A Genetic Algorithm That Seeks Native States of Peptides and Proteins

Overview

Journal Biophys J

Publisher Cell Press

Specialty Biophysics

Date 1995 Aug 1

PMID 8527647

Citations 6

Authors

S Sun

Affiliations

Soon will be listed here.

Abstract

We describe a computer algorithm to predict native structures of proteins and peptides from their primary sequences, their known native radii of gyration, and their known disulfide bonding patterns, starting from random conformations. Proteins are represented as simplified real-space main chains with single-bead side chains. Nonlocal interactions are taken from structural database-derived statistical potentials, as in an earlier treatment. Local interactions are taken from simulations of (phi, psi) energy surfaces for each amino acid generated using the Biosym Discover program. Conformational searching is done by a genetic algorithm-based method. Reasonable structures are obtained for melittin (a 26-mer), avian pancreatic polypeptide inhibitor (a 36-mer), crambin (a 46-mer), apamin (an 18-mer), tachyplesin (a 17-mer), C-peptide of ribonuclease A (a 13-mer), and four different designed helical peptides. A hydrogen bond interaction was tested and found to be generally unnecessary for helical peptides, but it helps fold some sheet regions in these structures. For the few longer chains we tested, the method appears not to converge. In those cases, it appears to recover native-like secondary structures, but gets incorrect tertiary folds.

Citing Articles

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Exploring conformational space using a mean field technique with MOLS sampling.

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Protein structure prediction in a 210-type lattice model: parameter optimization in the genetic algorithm using orthogonal array.

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Low-resolution structures of proteins in solution retrieved from X-ray scattering with a genetic algorithm.

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Application of a genetic algorithm in the conformational analysis of methylene-acetal-linked thymine dimers in DNA: comparison with distance geometry calculations.

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