PROTEIN-PROTEIN DOCKING USING LOCAL SHAPE INVARIANTS

这个子项目是许多研究子项目中利用 资源由NIH/NCRR资助的中心拨款提供。子项目和 调查员(PI)可能从NIH的另一个来源获得了主要资金， 并因此可以在其他清晰的条目中表示。列出的机构是 该中心不一定是调查人员的机构。 该项目的目标是设计和开发使用对接来预测蛋白质-蛋白质相互作用的算法。对接的复合体的结构有助于阐明蛋白质的生物学功能。由于用实验方法求解蛋白质结构既耗时又具有技术挑战性，发展计算对接已成为蛋白质生物信息学的一项紧迫任务。这种方法的出发点是将相互作用的蛋白质的结晶结构视为刚性的，并广泛地探索了两种相互作用的蛋白质所产生的构象空间。为了帮助指导搜索，使用了一组矩不变量。其基本思想是捕获在一组兴趣点的小邻域上定义的局部形状属性，根据一组称为Zernike Moments的数字。这些局部描述子对旋转变换是不变的，对噪声也是稳健的。使用几何散列算法对旋转和平移空间(6D空间)进行采样。然后使用合适的能量函数对预测模型进行排序。这一步之后是使用分子动力学模拟对排名靠前的模型进行后续改进。蛋白质天生具有弹性，这意味着它的三维结构可能会在不同的条件下发生变化。考虑到这一点是非常具有挑战性的，因为除了刚体取向的采样之外，还需要适当考虑蛋白质的折叠。为了避免在对接或精化过程中在两个蛋白质的整个柔性构象空间中进行耗时的搜索，采用了集成方法，其中，预先生成的不同可行构象的集合被交叉对接。

This subproject is one of many research subprojects utilizing the resources provided by a Center grant funded by NIH/NCRR. The subproject and investigator (PI) may have received primary funding from another NIH source, and thus could be represented in other CRISP entries. The institution listed is for the Center, which is not necessarily the institution for the investigator. The aim of the project is to design and develop algorithms to predict protein-protein interactions using docking. The structure of the docked complex is useful in elucidating the biological function of the protein. Since solving a protein structure experimentally is time consuming and technically challenging, development of computational docking has become an urgent task in protein bioinformatics. The starting point in this approach are the crystallized structures of the interacting proteins which are treated as rigid, and the conformational space generated by the two interacting proteins is explored extensively. To help guide the search, a set of moment invariants are used. The underlying idea is to capture local shape properties defined over a small neighborhood of a set of interest points, in terms of a set of numbers called Zernike moments. These local descriptors are invariant to rotation transform and robust to noise. The rotational and translational space (6D space) is sampled using a geometric hashing algorithm. The predicted models are then ranked using a suitable energy function. This step is followed by the subsequent refinement of the top ranking models using molecular dynamics simulations. Proteins are inherently flexible which means that its 3-D structure may change under different conditions. Accounting for this is very challenging as in addition to the sampling of the rigid-body orientations, due consideration needs to be given to the folding of the protein. In order to avoid the heavily time consuming search through the entire flexible conformational space of two proteins during the docking or refinement process, an ensemble approach is adopted wherein, a pre-generated set of different feasible conformations are cross-docked.