Method Development: Efficient Computer Vision Based Algo

我们方法的独特性来自于将蛋白质结构视为3D空间中的点(例如，原子坐标或描述分子表面的点)的集合，而不考虑链上残基的顺序。这种基于计算机视觉和机器人的算法能够对蛋白质表面、界面或蛋白质核心进行比较，而不受顺序的限制。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、结合位点比较和检测)已经在上面描述过了。列举自上次实地考察以来我们开发的方法：基于残基的多重蛋白质结构比较(MultiProt；蛋白质在其二级结构表示中的多重比对(MASS)；蛋白质结构在官能团表示中的多重比对(MultiBind)，以及蛋白质-蛋白质界面的多重比对(MAPPIS)；SiteEngine，执行小分子和蛋白质结合位点识别；I2ISiteEngine，执行界面的成对结构比较；蛋白质结构的灵活比对(FlexProt；刚体对接(PatchDock)；柔性铰链-弯曲对接(FlexDock)；对称对接(SymmDock；折叠和多分子组装的组合对接(CombDock)；利用噬菌体展示文库(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被组装。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-蛋白质界面的多对齐)。下面我将简要介绍FlexProt、MASS和MultiProt。大多数多重比对方法都是从成对比对解决方案开始的。相反，质量和多蛋白从输入分子的同时叠加中获得多个比对。此外，这两种方法都不要求所有的输入分子都参与比对。实际上，它们有效地检测了输入中所有可能数量的分子的高分部分多重比对。MASS(基于二级结构的多重比对)和MultiProt(多个蛋白质)是全自动化的高效技术，用于检测蛋白质结构的多个结构比对和输入分子之间的共同几何核心。此外，这两种方法都是顺序无关的。质量基于两级比对，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，实现了效率和稳健性。质量能够检测到非拓扑结构基序，其中二级结构在链上以不同的顺序排列。此外，质量不仅能够检测所有输入分子共享的结构基序，而且还能够检测仅由分子子集共享的基序。我们已经证明了它有能力处理数十个分子的数量级，检测非拓扑基序，并在输入的非预定义子集内找到具有生物学意义的比对。MASS可在http://bioinfo3d.cs.tau.ac.il/MASS/.上获得MultiProt认为蛋白质结构是由空间中的点表示的，这些点要么是C-Alpha坐标，要么是C-Alpha和原子或侧链的几何中心。在http://bioinfo3d.cs.tau.ac.il/MultiProt/.上可以获得MultiProt。我们已经在一系列应用中说明了这两种方法的强大功能。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，使其成为一种非常有用的结构工具。FlexProt是一种用于柔性蛋白质比对的新技术。

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.