Skolnick J, Kolinski A, Ortiz A
Laboratory of Computational Genomics, Danforth Plant Science Center, St. Louis, Missouri 63108, USA.
Proteins. 2000 Jan 1;38(1):3-16.
A method is presented for the derivation of knowledge-based pair potentials that corrects for the various compositions of different proteins. The resulting statistical pair potential is more specific than that derived from previous approaches as assessed by gapless threading results. Additionally, a methodology is presented that interpolates between statistical potentials when no homologous examples to the protein of interest are in the structural database used to derive the potential, to a Go-like potential (in which native interactions are favorable and all nonnative interactions are not) when homologous proteins are present. For cases in which no protein exceeds 30% sequence identity, pairs of weakly homologous interacting fragments are employed to enhance the specificity of the potential. In gapless threading, the mean z score increases from -10.4 for the best statistical pair potential to -12.8 when the local sequence similarity, fragment-based pair potentials are used. Examination of the ab initio structure prediction of four representative globular proteins consistently reveals a qualitative improvement in the yield of structures in the 4 to 6 A rmsd from native range when the fragment-based pair potential is used relative to that when the quasichemical pair potential is employed. This suggests that such protein-specific potentials provide a significant advantage relative to generic quasichemical potentials.
本文提出了一种推导基于知识的配对势的方法，该方法可校正不同蛋白质的各种组成。通过无间隙穿线结果评估，所得的统计配对势比先前方法推导的配对势更具特异性。此外，还提出了一种方法，当用于推导势的结构数据库中没有与目标蛋白质同源的实例时，该方法可在统计势之间进行插值；当存在同源蛋白质时，该方法可插值到类似Go的势（其中天然相互作用是有利的，所有非天然相互作用是不利的）。对于没有蛋白质超过30%序列同一性的情况，使用弱同源相互作用片段对来提高势的特异性。在无间隙穿线中，当使用局部序列相似性、基于片段的配对势时，平均z分数从最佳统计配对势的-10.4增加到-12.8。对四种代表性球状蛋白质的从头结构预测进行检查，结果一致表明，与使用准化学配对势时相比，当使用基于片段的配对势时，在与天然结构相差4至6 Å均方根偏差范围内的结构产率有定性的提高。这表明相对于通用的准化学势，这种蛋白质特异性势具有显著优势。
