Skip to content Skip to navigation
University of Warwick
  • Study
  • |
  • Research
  • |
  • Business
  • |
  • Alumni
  • |
  • News
  • |
  • About

University of Warwick
Publications service & WRAP

Highlight your research

  • WRAP
    • Home
    • Search WRAP
    • Browse by Warwick Author
    • Browse WRAP by Year
    • Browse WRAP by Subject
    • Browse WRAP by Department
    • Browse WRAP by Funder
    • Browse Theses by Department
  • Publications Service
    • Home
    • Search Publications Service
    • Browse by Warwick Author
    • Browse Publications service by Year
    • Browse Publications service by Subject
    • Browse Publications service by Department
    • Browse Publications service by Funder
  • Help & Advice
University of Warwick

The Library

  • Login
  • Admin

SSNN, a method for neural network protein secondary structure fitting using circular dichroism data

Tools
- Tools
+ Tools

Hall, Vincent Austin, Nash, Anthony and Rodger, Alison (2014) SSNN, a method for neural network protein secondary structure fitting using circular dichroism data. Analytical Methods, 6 (17). pp. 6721-6726. doi:10.1039/c3ay41831f ISSN 1759-9660.

[img]
Preview
PDF
WRAP_9471544-ch-040116-140618_ssnn_a_method_for_neural_network_protein_secondary_structure_fitting_using_circular_dichroism_data_main.pdf - Accepted Version - Requires a PDF viewer.

Download (786Kb) | Preview
Official URL: http://dx.doi.org/10.1039/C3AY41831F

Request Changes to record.

Abstract

Circular dichroism (CD) spectroscopy is a quick method for measuring data that can be used to determine the average secondary structures of proteins, probe their interactions with their environment, and aid in drug discovery. This paper describes the operation and testing of a self-organising map (SOM) structure-fitting methodology named Secondary Structure Neural Network (SSNN), which is a methodology for estimating protein secondary structure from CD spectra of unknown proteins using CD spectra of proteins with known X-ray structures. SSNN comes in two standalone MATLAB applications for estimating unknown proteins' structures, one that uses a pre-trained map and one that begins by training the SOM with a reference set of the user's choice. These are available at http://www2.warwick.ac.uk/fac/sci/chemistry/research/arodger/arodgergroup/research_intro/instrumentation/ssnn/ as SSNNGUI and SSNN1_2 respectively. They are available for both Macintosh and Windows formats with two reference sets: one obtained from the CDPro website, referred to as CDDATA.48 which has 48 protein spectra and structures, and one with 53 proteins (CDDATA.48 with 5 additional spectra). Here we compare SSNN with CDSSTR, a widely-used secondary structure methodology, and describe how to use the standalone SSNN applications. Current input format is Δε per amino acid residue from 240 nm to 190 nm in 1 nm steps for the known and unknown proteins and a vector summarising the secondary structure elements of the known proteins. The format is readily modified to include input data with e.g. extended wavelength ranges or different assignment of secondary structures.

Item Type: Journal Article
Subjects: Q Science > QD Chemistry
Divisions: Faculty of Science, Engineering and Medicine > Science > Chemistry
Library of Congress Subject Headings (LCSH): Circular dichroism, Synchrotron radiation, Molecular spectroscopy, DNA-binding proteins, Proteins -- Structure -- Data processing, Neural networks (Computer science)
Journal or Publication Title: Analytical Methods
Publisher: Royal Society of Chemistry
ISSN: 1759-9660
Official Date: 7 September 2014
Dates:
DateEvent
7 September 2014Published
29 June 2014Accepted
18 October 2013Submitted
Volume: 6
Number: 17
Page Range: pp. 6721-6726
DOI: 10.1039/c3ay41831f
Status: Peer Reviewed
Publication Status: Published
Access rights to Published version: Restricted or Subscription Access
Date of first compliant deposit: 13 January 2016
Date of first compliant Open Access: 13 January 2016
Funder: Engineering and Physical Sciences Research Council (EPSRC)
Grant number: EP/F500378/1

Request changes or add full text files to a record

Repository staff actions (login required)

View Item View Item

Downloads

Downloads per month over past year

View more statistics

twitter

Email us: wrap@warwick.ac.uk
Contact Details
About Us