Page - 93 - in Charge Transport in DNA - Insights from Simulations

7.2Modeling the IonizationPotentials 7.2 Modeling the IonizationPotentials MD simulations of 100 ps of polyA and polyG sequences were performed, and theCTparameterswere calculated every 1 fs. Theobtained time series of IPwere analyzed in terms of a Fourier transformation to obtain a power spectrum. The spectra reveal basically twoseparate regions. Thefirst are thewavenumbers above 1000 cm−1, which correspond to the internal structural fluctuations of the nucle- obases. Note that thesefluctuations are slightlydifferent for adenineandguanine. (Seefigure 7.3 for the comparison). Guanine reveals a fewmore characteristic fre- quencies in the region of 1800 cm−1. The other region contains the characteristic frequencies due to the dynamics of the environment, i.e. the solvent and DNA backbone,which canbe foundbelow1000 cm−1. Figure7.3: IP calculated fromMDsimulationof100ps. Left: Time series of IP shown for 500 fs calculated for 6 adenines. Middle: Power spectrum of the time series of the IP of a adenine. Right: Power spectrum of the time series of the IPof a guanine. Themostprominentpeaks inbothregionsof thesepowerspectraare identifiedand taken as characteristic frequencies. Thisway, 15 and 24 characteristic frequencies were found for the internal (>1000 cm−1) and for the environmental fluctuations, respectively. Table7.2 showsanoverviewof theseobtainedwavenumbers. While thewavenumbers for internalfluctuationsof theadenineandguaninenucle- obases reveal certaindifferences, thewavenumbersobtained for theenvironmental fluctuations are the same for bothnucleobases. Thevery lowwavenumbers of the environmenthavebeenfoundcrucial toobtainthecorrectprobabilitydistributions. Indetail, the rareeventswhere the IP isveryhighorvery lowcanonlybesampled with thiswavenumbers included. Having evaluated the characteristic frequencies, a sum of cosine functions was created tomodel the timecourseof the IP. 93