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中文摘要
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描述(由申请人提供):蛋白质动力学在细胞中的分子事件中起关键作用。在计算生物学的重大努力已经投入到理解和建模构象动力学。为此,我们的实验室引入了弹性网络模型(ENM)和谱图理论分析方法来探索结构动力学。这些方法已经在许多应用中发现了实用性,并帮助我们深入了解蛋白质的内在结构编码能力,以促进特定的构象变化,以及它们与实验观察到的功能亚态的相关性。我们开发了两个服务器:各向异性网络模型(ANM)和在线高斯网络模型(oGNM),用于预测已知结构的集体动力学,2010年访问量超过40,000次。在实验方面,蛋白质数据库(PDB)现在托管数百种蛋白质的多个结构,这些结构形成了不同形式的相同蛋白质的异质结构数据集(例如,直向同源物、突变体、在变构循环期间访问的子状态或不同的复合物/组装体)。我们最近的工作表明,结构的功能变化可以从这些数据集的主成分分析(PCA)推断。我们还开发了一个用于分析NMR模型的PCA服务器(PCA_NEST)。值得注意的是,从这些实验数据集推断的信息,以及通过理论和计算预测的信息,可以有利地结合起来,以揭示靶蛋白的激活或抑制机制,并识别调节集体运动的关键残基。受我们研究的效用以及我们现有软件和服务器的广泛使用的激励,我们建议(i)改进、现代化并将我们现有的蛋白质动力学软件集成到一个易于修改和可扩展的应用程序编程接口(API)ProDy中,该接口将允许除了理论预测之外还对实验数据进行系统分析,(ii)扩展ProDy API与现有序列和结构数据库的互操作性,以便能够评估蛋白质家族特异性动力学;(iii)通过继续开发和测试,并建立其与分子动力学模拟软件的互操作性,推进ProDy的实用性。交付的成果将包括两个图形用户界面(VMD插件和Chimera扩展),以及一个数据库和网络用户界面,使没有编程经验的用户能够方便地访问软件的全部功能。这套工具的主要用途是阐明结构与功能之间的桥梁,不仅通过为此目的广泛利用的计算方法,而且通过提取和分析迄今为止积累的所有结构数据。
英文摘要
DESCRIPTION (provided by applicant): Protein dynamics plays a key role in molecular events in the cell. Significant efforts in computational biology have been invested in understanding and modeling conformational dynamics. To this aim, our lab has introduced elastic network models (ENMs) and spectral graph theoretical analysis methods for exploring structural dynamics. These methods have found utility in many applications and have helped us gain insights into the intrinsic, structure-encoded ability of proteins to favor particular changes in conformation, and their relevance to experimentally observed functional substates. We have developed two servers: anisotropic network model (ANM, and the online Gaussian network model (oGNM) for predicting the collective dynamics of known structures, which have been visited over 40,000 times in 2010. On the experimental side, the Protein Data Bank (PDB) now hosts multiple structures for hundreds of proteins, which form heterogeneous structural datasets for the same protein in different forms (e.g., orthologs, mutants, substates visited during an allosteric cycle, or different complexes/assemblies). Our recent work showed that functional changes in structure may be inferred from the principal component analysis (PCA) of these datasets. We also developed a PCA server (PCA_NEST) for analyzing NMR models. Significantly, the information inferred from these experimental datasets, and those predicted by theory and computations, can be advantageously combined to disclose the mechanisms of activation or inhibition of target proteins, and to identify key residues that modulate collective movements. Motivated by the utility of our studies, and the broad use of our existing software and servers, we propose (i) to improve, modernize and integrate our existing software for protein dynamics into an easily modifiable and extensible application programming interface (API), ProDy, which will allow for systematic analysis of experimental data in addition to theoretical predictions, (ii) to extend the interoperability of ProDy API with existing sequence- and structure-databases to enable the assessment of protein family-specific dynamics and (iii) to advance the utility of ProDy through continued development and testing, and establishing its interoperation with molecular dynamics simulation software. The deliverables will include two graphical user interfaces (a VMD plugin and a Chimera extension), and a database and web user interface that will provide convenient access to the full functionality of the software by users without experience in programming. The primarily utility of this set of tools will be elucidating the bridge between structure and function, not only via computational methods that are widely exploited toward this aim, but also by extracting and analyzing all structural data accumulated to date.
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Toward a deeper understanding of allostery and allotargeting by computational approaches
Toward a deeper understanding of allostery and allotargeting by computational approaches
Toward a deeper understanding of allostery and allotargeting by computational approaches
Toward a deeper understanding of allostery and allotargeting by computational approaches
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