Predicting three-dimensional structure of protein fragments from dihedral angle propensities and molecular dynamics

Jaine K. Blayney, Piyush C. Ojha, Mary Shapcott

Research output: Contribution to journalArticlepeer-review

1 Citation (Scopus)

Abstract

Incorporating the existing knowledge of protein structural preferences, e.g., amino acid angle frequencies, in structure prediction have proven to be less successful with smaller peptides. In this work, we compare the effectiveness of backbone angle propensity libraries derived from two protein data sets: one consisting of proteins of unrestricted lengths; the second containing proteins ranging in size from 40 to 75 residues. Model structures for 29 target peptides are predicted using a threading algorithm and their stability evaluated using in vacuo molecular dynamics simulations. Structures derived from the data set consisting of smaller proteins outperformed those developed from that unrestricted by protein length.

Original languageEnglish
Pages (from-to)146-163
Number of pages18
JournalInternational Journal of Computational Biology and Drug Design
Volume3
Issue number2
DOIs
Publication statusPublished - 01 Sep 2010
Externally publishedYes

Keywords

  • Amino acid propensities
  • Proteins
  • Tertiary structure prediction

ASJC Scopus subject areas

  • Drug Discovery
  • Computer Science Applications

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