Prediction of the amount of secondary structure of proteins using unassigned NMR spectra: a tool for target selection in structural proteomics

Vitor Hugo Moreau,Fábio C.L Almeida,Ana Paula Valente

doi:10.1590/s1415-47572006000400030

Abstract

With the advent of structural genomics, the need for fast structural information about unknown proteins has increased. We describe a new methodology, based on 13C, 15N and ¹H chemical shift dispersion to predict the amount of secondary structure of unassigned proteins from their 15N- and/or 13C-edited heteronuclear single quantum coherence (HSQC) spectra. This methodology has been coded into a software called PASSNMR (Prediction of the Amount of Secondary Structure by Nuclear Magnetic Resonance), which can be accessed directly from the Internet. PASSNMR program is a powerful tool for screening proteins for proteomic or structural genomic investigations when used with recent methodologies that take advantage of the use of the antibiotic rifampicin to selectively label the heterologous proteins expressed in E. coli. PASSNMR analysis can be useful as a first approach to predict the amount of secondary structure in proteins to structural genomics. Information about the secondary structure of proteins can be obtained even before protein purification, with small quantities of protein, just by performing two simple nuclear magnetic resonance (NMR) experiments and using PASSNMR program.

Highlights

The genome of a variety of organisms has been sequenced and the scientific community is investigating the large amount of information available
To correlate chemical shift dispersion with the amount of secondary structure, 13C-heteronuclear single quantum coherence (HSQC) and 15N-HSQC spectra were constructed based on the assignments obtained from Star files of 72 proteins taken from the BioMagRes Bank
The ratio of the number of peaks in each area divided by the total number of cross-peaks in each spectrum was calculated and found to be proportional to the amount of secondary structure in each protein obtained from the protein data bank

Summary

Introduction

The genome of a variety of organisms has been sequenced and the scientific community is investigating the large amount of information available. The scientific community is discussing strategies for quickly analyzing this deluge of new information. In this sense, computational methods are important for mining the genome to look for primary, secondary and tertiary structure homologies between proteins. One problem in structural proteomics is that only a small group of protein folds are determined because the selection of proteins for experimental analysis is often based on their solubility and flexibility. In this way, this leads to the same classes of “well-behaved” proteins being selected for study and, only known folding motifs be-

Methods

Results

Conclusion