Method Development: Efficient Computer Vision Based Algo
Method Development: Efficient Computer Vision Based Algo
批准号:
7338445
负责人:
Ruth Nussinov
金额:
$0.0万
依托单位国家:
美国
项目类别:
财政年份:
--
资助国家:
美国
项目状态:
未结题
起止时间:
至
中文摘要
我们方法的独特性源于将蛋白质结构视为3D空间中点的集合(例如,原子坐标或描述分子表面的点),而忽略链上残基的顺序。这种基于计算机视觉和机器人的算法可以在不受顺序限制的情况下对蛋白质表面、界面或蛋白质核心进行比较。自上次实地考察以来,我们在开发新算法方面取得了实质性进展。其中一些(对接和结合位点的比较和检测)已经在上面描述过了。列举自上次现场访问以来我们开发的方法:基于残基的多蛋白质结构比较(MultiProt);蛋白质二级结构表示的多重比对(MASS);蛋白质结构在功能基团表示及其结合位点(MultiBind)和蛋白质-蛋白质界面(MAPPIS)中的多重比对;SiteEngine用于小分子和蛋白质结合位点识别,I2ISiteEngine用于界面的两两结构比较;蛋白质结构的柔性对齐(FlexProt);刚体对接(PatchDock);柔性铰链弯曲对接(FlexDock);对称对接(symdock);折叠和多分子组装组合对接(CombDock);利用噬菌体展示库(SiteLight)预测结合位点。此外,利用这些,蛋白质-蛋白质界面的两个非冗余数据集已经组装。这些方法都是高效的,具有最先进的功能。我已经讨论了对接方法,SiteEngine和MAPPIS(蛋白质-蛋白质接口的多重对齐)。下面我简要介绍一下FlexProt、MASS和MultiProt。大多数多重对准方法都是从成对对准解开始的。相比之下,MASS和MultiProt从输入分子的同时叠加中获得多个排列。此外,这两种方法都不要求所有输入分子都参与比对。实际上,它们有效地检测到输入中所有可能数量的分子的高分部分多重比对。MASS (Multiple Alignment by Secondary Structures)和MultiProt (Multiple Proteins)是全自动、高效的蛋白质结构比对检测技术,可检测输入分子之间的共同几何核心。此外,这两种方法都是序列顺序无关的。MASS基于两级对齐,同时使用二级结构和原子表示。利用二级结构信息有助于滤除噪声解,达到高效和鲁棒性。MASS能够检测非拓扑结构基序,其中二级结构以不同的顺序排列在链上。此外,MASS不仅能够检测所有输入分子共享的结构基序,还能够检测仅由分子子集共享的基序。我们已经证明了它能够处理数十个分子的顺序,检测非拓扑基序,并在输入的非预定义子集中找到具有生物学意义的排列。MASS的网址是http://bioinfo3d.cs.tau.ac.il/MASS/。MultiProt考虑用空间中的点来表示的蛋白质结构,这些点要么是c - α坐标,要么是c - α和侧链的原子或几何中心。MultiProt可在http://bioinfo3d.cs.tau.ac.il/MultiProt/上获得。我们已经说明了这两种方法在一系列应用程序中的强大功能。顺序无关性允许将MultiProt应用于结合位点和蛋白质-蛋白质界面,使MultiProt成为非常有用的结构工具。FlexProt是一种用于柔性蛋白排列的新技术。
英文摘要
The uniqueness of our methodologies derives from viewing protein structures as collections of points (e.g., atom coordinates, or points describing molecular surfaces) in 3D space, disregarding the order of the residues on the chains. Such computer-vision and robotics-based algorithms enable comparisons of protein surfaces, interfaces, or protein cores without being limited by the sequential order. Since the last site visit, we have made substantial progress in the development of new algorithms. Some of these (docking, and binding site comparison and detection) have already been described above. To enumerate the methods we have developed since the last site visit: residue-based multiple protein structure comparison (MultiProt; multiple alignment of proteins in their secondary structure representation (MASS); multiple alignment of protein structures in the functional group representation and of their binding sites (MultiBind), and of protein-protein interfaces (MAPPIS); SiteEngine, which carries out small molecule and protein-binding site recognition and I2ISiteEngine, which carries out pairwise structural comparisons of interfaces; flexible alignment of protein structures (FlexProt; Rigid body docking (PatchDock); Flexible hinge-bending docking (FlexDock); Symmetry docking (SymmDock; Combinatorial docking for folding and multimolecular assembly (CombDock); Prediction of binding sites using phage display libraries (SiteLight). In addition, using these, two nonredundant datasets of protein-protein interfaces have been assembled. The methods are all highly efficient with state of-the-art capabilities. I have already discussed the docking methods, SiteEngine and MAPPIS (Multiple Alignment of Protein-Protein InterfaceS). Below I briefly describe FlexProt, MASS and MultiProt.Most methods for multiple alignment start from the pairwise alignment solutions. In contrast, MASS and MultiProt derive multiple alignments from simultaneous superpositions of input molecules. Further, both methods do not require that all input molecules participate in the alignment. Actually, they efficiently detect high scoring partial multiple alignments for all possible number of molecules in the input. MASS (Multiple Alignment by Secondary Structures) and MultiProt (Multiple Proteins) are fully automated highly efficient techniques to detect multiple structural alignments of protein structures and detect common geometrical cores between input molecules. Furthermore, both methods are sequence-order independent. MASS is based on a two-level alignment, using both secondary structure and atomic representation. Utilizing secondary structure information aids in filtering out noisy solutions and achieves efficiency and robustness. MASS is capable of detecting nontopological structural motifs, where the secondary structures are arranged in a different order on the chains. Further, MASS is able to detect not only structural motifs, shared by all input molecules, but also motifs shared only by subsets of the molecules. We have demonstrated its ability to handle on the order of tens of molecules, to detect nontopological motifs and to find biologically meaningful alignments within nonpredefined subsets of the input. MASS is available at http://bioinfo3d.cs.tau.ac.il/MASS/. MultiProt considers protein structures as represented by points in space, where the points are either the C-alpha coordinates or the C-alpha and atoms or geometric center of the side chain. MultiProt is available at http://bioinfo3d.cs.tau.ac.il/MultiProt/. We have illustrated the power of both methods on a range of applications. The order-independence allows application of MultiProt to binding sites and protein-protein interfaces, making MultiProt an extremely useful structural tool.FlexProt is a novel technique for the alignment of flexible proteins.
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Method Development: Efficient Computer Vision Based Algo
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批准号:7291814
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项目类别:
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资助金额:$0.0万
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财政年份:--
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负责人:Ruth Nussinov
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依托单位:
Method Development: Efficient Computer Vision Based Algorithms
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批准号:7965320
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项目类别:
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资助金额:$13.03万
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财政年份:--
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负责人:Ruth Nussinov
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依托单位:
Method Development: Efficient Computer Vision Based Algorithms
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批准号:8937737
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项目类别:
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资助金额:$10.87万
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财政年份:--
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负责人:Ruth Nussinov
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依托单位:
Biomolecular Recognition and Binding Mechanisms
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批准号:9153571
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项目类别:
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资助金额:$43.97万
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财政年份:--
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负责人:Ruth Nussinov
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依托单位:
Method Development: Efficient Computer Vision Based Algorithms
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批准号:8349006
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项目类别:
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资助金额:$12.85万
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财政年份:--
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负责人:Ruth Nussinov
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依托单位:
Protein Structure, Stability, and Amyloid Formation
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批准号:8349004
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项目类别:
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资助金额:$64.26万
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财政年份:--
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负责人:Ruth Nussinov
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依托单位:
Biomolecular Recognition and Binding Mechanisms
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批准号:8349005
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项目类别:
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资助金额:$51.4万
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财政年份:--
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负责人:Ruth Nussinov
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依托单位:
Protein Structure, Stability, and Amyloid Formation
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批准号:8552693
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项目类别:
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资助金额:$53.14万
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财政年份:--
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负责人:Ruth Nussinov
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依托单位:
Biomolecular Recognition and Binding Mechanisms
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批准号:10014370
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项目类别:
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资助金额:$68.71万
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财政年份:--
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负责人:Ruth Nussinov
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依托单位:
Method Development: Efficient Computer Vision Based Algorithms
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批准号:10262089
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项目类别:
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资助金额:$11.83万
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财政年份:--
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负责人:Ruth Nussinov
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依托单位:
Biomolecular Recognition and Binding Mechanisms
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批准号:10262088
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项目类别:
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资助金额:$47.34万
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财政年份:--
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负责人:Ruth Nussinov
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依托单位:
Biomolecular Recognition and Binding Mechanisms
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批准号:7291812
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项目类别:
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资助金额:$0.0万
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财政年份:--
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负责人:Ruth Nussinov
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依托单位:
Biomolecular Recognition and Binding Mechanisms
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批准号:8552694
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项目类别:
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资助金额:$42.51万
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财政年份:--
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负责人:Ruth Nussinov
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依托单位:
Method Development: Efficient Computer Vision Based Algorithms
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批准号:8552695
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项目类别:
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资助金额:$10.63万
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财政年份:--
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负责人:Ruth Nussinov
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依托单位:
Protein Structure, Stability, and Amyloid Formation
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批准号:10702352
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项目类别:
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资助金额:$69.45万
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财政年份:--
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负责人:Ruth Nussinov
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依托单位:
Protein Structure, Stability, and Amyloid Formation
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批准号:7338385
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项目类别:
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资助金额:$0.0万
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财政年份:--
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负责人:Ruth Nussinov
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依托单位:
Method Development: Efficient Computer Vision Based Algorithms
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批准号:8763103
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项目类别:
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资助金额:$9.89万
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财政年份:--
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负责人:Ruth Nussinov
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依托单位:
Biomolecular Recognition and Binding Mechanisms
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批准号:7733032
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项目类别:
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资助金额:$67.32万
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财政年份:--
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负责人:Ruth Nussinov
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依托单位:
Protein Structure, Stability, and Amyloid Formation
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批准号:7592701
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项目类别:
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资助金额:$57.07万
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财政年份:--
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负责人:Ruth Nussinov
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依托单位:
Protein Structure, Stability, and Amyloid Formation
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批准号:10262087
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项目类别:
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资助金额:$59.17万
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财政年份:--
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负责人:Ruth Nussinov
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依托单位:
国内基金
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批准号:32070202
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项目类别:面上项目
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资助金额:58.0万元
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批准年份:2020
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负责人:汪泉
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依托单位:
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批准号:--
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