Method Development: Efficient Computer Vision Based Algorithms

方法开发：基于高效计算机视觉的算法

• 批准号: 8349006
• 负责人: Ruth Nussinov
• 金额: $ 12.85万
• 依托单位: DIVISION OF BASIC SCIENCES - NCI
• 依托单位国家: 美国
• 资助国家: 美国
• 起止时间: 至
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/8349006
• 关键词: Address; Algorithms; Benchmarking; Binding; Binding Sites; Biological; Biological Process; CASP8 gene; CCR; Categories; Cells; Characteristics; Chemical Engineering; Complex; Computational Biology; Computer Simulation; Computer Vision Systems; Data; Detection; Docking; Fiber; Generations; Goals; Guidelines; Image; Libraries; Life; Ligands; Light; Link; Location; Maps; Membrane Proteins; Methods; Modeling; Molecular; Molecular Conformation; Movement; Names; Nature; Organism; Pathway interactions; Phage Display; Procedures; Protein Fragment; Proteins; RNA; Reporting; Resources; Robotics; Roentgen Rays; Route; Series; Side; Site; Solutions; Specific qualifier value; Staging; Structure; System; Techniques; Testing; Time; Update; Validation; Vertebral column; Work; base; biological research; comparative; computerized tools; data management; density; experience; flexibility; functional group; globular protein; improved; instrument; method development; molecular dynamics; monomer; novel; operation; prevent; programs; protein complex; protein folding; protein structure; protein structure prediction; research study; tau Proteins; three dimensional structure; tool; two-dimensional; web site

Several methods have been developed to address (i) protein docking; (ii) helical symmetry description and (iii) protein folding using docking techniques. (i) Symmetric protein complexes are abundant in the living cell. Predicting their atomic structure can shed light on the mechanism of many important biological processes. Symmetric docking methods aim to predict the structure of these complexes given the unbound structure of a single monomer, or its model. Symmetry constraints reduce the search-space of these methods and make the prediction easier compared to asymmetric protein-protein docking. However, the challenge of modeling the conformational changes that the monomer might undergo is a major obstacle. In this article, we present SymmRef, a novel method for refinement and reranking of symmetric docking solutions. The method models backbone and side-chain movements and optimizes the rigid-body orientations of the monomers. The backbone movements are modeled by normal modes minimization and the conformations of the side-chains are modeled by selecting optimal rotamers. Since solved structures of symmetric multimers show asymmetric side-chain conformations, we do not use symmetry constraints in the side-chain optimization procedure. The refined models are re-ranked according to an energy score. We tested the method on a benchmark of unbound docking challenges. The results show that the method significantly improves the accuracy and the ranking of symmetric rigid docking solutions. (ii) Assemblies with helical symmetry can be conveniently formulated in many distinct ways. Here, a new convention is presented which unifies the two most commonly used helical systems for generating helical assemblies from asymmetric units determined by X-ray fibre diffraction and EM imaging. A helical assembly is viewed as being composed of identical repetitive units in a one- or two-dimensional lattice, named 1-D and 2-D helical systems, respectively. The unification suggests that a new helical description with only four parameters [n(1), n(2), twist, rise], which is called the augmented 1-D helical system, can generate the complete set of helical arrangements, including coverage of helical discontinuities (seams). A unified four-parameter characterization implies similar parameters for similar assemblies, can eliminate errors in reproducing structures of helical assemblies and facilitates the generation of polymorphic ensembles from helical atomic models or EM density maps. Further, guidelines are provided for such a unique description that reflects the structural signature of an assembly, as well as rules for manipulating the helical symmetry presentation. (iii) The pathways by which proteins fold into their specific native structure are still an unsolved mystery. Currently, many methods for protein structure prediction are available, and most of them tackle the problem by relying on the vast amounts of data collected from known protein structures. These methods are often not concerned with the route the protein follows to reach its final fold. This work is based on the premise that proteins fold in a hierarchical manner. We present FOBIA, an automated method for predicting a protein structure. FOBIA consists of two main stages: the first finds matches between parts of the target sequence and independently folding structural units using profile-profile comparison. The second assembles these units into a 3D structure by searching and ranking their possible orientations toward each other using a docking-based approach. We have previously reported an application of an initial version of this strategy to homology based targets. Since then we have considerably enhanced our method's abilities to allow it to address the more difficult template-based target category. This allows us to now apply FOBIA to the template-based targets of CASP8 and to show that it is both very efficient and promising. Our method can provide an alternative for template-based structure prediction, and in particular, the docking-basedranking technique presented here can be incorporated into any profile-profile comparison based method.

已经开发了几种方法来解决（i）蛋白质对接;（ii）螺旋对称描述和（iii）使用对接技术的蛋白质折叠。 (i)对称蛋白质复合物在活细胞中大量存在。预测它们的原子结构可以揭示许多重要生物过程的机制。对称对接方法的目的是预测这些复合物的结构给定的单个单体的未结合的结构，或其模型。与不对称蛋白质-蛋白质对接相比，对称性约束减少了这些方法的搜索空间，使预测更容易。然而，单体可能经历的构象变化建模的挑战是一个主要障碍。在这篇文章中，我们提出了SymmRef，对称对接解决方案的细化和重新排序的一种新方法。该方法建模的骨干和侧链的运动和优化的单体的刚体取向。主链运动由简正模最小化建模，侧链的构象由选择最佳旋转异构体建模。由于对称多聚体的结构显示出不对称的侧链构象，因此我们在侧链优化过程中不使用对称性约束。根据能量分数对改进的模型进行重新排名。我们测试的方法上的基准未绑定对接的挑战。结果表明，该方法显著提高了对称刚性对接解的精度和排序。(ii)具有螺旋对称性的组件可以方便地以许多不同的方式来表达。在这里，提出了一个新的公约，统一了两个最常用的螺旋系统，用于产生螺旋组件从不对称的单位确定的X射线纤维衍射和EM成像。一个螺旋装配被看作是由相同的重复单元在一个一维或二维晶格，命名为1-D和2-D螺旋系统，分别。这种统一性表明，一个新的螺旋描述只有四个参数[n（1），n（2），twist，rise]，这就是所谓的增广1-D螺旋系统，它可以产生一套完整的螺旋排列，包括覆盖螺旋间断（缝）。一个统一的四参数表征意味着相似的参数相似的组件，可以消除错误的螺旋组装的再现结构，并有利于从螺旋原子模型或EM密度图的多态系综的产生。此外，为反映组件的结构签名的这种唯一描述提供了指导方针，以及用于操纵螺旋对称表示的规则。(iii)蛋白质折叠成其特定天然结构的途径仍然是一个未解之谜。目前，蛋白质结构预测的方法有很多，其中大多数是依靠从已知蛋白质结构中收集的大量数据来解决这个问题的。这些方法通常不关心蛋白质到达其最终折叠所遵循的路线。这项工作是基于蛋白质以分层方式折叠的前提。我们提出了FOBIA，一个自动化的方法来预测蛋白质结构。FOBIA由两个主要阶段组成：第一个阶段使用轮廓-轮廓比较找到靶序列部分和独立折叠结构单元之间的匹配。第二个组装成一个3D结构，通过搜索和排名他们可能的方向对彼此使用基于对接的方法这些单位。我们以前已经报道了应用程序的初始版本的这种策略同源性为基础的目标。从那时起，我们已经大大增强了我们的方法的能力，使其能够解决更困难的基于模板的目标类别。这使得我们现在可以将FOBIA应用于CASP8的基于模板的靶标，并表明它既非常有效又有前途。我们的方法可以为基于模板的结构预测提供一种替代方案，特别是，这里提出的docking-basedranking技术可以被纳入任何基于轮廓-轮廓比较的方法。