Determining protein topology from skeletons of secondary structures

Yinghao Wu, Mingzhi Chen, Mingyang Lu, Qinghua Wang, Jianpeng Ma

Research output: Contribution to journalArticle

28 Citations (Scopus)

Abstract

We report a novel computational procedure for determining protein native topology, or fold, by defining loop connectivity based on skeletons of secondary structures that can usually be obtained from low to intermediate-resolution density maps. The procedure primarily involves a knowledge-based geometry filter followed by an energetics-based evaluation. It was tested on a large set of skeletons covering a wide range of protein architecture, including one modeled from an experimentally determined 7.6 Å cryo-electron microscopy (cryo-EM) density map. The results showed that the new procedure could effectively deduce protein folds without high-resolution structural data, a feature that could also be used to recognize native fold in structure prediction and to interpret data in fields like structure genomics. Most importantly, in the energetics-based evaluation, it was revealed that, despite the inevitable errors in the artificially constructed structures and limited accuracy of knowledge-based potential functions, the average energy of an ensemble of structures with slightly different configurations around the native skeleton is a much more robust parameter for marking native topology than the energy of individual structures in the ensemble. This result implies that, among all the possible topology candidates for a given skeleton, evolution has selected the native topology as the one that can accommodate the largest structural variations, not the one rigidly trapped in a deep, but narrow, conformational energy well.

Original languageEnglish (US)
Pages (from-to)571-586
Number of pages16
JournalJournal of Molecular Biology
Volume350
Issue number3
DOIs
StatePublished - Jul 15 2005
Externally publishedYes

Fingerprint

Skeleton
Proteins
Cryoelectron Microscopy
Genomics

Keywords

  • Geometry scoring
  • Protein fold
  • Secondary structure assignment
  • Secondary-structural skeleton
  • Topology

ASJC Scopus subject areas

  • Virology

Cite this

Determining protein topology from skeletons of secondary structures. / Wu, Yinghao; Chen, Mingzhi; Lu, Mingyang; Wang, Qinghua; Ma, Jianpeng.

In: Journal of Molecular Biology, Vol. 350, No. 3, 15.07.2005, p. 571-586.

Research output: Contribution to journalArticle

Wu, Yinghao ; Chen, Mingzhi ; Lu, Mingyang ; Wang, Qinghua ; Ma, Jianpeng. / Determining protein topology from skeletons of secondary structures. In: Journal of Molecular Biology. 2005 ; Vol. 350, No. 3. pp. 571-586.
@article{eadfd5852488471aa737dedd957cfcbb,
title = "Determining protein topology from skeletons of secondary structures",
abstract = "We report a novel computational procedure for determining protein native topology, or fold, by defining loop connectivity based on skeletons of secondary structures that can usually be obtained from low to intermediate-resolution density maps. The procedure primarily involves a knowledge-based geometry filter followed by an energetics-based evaluation. It was tested on a large set of skeletons covering a wide range of protein architecture, including one modeled from an experimentally determined 7.6 {\AA} cryo-electron microscopy (cryo-EM) density map. The results showed that the new procedure could effectively deduce protein folds without high-resolution structural data, a feature that could also be used to recognize native fold in structure prediction and to interpret data in fields like structure genomics. Most importantly, in the energetics-based evaluation, it was revealed that, despite the inevitable errors in the artificially constructed structures and limited accuracy of knowledge-based potential functions, the average energy of an ensemble of structures with slightly different configurations around the native skeleton is a much more robust parameter for marking native topology than the energy of individual structures in the ensemble. This result implies that, among all the possible topology candidates for a given skeleton, evolution has selected the native topology as the one that can accommodate the largest structural variations, not the one rigidly trapped in a deep, but narrow, conformational energy well.",
keywords = "Geometry scoring, Protein fold, Secondary structure assignment, Secondary-structural skeleton, Topology",
author = "Yinghao Wu and Mingzhi Chen and Mingyang Lu and Qinghua Wang and Jianpeng Ma",
year = "2005",
month = "7",
day = "15",
doi = "10.1016/j.jmb.2005.04.064",
language = "English (US)",
volume = "350",
pages = "571--586",
journal = "Journal of Molecular Biology",
issn = "0022-2836",
publisher = "Academic Press Inc.",
number = "3",

}

TY - JOUR

T1 - Determining protein topology from skeletons of secondary structures

AU - Wu, Yinghao

AU - Chen, Mingzhi

AU - Lu, Mingyang

AU - Wang, Qinghua

AU - Ma, Jianpeng

PY - 2005/7/15

Y1 - 2005/7/15

N2 - We report a novel computational procedure for determining protein native topology, or fold, by defining loop connectivity based on skeletons of secondary structures that can usually be obtained from low to intermediate-resolution density maps. The procedure primarily involves a knowledge-based geometry filter followed by an energetics-based evaluation. It was tested on a large set of skeletons covering a wide range of protein architecture, including one modeled from an experimentally determined 7.6 Å cryo-electron microscopy (cryo-EM) density map. The results showed that the new procedure could effectively deduce protein folds without high-resolution structural data, a feature that could also be used to recognize native fold in structure prediction and to interpret data in fields like structure genomics. Most importantly, in the energetics-based evaluation, it was revealed that, despite the inevitable errors in the artificially constructed structures and limited accuracy of knowledge-based potential functions, the average energy of an ensemble of structures with slightly different configurations around the native skeleton is a much more robust parameter for marking native topology than the energy of individual structures in the ensemble. This result implies that, among all the possible topology candidates for a given skeleton, evolution has selected the native topology as the one that can accommodate the largest structural variations, not the one rigidly trapped in a deep, but narrow, conformational energy well.

AB - We report a novel computational procedure for determining protein native topology, or fold, by defining loop connectivity based on skeletons of secondary structures that can usually be obtained from low to intermediate-resolution density maps. The procedure primarily involves a knowledge-based geometry filter followed by an energetics-based evaluation. It was tested on a large set of skeletons covering a wide range of protein architecture, including one modeled from an experimentally determined 7.6 Å cryo-electron microscopy (cryo-EM) density map. The results showed that the new procedure could effectively deduce protein folds without high-resolution structural data, a feature that could also be used to recognize native fold in structure prediction and to interpret data in fields like structure genomics. Most importantly, in the energetics-based evaluation, it was revealed that, despite the inevitable errors in the artificially constructed structures and limited accuracy of knowledge-based potential functions, the average energy of an ensemble of structures with slightly different configurations around the native skeleton is a much more robust parameter for marking native topology than the energy of individual structures in the ensemble. This result implies that, among all the possible topology candidates for a given skeleton, evolution has selected the native topology as the one that can accommodate the largest structural variations, not the one rigidly trapped in a deep, but narrow, conformational energy well.

KW - Geometry scoring

KW - Protein fold

KW - Secondary structure assignment

KW - Secondary-structural skeleton

KW - Topology

UR - http://www.scopus.com/inward/record.url?scp=20444490870&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=20444490870&partnerID=8YFLogxK

U2 - 10.1016/j.jmb.2005.04.064

DO - 10.1016/j.jmb.2005.04.064

M3 - Article

C2 - 15961102

AN - SCOPUS:20444490870

VL - 350

SP - 571

EP - 586

JO - Journal of Molecular Biology

JF - Journal of Molecular Biology

SN - 0022-2836

IS - 3

ER -