Modeling Nucleic Acids at the Residue-Level Resolution

Leonarski, Filip; Trylska, Joanna

doi:10.1007/978-3-642-28554-7_5

Cited by 5 publications

(5 citation statements)

References 129 publications

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“…The coarse-grained (CG) models, where superatoms represent groups of atoms or even whole molecules, decrease the computational cost significantly. [23][24][25][26][27][28] The dynamics of single-stranded DNA translocation through a nanopore were studied by Guy et al [29] However, that model was not optimized to study the unzipping process. Therefore, we explored the kinetics of DNA unzipping using our CG model, [30] which allows simulations with explicit solvent and ions.…”

Section: Introductionmentioning

confidence: 99%

Diffusive dynamics of DNA unzipping in a nanopore

Stachiewicz

Molski

2015

J Comput Chem

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When an electric field is applied to an insulating membrane, movement of charged particles through a nanopore is induced. The measured ionic current reports on biomolecules passing through the nanopore. In this work, we explored the kinetics of DNA unzipping in a nanopore using our coarse-grained model (Stachiewicz and Molski, J. Comput. Chem. 2015, 36, 947). Coarse graining allowed a more detailed analysis for a wider range of parameters than all-atom simulations. Dependence of the translocation mode (unzipping or distortion) on the pore diameter was examined, and the threshold voltages were estimated. We determined the potential of mean force, position-dependent diffusion coefficient, and position-dependent effective charge for the DNA unzipping. The three molecular profiles were correlated with the ionic current and molecular events. On the unzipping/translocation force profile, two energy maxima were found, one of them corresponding to the unzipping, and the other to the translocation barriers. The unzipping kinetics were further explored using Brownian dynamics.

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Section: Introductionmentioning

confidence: 99%

Diffusive dynamics of DNA unzipping in a nanopore

Stachiewicz

Molski

2015

J Comput Chem

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“…Molecular dynamics (MD) simulations can provide detailed information on the molecular mechanism of translocation and unzipping. The coarse-grained (CG) models, where superatoms represent groups of atoms or even whole molecules, significantly reduce the computational time. − …”

Section: Introductionmentioning

confidence: 99%

Sequence-Dependent Unzipping Dynamics of DNA Hairpins in a Nanopore

Stachiewicz

Molski

2019

J. Phys. Chem. B

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By applying an electric field to an insulating membrane, movement of charged particles through a nanopore can be induced. The measured ionic current reports on biomolecules passing through the nanopore. In this paper, we explore the sequence-dependent dynamics of DNA unzipping using our recently developed coarse-grained model. We estimated three molecular profiles (the potential of mean force, position-dependent diffusion coefficient, and positiondependent effective charge) for the DNA unzipping of four hairpins with different sequences. We found that the molecular profiles are correlated with the ionic current and molecular events. We also explored the unzipping kinetics using Brownian dynamics. We found that the effect of hairpin structure on the unzipping/translocation times is not only energetic (weaker hairpins unzip more quickly) but also kinetic (different unzipping and translocation pathways play an important role).

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“…Furthermore, the exploration of the conformational phase space is intrinsically enhanced as a consequence of smoothing of the free energy surface. Various CG models for polypeptides and nucleic acids have been designed for and successfully used in MD simulations (e.g., refs − or in review articles − ). Nevertheless, it is difficult to combine accuracy, transferability and predictivity of these models in such a small number of parameters.…”

Section: Introductionmentioning

confidence: 99%

“…Coarse-grained RNA models differ in the number and placement of the interacting centers and the functional forms associated with the force fields terms. , The FF is chosen based on a particular application and biological problem one wants to examine. Some FFs aim for predicting a 3D structure of RNA, − and others have been designed to determine the internal dynamics of an already folded RNA. − Universality of the models decreases with the reduction of degrees of freedom.…”

Section: Introductionmentioning

confidence: 99%

“…The FF transferability depends on many factors such as the number of beads and their placement and explicitly represented interactions. The procedure to design a FF is often based on manual trial and error tests driven by the knowledge of physics and chemistry . We propose to replace these time-consuming procedures by automatic design and parametrization.…”

Section: Introductionmentioning

confidence: 99%

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Evolutionary Algorithm in the Optimization of a Coarse-Grained Force Field

Leonarski

Trovato

Tozzini

et al. 2013

J. Chem. Theory Comput.

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Simulations using residue-scale coarse-grained models of biomolecules are less computationally demanding than simulations employing full-atomistic force fields. However, the coarse-grained models are often difficult and tedious to parametrize for certain applications. Therefore, a systematic and objective method to help develop or adapt the coarse-grained models is needed. We present an automatic method that implements an evolutionary algorithm to find a set of optimal force field parameters for a one-bead coarse-grained model. In addition to an optimized force field, parameter correlations and significance of the potential energy terms can be determined. The method is applied to two classes of problems: the dynamics of an RNA helix and the RNA structure prediction.

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Modeling Nucleic Acids at the Residue-Level Resolution

Cited by 5 publications

References 129 publications

Diffusive dynamics of DNA unzipping in a nanopore

Diffusive dynamics of DNA unzipping in a nanopore

Sequence-Dependent Unzipping Dynamics of DNA Hairpins in a Nanopore

Evolutionary Algorithm in the Optimization of a Coarse-Grained Force Field

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