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Mapping the intramolecular signal propagation pathways in protein using Bayesian change point analysis of atomic motions
Institution:1. Google Inc., 1600 Amphitheatre Parkway, Mountain View, CA 94043, USA;2. Texas College, 2404 N. Grand Avenue, Tyler, TX 75702, USA;1. Laboratory of Virology and Vaccinology, Division of Biomedical Research, National Institute of Biomedical Innovation, Ibaraki, Osaka, Japan;2. National Institute of Biomedical Innovation, Ibaraki, Osaka, Japan;3. Division of Clinical Virology, Kobe University Graduate School of Medicine, Kobe, Japan;1. State Key Laboratory of Medicinal Chemical Biology and College of Pharmacy, Nankai University, Tianjin 300071, People’s Republic of China;2. Tianjin Key Laboratory of Molecular Drug Research, Nankai University, Tianjin 300071, People’s Republic of China;3. College of Biotechnology, Tianjin University of Science & Technology, TEDA (Tianjin Economic-Technological Development Area), Tanggu District, Tianjin 300457, People’s Republic of China;1. Chongqing Key Laboratory of Multi-scale Manufacturing Technology, Chongqing Institute of Green and Intelligent Technology, Chinese Academy of Sciences, Chongqing 400714, China;2. College of Mechanical and Electrical Engineering, East China Jiaotong University, Nanchang 330013, China;3. College of Chemistry & Environmental Science, Hebei University, Baoding 071000, China;1. Graduate School of Life and Environmental Sciences, Kyoto Prefectural University, 1-5 Hangi-cho, Shimogamo, Sakyo-ku, Kyoto, Kyoto 606-8522, Japan;2. Graduate School of Life and Environmental Sciences, Osaka Prefecture University, 1-1 Gakuen-cho, Naka-ku, Sakai, Osaka 599-8531, Japan
Abstract:We propose to use change points of atomic positions in the molecular dynamics trajectory as indicators of the propagating signals in protein. We designate these changes as signals because they can propagate within the molecule in the form of “perturbation wave”, transmit energy or information between different parts of protein, and serve as allosteric signals. We found that change points can distinguish between thermal fluctuations of atoms (noise) and signals in a protein despite the differences in the motility of amino acid residues. Clustering of the spatially close residues that were experiencing change points close in time, allowed us to map pathways of signal propagation in a protein at the atomic level of resolution. We propose a potential mechanism for the origin of the signal and its propagation that relies on the autonomic coherence resonance in atomic fluctuations. According to this mechanism, random synchronization of fluctuations of neighboring atoms results in a resonance, which increases amplitude of vibration of these atoms. This increase can be transmitted to the atoms colliding with the resonant atoms, leading to the propagating signal. The wavelet-based coherence analysis of the inter-atomic distances between carbon-alpha atoms and surrounding atoms for the residue pairs that belong to the same communication pathway allowed us to find time periods with temporarily locked phases, confirming the occurrence of conditions for resonance. Analysis of the mapped pathways demonstrated that they form a network that connects different regions of the protein.
Keywords:Bayesian change point analysis  Protein  Molecular dynamics  Intramolecular signal propagation  Wavelet coherence  Stochastic resonance
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