Mechanical Mass-Spring Model for Understanding Globular Motion of Proteins

J. I. Kim, K. Eom, Sung Soo Na

Research output: Contribution to journalArticlepeer-review

Abstract

The conformational (structural) change of proteins plays an essential role in their functions. Experiments have been conducted to try to understand the conformational change of proteins, but they have not been successful in providing information on the atomic scale. Simulation methods have been developed to understand the conformational change at an atomic scale in detail. Coarse-grained methods have been developed to calculate protein dynamics with computational efficiency when compared with than all-atom models. A structure-based mass-spring model called the elastic network model (ENM) showed excellent performance in various protein studies. Coarse-grained ENM was modified in various ways to improve the computational efficiency, and consequently to reduce required computational cost for studying the large-scale protein structures. Our previous studies report a modified mass-spring model, which was developed based on condensation method applicable to ENM, and show that the model is able to accurately predict the fluctuation behavior of proteins. We applied this modified mass-spring model to analyze the conformational changes in proteins. We consider two model proteins as an example, where these two proteins exhibit different functions and molecular sizes. It is shown that the modified mass-spring model allows for accurately predicting the pathways of conformation changes for proteins. Our model provides structural insights into the conformation change of proteins related to the biological functions of large protein complexes.

Original languageEnglish
Pages (from-to)1-7
Number of pages7
JournalJournal of Mechanics
DOIs
Publication statusAccepted/In press - 2016 Jan 25

Keywords

  • Condensation method
  • Conformation change
  • Mass-spring model
  • Normal mode analysis

ASJC Scopus subject areas

  • Mechanical Engineering
  • Condensed Matter Physics
  • Applied Mathematics

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