DNA-Guided Assembly for Fibril Proteins

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 and Eugen Czeizler
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Alexandru Amărioarei: Faculty of Mathematics and Computer Science, University of Bucharest, 030018 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
Mihaela Păun: National Institute of Research and Development for Biological Sciences, Department of Bioinformatics, 060031 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

Mathematics, 2021, vol. 9, issue 4, 1-17

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.

Keywords: DNA nanotechnology; DNA-guided assembly; self-assembly system; computational modeling; numerical simulations; structure prediction (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2021
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