In aqueous solution, solute conformational transitions are governed by intimate interplays of the fluctuations of
solute–solute, solute–water, and water–water interactions. To more effectively sample conformational transitions in aqueous solution, we
devised a predictive sampling method: the generalized orthogonal space tempering (gOST) algorithm. Specifically, in the Hamiltonian
perturbation part, a solvent-accessible-surface-area-dependent term is introduced to implicitly perturb near-solute water–water
fluctuations; more importantly in the orthogonal space response part, the generalized force order parameter is generalized as a
two-dimension order parameter set, in which essential solute–solvent and solute–solute components are separately treated. The gOST
algorithm is evaluated through a molecular dynamics simulation study on the explicitly solvated deca-alanine peptide. On the basis of a
fully automated sampling protocol, the gOST simulation enabled repetitive folding and unfolding of the solvated peptide within a single
continuous trajectory and allowed for detailed constructions of deca-alanine folding/unfolding free energy surfaces. In addition, by
employing the gOST method we enabled efficient molecular dynamics simulation of repetitive breaking and reforming of salt bridge
structures within a minimalist salt-bridge model, the Asp-Arg dipeptide and thereby were able to map its detailed free energy landscape in
aqueous solution. Our results reveal the critical role of local solvent structures in modulating salt-bridge partner interactions and
imply the importance of water fluctuations on conformational dynamics that involves solvent accessible salt bridge formations. Based on
the gOST method, we have developed a solvation force orthogonal space tempering (SFOST) algorithm, in which several major changes were
made from the original gOST method. Due to compensating fluctuations of essential solute-solvent and solute-solute interactions, only
essential solute-solvent interactions are perturbed in the SFOST algorithm. Importantly, the above treatment enabled us to incorporate a
high order orthogonal space sampling strategy. Specifically, to enlarge fluctuations of essential solute-solvent interactions, a third
order treatment was introduced to accelerate the coupled responses caused by fluctuations of essential solute-solvent interactions, which
come from synchronous fluctuations of essential solute-solute interactions and solvent-solvent interactions. The SFOST algorithm was
evaluated through a molecular dynamics simulation study on the explicitly solvated deca-alanine peptide. More importantly, the SFOST
simulation explicitly revealed the compensating fluctuations between the essential solute-solvent interactions and the solvent-solvent
interactions, suggesting that solvent cooperative fluctuations intimately interplay with deca-alanine conformational transitions. In
addition, the SFOST algorithm was also employed to study ion conduction through gramicidin A (gA). By enlarging fluctuations of the
ion-environment interactions, the SFOST simulation enabled several round trips of ion permeation through the channel and allowed detailed
construction of free energy surfaces along the conduction. The calculated observables agree very well with experiment. We also found that
fluctuations of channel orientations play an essential role in ion conduction. Furthermore, by employing the SFOST algorithm we enabled
predictive sampling of the conformational ensemble of the p53 transcriptional activation domain 1 (TAD1). Strikingly, a helical structure
resembling the MDM2-bound form was found in our SFOST simulation, indicating the pre-existing nature of the structure. Detailed studies of
free energy surfaces revealed that the most popular state is not a fully disordered form but a partially helical state. Upon binding to
MDM2, the hydrophobic interactions at the interface shift the conformational equilibrium to favor the total helical structure. In addition
to the predictive sampling methods, we developed a Gaussian kernel Monte Carlo (GKMC) method to smoothly approximate multidimensional free
energy surfaces of biomolecular processes. By taking a discrete probability distribution of sampled collective variables as an input, a
biased Monte Carlo simulation is performed to efficiently resample the distribution in the collective variable space, leading to a smooth
analytical estimate of the free energy surface. The GKMC method is evaluated by resampling data of a generalized orthogonal space
tempering simulation of deca-alanine peptide, aiming to construct smooth one-dimensional and two-dimensional free energy surfaces along
certain collective variables. As demonstrated in these model studies, the GKMC method can robustly construct smooth multidimensional free
energy surfaces with super resolutions, which preserve probability distributions of target molecular processes. Constructing smooth free
energy surfaces plays a vital role in interpreting simulation data to understand molecular processes of interest. / A Dissertation submitted to the Department of Chemistry and Biochemistry in partial fulfillment of
the Doctor of Philosophy. / Fall Semester 2016. / November 22, 2016. / Orthogonal Space Tempering, Predictive Sampling, Protein Dynamics, Solvation Force / Includes bibliographical references. / Wei Yang, Professor Directing Dissertation; Kenneth A. Taylor, University Representative; Oliver
Steinbock, Committee Member; Hong Li, Committee Member; Timothy A. Cross, Committee Member.
| Identifer | oai:union.ndltd.org:fsu.edu/oai:fsu.digital.flvc.org:fsu_405663 |
| Contributors | Li, Xubin (authoraut), Yang, Wei (professor directing dissertation), Taylor, Kenneth A. (university representative), Steinbock, Oliver (committee member), Li, Hong (committee member), Cross, Timothy A. (committee member), Florida State University (degree granting institution), College of Arts and Sciences (degree granting college), Department of Chemistry and Biochemistry (degree granting departmentdgg) |
| Publisher | Florida State University, Florida State University |
| Source Sets | Florida State University |
| Language | English, English |
| Detected Language | English |
| Type | Text, text |
| Format | 1 online resource (136 pages), computer, application/pdf |
| Rights | This Item is protected by copyright and/or related rights. You are free to use this Item in any way that is permitted by the copyright and related rights legislation that applies to your use. For other uses you need to obtain permission from the rights-holder(s). The copyright in theses and dissertations completed at Florida State University is held by the students who author them. |
Page generated in 0.0136 seconds