Srijeeta Talukder

Determining the DNA stability parameters for the breathing dynamics of heterogeneous DNA by stochastic optimization

We suggest that the thermodynamic stability parameters (nearest neighbor stacking and hydrogen bonding free energies) of double-stranded DNA molecules can be inferred reliably from time series of the size fluctuations (breathing) of local denaturation zones (bubbles). On the basis of the reconstructed bubble size distribution, this is achieved through stochastic optimization of the free energies in terms of simulated annealing. In particular, it is shown that even noisy time series allow the identification of the stability parameters at remarkable accuracy. This method will be useful to obtain the DNA stacking and hydrogen bonding free energies from single bubble breathing assays rather than equilibrium data.

Selective bond breaking mediated by state specific vibrational excitation in model HOD molecule through optimized femtosecond IR pulse: A simulated annealing based approach

The selective control of O-H/O-D bond dissociation in reduced dimensionality model of HOD molecule has been explored through IR+UV femtosecond pulses. The IR pulse has been optimized using simulated annealing stochastic approach to maximize population of a desired low quanta vibrational state. Since those vibrational wavefunctions of the ground electronic states are preferentially localized either along the O-H or O-D mode, the femtosecond UV pulse is used only to transfer vibrationally excited molecule to the repulsive upper surface to cleave specific bond, O-H or O-D. While transferring from the ground electronic state to the repulsive one, the optimization of the UV pulse is not necessarily required except specific case. The results so obtained are analyzed with respect to time integrated flux along with contours of time evolution of probability density on excited potential energy surface. After preferential excitation from [line]0, 0> ([line]m, n> stands for the state having m and n quanta of excitations in O-H and O-D mode, respectively) vibrational level of the ground electronic state to its specific low quanta vibrational state ([line]1, 0> or [line]0, 1> or [line]2, 0> or [line]0, 2>) by using optimized IR pulse, the dissociation of O-D or O-H bond through the excited potential energy surface by UV laser pulse appears quite high namely, 88% (O-H ; [line]1, 0>) or 58% (O-D ; [line]0, 1>) or 85% (O-H ; [line]2, 0>) or 59% (O-D ; [line]0, 2>). Such selectivity of the bond breaking by UV pulse (if required, optimized) together with optimized IR one is encouraging compared to the normal pulses.

Optimised polychromatic field-mediated suppression of H-atom tunnelling in a coupled symmetric double well: two-dimensional malonaldehyde model

The cis–cis isomerisation motion of malonaldehyde can be modelled as a symmetric double well coupled with an asymmetric double well, which includes the effect of the cis–trans out-of-plane motion on the cis–cis motion. We have presented an effective method for having control over the tunnelling dynamics of the symmetric double well which is coupled with the asymmetric double well by monitoring tunnelling splitting. When a suitable external field is allowed to interact with the system, the tunnelling splitting gets modified. As the external time perturbation is periodic in nature, the Floquet theory can be applied to calculate the quasi-energies of the perturbed system and hence the tunnelling splitting. The Floquet analysis is coupled with a stochastic optimiser in order to minimise the tunnelling splitting, which is related to slowering of the tunnelling process. The minimisation has been done by one of the stochastic optimisers, simulated annealing. Optimisation has been performed on the parameters which define the external polychromatic field, such as intensities and frequencies of the components of the polychromatic field. With the optimised sets of parameters, we have followed the dynamics of the system and have found suppression of tunnelling which is manifested by a much higher tunnelling time.

Enhancing the branching ratios in the dissociation channels for O16O16O18 molecule by designing optimum laser pulses: A study using stochastic optimization

We propose a strategy of using a stochastic optimization technique, namely, simulated annealing to design optimum laser pulses (both IR and UV) to achieve greater fluxes along the two dissociating channels (O(18) + O(16)O(16) and O(16) + O(16)O(18)) in O(16)O(16)O(18) molecule. We show that the integrated fluxes obtained along the targeted dissociating channel is larger with the optimized pulse than with the unoptimized one. The flux ratios are also more impressive with the optimized pulse than with the unoptimized one. We also look at the evolution contours of the wavefunctions along the two channels with time after the actions of both the IR and UV pulses and compare the profiles for unoptimized (initial) and optimized fields for better understanding the results that we achieve. We also report the pulse parameters obtained as well as the final shapes they take.

Stochastic optimization-based study of dimerization kinetics

AbstractWe investigate the potential of numerical algorithms to decipher the kinetic parameters involved in multi-step chemical reactions. To this end, we study dimerization kinetics of protein as a model system. We follow the dimerization kinetics using a stochastic simulation algorithm and combine it with three different optimization techniques (genetic algorithm, simulated annealing and parallel tempering) to obtain the rate constants involved in each reaction step. We find good convergence of the numerical scheme to the rate constants of the process. We also perform a sensitivity test on the reaction kinetic parameters to see the relative effects of the parameters for the associated profile of the monomer/dimer distribution. Graphical AbstractWe have evaluated the rate parameters of a 5-step dimerization kinetics by combining Stochastic Simulation Algorithm with three different optimization techniques: Genetic Algorithm, Simulated Annealing and Parallel tempering. We have performed the sensitivity analysis of the rate constants and also examined the effect on the convergence of the optimization method used.

Breathing dynamics based parameter sensitivity analysis of hetero-polymeric DNA

We study the parameter sensitivity of hetero-polymeric DNA within the purview of DNA breathing dynamics. The degree of correlation between the mean bubble size and the model parameters is estimated for this purpose for three different DNA sequences. The analysis leads us to a better understanding of the sequence dependent nature of the breathing dynamics of hetero-polymeric DNA. Out of the 14 model parameters for DNA stability in the statistical Poland-Scheraga approach, the hydrogen bond interaction ε(hb)(AT) for an AT base pair and the ring factor ξ turn out to be the most sensitive parameters. In addition, the stacking interaction ε(st)(TA-TA) for an TA-TA nearest neighbor pair of base-pairs is found to be the most sensitive one among all stacking interactions. Moreover, we also establish that the nature of stacking interaction has a deciding effect on the DNA breathing dynamics, not the number of times a particular stacking interaction appears in a sequence. We show that the sensitivity analysis can be used as an effective measure to guide a stochastic optimization technique to find the kinetic rate constants related to the dynamics as opposed to the case where the rate constants are measured using the conventional unbiased way of optimization.

Deciphering Parameter Sensitivity in the BvgAS Signal Transduction.

To understand the switching of different phenotypic phases of Bordetella pertussis, we propose an optimized mathematical framework for signal transduction through BvgAS two-component system. The response of the network output to the sensory input has been demonstrated in steady state. An analysis in terms of local sensitivity amplification characterizes the nature of the molecular switch. The sensitivity analysis of the model parameters within the framework of various correlation coefficients helps to decipher the contribution of the modular structure in signal propagation. Once classified, the model parameters are tuned to generate the behavior of some novel strains using simulated annealing, a stochastic optimization technique.