Approaches for studying RNA aptamers with molecular dynamics simulation

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2019-01-01
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Yan, Shuting
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Monica H. Lamm
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Chemical and Biological Engineering

The function of the Department of Chemical and Biological Engineering has been to prepare students for the study and application of chemistry in industry. This focus has included preparation for employment in various industries as well as the development, design, and operation of equipment and processes within industry.Through the CBE Department, Iowa State University is nationally recognized for its initiatives in bioinformatics, biomaterials, bioproducts, metabolic/tissue engineering, multiphase computational fluid dynamics, advanced polymeric materials and nanostructured materials.

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The Department of Chemical Engineering was founded in 1913 under the Department of Physics and Illuminating Engineering. From 1915 to 1931 it was jointly administered by the Divisions of Industrial Science and Engineering, and from 1931 onward it has been under the Division/College of Engineering. In 1928 it merged with Mining Engineering, and from 1973–1979 it merged with Nuclear Engineering. It became Chemical and Biological Engineering in 2005.

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1913 - present

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  • Department of Chemical Engineering (1913–1928)
  • Department of Chemical and Mining Engineering (1928–1957)
  • Department of Chemical Engineering (1957–1973, 1979–2005)
    • Department of Chemical and Biological Engineering (2005–present)

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The objective of this dissertation is to study RNA aptamers with molecular dynamics simulation. It addresses fundamental challenges associated with RNA aptamers that can be investigated via molecular dynamics simulation, including the unavailability of 3D structures for the apo state, the challenge of ensuring good sampling for a flexible molecule, and the uncertainties that accompany molecular properties. The results presented in this dissertation focus on the application of multiple independent simulations to address these issues. I present results from multiple independent molecular dynamics simulations that are started from selected de novo predicted structures, according to experimentally determined base stacking, as a workflow to characterize the flexible apo state of an aptamer. I systematically investigate the sampling of multiple independent simulations by studying the nonlinear dynamic behavior, including principal component analysis and multivariate recurrent quantification analysis. I further propose a simulation assessment approach based on the root mean square deviation (RMSD) matrix eigenvalue and estimate molecular properties of interest with rigorous statistical analysis.

I first develop a workflow that combines computational modeling and fluorescence experiments to study the structure and dynamics of the aptamer apo state. The selected predicted structures pass rounds of clustering and satisfy the stacking condition of critical bases in apo state determined from experiments. Multiple independent simulations from these selected structures effectively achieve better sampling than using the available NMR complex structure with ligand removed. It is also noticed that when the backbone is well aligned, a different base at the same position might also be potential binding site. This provides insight to the ligand binding mechanism, specifically, whether the flexible terminal loop adjust its whole structure or a critical base flips to fit the ligand.

With the evidence that multiple molecular dynamics simulations can be used to investigate the conformation of aptamer for situations where a 3D structure is not available, I next investigate how well multiple independent simulations from different initial conformations sample the conformational space. The sampling of simulations started from different predicted structures is compared both qualitatively and quantitatively. The projection of sampled structures on selected principal components axes shows overlap among different groups of simulations as well as regions visited only by a specific group. The sampling of different groups of simulations is then further compared via recurrence quantification analysis using the top 10 principal components. The minimum length required for each independent simulation is determined. The number of independent simulations for sufficient sampling of the system is recommended based on the standard error of the mean for the molecular property of interest.

Once the number of independent simulations and the minimum length of each simulation are known, it is necessary to systematically perform rigorous statistical analysis on any property of interest. Examination of the simulation quality can be done by looking at the progress of the largest eigenvalue from the RMSD matrix. Simulations or sections of simulations can be grouped as repeated measurements or enrichment, which further determines the uncertainty calculation. I recommend such a procedure because the sampling achieved with molecular dynamics simulations performed with limited timescales might display dependence on the initial conditions. This would lead to an outcome where different simulations could exhibit different error. I urge that care be taken in analyzing simulation outcomes and emphasize that taking the average is not sufficient.

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Sun Dec 01 00:00:00 UTC 2019