Protein Sequence Alignment and Database Scanning

Geoffrey J. Barton

Laboratory of Molecular Biophysics
University of Oxford
Rex Richards Building
South Parks Road
Oxford OX1 3QU
U.K.

Tel: 0865-275368
Fax: 0865-510454
e-mail: gjb@bioch.ox.ac.uk

This is a preprint of the chapter in: Protein Structure prediction - a practical approach,
Edited by M. J. E. Sternberg, IRL Press at Oxford University Press, 1996, ISBN 0 19 963496 3.
Please see that book for the final version.

• Contents
• Introduction
• Amino acid scoring schemes
  • Identity scoring
  • Genetic code scoring
  • Chemical similarity scoring
  • Observed substitutions
    • The Dayhoff mutation data matrix
    • PET91 - An updated Dayhoff matrix
    • BLOSUM - matrix from ungapped alignments.
    • Matrices derived from tertiary structure alignments
  • Which matrix should I use?
• Comparison of two sequences
  • Sequence comparison without gaps - fixed length segments
    • Correlation methods
    • Variable length segments
  • Sequence comparison with gaps
    • Finding the best alignment with dynamic programming
    • Alternative weighting for gaps
  • Identification of local similarities
    • Finding second and subsequent best local alignments
• Evaluation of alignment accuracy
  • Predicting overall alignment accuracy
    • Predicting quality using percentage identity
  • Predicting the reliable regions of an alignment
  • Incorporating non-sequence information into alignment
• Multiple sequence alignment
  • Extension of dynamic programming to more than two sequences
  • Tree or hierarchical methods using dynamic programming
  • Extension of segment methods to multiple alignment
  • Representation and analysis of multiple alignments
• Database scanning
  • Basic principles of database searching
  • Time considerations
  • Which database should I search? Local or network?
  • Searching with dynamic programming
    • Scanning with parallel computers Prosrch, MPsrch and others
  • Index methods
    • Simple index for identical matching
    • Indexing with gaps - the FLASH algorithm
  • Approximations: The FASTP and FASTA algorithm
  • Approximations: BLAST Basic Local Alignment Search Tool
  • Guidelines for Database Scanning
• Summary
• Figure Legends
  • Figure 1
  • Figure 2
  • Figure 3
  • Figure 4
  • Figure 5
  • Figure 6
  • Figure 7
  • Figure 8
  • Figure 9
  • Figure 10
• References
• About this document ...