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DNA-Guided Assembly for Fibril Proteins

Author

Listed:
  • Alexandru Amărioarei

    (Faculty of Mathematics and Computer Science, University of Bucharest, 030018 Bucharest, Romania
    National Institute of Research and Development for Biological Sciences, Department of Bioinformatics, 060031 Bucharest, Romania)

  • Frankie Spencer

    (Computational Biomodeling Laboratory, Turku Centre for Computer Science and Department of Computer Science, Åbo Akademi University, 20500 Turku, Finland)

  • Gefry Barad

    (National Institute of Research and Development for Biological Sciences, Department of Bioinformatics, 060031 Bucharest, Romania)

  • Ana-Maria Gheorghe

    (National Institute of Research and Development for Biological Sciences, Department of Bioinformatics, 060031 Bucharest, Romania)

  • Corina Iţcuş

    (National Institute of Research and Development for Biological Sciences, Department of Bioinformatics, 060031 Bucharest, Romania)

  • Iris Tuşa

    (National Institute of Research and Development for Biological Sciences, Department of Bioinformatics, 060031 Bucharest, Romania)

  • Ana-Maria Prelipcean

    (National Institute of Research and Development for Biological Sciences, Cellular and Molecular Biology Department, 060031 Bucharest, Romania)

  • Andrei Păun

    (Faculty of Mathematics and Computer Science, University of Bucharest, 030018 Bucharest, Romania
    National Institute of Research and Development for Biological Sciences, Department of Bioinformatics, 060031 Bucharest, Romania)

  • Mihaela Păun

    (National Institute of Research and Development for Biological Sciences, Department of Bioinformatics, 060031 Bucharest, Romania
    Faculty of Administration and Business, University of Bucharest, 050663 Bucharest, Romania)

  • Alfonso Rodriguez-Paton

    (Departamento de Inteligencia Artificial, Universidad Politecnica de Madrid, 28040 Madrid, Spain)

  • Romică Trandafir

    (National Institute of Research and Development for Biological Sciences, Department of Bioinformatics, 060031 Bucharest, Romania)

  • Eugen Czeizler

    (National Institute of Research and Development for Biological Sciences, Department of Bioinformatics, 060031 Bucharest, Romania
    National Institute of Research and Development for Biological Sciences, Cellular and Molecular Biology Department, 060031 Bucharest, Romania)

Abstract

Current advances in computational modelling and simulation have led to the inclusion of computer scientists as partners in the process of engineering of new nanomaterials and nanodevices. This trend is now, more than ever, visible in the field of deoxyribonucleic acid (DNA)-based nanotechnology, as DNA’s intrinsic principle of self-assembly has been proven to be highly algorithmic and programmable. As a raw material, DNA is a rather unremarkable fabric. However, as a way to achieve patterns, dynamic behavior, or nano-shape reconstruction, DNA has been proven to be one of the most functional nanomaterials. It would thus be of great potential to pair up DNA’s highly functional assembly characteristics with the mechanic properties of other well-known bio-nanomaterials, such as graphene, cellulos, or fibroin. In the current study, we perform projections regarding the structural properties of a fibril mesh (or filter) for which assembly would be guided by the controlled aggregation of DNA scaffold subunits. The formation of such a 2D fibril mesh structure is ensured by the mechanistic assembly properties borrowed from the DNA assembly apparatus. For generating inexpensive pre-experimental assessments regarding the efficiency of various assembly strategies, we introduced in this study a computational model for the simulation of fibril mesh assembly dynamical systems. Our approach was based on providing solutions towards two main circumstances. First, we created a functional computational model that is restrictive enough to be able to numerically simulate the controlled aggregation of up to 1000s of elementary fibril elements yet rich enough to provide actionable insides on the structural characteristics for the generated assembly. Second, we used the provided numerical model in order to generate projections regarding effective ways of manipulating one of the the key structural properties of such generated filters, namely the average size of the openings (gaps) within these meshes, also known as the filter’s aperture. This work is a continuation of Amarioarei et al., 2018, where a preliminary version of this research was discussed.

Suggested Citation

  • Alexandru Amărioarei & Frankie Spencer & Gefry Barad & Ana-Maria Gheorghe & Corina Iţcuş & Iris Tuşa & Ana-Maria Prelipcean & Andrei Păun & Mihaela Păun & Alfonso Rodriguez-Paton & Romică Trandafir & , 2021. "DNA-Guided Assembly for Fibril Proteins," Mathematics, MDPI, vol. 9(4), pages 1-17, February.
    • Handle: RePEc:gam:jmathe:v:9:y:2021:i:4:p:404-:d:501781
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    References listed on IDEAS

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    1. Li Ding & Yanying Wei & Libo Li & Tao Zhang & Haihui Wang & Jian Xue & Liang-Xin Ding & Suqing Wang & Jürgen Caro & Yury Gogotsi, 2018. "MXene molecular sieving membranes for highly efficient gas separation," Nature Communications, Nature, vol. 9(1), pages 1-7, December.
    2. Luceno, Alberto, 2006. "Fitting the generalized Pareto distribution to data using maximum goodness-of-fit estimators," Computational Statistics & Data Analysis, Elsevier, vol. 51(2), pages 904-917, November.
    3. Erik Benson & Abdulmelik Mohammed & Johan Gardell & Sergej Masich & Eugen Czeizler & Pekka Orponen & Björn Högberg, 2015. "DNA rendering of polyhedral meshes at the nanoscale," Nature, Nature, vol. 523(7561), pages 441-444, July.
    4. Guoping Xiong & Pingge He & Zhipeng Lyu & Tengfei Chen & Boyun Huang & Lei Chen & Timothy S. Fisher, 2018. "Bioinspired leaves-on-branchlet hybrid carbon nanostructure for supercapacitors," Nature Communications, Nature, vol. 9(1), pages 1-11, December.
    5. Dutang, Christophe & Goulet, Vincent & Pigeon, Mathieu, 2008. "actuar: An R Package for Actuarial Science," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 25(i07).
    6. Anton Kuzyk & Robert Schreiber & Zhiyuan Fan & Günther Pardatscher & Eva-Maria Roller & Alexander Högele & Friedrich C. Simmel & Alexander O. Govorov & Tim Liedl, 2012. "DNA-based self-assembly of chiral plasmonic nanostructures with tailored optical response," Nature, Nature, vol. 483(7389), pages 311-314, March.
    7. Paul W. K. Rothemund, 2006. "Folding DNA to create nanoscale shapes and patterns," Nature, Nature, vol. 440(7082), pages 297-302, March.
    8. Kyle Lund & Anthony J. Manzo & Nadine Dabby & Nicole Michelotti & Alexander Johnson-Buck & Jeanette Nangreave & Steven Taylor & Renjun Pei & Milan N. Stojanovic & Nils G. Walter & Erik Winfree & Hao Y, 2010. "Molecular robots guided by prescriptive landscapes," Nature, Nature, vol. 465(7295), pages 206-210, May.
    9. Marie Laure Delignette-Muller & Christophe Dutang, 2015. "fitdistrplus : An R Package for Fitting Distributions," Post-Print hal-01616147, HAL.
    10. Grigory Tikhomirov & Philip Petersen & Lulu Qian, 2017. "Fractal assembly of micrometre-scale DNA origami arrays with arbitrary patterns," Nature, Nature, vol. 552(7683), pages 67-71, December.
    11. Vincent Goulet & Christophe Dutang & Mathieu Pigeon, 2008. "actuar : An R Package for Actuarial Science," Post-Print hal-01616144, HAL.
    12. Delignette-Muller, Marie Laure & Dutang, Christophe, 2015. "fitdistrplus: An R Package for Fitting Distributions," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 64(i04).
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