Department of Computer Science, Old Dominion University, Norfolk, VA 23529, USA.
BMC Bioinformatics. 2010 Jan 18;11 Suppl 1(Suppl 1):S44. doi: 10.1186/1471-2105-11-S1-S44.
The current advances in electron cryo-microscopy technique have made it possible to obtain protein density maps at about 6-10 A resolution. Although it is hard to derive the protein chain directly from such a low resolution map, the location of the secondary structures such as helices and strands can be computationally detected. It has been demonstrated that such low-resolution map can be used during the protein structure prediction process to enhance the structure prediction.
We have developed an approach to predict the 3-dimensional structure for the helical skeletons that can be detected from the low resolution protein density map. This approach does not require the construction of the entire chain and distinguishes the structures based on the conformation of the helices. A test with 35 low resolution density maps shows that the highest ranked structure with the correct topology can be found within the top 1% of the list ranked by the effective energy formed by the helices.
The results in this paper suggest that it is possible to eliminate the great majority of the bad conformations of the helices even without the construction of the entire chain of the protein. For many proteins, the effective contact energy formed by the secondary structures alone can distinguish a small set of likely structures from the pool.
目前电子低温显微镜技术的进展已经使得在约 6-10埃分辨率下获得蛋白质密度图成为可能。尽管很难从如此低的分辨率图中直接推导出蛋白质链，但可以通过计算来检测二级结构如螺旋和链的位置。已经证明，这种低分辨率的地图可以在蛋白质结构预测过程中使用，以增强结构预测。
我们已经开发了一种从低分辨率蛋白质密度图中检测到的螺旋骨架的三维结构预测方法。该方法不需要构建整个链，并基于螺旋的构象来区分结构。对 35 个低分辨率密度图的测试表明，在通过螺旋形成的有效能量排序的列表中，排名前 1%的结构中可以找到具有正确拓扑结构的最高排名结构。
本文的结果表明，即使不构建蛋白质的整个链，也有可能消除螺旋的绝大多数不良构象。对于许多蛋白质来说，仅由二级结构形成的有效接触能量就可以将一小部分可能的结构从池中区分出来。
