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A multiscale modeling approach to predict the sequence-dependent shape and mechanical properties of DNA nanostructures : DNA 나노구조체의 염기서열에 따른 형상 및 역학적 특성을 예측하는 멀티스케일 모델링 방법

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dc.contributor.advisor김도년-
dc.contributor.author이재영-
dc.date.accessioned2020-10-13T02:40:37Z-
dc.date.available2020-10-13T02:40:37Z-
dc.date.issued2020-
dc.identifier.other000000161256-
dc.identifier.urihttps://hdl.handle.net/10371/169156-
dc.identifier.urihttp://dcollection.snu.ac.kr/common/orgView/000000161256ko_KR
dc.description학위논문 (박사) -- 서울대학교 대학원 : 공과대학 기계항공공학부, 2020. 8. 김도년.-
dc.description.abstractDNA nanotechnology is a rising field that designs, manufactures, and analyzes DNA nanostructures using the self-assembly principle, creating various related applications. DNA nanostructures are based on the connection between sequences (A, T, G, and C), and its mechanical properties are derived from interactions between atoms. Therefore, to completely understand the mechanical characteristics of DNA nanostructures, all-atomic simulation is required. However, in general, a DNA nanostructure is composed of connections between thousands of sequences in a salt solution, and in order to simulate it on an atomic scale, the atomic system containing billions of degrees of freedom should be solved numerically, which is almost impossible. Accordingly, coarse-grained models have been developed to analyze DNA nanostructures by reducing the degree of freedom, but there are still difficulties to achieve both high efficiency and accuracy of the analysis. Here, this study presents a method to rapidly predict DNA nanostructures at the nanoscale accuracy through multiscale modeling. First, the connections between sequences were classified, and molecular dynamics simulations of a reduced system including them were performed to quantify the sequence-dependent mechanical properties. Next, a finite element model was developed to embody the unique properties, and electrostatic repulsion inside the structure due to the negative charge of DNA in the solution. The assembled finite elements incorporate all the mechanical properties at the sequence-level. Through numerical procedure and normal mode analysis, the equilibrium shape and dynamic properties are rapidly and accurately predicted. The proposed approach can be applied to the analysis of nucleic-acid-based structures and extended to multiscale modeling methods of biomaterials.-
dc.description.abstractDNA 나노기술은 DNA의 자가조립원리를 이용해 나노 해상도의 정밀한 구조체를 설계 및 제작, 해석하는 분야로, DNA 나노구조체를 이용한 수많은 응용 연구가 지속적으로 제시되고 있다. DNA 나노구조체는 기본 염기(A, T, G, C) 간의 연결체로서, 이에 따른 국소적인 역학적 물성은 염기를 구성하는 원자 간의 상호작용에 의해 발현된다. 따라서 DNA 나노구조체의 역학적 거동을 온전히 이해하기 위해서는 나노 스케일의 전원자 시뮬레이션이 필요하다. 그러나 일반적으로 DNA 나노구조체는 염이 포함된 수용액 환경에서 수천 개의 염기가 연결되어 구성되므로, 이를 원자 스케일에서 해석하기 위해서는 억 단위의 원자 자유도 문제를 수치적으로 해결해야 하여, 시스템 전체의 전원자 시뮬레이션은 거의 불가능하다. 이에 자유도를 줄여 DNA 나노구조체를 해석하기 위한 여러 축소모델이 개발되고 있으나, 해석의 높은 효율성과 정확성을 모두 달성하려면 여전히 난제가 많다. 이에 본 연구에서는 멀티스케일 모델링을 통해 염기 스케일의 정확도로 DNA 나노구조체를 효율적으로 해석하는 방법을 제시한다. 먼저 염기 간의 다양한 연결 방식을 분류하고, 이를 포함한 작은 시스템의 분자동역학 시뮬레이션을 통해, 염기에 따른 역학적 특성을 정량화하고 물성 라이브러리를 구축하였다. 다음으로 염기 간의 연결에 따른 고유한 역학적 물성과 수용액 환경에서 DNA의 음전하로 인해 발생하는 구조체 내부의 정전기적 반발력을 완전히 반영하는 유한요소 모델을 개발하여, DNA 나노구조체를 구성하는 모든 염기 간의 연결과 구조체 내부의 상호작용을 유한요소 연결체로 변환하였다. 구성된 유한요소 연결체는 염기 스케일의 해상도로 DNA 나노구조체의 역학적 특성을 모두 내포하고 있어, 비선형 수치해석과 고유모드 분석을 통해 DNA 나노구조체의 염기서열에 따른 평형 형상과 동적 특성을 정확하고 빠르게 예측할 수 있다. 본 연구에서 제시하는 기법은 핵산 기반의 구조체 해석에 쉽게 적용할 수 있으며, 다양한 바이오 재료의 멀티스케일 모델링 기술로 확장될 수 있다.-
dc.description.tableofcontents1. Introduction 28
1.1. Background and objectives 28
1.2. Research outline 30
1.3. Overview of the multiscale modeling approach 32
2. Investigation of the mechanical properties of DNA 37
2.1. Abstract 37
2.2. Methods 38
2.2.1. Generation of DNA oligomers 38
2.2.2. Molecular dynamics simulations of DNA oligomers 41
2.2.3. Overview of characterizing mechanical properties 43
2.2.4. Mechanical properties of a base-pair step 57
2.2.5. Elastic theory for the base-pair step 60
2.2.6. Equivalent isotropic rigidities in bending and shearing 64
2.3. Mechanical rigidities of base-pair steps 66
2.4. Mechanical coupling coefficients of base-pair steps 72
2.5. Effects of simulation parameters and neighboring sequence 75
3. Multiscale modeling of DNA nanostructures 90
3.1. Abstract 90
3.2. Finite element framework for structural motifs 91
3.2.1. Operators 92
3.2.2. The co-rotational formulation of the two-node beam element 93
3.2.3. Internal force vector in the global coordinate 96
3.2.4. Stiffness matrix in the global coordinate 99
3.3. Local stiffness matrix and internal force vector 101
3.3.1. Net displacement in the local coordinate 102
3.3.2. Displacement field 103
3.3.3. Strain field 104
3.3.4. Strain energy 107
3.3.5. Stiffness matrix in the local coordinate 109
3.3.6. Internal force vector in the local coordinate 110
3.4. Intrinsic properties of the base-pair step 111
3.4.1. Relative geometric parameters in the 3DNA definition 111
3.4.2. Relative geometry and mechanical properties 115
3.4.3. Modification of triad axes for beam element 117
3.4.4. Intrinsic properties of the BP step 118
3.5. Intrinsic properties of the crossover step 130
3.5.1. Modification of triad axes in the crossover step 130
3.5.2. Triad angle correction 131
3.5.3. Intrinsic properties of the crossover step 132
3.6. Characterization and modeling of single-stranded DNA 142
3.6.1. Intrinsic end-to-end length 142
3.6.2. Single-stranded DNA properties 145
3.7. Finite element framework for electrostatic interaction 147
3.7.1. Electrostatic interaction model 147
3.7.2. Finite element model of electrostatic interaction 148
3.8. Estimation of characteristic values on the electrostatic interaction 152
3.9. Construction of initial configuration 154
3.9.1. General description 154
3.9.2. Initial BP triads for the 2-helix-bundle structure 155
3.9.3. Initial configuration of structural elements for base-pair steps 158
3.9.4. Initial configuration of structural elements for crossover steps 160
3.9.5. Generation of electrostatic elements 161
3.10. Nonlinear solution procedure 162
3.10.1. Overview of the solution procedure 162
3.10.2. Element properties in the initial and final configuration 164
3.10.3. Boundary condition 165
3.10.4. Control of properties in structural elements 166
3.10.5. Control of the number of electrostatic elements 167
3.10.6. Iterative solution methods 168
3.10.7. Subdivision of time interval 170
3.10.8. Condition number of stiffness matrix 172
3.11. Molecular dynamics simulation of DNA nanostructures 173
4. Structural analysis of DNA nanostructures 183
4.1. Abstract 183
4.2. Shape prediction of monomeric structures 184
4.2.1. Electrostatic effects on the structural shape 184
4.2.2. Control of included angle in hinge structures 187
4.2.3. Structural distortion by the mean helicity 189
4.2.4. Bending and twist control by inserting or deleting base-pairs 193
4.3. Shape prediction of hierarchical assemblies 200
4.3.1. Control of opening angle in geometrically-constrained V brick 200
4.3.2. Assessment of the twist-correction effect in the tube structure 204
4.3.3. Prediction of hierarchically assembled polyhedral structures 206
4.4. Structural details at the base-pair level 212
4.4.1. The dimension of the pointer structure 212
4.4.2. Prediction of the base-pair and crossover configuration 216
5. Twist control of DNA nanostructures through sequence design 218
5.1. Abstract 218
5.2. Methods 219
5.2.1. Mechanical analysis of DNA structures with base-pair insertion 219
5.2.2. Design and simulation of twisted DNA origami structures 223
5.2.3. Molecular dynamics simulation of 6-helix-bundle blocks 228
5.2.4. Measurement of the twist angle of 6-helix-bundle structures 229
5.2.5. CanDo simulation based on finite element method 231
5.2.6. Relation of the trans ratio with the global twist angle 233
5.2.7. Preparation of DNA origami structures 239
5.2.8. Image analysis using atomic force microscopy 240
5.2.9. Agarose gel electrophoresis 249
5.2.10. Comparison of Bio-RP and PAGE in the purification of staples 250
5.3. Twist control of DNA nanostructures by programming nick sequences 253
5.3.1. Sequences design to control the twist of DNA nanostructure 254
5.3.2. Prediction and experimental validation of the global twist angle 257
6. Dynamic characteristics of DNA nanostructures 260
6.1. Abstract 260
6.2. Methods 261
6.2.1. Normal mode analysis 261
6.2.2. Root-mean-square fluctuation and correlation coefficients 263
6.3. Prediction of structural fluctuation 267
6.4. Prediction of correlation coefficients 270
7. Global mechanical rigidities of DNA nanostructures 272
7.1. Abstract 272
7.2. Methods 273
7.2.1. Estimation of persistence length from normal mode analysis 273
7.2.2. Theoretical estimation of persistence lengths 278
7.3. Prediction of bending and torsional persistence length 281
8. Conclusion 291
A. SNUPI (Structured NUcleic acids Programming Interface) 292
A.1. System requirement 292
A.2. Preparation for the analysis 293
A.3. General procedure 294
A.4. Examples 295
A.4.1. Example 1: Simple structural analysis using the default option 295
A.4.2. Example 2: Prediction of structural and dynamic properties 299
A.5. Analysis options 304
A.5.1. Finite element analysis option 304
A.5.2. Base-pair and crossover steps options 305
A.5.3. Single-stranded DNA options 306
A.5.4. Electrostatic interaction options 308
A.5.5. Normal mode analysis options 311
A.5.6. RMSF and correlation options 312
A.5.7. Configuration plot options 314
A.5.8. Output file options 315
Bibliography 317
Abstract in Korean 325
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dc.language.isoeng-
dc.publisher서울대학교 대학원-
dc.subjectDNA nanotechnology-
dc.subjectDNA nanostructure-
dc.subjectMechanical properties-
dc.subjectMultiscale modeling-
dc.subjectMolecular dynamics simulation-
dc.subjectFinite element analysis-
dc.subject.ddc621-
dc.titleA multiscale modeling approach to predict the sequence-dependent shape and mechanical properties of DNA nanostructures-
dc.title.alternativeDNA 나노구조체의 염기서열에 따른 형상 및 역학적 특성을 예측하는 멀티스케일 모델링 방법-
dc.typeThesis-
dc.typeDissertation-
dc.contributor.AlternativeAuthorJae Young Lee-
dc.contributor.department공과대학 기계항공공학부-
dc.description.degreeDoctor-
dc.date.awarded2020-08-
dc.identifier.uciI804:11032-000000161256-
dc.identifier.holdings000000000043▲000000000048▲000000161256▲-
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