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Investigating large-amplitude protein loop motions as extreme events using recurrence interval analysis

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  • Karain, Wael I.

Abstract

We investigate large amplitude motions of the two key residues ASP49 and PHE142 in β-lactamase inhibitor protein BLIP as extreme events, using recurrence interval analysis. The recurrence intervals for distance returns between the centers of mass of these two residues over a period of 300 ns are calculated. We find that the probability distribution functions for these recurrence intervals above a range of positive threshold q>0, Pq(τ), show limited scaling with the mean recurrence interval τavgat each respective threshold as Pq(τ)=1τavgf(τ∕τavg). Half of the scaled distributions are fitted by a power law t−γ at the significance level of 1%, with γ’s ranging from 1.72 to 1.79 for the corresponding thresholds. A stretched exponential fit exp−(ττavg)γ, fails at the 1% significance level for all of the scaled distributions. The scaled distributions also show short term and long term memory behavior, which is removed by shuffling the distance return time series.

Suggested Citation

  • Karain, Wael I., 2019. "Investigating large-amplitude protein loop motions as extreme events using recurrence interval analysis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 520(C), pages 1-10.
  • Handle: RePEc:eee:phsmap:v:520:y:2019:i:c:p:1-10
    DOI: 10.1016/j.physa.2018.12.039
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    References listed on IDEAS

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    1. Hao Meng & Fei Ren & Gao-Feng Gu & Xiong Xiong & Yong-Jie Zhang & Wei-Xing Zhou & Wei Zhang, 2012. "Effects of long memory in the order submission process on the properties of recurrence intervals of large price fluctuations," Papers 1201.2825, arXiv.org.
    2. Fei Ren & Wei-Xing Zhou, 2010. "Recurrence interval analysis of trading volumes," Papers 1002.1653, arXiv.org.
    3. Zhi-Qiang Jiang & Gang-Jin Wang & Askery Canabarro & Boris Podobnik & Chi Xie & H. Eugene Stanley & Wei-Xing Zhou, 2018. "Short term prediction of extreme returns based on the recurrence interval analysis," Quantitative Finance, Taylor & Francis Journals, vol. 18(3), pages 353-370, March.
    4. Xie, Wen-Jie & Jiang, Zhi-Qiang & Zhou, Wei-Xing, 2014. "Extreme value statistics and recurrence intervals of NYMEX energy futures volatility," Economic Modelling, Elsevier, vol. 36(C), pages 8-17.
    5. Ren, Fei & Guo, Liang & Zhou, Wei-Xing, 2009. "Statistical properties of volatility return intervals of Chinese stocks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 388(6), pages 881-890.
    6. Bunde, Armin & F. Eichner, Jan & Havlin, Shlomo & Kantelhardt, Jan W., 2003. "The effect of long-term correlations on the return periods of rare events," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 330(1), pages 1-7.
    7. Rémy Chicheportiche & Anirban Chakraborti, 2014. "Copulas and time series with long-ranged dependencies," Post-Print hal-00977135, HAL.
    8. M. S. Santhanam & Holger Kantz, 2008. "Return interval distribution of extreme events and long term memory," Papers 0803.1706, arXiv.org.
    9. Lucheng Hong & Wantao Shu & Angela C. Chao, 2018. "Recurrence Interval Analysis on Electricity Consumption of an Office Building in China," Sustainability, MDPI, vol. 10(2), pages 1-15, January.
    10. Zhi-Qiang Jiang & Askery Canabarro & Boris Podobnik & H. Eugene Stanley & Wei-Xing Zhou, 2016. "Early warning of large volatilities based on recurrence interval analysis in Chinese stock markets," Quantitative Finance, Taylor & Francis Journals, vol. 16(11), pages 1713-1724, November.
    11. Fengzhong Wang & Kazuko Yamasaki & Shlomo Havlin & H. Eugene Stanley, 2005. "Scaling and memory of intraday volatility return intervals in stock market," Papers physics/0511101, arXiv.org.
    12. Eduardo G Altmann & Janet B Pierrehumbert & Adilson E Motter, 2009. "Beyond Word Frequency: Bursts, Lulls, and Scaling in the Temporal Distributions of Words," PLOS ONE, Public Library of Science, vol. 4(11), pages 1-7, November.
    13. R'emy Chicheportiche & Anirban Chakraborti, 2013. "A model-free characterization of recurrences in stationary time series," Papers 1302.3704, arXiv.org, revised Sep 2013.
    14. Katherine Henzler-Wildman & Dorothee Kern, 2007. "Dynamic personalities of proteins," Nature, Nature, vol. 450(7172), pages 964-972, December.
    Full references (including those not matched with items on IDEAS)

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