FACTORS INFLUENCING THE ABILITY OF KNOWLEDGE-BASED POTENTIALS TO IDENTIFY NATIVE SEQUENCE-STRUCTURE MATCHES
FACTORS INFLUENCING THE ABILITY OF KNOWLEDGE-BASED POTENTIALS TO IDENTIFY NATIVE SEQUENCE-STRUCTURE MATCHES
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DOI：
10.1006/jmbi.1994.1109
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发表时间：
1994-02-04
影响因子：
5.6
通讯作者：
WODAK, SJ
中科院分区：
文献类型：
--
作者：
KOCHER, JPA;ROOMAN, MJ;WODAK, SJ
通过计算氨基酸序列与蛋白质构象的不同描述之间的统计关系，从已知蛋白质结构的数据集导出几种类型的势。这些潜力制定以不同的方式骨干二面角偏好，成对的氨基酸残基之间的距离依赖性的相互作用，和溶剂化效应的基础上可访问的表面积计算。通过在严格的筛选测试中监测天然折叠的识别来严格评估影响特性和性能的参数，其中数据集中的每个测序仪通过从所有相应结构生成的基序库进行线程化。不允许序列间隙，以避免额外的近似。结果表明，由平均侧链质心间距离计算的残基相互作用势在该测试中的表现明显优于考虑C α或C β间距离计算的残基相互作用势。结合基于不同结构描述和不同相互作用的势也是有益的。事实上，这些电位中的一些的性能是如此之好，以至于它们识别所有测试蛋白质的正确折叠，包括已知在没有四级相互作用的情况下不稳定的亚基。最引人注目的是，潜力代表骨干二面角的偏好，承认多达68个蛋白质链的总数为74，即使他们只考虑局部相互作用沿着的链，这是相同的二级结构预测方法中考虑的，是众所周知的是不能确定完整的三维折叠。这使我们质疑筛选有限结构库的程序作为对潜力的严格测试的能力。然而，我们承认，它们是有用的和快速的测试，能够揭示潜在的严重缺陷，或可能的偏见，对本地识别由于，例如，序列记忆的影响。
Several types of potentials are derived from a dataset of known protein structures by computing statistical relations between amino acid sequence and different descriptions of the protein conformation. These potentials formulate in different ways backbone dihedral angle preferences, pairwise distance-dependent interactions between amino acid residues, and solvation effects based on accessible surface area calculations. Parameters affecting the characteristics and the performance of the potentials are critically assessed by monitoring recognition of the native fold in a strict screening test, where each sequencer in the dataset is threaded through a repertoire of motifs, generated from all corresponding structures. Sequence gaps are not allowed, to avoid additional approximations. Results show that residue interaction potentials computed from distances between average side-chain centroids perform significantly better on this test than those computed considering inter-Cα or inter-Cβ distances. Combining potentials that are based on different structural descriptions and different interactions is also beneficial. The performance of some of these potentials is in fact so good that they recognize the correct fold for all the tested proteins, including subunits known to be unstable in the absence of quaternary interactions. Most strikingly, potentials representing backbone dihedral angle preferences recognize as many as 68 protein chains out of a total of 74, even though they consider solely local interactions along the chain, which, being the same as those considered in secondary structure prediction methods, are well known to be incapable of determining the full three-dimensional fold. This leads us to question the ability of procedures that screen a limited repertoire of structures to act as a stringent test for the potentials. We concede, however, that they are useful and fast tests, capable of revealing gross shortcomings of the potentials, or possible biases towards native recognition due, for example, to effects of sequence memory.