Alternative approach to protein structure prediction based on sequential similarity of physical properties

被引：13

作者：

He, Yi ^{[1
]}

Rackovsky, S. ^{[1
,2
]}

Yin, Yanping ^{[1
]}

Scheraga, Harold A. ^{[1
]}

机构：

[1] Cornell Univ, Dept Chem & Chem Biol, Ithaca, NY 14853 USA

[2] Icahn Sch Med Mt Sinai, Dept Pharmacol & Syst Therapeut, New York, NY 10029 USA

来源：

PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA | 2015年 / 112卷 / 16期

基金：

美国国家卫生研究院; 美国国家科学基金会;

关键词：

homology modeling; amino acid physical properties; protein structure prediction; HIDDEN MARKOV-MODELS; ALPHA-LACTALBUMIN; AMINO-ACIDS; PSI-BLAST; SEQUENCES; INFORMATION; ALIGNMENT; LYSOZYME;

D O I：

10.1073/pnas.1504806112

中图分类号：

O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];

学科分类号：

07 ; 0710 ; 09 ;

摘要：

The relationship between protein sequence and structure arises entirely from amino acid physical properties. An alternative method is therefore proposed to identify homologs in which residue equivalence is based exclusively on the pairwise physical property similarities of sequences. This approach, the property factor method (PFM), is entirely different from those in current use. A comparison is made between our method and PSI BLAST. We demonstrate that traditionally defined sequence similarity can be very low for pairs of sequences (which therefore cannot be identified using PSI BLAST), but similarity of physical property distributions results in almost identical 3D structures. The performance of PFM is shown to be better than that of PSI BLAST when sequence matching is comparable, based on a comparison using targets from CASP10 (89 targets) and CASP11 (51 targets). It is also shown that PFM outperforms PSI BLAST in informatically challenging targets.

引用

页码：5029 / 5032

页数：4