Lasker Keren, Topf Maya, Sali Andrej, Wolfson Haim J
Blavatnik School of Computer Science, Raymond and Beverly Sackler Faculty of Exact Sciences, Tel Aviv University, Tel-Aviv 69978, Israel.
J Mol Biol. 2009 Apr 24;388(1):180-94. doi: 10.1016/j.jmb.2009.02.031. Epub 2009 Feb 20.
Models of macromolecular assemblies are essential for a mechanistic description of cellular processes. Such models are increasingly obtained by fitting atomic-resolution structures of components into a density map of the whole assembly. Yet, current density-fitting techniques are frequently insufficient for an unambiguous determination of the positions and orientations of all components. Here, we describe MultiFit, a method used for simultaneously fitting atomic structures of components into their assembly density map at resolutions as low as 25 A. The component positions and orientations are optimized with respect to a scoring function that includes the quality-of-fit of components in the map, the protrusion of components from the map envelope, and the shape complementarity between pairs of components. The scoring function is optimized by our exact inference optimizer DOMINO (Discrete Optimization of Multiple INteracting Objects) that efficiently finds the global minimum in a discrete sampling space. MultiFit was benchmarked on seven assemblies of known structure, consisting of up to seven proteins each. The input atomic structures of the components were obtained from the Protein Data Bank, as well as by comparative modeling based on a 16-99% sequence identity to a template structure. A near-native configuration was usually found as the top-scoring model. Therefore, MultiFit can provide initial configurations for further refinement of many multicomponent assembly structures described by electron microscopy.
大分子组装体模型对于细胞过程的机制描述至关重要。此类模型越来越多地通过将组件的原子分辨率结构拟合到整个组装体的密度图中获得。然而,当前的密度拟合技术常常不足以明确确定所有组件的位置和方向。在此,我们描述了MultiFit,一种用于将组件的原子结构同时拟合到其组装密度图中的方法,分辨率低至25埃。组件的位置和方向相对于一个评分函数进行优化,该评分函数包括组件在图中的拟合质量、组件从图包络的突出程度以及组件对之间的形状互补性。评分函数由我们的精确推理优化器DOMINO(多个相互作用对象的离散优化)进行优化,该优化器在离散采样空间中有效地找到全局最小值。MultiFit在七个已知结构的组装体上进行了基准测试,每个组装体由多达七种蛋白质组成。组件的输入原子结构从蛋白质数据库中获取,以及通过基于与模板结构16 - 99%的序列同一性进行比较建模获得。通常会找到一个接近天然的构型作为得分最高的模型。因此,MultiFit可以为通过电子显微镜描述的许多多组件组装体结构的进一步优化提供初始构型。