MINRMS: An Efficient Algorithm for Determining Protein Structure Similarity Using Root-Mean-Squared-Distance

Bioinformatics. 2003 Mar 22;19(5):625-34. doi: 10.1093/bioinformatics/btg035.

Abstract

Motivation: Existing algorithms for automated protein structure alignment generate contradictory results and are difficult to interpret. An algorithm which can provide a context for interpreting the alignment and uses a simple method to characterize protein structure similarity is needed.

Results: We describe a heuristic for limiting the search space for structure alignment comparisons between two proteins, and an algorithm for finding minimal root-mean-squared-distance (RMSD) alignments as a function of the number of matching residue pairs within this limited search space. Our alignment algorithm uses coordinates of alpha-carbon atoms to represent each amino acid residue and requires a total computation time of O(m(3) n(2)), where m and n denote the lengths of the protein sequences. This makes our method fast enough for comparisons of moderate-size proteins (fewer than approximately 800 residues) on current workstation-class computers and therefore addresses the need for a systematic analysis of multiple plausible shape similarities between two proteins using a widely accepted comparison metric.

Publication types

  • Comparative Study
  • Evaluation Study
  • Research Support, U.S. Gov't, Non-P.H.S.
  • Research Support, U.S. Gov't, P.H.S.
  • Validation Study

MeSH terms

  • Algorithms*
  • Amino Acid Sequence
  • Linear Models
  • Molecular Sequence Data
  • Muramidase / chemistry
  • Protein Conformation
  • Proteins / chemistry*
  • Proteins / genetics
  • Quality Control
  • Sequence Alignment / methods*
  • Sequence Analysis, Protein / methods*

Substances

  • Proteins
  • Muramidase