Protein-Folding Analysis Using Features Obtained by Persistent Homology

Takashi Ichinomiya, Ippei Obayashi, Yasuaki Hiraoka

Research output: Contribution to journalArticlepeer-review

2 Citations (Scopus)

Abstract

Understanding the protein-folding process is an outstanding issue in biophysics; recent developments in molecular dynamics simulation have provided insights into this phenomenon. However, the large freedom of atomic motion hinders the understanding of this process. In this study, we applied persistent homology, an emerging method to analyze topological features in a data set, to reveal protein-folding dynamics. We developed a new, to our knowledge, method to characterize the protein structure based on persistent homology and applied this method to molecular dynamics simulations of chignolin. Using principle component analysis or nonnegative matrix factorization, our analysis method revealed two stable states and one saddle state, corresponding to the native, misfolded, and transition states, respectively. We also identified an unfolded state with slow dynamics in the reduced space. Our method serves as a promising tool to understand the protein-folding process.

Original languageEnglish
Pages (from-to)2926-2937
Number of pages12
JournalBiophysical Journal
Volume118
Issue number12
DOIs
Publication statusPublished - Jun 16 2020
Externally publishedYes

ASJC Scopus subject areas

  • Biophysics

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