Comparison between fluorescence simulations

Substantial evidence suggests that in highly asymmetric supercritical mixtures the local and bulk environment of a solute molecule differ appreciably. The concept of a local density enhancement around a solute molecule is supported by spectroscopic, theoretical, and computational investigations of intermolecular interactions in supercritical solutions. Here we make for the first time direct comparison between local density enhancements determined for the system pyrene in CO2 by two very different methods-fluorescence spectroscopy and molecular dynamics simulation. The qualitative agreement is quite satisfactory, and the results show great promise for an improved understanding at a molecular level of supercritical fluid solutions. 

Figure 6 shows a comparison between the density enhancements deduced from experiments and those calculated via simulation (the latter at R = 1.94). The reduced temperature in both cases is 1.02. This very good agreement suggests that the density augmentation measured in the fluorescence spectra corresponds to the first solvation shell. 

Figure 6 Comparison between local density augmentation deduced from fluorescence spectroscopy ( ), and the corresponding molecular dynamics simulations at R = 1.94 (Q). Both curves are for a reduced temperature of 1.02. The arrow denotes the critical density of carbon dioxide.

MD simulations provide a detailed insight in the behavior of molecular systems in both space and time, with ranges of up to nanometers and nanoseconds attainable for a system of the size of a CYP enzyme in solution. However, MD simulations are based on empirical molecular mechanics (MM) force field descriptions of interactions in the system, and therefore depend directly on the quality of the force field parameters (92). Commonly used MD programs for CYPs are AMBER (93), CHARMM (94), GROMOS (95), and GROMACS (96), and results seem to be comparable between methods (also listed in Table 2). For validation, direct comparisons between measured parameters and parameters calculated from MD simulations are possible, e.g., for fluorescence (97) and NMR (cross-relaxation) (98,99). In many applications where previously only energy minimization would be applied, it is now common to perform one or several MD simulations, as Ludemann et al. and Winn et al. (100-102) performed in studies of substrate entrance and product exit. 

The inner dynamics are determined by the cell distribution over the fluorescence changing with time. For comparability the cell concentrations have to be converted into number density functions, which are obtained by normalization with the overall cell concentration at the specific time point and division by the specific class width in logarithmic scale. All cells (uninfected, infected and dead) contribute to the distribution as they all show fluorescence. Figure 2 shows the comparison between simulation results and the flow cytometric data reported by Schulze-Horsel et al. [3] for MOI = 3.0. The simulation peak lags behind in the beginning and catches up for later time points, but the overall tendency of increasing mean values can be reproduced quite well. However, the present model has a drawback for an unknown biological reason the experimental distributions fall back to smaller fluorescence intensities at later time points (data not shown). So far, this effect cannot be simulated with the presented model formulation adequately. 

The conformational landscape of phenylalanine (R=CH2-C6Hs, m.p. = 270-275°C) has been widely investigated [11, 137-147]. Six conformational species were identified using laser induced fluorescence LIF, hole burning UV-UV, and ion dip IR-UV spectroscopy coupled with ab initio calculations [11, 137-141]. Lee et al. [141] carried out a definitive identification of the conformers of phenylalanine, based upon comparisons between the partially resolved ultraviolet band contours and that simulated by ab initio computations. The study of the rotational spectrum of phenylalanine by LA-MB-FTMW [153] showed rather weak spectra of only two conformers, Ila and Ilb (see Fig. 21). Both conformers exhibit a trans configuration in the COOH group, being stabilized by O-H- N and N-H- - -it... 

The remainder of this contribution is organized as follows In the next section, the connection between the experimentally observed dynamic Stokes shift in the fluorescence spectrum and its representation in terms of intermolecular interactions will be given. The use of MD simulation to obtain the SD response will be described and a few results presented. In Section 3.4.3 continuum dielectric theories for the SD response, focusing on the recent developments and comparison with experiments, will be discussed. Section 3.4.4 will be devoted to MD simulation results for e(k, w) of polar liquids. In Section 3.4.5 the relevance of wavevector-dependent dielectric relaxation to SD will be further explored and the factors influencing the range of validity of continuum approaches to SD discussed. 

Fig. 4A-H Comparison of two different variants of FRAP strip-FRAP and FLIP-FRAP (see also Fig. 3B, C). The combined use of the two protocols may allow to discriminate between transient binding and slow diffusion. The curves are based on computer simulated FRAP experiments (see the text) A, B schematic drawings of the strip-FRAP (see also Fig. 1C) and FLIP-FRAP methods. The FLIP-FRAP method differs from the strip-FRAP in that two areas are monitored after bleaching. Briefly, a strip at one pole of the nucleus is bleached for a relatively long period at a moderate excitation intensity. Subsequently the fluorescence is monitored in that region (FRAP), but also in the area at the other side of the nucleus (FLIP). Subsequently the difference between the two (normalised) fluorescence levels is plotted against time C schematic drawing of two scenarios where molecules are either free, but relatively slow (D=4 pmVs, top panel), or relatively fast (D=7 pm /s), but transiently immobilised such that 30% is immobile in steady state and individual molecules are immobilised for 45 s (bottom panel) D, E strip-FRAP and FLIP-FRAP curves of the scenarios depicted in C. In this case strip-FRAP can discriminate between the two cases, whereas the FLIP-FRAP curves are nearly identical F schematic drawing of a situation where freely mobile molecules are slower (D=l pmVs, top panel) than in C G,H strip-FRAP curves are identical whereas the FLIP-FRAP method can now discriminate between the two scenarios...

---