The Simulation of Pathogenic Protein False Folding Dynamics and the Calculation of its Experimental Spectrum:

The mechanism of protein folding is a biology problem that has aroused extensive concern. It is very significant to thoroughly understand protein folding dynamics and establish a predictive protein folding framework model in the biopharmaceutics field, especially in the aspect of folding-related diseases. Such a model framework can help learn about the pathogenic mechanism of protein false folding diseases, such as cystic fibrosis, Alzheimer, Huntington disease and type II diabetes. And this is very important for preventing false folding and protein aggregation.

Though after many years' theory and experiment research, we still can not achieve a clear understanding of its folding mechanism. One of the major reasons comes from the gulf between experiment and theoretical methods. The major reasons that lead to the gulf are the following two ones. Firstly, there is a scale difference between the folding time(longer than several microseconds) of the usual protein system and the time(a hundred nanoseconds) that computational simulation methods can reach. Recently there appears some inspiring development in computational simulation, including calculation with graphics processor, and the design of software and hardware specially used for molecule dynamic simulation, etc. However, in spite of these developments, it still remains a hard job to obtain a good statistical result of microsecond above dynamics with computational simulation. Secondly, even though the excellent statistical sampling can be obtained, it is very difficult to compare the result of computational simulation with that of experiments directly. In order to establish a relationship between the results of theory and experiments and achieve a deep understanding of protein folding mechanism, a theoretical method that can simulate long-time scale dynamics and calculate relevant time resolution spectrum signal needs to be developed.

The methods that employs laser pulse to trigger folding process is widely used in the protein folding research. In these methods, the most commonly used one is T-jump technology. T-jump uses a bunch of powerful laser to cause the immediate temperature rise, so the system is put in an unstable state on the free energy level, and we can trace the relaxation and the unfolding process of the system with the spectrum technology such as infrared and fluorescence.

We have developed a methodology that combines the simulation of molecule dynamics theory and theoretical spectrum to study the mechanism of typical protein structure fast folding process and its experiment characterization microscopic dynamics. This is a set of theoretical framework that combines statistical mechanics simulation, density functional theory, exciton model and Green function theory. Markovian State Model (MSM) is used to simulate the process that T-jump triggers long-time(longer than microsecond) protein folding, and Nonlinear Exciton Propagation(NEP) is employed to calculate the transmutation of optical line shape in the protein folding process.

Energy Transfer in Natural Solar Energy Collector and the Regulation Function of Protein Environment on it:

Photosynthesis provides chemical energy for almost all the living things on the earth. It is critical to study deep into the mechanism of photosynthesis in nature in the situation of global warming and fossil energy depletion, and it is closely related to biometric electro-optical device. Photosynthesis system is a naturally evolutionary and excellent biological electrical device. Photosynthesis tissue unit contains a set of complex pigment-protein complex (PPC). The distribution in space and energy level are in order, and the light conversion efficiency can reach more than 95%, so every absorbed photon will lead to the reduction of one CO2 molecule. The energy of absorbed photon is transferred through excitation, and is collected in the pigment in reaction center, which provides energy for the following series of charge transfer and Redox reaction in the reaction center. In recent years, with the development of various spectrum, other microscopic probing technology and theoretical methods of complex system microscopic dynamics, the molecule-level photosynthesis is actively studied. The analysis of experiments reveals that the traditional quantum dissipation theory which is based on perturbation and Markovian approximation, such as Förster velocity theory and Redfield equation, etc., is not applicable to the excitation energy process in photosynthesis system. In order to compete with excited state quench, fast excited state energy transfer is usually needed. However, due to a lack of suitable experiment and theory instrument to clearly reveal the dynamic phenomenon of coupling among each part in PPC, it is still difficult for people to explain this effective transport mechanism on molecule level.

Our research focuses on developing rigious and non-perturbative quantum theory of dissipative dynamics, as the basis to study excitation energy transfer of complex molecular systems, and carrying out calculation and simulation of linear and nonlinear spectra. Through practical and effective quantum dissipative dynamics, computational chemistry to determine the molecular aggregates with the excited state energy distribution (energy landscape) and the dissipative structure of the associated spectral density. Studying the photosynthetic system excitation energy transfer efficiency of the mechanism by spectral simulation of various experiments. The research can be summarized in the following two aspects:(1)relationship between non-Markovian quantum effect and excitation energy transfer mechanism; (2) the spatial distribution of PPC in photosynthetic system, and the role of interaction between each molecule in the excitation transfer.