Volume 24, Issue 3
Minimum Energy Conformations of Self-Interacting Polymer Chains via Multipopulation Genetic Algorithms (MpGA)

Luis Olivares-Quiroz & Marcos A. González-Olvera

Commun. Comput. Phys., 24 (2018), pp. 810-829.

Published online: 2018-05

Preview Purchase PDF 9 1857
Export citation
  • Abstract

Identification of stable three-dimensional conformations in proteins and peptides that correspond to minima in potential and free energy hypersurfaces has been under intense scrutiny over the past decades since the paradigm structure-function was proposed [1]. This classical paradigm states that most of biologically active conformations in proteins and peptides can be associated with global minima energy states on the energy hypersurface of the polypeptide chain [2, 3]. In this work we discuss the onset of macroscopic minimum-energy conformations on small interacting peptides composed by only two types of residues: hydrophobic (A) or polar (B). Based on a previous work in 2D [4], we consider here an interacting three dimensional potential $V$ =$V_1$+$V_2$ where $V_1$ corresponds to a intramolecular bending potential between adjacent residues whereas $V_2$ is a Lennard-Jones (LJ) type intermolecular potential with both an attractive and repulsive part. In addition, the $V_2$ term can switch to repulsive or attractive depending on the type of pair interaction AA, AB or BB considered. As a novel approach to the standard geometric-based minimization methods [5–7], we propose a Multipopulation Genetic Algorithm (MpGA) as a minimization algorithm [8]. The central advantage of this approach is a wider search on the energy hypersurface. In order to test the validity of our method, we reproduced in excellent agreement the results previously obtained in 2D by [4]. Our results show that in three dimensions our method enlarges the number of stable macroscopic conformations found for a given polypeptide. As an example of the role played by the interacting pairs AB, AA and BB, we discuss as well the case of small diblock polymers and quantify the degree of compactness expected in the three dimensional structure as function of the composition of the chain.

  • Keywords

Protein folding, genetic algorithms, energy minimization, interacting heteropolymers, coarse-grained models.

  • AMS Subject Headings

92D20, 68T20, 92C05, 82C22, 82B30

  • Copyright

COPYRIGHT: © Global Science Press

  • Email address
  • BibTex
  • RIS
  • TXT
@Article{CiCP-24-810, author = {Luis Olivares-Quiroz , and Marcos A. González-Olvera , }, title = {Minimum Energy Conformations of Self-Interacting Polymer Chains via Multipopulation Genetic Algorithms (MpGA)}, journal = {Communications in Computational Physics}, year = {2018}, volume = {24}, number = {3}, pages = {810--829}, abstract = {

Identification of stable three-dimensional conformations in proteins and peptides that correspond to minima in potential and free energy hypersurfaces has been under intense scrutiny over the past decades since the paradigm structure-function was proposed [1]. This classical paradigm states that most of biologically active conformations in proteins and peptides can be associated with global minima energy states on the energy hypersurface of the polypeptide chain [2, 3]. In this work we discuss the onset of macroscopic minimum-energy conformations on small interacting peptides composed by only two types of residues: hydrophobic (A) or polar (B). Based on a previous work in 2D [4], we consider here an interacting three dimensional potential $V$ =$V_1$+$V_2$ where $V_1$ corresponds to a intramolecular bending potential between adjacent residues whereas $V_2$ is a Lennard-Jones (LJ) type intermolecular potential with both an attractive and repulsive part. In addition, the $V_2$ term can switch to repulsive or attractive depending on the type of pair interaction AA, AB or BB considered. As a novel approach to the standard geometric-based minimization methods [5–7], we propose a Multipopulation Genetic Algorithm (MpGA) as a minimization algorithm [8]. The central advantage of this approach is a wider search on the energy hypersurface. In order to test the validity of our method, we reproduced in excellent agreement the results previously obtained in 2D by [4]. Our results show that in three dimensions our method enlarges the number of stable macroscopic conformations found for a given polypeptide. As an example of the role played by the interacting pairs AB, AA and BB, we discuss as well the case of small diblock polymers and quantify the degree of compactness expected in the three dimensional structure as function of the composition of the chain.

}, issn = {1991-7120}, doi = {https://doi.org/10.4208/cicp.OA-2017-0217}, url = {http://global-sci.org/intro/article_detail/cicp/12282.html} }
TY - JOUR T1 - Minimum Energy Conformations of Self-Interacting Polymer Chains via Multipopulation Genetic Algorithms (MpGA) AU - Luis Olivares-Quiroz , AU - Marcos A. González-Olvera , JO - Communications in Computational Physics VL - 3 SP - 810 EP - 829 PY - 2018 DA - 2018/05 SN - 24 DO - http://dor.org/10.4208/cicp.OA-2017-0217 UR - https://global-sci.org/intro/article_detail/cicp/12282.html KW - Protein folding, genetic algorithms, energy minimization, interacting heteropolymers, coarse-grained models. AB -

Identification of stable three-dimensional conformations in proteins and peptides that correspond to minima in potential and free energy hypersurfaces has been under intense scrutiny over the past decades since the paradigm structure-function was proposed [1]. This classical paradigm states that most of biologically active conformations in proteins and peptides can be associated with global minima energy states on the energy hypersurface of the polypeptide chain [2, 3]. In this work we discuss the onset of macroscopic minimum-energy conformations on small interacting peptides composed by only two types of residues: hydrophobic (A) or polar (B). Based on a previous work in 2D [4], we consider here an interacting three dimensional potential $V$ =$V_1$+$V_2$ where $V_1$ corresponds to a intramolecular bending potential between adjacent residues whereas $V_2$ is a Lennard-Jones (LJ) type intermolecular potential with both an attractive and repulsive part. In addition, the $V_2$ term can switch to repulsive or attractive depending on the type of pair interaction AA, AB or BB considered. As a novel approach to the standard geometric-based minimization methods [5–7], we propose a Multipopulation Genetic Algorithm (MpGA) as a minimization algorithm [8]. The central advantage of this approach is a wider search on the energy hypersurface. In order to test the validity of our method, we reproduced in excellent agreement the results previously obtained in 2D by [4]. Our results show that in three dimensions our method enlarges the number of stable macroscopic conformations found for a given polypeptide. As an example of the role played by the interacting pairs AB, AA and BB, we discuss as well the case of small diblock polymers and quantify the degree of compactness expected in the three dimensional structure as function of the composition of the chain.

Luis Olivares-Quiroz & Marcos A. González-Olvera. (2020). Minimum Energy Conformations of Self-Interacting Polymer Chains via Multipopulation Genetic Algorithms (MpGA). Communications in Computational Physics. 24 (3). 810-829. doi:10.4208/cicp.OA-2017-0217
Copy to clipboard
The citation has been copied to your clipboard