Fourier analysis of frequency domain discrete event simulation experiments

Frequency Domain Experiments (FDEs) were first used in discrete-event simulation to perform system parameter sensitivity analysis for factor screening in stochastic system simulations. FDEs are based on the intuitive assertion that if one or more system parameters are oscillated at fixed frequencies throughout a simulation run, then oscillations at the same frequencies will be induced in the system\u27s response. Spectral (Fourier) analysis of these induced oscillations is then used to characterize and analyze the system. Since their introduction 12 years ago, significant work has been done to extend the applicability of FDEs to regression analysis, simulation optimization and gradient estimation. Two fundamental theoretical and data analysis FDE problems remain, however. Both problems are addressed in this dissertation.;To perform a FDE Fourier analysis, a sampled data sequence of response observations is used; i.e., the selected system response is sampled using a suitable oscillation (sampling) index. The choice of an appropriate oscillation index is an open problem in the literature known as the FDE indexing problem. This dissertation presents a solution to the FDE indexing problem. Specifically, a FDE Fourier data analysis algorithm is developed which uses the simulation clock as the oscillation index. This algorithm is based on the well-established theory of counting (Poisson) processes. The algorithm is implemented and tested on a variety of systems including several networks of nonstationary M/G/1 queues.;To justify the use of Fourier methods, a basic FDE model assumption is that if a particular system response statistic is sensitive to a system parameter, then sinusoidal variation of that system parameter at a fixed frequency will induce similar sinusoidal variations in the response statistic, at the same frequency. There is, however, a lack of theoretical support for this model assumption. This dissertation provides some of that theoretical support; i.e., the FDE Fourier data analysis algorithm developed in this dissertation is used to analyze the frequency response of a M/M/1 queuing system. An equation is derived which accurately characterizes the extent to which the departure process from a M/M/1 queuing system can be modeled as an amplitude-modulated, phase-shifted version of the oscillated arrival process

Comparative molecular dynamics simulation studies for determining factors contributing to the thermostability of chemotaxis protein “CheY”

<div><p>Comparative molecular dynamics simulations of chemotaxis protein “CheY” from thermophilic origin <i>Thermotoga maritima</i> and its mesophilic counterpart <i>Salmonella enterica</i> have been performed for 10 ns each at 300 and 350 K, and 20 ns each at 400 and 450 K. The trajectories were analyzed in terms of different factors like root-mean-square deviation, root-mean-square fluctuation, radius of gyration, solvent accessible surface area, H-bonds, salt bridge content, and protein–solvent interactions which indicate distinct differences between the two of them. The two proteins also follow dissimilar unfolding pathways. The overall flexibility calculated by the trace of the diagonalized covariance matrix displays similar flexibility of both the proteins near their optimum growth temperatures. However, at higher temperatures mesophilic protein shows increased overall flexibility than its thermophilic counterpart. Principal component analysis also indicates that the essential subspaces explored by the simulations of two proteins at different temperatures are nonoverlapping and they show significantly different directions of motion. However, there are significant overlaps within the trajectories and similar direction of motions are observed for both proteins at 300 K. Overall, the mesophilic protein leads to increased conformational sampling of the phase space than its thermophilic counterpart. This is the first ever study of thermostability of CheY protein homologs by using protein dynamism as a main impact. Our study might be used as a model for studying the molecular basis of thermostability of two homologous proteins from two organisms living at different temperatures with less visible differences.</p></div

In Silico Designing of an Industrially Sustainable Carbonic Anhydrase Using Molecular Dynamics Simulation

Carbonic anhydrase (CA) is a family of metalloenzymes that has the potential to sequestrate carbon dioxide (CO₂) from the environment and reduce pollution. The goal of this study is to apply protein engineering to develop a modified CA enzyme that has both higher stability and activity and hence could be used for industrial purposes. In the current study, we have developed an in silico method to understand the molecular basis behind the stability of CA. We have performed comparative molecular dynamics simulation of two homologous α-CA, one of thermophilic origin (<i>Sulfurihydrogenibium</i> sp.) and its mesophilic counterpart (Neisseria gonorrhoeae), for 100 ns each at 300, 350, 400, and 500 K. Comparing the trajectories of two proteins using different stability-determining factors, we have designed a highly thermostable version of mesophilic α-CA by introducing three mutations (S44R, S139E, and K168R). The designed mutant α-CA maintains conformational stability at high temperatures. This study shows the potential to develop industrially stable variants of enzymes while maintaining high activity