ol></li><li> 一致性分析 <ol><li>通过点击蓝色的"下一步"（Plot）按钮将各个结构投影到两个选定的PC上。 </li><li>确保"X轴上的PC"设置为1，"PC on Y轴"到2.将结构投影到其他PC上，相应调整PC编号。 </li><li>选择"通过PC子空间集群"，通过基于PC的聚类对图中的结构进行着色; "RMSD"通过"基于RMSD"进行聚类;和"序列"按照基于序列的聚类进行着色。 </li><li>点击绘图中的任何一个点来标记结构。或者，突出显示图表下方的"PCA构图图"注释中的一个或多个结构。 </li><li>将子空间滑块中的PC滑动到包含更多/更少的PC用于聚类算法。 </li></ol></li><li> 剩余贡献 <ol><li>通过点击蓝色的"下一步"（残留贡献）按钮计算残留物对各个PC的贡献。 </li><li>通过在"选择主体组件"文本框中添加PC编号，为其他PC添加贡献。 </li><li>切换"传播李nes"复选框可以避免将残差贡献绘制在彼此之间。 </li><li>关闭"多谱图"复选框以在不同的图中绘制残差贡献。 </li><li>切换"显示RMSF"以包括RMSF值（来自FIT选项卡）。 </li></ol></li></ol>正常模式分析（eNMA） <ol><li>单击eNMA选项卡以启动正常模式（NM）计算。 </li><li> 过滤器结构 <ol><li>通过降低或增加结构包含/排除的"截止"来调整结构数量。 </li><li>点击绿色的"Run Ensemble NMA"开始NMA计算。 </li></ol></li><li> 正常模式可视化 <ol><li>向下滚动到eNMA选项卡（正常模式可视化）的第二个面板，用于NM的可视化。 注意:默认情况下，视觉上显示与PC-1重叠（相似度）最高的NM化窗口</li><li>为了可视化其他NM或其他PDB结构描述的动作，请分别从"选择模式"和"显示结构的 NM "下拉菜单中选择所需的NM和结构。 </li></ol></li><li> 残留波动 <ol><li>点击蓝色的"下一步"（波动）按钮来计算eNMA选择的结构的残留波动。 </li><li>切换"通过RMSD集群"，以通过基于RMSD的聚类对波动分布进行着色。 </li><li>通过RMSIP切换"Cluster"，通过基于RMSIP的聚类来对波动特征进行着色。 </li><li>切换"扩展行"复选框，以便将分组的波动曲线彼此分开。 </li></ol></li><li> 比较NMA和PCA <ol><li>点击蓝色的"下一步"（PCA-vs-NMA）按钮来计算各个NM和PC之间的相似度。 </li><li>选择PDB ID从"比较结构的NM"下拉菜单中计算出这个结构的NM与PCA选项卡中计算的PC之间的相似度。 </li></ol></li><li> 重叠分析 <ol><li>点击蓝色的"下一步"（重叠分析）按钮，计算计算的NM与两个选定结构之间的结构差向量之间的重叠。 </li><li>从"结构的比较NM"下拉菜单中选择一个"引用"PDB ID，或者在结构表中选择与参考PDB成对比较的一个或多个PDB ID。 </li></ol></li><li> 聚类分析 <ol><li>单击蓝色的"下一步"（聚类）按钮，根据成对的NM相似度（RMSIP）进行结构聚类。 </li></ol></li></ol>

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作者宣称他们没有竞争的经济利益。

Bio3D-web可用于交互式探索并绘制来自可用晶体结构的蛋白质的结构，动态和功能状态。此外，基于NMA和PCA的聚类结果以及注释和基于序列的分析可以特别适用于选择代表性结构以进行更耗时的分析，例如整体小分子对接或分子动力学模拟。因此，Bio3D-web通过减少所需的技术专长水平，为更广泛的研究人员提供先进的结构生物信息学分析。 Bio3D-web的当前设计强调简单易懂，包含完整的独立Bio3D包中可用的许多分析方法。在许多情况下，设想研究人员将使用Bio3D-web来了解其蛋白质家族或感兴趣的超家族的总体趋势，然后可以提供更专业的分析。 Bio3D-web是重新设计用于快速探索生物分子结构数据集并充当假设生成工具。我们鼓励用户通过在可重复报告中提供示例Bio3D代码来进一步探索其数据，该代码也存储所有查询详细信息和分析结果。 在上述代表性的示例协议中，我们展示了Bio3D-web揭示Adk功能构象转换的结构特征的能力。 Bio3D-web的其他应用包括用户上传的PDB结构的结构和动力学分析。例如，用户可以上传新的结构或确实的蛋白质序列进行分析。前面提到的分析步骤，特别是eNMA步骤，可以揭示蛋白质运动的局部和全球趋势，集体运动具有功能意义。与apo结构的比较也可以揭示未绑定到构象转换的特征。应用的其他示例在线提供了一系列不同的蛋白质家族。 尽管所有蛋白质都是灵活和动态的实体，但并非所有蛋白质都具有在不同状态（ 例如活性和非活性状态）范围内可用的原子分辨率结构。因此，我们对蛋白质结构空间的观点是有限的，因此从诸如Bio3D-web的工具获得的洞察力对于某些蛋白质也是有限的。然而，随着目前的技术进步和结构基因组学的新举措，这里提出的协议将越来越成为了解重要的结构 - 功能关系的重要途径。在分析更远的相关蛋白质时特别重要的关键步骤是ALIGN标签中对齐错误的潜在出现。当序列相似性下降到30％以下时，不可避免地发生对准误差，并且在这种情况下用户必须双重检查并校正序列比对在ALIGN标签中。对齐错误可能导致FIT选项卡中不正确的叠加结构，并掩盖后续PCA的最相关的构象变体。此外，用户应该知道所选PDB结构中缺少的残留物，如在当前实施方案中，PCA只能对其中所有结构具有相应碳原子被解离的蛋白质残基进行。因此，如果选择的PDB对于蛋白质的特定区域具有未解决的残基，则该区域将从PCA中省略。 Bio3D-web目前仅限于单链PDB结构的分析。因此，使用当前的方案不能探索在四级水平发生的功能运动。尽管我们正在开发新的算法来将这种分析纳入Bio3D-web，但目前唯一的选择是通过传统的Bio3D使用。 Bio3D-web是唯一的在线应用程序离子，可以查询和识别结构集，解释其序列模式和结构变异性，并从其结构可塑性的分析和预测中提取机械信息。各种分子可视化工具和在线服务器使研究人员能够探索和分析各种生物分子结构。然而，用于分析大型异质蛋白家族的序列，结构和动力学的现有工具通常需要大量的计算专业知识，并且通常只有具有相关编程技能的用户才能访问。例如，Bio3D包需要R 8，PRODY需要Python和Maven需要Matlab的知识9,10。相反，Bio3D-web不需要编程知识，从而增加了可访问性，并减少了执行高级比较序列，结构和染色的进入障碍动态分析。此外，Bio3D-Web服务还包含了有效分析所需的分子结构的准备，策划，注释和清理。另外，通过我们的服务器实例，可以减轻对能力计算资源进行分析的限制，可以对任何现代Web浏览器启动和控制的许多结构进行大规模分析。 Bio3D-Web的开放性开发正在进行中（请参阅https://bitbucket.org/Grantlab/bio3d）。我们继续添加新的分析功能并改进现有的方法。未来的发展将侧重于增加基于距离矩阵的PCA和扭转PCA，更广泛的序列保守方法，包括系统发育成分，整体结合位点识别以及蛋白质家族动态网络分析的新方法。在这方面，当前的Web应用程序代表了起始点通过在用户定义的实验结构集上实现可重复和可共享的步骤，可以为许多其他协作结构生物信息学分析工作流程。我们还计划从PDB结构的不对称单位除个体和多个链之外重建生物单位坐标集的未来支持。其他功能将包括增强协同工作空间的保存和加载以及撤消可能性。 Bio3D-Web是生物分子结构数据交互式分析的在线应用。 Bio3D-web可在任何现代Web浏览器上运行，并提供以下功能:（1）将相关蛋白质结构集合识别为用户指定的相似阈值; （2）它们的多重对齐和结构叠加; （3）序列和结构守恒分析; （4）构象间关系映射与主成分分析，（5）通过集合比较预测的内部动力学mal模式分析。该综合功能为蛋白质家族和超家族中序列结构 - 动态关系的调查提供了完整的工作流程。除了方便易用的动态界面，用于探索参数和方法选择的影响，Bio3D-web还记录了用户会话的完整用户输入和后续图形结果。这允许用户轻松共享和重现创建其结果的分析步骤序列.Bio3D-Web完全以R语言实现，并基于Bio3D和Shiny R软件包。它可以从我们的在线服务器运行，也可以在任何运行R的计算机上本地运行。这包括本地服务器安装，以提供定制的多用户实例，可访问优先结构数据集，如制药行业常见的数据集。完整的源代码和广泛的文档是根据GPL-3开源许可证提供的:http://thegrantlab.org/ bio3d / webapps中

蛋白质数据库（PDB）现在包含超过120,000个蛋白质结构 - 其中许多蛋白质家族具有相同的蛋白质家族，但在不同的实验条件下被解析。这些多重结构代表了理解蛋白质形式和功能复杂性的宝贵资源。例如，这些结构合奏的严格的比较可以揭示重要的分子机制1，2，3，并通知上涉及过程，包括配体结合，酶催化和双分子识别4，5，6，7构象动力学。通常可以从蛋白质家族的序列，结构和动力学的详细的大规模分析中获得新的见解。然而，这通常需要相当大的生物ormatics和计算机程序设计专业知识，以及对正在研究的蛋白质系统的熟悉程度。例如，软件包如Bio3D，PRODY和Maven需要在R，蟒和Matlab，分别为8，9，10编程。相反，对于结构灵活性分析的在线工具一般仅限于个别结构11的调查，12。这方面的一个例外是最近开发的WebNM @服务器，其允许比较从几个预对齐用户指定结构13的正常模式分析（NMA）获得的灵活性模式。然而，该服务器缺少自动化程序来识别用于比较的结构，它们的对准或超出NMA的进一步分析。另一个最近的贡献是在线PDBFlex数据库，其中提供了c共享95％或更高序列同一性的PDB结构的有限分析14 。然而，目前尚不能分析更多样化的结构集。 我们以前介绍过Bio3D-web - 一个易于使用的Web应用程序，用于分析蛋白质序列结构 - 动态关系15 。 Bio3D-web是提供易于使用的集成功能，用于在线大型同源结构集的识别，比较和详细分析。在这里，我们提出了使用Bio3D-web在线调查蛋白质序列结构 - 动力学关系的详细协议。 Bio3D-web提供了多种功能，支持图1所示的五个主要步骤的数据分析，并在下面详细讨论。这些步骤构成了从查询序列或结构输入，跨序列结构动态分析的多个级别到总结的工作流程y报告生成。通过广泛的浏览器可视化和绘图设备，以及通过以常用格式下载结果文件，可以立即获得结果。除了方便易用的动态界面，用于探索参数和方法选择的影响，Bio3D-web还将用户会话的完整用户输入和后续图形结果记录为PDF，DOC和HTML格式的可共享的可重复报告。用户会话可以在以后的时间保存和重新加载，并在用户的本地计算机上通过Bio3D R软件包下载并进一步解释完整的结果。 Bio3D幅材由Bio3Dř包生物分子的结构，序列和分子模拟数据8，16的分析供电。特别是用于刚性核识别的Bio3D算法 8 ，叠加，主成分分析（PCA） 8 ，集合正常模式分析（eNMA） 16构成了应用的基础。我们还使用依赖于pHMMER 17的 Bio3D方案来鉴定相关的蛋白质结构，并且使用MUSCLE 18进行多重序列比对。结构和序列注释通过来自RCSB PDB 19和PFAM数据库20的 Bio3D实用程序得到。 Bio3D-web可以从我们的在线服务器运行，也可以在任何运行R的计算机上安装。Bio3D-web对所有用户都是开放的，根据GPL-3开源许可证免费提供:http:// thegrantlab。组织/ bio3d / webapps中

<table><tbody><tr><td>Bio3D-web</td><td></td><td></td><td></td></tr><tr><td>Web-site</td><td>http://thegrantlab.org/bio3d-web/</td><td></td><td></td></tr><tr><td>Requirements</td><td>Web browser</td><td></td><td></td></tr></tbody></table>

investigating protein sequence-structure-dynamics relationships with bio3d-web

我们展示了Bio3D-Web在生物分子结构数据交互式分析中的应用。 Bio3D-Web应用程序提供在线功能:（1）将相关蛋白质结构集合识别为用户指定的相似阈值; （2）它们的多重对齐和结构叠加; （3）序列和结构守恒分析; （4）主成分分析的构象间关系映射，（5）通过整体正态分析比较预测的内部动力学。该集成功能提供了一个完整的在线工作流程，用于调查蛋白质家族和超家族中的序列结构 - 动态关系。

腺苷酸激酶（Adk）是普遍存在的酶，其功能是维持许多细胞过程所必需的细胞质核苷酸之间的平衡。 Adk通过催化磷酰基从ATP向AMP的可逆转移而起作用。该反应是伴随着充分研究的速率限制的构象转变3,21。在这里，我们使用Bio3D-web分析目前可用的所有Adk结构，以揭示这些基本过渡的详细功能和机制原理。 我们可以通过输入任何已知的Adk结构的RCSB PDB代码开始对Adk的Bio3D-web分析。例如，在"搜索"选项卡的面板A中输入PDB ID 1AKE会返回167个序列相似的结构，从中自动选择顶部26进行进一步分析（见图B）。注释存在在图C中表示这些选定的结构全部来自大肠杆菌，通过在一定范围的空间组中的x射线衍射来求解;分辨率范围为1.63至2.8Å，并与一系列不同的配体（不含配体，AMP，ADP，MG和抑制剂AP5）共结晶。请注意，通过单击面板C中的"显示/隐藏列"选项可以显示附加注释详细信息。 进入ALIGN选项卡时执行多序列对齐。 ALIGN选项卡的第一个面板显示对齐的摘要，提供有关序列行数（相当于PDB结构数）的详细信息以及位置数（ 即对齐列）。这包括间隙数和非间隙数列的规格。第一行右侧的图提供了序列比对的示意图。这里e灰色区域表示非间隙位置，而对齐的白色区域对应于间隙。序列保守性的表示在与指示保守位置的红色区域的对准之上显示，并且白色表示较不守恒。注意，该图中的序列是基于它们在左侧的聚类树形图提供的相似性来排序的。该选项卡的第二个面板进一步促进了所选PDB的聚类，这些PDB基于它们的成对序列相似性，可以将其视为树形图或热图。默认情况下，显示了表示簇的布置的树形图（或树形图）。树形图的y轴表示簇之间的距离（以序列同一性计）。 进入FIT标签后，会自动执行结构叠加。叠加结构，在面板A中交互显示，indic考虑到相对刚性的核心区域的存在（包括残留1-29,68-117和161-214;有关详细信息，请参阅FIT选项卡底部的"可选核心和RMSD详细信息"面板）。另外两个可变的核苷酸结合区（残基30-67和118-167）也清晰可见（ 图2 ）。基于RMSD的聚类将这些结构分成两个不同的构象。 单击PCA选项卡更清楚地显示了这些结构之间的关系，这些位置在有效结合相关结构中的结合核苷酸物种（ 图2B和2C ）的位置。大多数结构是"封闭"形式（ 图2C中的蓝色）并且与结合的配体或抑制剂相关联。相比之下，更多的"开放"构型是核苷酸和不含抑制剂的。这是一致的对Adk结构和动力学的广泛研究表明，这些区域的开放构型对于核苷酸结合是需要的，并且是有效的磷酰基转移和抑制有害水解事件的封闭构象。值得注意的是，单个PC捕获该Adk结构集合中总平均位移的97％，并且提供了开放到闭合过渡的明确和引人注目的描述以及对该功能位移的各个残差贡献（应用的面板C）和图2 ）。 访问NMA选项卡并增加考虑计算的结构数量（通过减少过滤类似结构的截止值）表明，与封闭形式结构相比，开放状态结构显示增强的局部和全局动力学（ 图2D和应用程序面板C） 。比较PCA和NMA的结果单个结构（图D）表示所有开放式结构的第一种模式与PC1显示相对较高的重叠（平均值为0.37±0.04）。相比之下，封闭形式的结构显示较低的值（平均值为0.30±0.01）。开放式结构的RMSIP值（0.62±0.003）也高于封闭结构（0.56±0.008）。此外，重叠分析表明，开放状态的第一种模式与描述开放和关闭状态差异的构象变化（图E）非常一致。基于RMSIP值的聚类再次显示了打开和关闭状态结构的一致分区（图F）。 这些结果总体上表明Adk存在两个主要的不同构象状态。这两个不同之处在于显示出不同柔性的两个核苷酸结合位点区域的低频位移核苷酸结合后的遗传。 <img alt="图1" src="/files/ftp_upload/55640/55640fig1.jpg" /> 图1: 具有PCA和NMA选项卡屏幕截图的Bio3D- Web概述。 Bio3D-web将用户提供的蛋白质结构或序列作为SEARCH选项卡（ 1 ）中的输入。服务器提供相关结构的列表，可以选择进行进一步分析。 （ 2 ）ALIGN标签提供了在SEARCH选项卡中选择的结构的序列比对和分析。 （ 3 ）在FIT标签中，所有的结构与传统的成对结构分析的结果一起叠加和可视化。 （ 4 ）结构集合的主成分分析在PCA选项卡中进行，以表征构象间关系。 （ 5 ）每个结构的正常模式分析可以在eNMA标签中进行探索可用结构状态的动态趋势。 <a href="https://ecsource-jove-com.bdigitaluss.remotexs.co/files/ftp_upload/55640/55640fig1large.jpg" target="_blank">请点击此处查看此图的较大版本。</a> <img alt="图2" src="/files/ftp_upload/55640/55640fig2.jpg" /> 图2: 腺苷酸激酶的Bio3D-web分析结果。 （ A ）叠加在确定的不变核上的腺苷酸激酶的可用PDB结构。结构根据FIT选项卡中提供的基于RMSD的聚类进行着色。 （ B ）主成分的可视化可从PCA选项卡中获取，以表征数据集中的主要构象变化。这里，对应于第一主成分的轨迹以管表示的方式示出，表示蛋白质的大规模闭合运动。 （ C ）结构在形成图中的两个第一主要成分上，显示构象变异性的低维表示。每个点（或结构）根据用户指定的标准进行着色，在这种情况下是基于PCA的聚类结果。 （ D ）eNMA标签中的正常模式分析表明，与封闭形式（蓝色）结构相比，打开状态（红色）中结构的局部和全局动力学增强。 <a href="https://ecsource-jove-com.bdigitaluss.remotexs.co/files/ftp_upload/55640/55640fig2large.jpg" target="_blank">请点击此处查看此图的较大版本。</a>

Watch this Scientific Journal Video about Investigating Protein Sequence-structure-dynamics Relationships with Bio3D-web at JoVE.com

Investigating Protein Sequence-structure-dynamics Relationships with Bio3D-web

介绍了使用Bio3D-web在线调查蛋白质序列结构 - 动力学关系的协议。

研究与Bio3D-web的蛋白质序列 - 结构 - 动力学关系

We demonstrate the usage of Bio3D-web for the interactive analysis of biomolecular structure data. The Bio3D-web application provides online functionality ...

investigating-protein-sequence-structure-dynamics-relationships-with

Universidad San Sebastian

Research

JoVE Journal

Biochemistry

15.3K 次观看.  University of Michigan Medical School. 介绍了使用Bio3D-web在线调查蛋白质序列结构 - 动力学关系的协议。 

视频: Investigating Protein Sequence-structure-dynamics Relationships with Bio3D-web

Assessment of Immunologically Relevant Dynamic Tertiary Structural Features of the HIV-1 V3 Loop Crown R2 Sequence by ab initio Folding

The antigenic diversity of HIV-1 has long been an obstacle to vaccine design, and this variability is especially pronounced in the V3 loop of the virus' surface envelope glycoprotein. We previously proposed that the crown of the V3 loop, although dynamic and sequence variable, is constrained throughout the population of HIV-1 viruses to an immunologically relevant &beta;-hairpin tertiary structure. Importantly, there are thousands of different V3 loop crown sequences in circulating HIV-1 viruses, making 3D structural characterization of trends across the diversity of viruses difficult or impossible by crystallography or NMR. Our previous successful studies with folding of the V3 crown1, 2 used the ab initio algorithm 3 accessible in the ICM-Pro molecular modeling software package (Molsoft LLC, La Jolla, CA) and suggested that the crown of the V3 loop, specifically from positions 10 to 22, benefits sufficiently from the flexibility and length of its flanking stems to behave to a large degree as if it were an unconstrained peptide freely folding in solution. As such, rapid ab initio folding of just this portion of the V3 loop of any individual strain of the 60,000+ circulating HIV-1 strains can be informative. Here, we folded the V3 loop of the R2 strain to gain insight into the structural basis of its unique properties. R2 bears a rare V3 loop sequence thought to be responsible for the exquisite sensitivity of this strain to neutralization by patient sera and monoclonal antibodies4, 5. The strain mediates CD4-independent infection and appears to elicit broadly neutralizing antibodies. We demonstrate how evaluation of the results of the folding can be informative for associating observed structures in the folding with the immunological activities observed for R2.

Assessment of Immunologically Relevant Dynamic Tertiary Structural Features of the HIV-1 V3 Loop Crown R2 Sequence by ab initio Folding

The crown region of different V3 loop sequences of the surface envelope glycoprotein (gp120) of HIV-1 can be structurally characterized in many cases by in silico folding of positions 10 to 22 of the loop using a state-of-the-art ab initio folding algorithm. Here we demonstrate the folding and evaluation of this region of the V3 loop from the R2 strain of HIV-1, a uniquely neutralization sensitive strain with puzzling functional properties.

免疫相关动态三级的HIV - 1 V3环冠R2的序列结构特点的评估从头折叠

The antigenic diversity of HIV-1 has long been an obstacle to vaccine design, and this variability is especially pronounced in the V3 loop of the virus' ...

科研

免疫与感染

Optimization of Synthetic Proteins: Identification of Interpositional Dependencies Indicating Structurally and/or Functionally Linked Residues

Protein alignments are commonly used to evaluate the similarity of protein residues, and the derived consensus sequence used for identifying functional units (e.g., domains). Traditional consensus-building models fail to account for interpositional dependencies &#8211; functionally required covariation of residues that tend to appear simultaneously throughout evolution and across the phylogentic tree. These relationships can reveal important clues about the processes of protein folding, thermostability, and the formation of functional sites, which in turn can be used to inform the engineering of synthetic proteins. Unfortunately, these relationships essentially form sub-motifs which cannot be predicted by simple &#8220;majority rule&#8221; or even HMM-based consensus models, and the result can be a biologically invalid &#8220;consensus&#8221; which is not only never seen in nature but is less viable than any extant protein. We have developed a visual analytics tool, StickWRLD, which creates an interactive 3D representation of a protein alignment and clearly displays covarying residues. The user has the ability to pan and zoom, as well as dynamically change the statistical threshold underlying the identification of covariants. StickWRLD has previously been successfully used to identify functionally-required covarying residues in proteins such as Adenylate Kinase and in DNA sequences such as endonuclease target sites.

Synthetic protein sequences based on consensus motifs typically ignore co-evolving residues, that imply interpositional dependencies (IPDs). IPDs can be essential to activity, and designs that disregard them may result in suboptimal results. This protocol uses StickWRLD to identify IPDs and help inform rational protein design, resulting in more efficient results.

优化合成蛋白质:Interpositional依赖性的鉴定指示在结构和/或功能性连接的残留

Protein alignments are commonly used to evaluate the similarity of protein residues, and the derived consensus sequence used for identifying functional ...

化学

Analyzing Dynamic Protein Complexes Assembled On and Released From Biolayer Interferometry Biosensor Using Mass Spectrometry and Electron Microscopy

In vivo, proteins are often part of large macromolecular complexes where binding specificity and dynamics ultimately dictate functional outputs. In this work, the pre-endosomal anthrax toxin is assembled and transitioned into the endosomal complex. First, the N-terminal domain of a cysteine mutant lethal factor (LFN) is attached to a biolayer interferometry (BLI) biosensor through disulfide coupling in an optimal orientation, allowing protective antigen (PA) prepore to bind (Kd 1 nM). The optimally oriented LFN-PAprepore complex then binds to soluble capillary morphogenic gene-2 (CMG2) cell surface receptor (Kd 170 pM), resulting in a representative anthrax pre-endosomal complex, stable at pH 7.5. This assembled complex is then subjected to acidification (pH 5.0) representative of the late endosome environment to transition the PAprepore into the membrane inserted pore state. This PApore state results in a weakened binding between the CMG2 receptor and the LFN-PApore and a substantial dissociation of CMG2 from the transition pore. The thio-attachment of LFN to the biosensor surface is easily reversed by dithiothreitol. Reduction on the BLI biosensor surface releases the LFN-PAprepore-CMG2 ternary complex or the acid transitioned LFN-PApore complexes into microliter volumes. Released complexes are then visualized and identified using electron microscopy and mass spectrometry. These experiments demonstrate how to monitor the kinetic assembly/disassembly of specific protein complexes using label-free BLI methodologies and evaluate the structure and identity of these BLI assembled complexes by electron microscopy and mass spectrometry, respectively, using easy-to-replicate sequential procedures.

Here we present a protocol to monitor the assembly and disassembly of the anthrax toxin using biolayer interferometry (BLI). Following assembly/disassembly on the biosensor surface, the large protein complexes are released from the surface for visualization and identification of components of the complexes using electron microscopy and mass spectrometry, respectively.

用质谱和电镜分析 Biolayer 干涉传感器上的动态蛋白复合物的组装和释放

In vivo, proteins are often part of large macromolecular complexes where binding specificity and dynamics ultimately dictate functional outputs. In this ...

生物化学

Analyzing Protein Architectures and Protein-Ligand Complexes by Integrative Structural Mass Spectrometry

Proteins are an important class of biological macromolecules that play many key roles in cellular functions including gene expression, catalyzing metabolic reactions, DNA repair and replication. Therefore, a detailed understanding of these processes provides critical information on how cells function. Integrative structural MS methods offer structural and dynamical information on protein complex assembly, complex connectivity, subunit stoichiometry, protein oligomerization and ligand binding. Recent advances in integrative structural MS have allowed for the characterization of challenging biological systems including large DNA binding proteins and membrane proteins. This protocol describes how to integrate diverse MS data such as native MS and ion mobility-mass spectrometry (IM-MS) with molecular dynamics simulations to gain insights into a helicase-nuclease DNA repair protein complex. The resulting approach provides a framework for detailed studies of ligand binding to other protein complexes involved in important biological processes.

Mass spectrometry (MS) has emerged as an important tool for the investigation of structure and dynamics of macromolecular assemblies. Here, we integrate MS-based approaches to interrogate protein complex formation and ligand binding.

综合结构质谱分析蛋白质结构和蛋白质配体配合物

Proteins are an important class of biological macromolecules that play many key roles in cellular functions including gene expression, catalyzing ...

Modeling an Enzyme Active Site using Molecular Visualization Freeware

Biomolecular visualization skills are paramount to understanding key concepts in the biological sciences, such as structure-function relationships and molecular interactions. Various programs allow a learner to manipulate 3D structures, and biomolecular modeling promotes active learning, builds computational skills, and bridges the gap between two dimensional textbook images and the three dimensions of life. A critical skill in this area is to model a protein active site, displaying parts of the macromolecule that can interact with a small molecule, or ligand, in a way that shows binding interactions. In this protocol, we describe this process using four freely available macromolecular modeling programs: iCn3D, Jmol/JSmol, PyMOL, and UCSF ChimeraX. This guide is intended for students seeking to learn the basics of a specific program, as well as instructors incorporating biomolecular modeling into their curriculum. The protocol enables the user to model an active site using a specific visualization program, or to sample several of the free programs available. The model chosen for this protocol is human glucokinase, an isoform of the enzyme hexokinase, which catalyzes the first step of glycolysis. The enzyme is bound to one of its substrates, as well as a non-reactive substrate analog, which allows the user to analyze interactions in the catalytic complex.

A key skill in biomolecular modeling is displaying and annotating active sites in proteins. This technique is demonstrated using four popular free programs for macromolecular visualization: iCn3D, Jmol, PyMOL, and UCSF ChimeraX.

使用分子可视化免费软件对酶活性位点进行建模

Biomolecular visualization skills are paramount to understanding key concepts in the biological sciences, such as structure-function relationships and ...

<meta charset="utf8"></head><body>预测蛋白质-蛋白质结合界面的氨基酸偏好

Computational Prediction of Amino Acid Preferences of Potentially Multispecific Peptide-Binding Domains Involved in Protein-Protein Interactions

Many protein-protein interactions involve the binding of short protein segments to peptide-binding domains. Usually, such interactions require the recognition of linear motifs with variable conservation. The combination of highly conserved and more variable regions in the same ligands often contributes to the multispecificity of binding, a common property of enzymes and cell signaling proteins. Characterization of amino acid preferences of peptide-binding domains is important for the design of mediators of protein-protein interactions (PPIs). Computational methods are an efficient alternative to the often costly and cumbersome experimental techniques, enabling the design of potential mediators that can be later validated in downstream experiments. Here, we described a methodology using the Pepspec application of the Rosetta molecular modeling package to predict the amino acid preferences of peptide-binding domains. This methodology is useful when the structure of the receptor protein and the nature of the peptide ligand are both known or can be inferred. The methodology starts with a well-characterized anchor from the ligand, which is extended by randomly adding amino acid residues. The binding affinity of peptides generated this way is then evaluated by flexible-backbone peptide docking in order to select the peptides with the best predicted binding scores. These peptides are then used to calculate amino acid preferences and to optionally compute a position-weight matrix (PWM) that can be used in further studies. To illustrate the application of this methodology, we used the interaction between subunits of human interferon regulatory factor 5 (IRF5), previously known to be multispecific but globally guided by a short conserved motif called pLxIS. The estimated amino acid preferences were consistent with previous knowledge about the IRF5 binding surface. Positions occupied by phosphorylatable serine residues exhibited a high frequency of aspartate and glutamate, likely because their negatively charged side chains are similar to phosphoserine.

<meta charset="utf8"></head><body>作者聚焦:一种破译多特异性蛋白质-蛋白质相互作用中氨基酸偏好的计算方法

We describe a methodology based on sequence diversification to estimate the amino acid preferences of multispecific binding sites in protein-protein interactions (PPIs). In this strategy, thousands of potential peptide ligands are generated and screened in silico, thus overcoming some limitations of available experimental methods.

参与蛋白质-蛋白质相互作用的潜在多特异性肽结合结构域的氨基酸偏好的计算预测

Many protein-protein interactions involve the binding of short protein segments to peptide-binding domains. Usually, such interactions require the ...

A Protocol for Computer-Based Protein Structure and Function Prediction

Genome sequencing projects have ciphered millions of protein sequence, which require knowledge of their structure and function to improve the understanding of their biological role. Although experimental methods can provide detailed information for a small fraction of these proteins, computational modeling is needed for the majority of protein molecules which are experimentally uncharacterized. The I-TASSER server is an on-line workbench for high-resolution modeling of protein structure and function. Given a protein sequence, a typical output from the I-TASSER server includes secondary structure prediction, predicted solvent accessibility of each residue, homologous template proteins detected by threading and structure alignments, up to five full-length tertiary structural models, and structure-based functional annotations for enzyme classification, Gene Ontology terms and protein-ligand binding sites. All the predictions are tagged with a confidence score which tells how accurate the predictions are without knowing the experimental data. To facilitate the special requests of end users, the server provides channels to accept user-specified inter-residue distance and contact maps to interactively change the I-TASSER modeling; it also allows users to specify any proteins as template, or to exclude any template proteins during the structure assembly simulations. The structural information could be collected by the users based on experimental evidences or biological insights with the purpose of improving the quality of I-TASSER predictions. The server was evaluated as the best programs for protein structure and function predictions in the recent community-wide CASP experiments. There are currently &gt;20,000 registered scientists from over 100 countries who are using the on-line I-TASSER server.

Guidelines for computer based structural and functional characterization of protein using the I-TASSER pipeline is described. Starting from query protein sequence, 3D models are generated using multiple threading alignments and iterative structural assembly simulations. Functional inferences are thereafter drawn based on matches to proteins with known structure and functions.

基于计算机的蛋白质结构与功能预测议定书

Genome sequencing projects have ciphered millions of protein sequence, which require knowledge of their structure and function to improve the ...

生物学

Analyzing and Building Nucleic Acid Structures with 3DNA

The 3DNA software package is a popular and versatile bioinformatics tool with capabilities to analyze, construct, and visualize three-dimensional nucleic acid structures. This article presents detailed protocols for a subset of new and popular features available in 3DNA, applicable to both individual structures and ensembles of related structures. Protocol 1 lists the set of instructions needed to download and install the software. This is followed, in Protocol 2, by the analysis of a nucleic acid structure, including the assignment of base pairs and the determination of rigid-body parameters that describe the structure and, in Protocol 3, by a description of the reconstruction of an atomic model of a structure from its rigid-body parameters. The most recent version of 3DNA, version 2.1, has new features for the analysis and manipulation of ensembles of structures, such as those deduced from nuclear magnetic resonance (NMR) measurements and molecular dynamic (MD) simulations; these features are presented in Protocols 4 and 5. In addition to the 3DNA stand-alone software package, the w3DNA web server, located at <a href="http://w3dna.rutgers.edu" target="_blank">http://w3dna.rutgers.edu</a>, provides a user-friendly interface to selected features of the software. Protocol 6 demonstrates a novel feature of the site for building models of long DNA molecules decorated with bound proteins at user-specified locations.

The 3DNA software package is a popular and versatile bioinformatics tool with capabilities to analyze, construct, and visualize three-dimensional nucleic acid structures. This article presents detailed protocols for a subset of new and popular features available in 3DNA, applicable to both individual structures and ensembles of related structures.

核酸结构分析及建设3DNA

The 3DNA software package is a popular and versatile bioinformatics tool with capabilities to analyze, construct, and visualize three-dimensional nucleic ...

研究与Bio3D-web的蛋白质序列 - 结构 - 动力学关系

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免疫相关动态三级的HIV - 1 V3环冠R2的序列结构特点的评估从头折叠

优化合成蛋白质:Interpositional依赖性的鉴定指示在结构和/或功能性连接的残留

用质谱和电镜分析 Biolayer 干涉传感器上的动态蛋白复合物的组装和释放

综合结构质谱分析蛋白质结构和蛋白质配体配合物

使用分子可视化免费软件对酶活性位点进行建模

参与蛋白质-蛋白质相互作用的潜在多特异性肽结合结构域的氨基酸偏好的计算预测

参与蛋白质-蛋白质相互作用的潜在多特异性肽结合结构域的氨基酸偏好的计算预测

参与蛋白质-蛋白质相互作用的潜在多特异性肽结合结构域的氨基酸偏好的计算预测

基于计算机的蛋白质结构与功能预测议定书

核酸结构分析及建设3DNA