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Design of sequences with good folding properties in coarse-grained protein models

Irbäck, A LU ; Peterson, C LU ; Potthast, F LU and Sandelin, E LU (1999) In Structure 7(3). p.60-347
Abstract

BACKGROUND: Designing amino acid sequences that are stable in a given target structure amounts to maximizing a conditional probability. A straightforward approach to accomplishing this is a nested Monte Carlo where the conformation space is explored over and over again for different fixed sequences; this requires excessive computational demand. Several approximate attempts to remedy this situation, based on energy minimization for fixed structure or high-T expansions, have been proposed. These methods are fast but often not accurate, as folding occurs at low T.

RESULTS: We have developed a multisequence Monte Carlo procedure where both sequence and conformational space are simultaneously probed with efficient prescriptions for... (More)

BACKGROUND: Designing amino acid sequences that are stable in a given target structure amounts to maximizing a conditional probability. A straightforward approach to accomplishing this is a nested Monte Carlo where the conformation space is explored over and over again for different fixed sequences; this requires excessive computational demand. Several approximate attempts to remedy this situation, based on energy minimization for fixed structure or high-T expansions, have been proposed. These methods are fast but often not accurate, as folding occurs at low T.

RESULTS: We have developed a multisequence Monte Carlo procedure where both sequence and conformational space are simultaneously probed with efficient prescriptions for pruning sequence space. The method is explored on hydrophobic/polar models. First we discuss short lattice chains in order to compare with exact data and with other methods. The method is then successfully applied to lattice chains with up to 50 monomers and to off-lattice 20mers.

CONCLUSIONS: The multisequence Monte Carlo method offers a new approach to sequence design in coarse-grained models. It is much more efficient than previous Monte Carlo methods, and is, as it stands, applicable to a fairly wide range of two-letter models.

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Please use this url to cite or link to this publication:
author
organization
publishing date
type
Contribution to journal
publication status
published
keywords
Energy Metabolism, Monte Carlo Method, Protein Conformation, Protein Folding
in
Structure
volume
7
issue
3
pages
14 pages
publisher
Cell Press
external identifiers
  • Scopus:0033103164
ISSN
0969-2126
language
English
LU publication?
yes
id
6e918aaa-2115-41b4-8ba8-892ff71383fd
date added to LUP
2016-08-17 16:28:57
date last changed
2016-10-13 05:12:28
@misc{6e918aaa-2115-41b4-8ba8-892ff71383fd,
  abstract     = {<p>BACKGROUND: Designing amino acid sequences that are stable in a given target structure amounts to maximizing a conditional probability. A straightforward approach to accomplishing this is a nested Monte Carlo where the conformation space is explored over and over again for different fixed sequences; this requires excessive computational demand. Several approximate attempts to remedy this situation, based on energy minimization for fixed structure or high-T expansions, have been proposed. These methods are fast but often not accurate, as folding occurs at low T.</p><p>RESULTS: We have developed a multisequence Monte Carlo procedure where both sequence and conformational space are simultaneously probed with efficient prescriptions for pruning sequence space. The method is explored on hydrophobic/polar models. First we discuss short lattice chains in order to compare with exact data and with other methods. The method is then successfully applied to lattice chains with up to 50 monomers and to off-lattice 20mers.</p><p>CONCLUSIONS: The multisequence Monte Carlo method offers a new approach to sequence design in coarse-grained models. It is much more efficient than previous Monte Carlo methods, and is, as it stands, applicable to a fairly wide range of two-letter models.</p>},
  author       = {Irbäck, A and Peterson, C and Potthast, F and Sandelin, E},
  issn         = {0969-2126},
  keyword      = {Energy Metabolism,Monte Carlo Method,Protein Conformation,Protein Folding},
  language     = {eng},
  month        = {03},
  number       = {3},
  pages        = {60--347},
  publisher    = {ARRAY(0x923e890)},
  series       = {Structure},
  title        = {Design of sequences with good folding properties in coarse-grained protein models},
  volume       = {7},
  year         = {1999},
}