Poly-proline-based chiral stationary phases are relatively new stationary phases and have shown to be competitive to other commercially available chiral stationary phases for high performance liquid chromatography (HPLC). The conformational studies, solvation properties and enantio-selective mechanism of this chiral stationary phase are the main focus of this thesis. Semi-flexible models are developed based on an extensive series of ab initio calculations for proline selectors from di- to hexa-proline and a series of six chiral analytes. Then molecular dynamics simulations are performed to study the solvation, conformational preferences at the interface, and the selectivity. The solvation and conformational preferences of poly-proline selectors at the interface are examined in a normal phase n-hexane/-2propanol and a reverse phase water/methanol solvent. We noticed a significant difference between conformational preferences of poly-proline chains in these solvents indicating the effect of solvent polarity and hydrogen bonding on the relative stabilities of poly-proline conformers. Solvent partitioning occurs at the interface and this creates a polarity gradient between the stationary phase and the bulk that encourages analyte docking at the interface. Hydrogen bonding to the poly-proline selectors is shown to be a function of solvent composition and poly-proline conformation at the interface. The selectivity of the poly-proline chains was studied by molecular dynamics simulations of chiral analytes docking into the interface. The selectivity factors for a set of enantiomers were predicted successfully. Enantio-resolution has been shown to mostly happen with hydrogen bonding to poly-proline carbonyl oxygens located close to the interface. Steric interactions and conformational flexibility of the analytes are also contributing factors for enantio-resolution. / Thesis (Ph.D, Chemistry) -- Queen's University, 2013-01-28 14:31:53.316

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Peptide-membrane interactions play an important role in a number of biological processes, such as antimicrobial defence mechanisms, viral translocation, membrane fusion and functions ofmembrane proteins. In particular, amphipathic α-helical peptides comprise a large family of membrane-active peptides that could exhibit a broad range of biological activities. A membrane, interacting with an amphipathic α-helical peptide, may experience a number of possible structural transitions, including stretching, reorganization of lipid molecules, formation of defects, transient and stable pores, formation of vesicles, endo- and pinocytosis and other phenomena. Naturally, theoretical and experimental studies of these interactions have been an intense on-going area of research. However, complete understanding of the relationship between the structure of the peptide and themechanismof interaction it induces, as well asmolecular details of this process, still remain elusive. Lack of this knowledge is a key challenge in our efforts to elucidate some of the biological functions of membrane active peptides or to design peptides with tailored functionalities that can be exploited in drug delivery or antimicrobial strategies. In principle,molecular dynamics is a powerful research tool to study peptide-membrane interactions, which can provide a detailed description of these processes on molecular level. However, a model operating on the appropriate time and length scale is imperative in this description. In this study, we adopt a coarse-grained approach where the accessible simulation time and length scales reach microseconds and tens of nanometers, respectively. Thus, the two key objectives of this study are to validate the applicability of the adopted coarse-grained approach to the study of peptide-membrane interactions and to provide a systematic description of these interactions as a function of peptide structure and surface chemistry. We applied the adopted strategy to a range of peptide systems, whose behaviour has been well established in either experiments or detailed atomistic simulations and outlined the scope and applicability of the coarse-grained model. We generated some useful insights on the relationship between the structure of the peptides and themechanism of peptide-membrane interactions. Particularly interesting results have been obtained for LS3, a membrane spanning peptide, with a propensity to self-assembly into ion-conducting channels. Firstly, we captured, for the first time, the complete process of self-assembly of LS3 into a hexameric ion-conducting channel and explored its properties. The channel has structure of a barrel-stave pore with peptides aligned along the lipid tails. However, we discovered that a shorter version of the peptide leads to a more disordered, less stable structure often classified as a toroidal pore. This link between two types of pores has been established for the first time and opens interesting opportunities in tuning peptide structures for a particular pore-inducing mechanism. We also established that different classes of peptides can be uniquely characterized by the distinct energy profile as they cross the membrane. Finally, we extended this investigation to the internalization mechanisms of more complex entities such as peptide complexes and nanoparticles. Coarse-grained steered molecular dynamics simulations of these model systems are performed and some preliminary results are presented in this thesis. To summarize, in this thesis, we demonstrate that coarse-grained models can be successfully used to underpin peptide interaction and self-assembly processes in the presence of membranes in their full complexity. We believe that these simulations can be used to guide the design of peptides with tailored functionalities for applications such as drug delivery vectors and antimicrobial systems. This study also suggests that coarse-grained simulations can be used as an efficient way to generate initial configurations for more detailed atomistic simulations. These multiscale simulation ideas will be a natural future extension of this work.

With a modest beginning from developing a model of dynamics of hard liquid spheres (Alder et al., 1957), molecular dynamics (MD) simulations have come to a point where complex biomolecules can be simulated with precision close to reality (Noskov et al., 2007). In this context, a parallel molecular dynamics program for simulation of ion channels associated with cellular membranes has been developed. The parallel MD code developed is simple, efficient, and easily coupled to other codes such as the hybrid molecular dynamics/ brownian dynamics (MD/BD) code developed for the study of protein interactions (Ying et al., 2005). The Atom Decomposition (AD) Method was used in partitioning calculations on atoms to processors. One of the major impediments in using AD was the relatively large size of data that had to be communicated by the processes (Plimpton et al., 1995). Replicating only positions of atoms eased the congestion created by communication of both force terms and positions of atoms between processes. The performance of the code was tested on KcsA, a bacterial potassium channel. The program was written in Fortran 90 with parallel functions from the library of mpich-1.2.7. The idle time of processes was optimized by message driven ordering of communication. The scaling of the parallel program with 2000 – 60,000 atoms was determined and compared with the results obtained from the serial program. As expected, the parallel program scaled better than the serial program as the number of atoms included in the simulation increased from 2000 - 60000. The performance of the parallel program was tested on 4-15 processes, for a system comprising 20,000 atoms. The results obtained were compared with results from the serial program. It was observed that the parallel program scaled better than the serial program as the number of processes increased from 4 to 15. When compared with serial program, which had application of Newton’s Third Law in calculating force terms once per each pair of atoms, it was observed that the parallel program scaled better on 6-15 processes for a physical system comprising of 20,000 atoms.

Master of Science / Department of Biochemistry / Jianhan Chen / Paul E. Smith / Intrinsically disordered proteins have been shown to be important in many physiological processes, including cell signaling, translation, and transcription. They are also associated with cancer, and neurodegenerative diseases. The tumor suppressor p53 contains several disordered regions, including the C-terminal negative regulatory domain (NRD). In cancer the function of p53 has been shown to be repressed by S100B(ββ) binding to p53-NRD. Binding of S100B(ββ) blocks acetylation and phosphorylation sites in the p53-NRD, which leads to tetramer dissociation and prevents p53 activation. NMR studies have shown that p53-NRD binds S100B(ββ) in a stable α-helix conformation. Interestingly, despite the well-converged and apparent rigid nature of the NMR structure ensemble, a majority of intermolecular NOEs used to calculate the NMR ensemble are very weak (≥6 Å). The final NMR structures also contains unsatisfied buried charged residues at the binding interface. It’s plausible that the p53-S100B(ββ) complex is more dynamic than previously believed. The goal of the study is to determine the potential conformational heterogeneity in p53-S100B(ββ) complex using molecular modeling. For this, five diverse structures were selected from the 40-member NMR ensemble. For each initial conformation, we performed 100 ns molecular dynamic simulations in explicit solvent to explore the structure and dynamics of the p53-NRD in complex with S100B(ββ). Several analytical tools were used to characterize the p53-NRD conformation, including root-mean squared deviation (RMSD), root-mean squared fluctuation (RMSF), and residue helicity. The accuracy of the simulations was mainly assessed by comparing with experimental NOEs. The results show that, even though the ensemble is heterogeneous it satisfies 82% of the experimental NOEs. Clustering analysis further suggests that many conformational sub-states coexist for this complex, and individual clusters appear to satisfy only subsets of NOE distances. Importantly, the buried surface analysis demonstrates that the heterogeneous ensemble generated from MD provides similar shielding of key residues, which include post-translational modification residues needed for p53 activation. This study also demonstrates that atomistic simulations can provide important insights into structure and dynamics of IDPs for understanding their biological function.

Protein molecules, sometimes referred to as the molecules of life, are the drivers of virtually every biological function. In this dissertation, we describe a series of computational studies to dissect the mystery of complex protein molecules. We consider a large collection of protein systems, ranging from globular proteins to Intrinsically Disordered Proteins (IDPs) with a focus on predicting thermodynamic observables that can be quantitatively compared with experimental data. In the first part of this dissertation, we study the effects of the phenomenon of macromolecular crowding and how it affects the properties of two different groups of proteins. First, we investigate the effects of crowding on globular proteins by calculating the free energy of all-atom proteins in crowded environments. Second, we study how crowding affect the conformational ensembles of disordered proteins with a focus on comparing computations with experiments. In the second part of this dissertation, we apply Monte Carlo simulation techniques to study protein droplet formation and Liquid Liquid Phase Separation in protein systems. / A Dissertation submitted to the Department of Physics in partial fulfillment of the requirements for the degree of Doctor of Philosophy. / Fall Semester 2018. / November 06, 2018. / Intrinsically Disordered Proteins, Monte Carlo simulations, Protein Droplets, Proteins / Includes bibliographical references. / Jorge Piekarewicz, Professor Directing Dissertation; Scott Stagg, University Representative; Huan-Xiang Zhou, Committee Member; Peng Xiong, Committee Member; David Van Winkle, Committee Member.

Aggregation of amyloid β (Aβ) protein has been linked to the development of Alzheimer's Disease (AD). The genesis of Aβ involves the cleavage Amyloid Precursor Protein (APP) by β-secretase, producing the 99-residue C99 peptide, and the subsequent cleavage of C99 by γ-secretase to produce Aβ. A detailed understanding of the γ-cleavage process is essential to our undertsanding of the pathological mechanisms linking the aggregation of Aβ to the development of AD. This work seeks to provide insight into critical aspects of the structure and dynamics of C99, and the particular roles played by (1) C99 amino acid sequence and (2) the lipid composition of the membrane environment. Many studies have focused on the importance of the C99 sequence, including known studies of Familial AD (FAD) mutants as well as engineered mutations. Specific mutations have been found to affect the processing of C99, which has been linked to changes in the structure of C99 and the formation of C99 homodimers. Similarly, changes in the membrane environment, through variation in lipid composition and the presence of cholesterol, have been found to affect C99 structure and positioning within the membrane as well as C99 dimerization. The results of this work extend our understanding of the APP-C99 system and its interaction with the environment. Using a multiscale simulation approach, we find key structural effects of engineered mutations that suggest possible mechanistic insight into the γ-cleavage process. Using C99 congener peptides, we examine the effect of local membrane environment on the dimerization of C99, focusing on the roles of both the transmembrane (TM) region as well as the juxtamembrane (JM) domain. Further studies characterize the role of a FAD mutation, and demonstrate the effect of the mutation on the dimerization of C99 in agreement with experimental findings. Overall, this work leads to critical insight into the role of sequence and membrane on the structure of C99 in a membrane environment, and provides support for the conjecture that the structure of C99 monomer and homodimer are critical to our understanding of the processing of C99, a critical step in the genesis of Aβ peptide and the etiology of Alzheimer's Disease.

by Ma Tak-lun. / Bibliography: leaves 68-69 / Thesis (M.Phil.) -- Chinese University of Hong Kong, 1983

Hon Wan Chee Nicole Wendy. / Thesis (M.Phil.)--Chinese University of Hong Kong, 2001. / Includes bibliographical references (leaves 85-87). / Abstracts in English and Chinese. / THESIS COMMITTEE --- p.ii / ABSTRACT (English version) --- p.iii / ABSTRACT (Chinese version) --- p.v / ACKNOWLEDGEMENTS --- p.vii / TABLE OF CONTENTS --- p.viii / LIST OF FIGURES --- p.x / LIST OF TABLES --- p.xiii / Chapter CHAPTER 1. --- General Introduction / Chapter Section 1.1 --- Introduction --- p.1 / Chapter Section 1.2 --- Electronic Structure Calculation --- p.2 / Chapter Section 1.3 --- Molecular Dynamics --- p.10 / Chapter CHAPTER 2. --- Ab Initio Molecular Dynamics Study on Thermal Dissociation of Azomethane / Chapter Section 2.1 --- Introduction / Chapter Section 2.2 --- Computational Method --- p.17 / Chapter Section 2.3 --- Results and Discussion --- p.21 / Chapter Section 2.4 --- Conclusion --- p.47 / Chapter CHAPTER 3. --- "Ab Initio Molecular Dynamics Study on Fluxionality of IF7, TeF7- and iof6-" / Chapter Section 3.1 --- Introduction --- p.49 / Chapter Section 3.2 --- Computational Method --- p.52 / Chapter Section 3.3 --- Analysis --- p.55 / Chapter Section 3.4 --- Results and Discussion --- p.56 / Chapter Section 3.5 --- Conclusion --- p.83 / REFERENCES --- p.85

Coarse-graining and multi-scale approaches are rapidly becoming important tools for computer simulations of large complex molecular systems. Such theoretical models are powerful tools because they allow one to probe the essential features of a complex, many-bodied system on length and time scales over which emergent phenomena may occur. Because of the computational advantages and fundamental insight made available through coarse-grained methods, a vast array of various phenomenological potentials to describe coarse-grained interactions have been developed; nonetheless, the ability of these potentials to provide quantitative information about several different properties of the same system is not evident. On a theoretical level, it is not well-understood how small correlations in the long-range structure propagate through the coarse-graining procedure into the effective potential and lead to incorrect thermodynamics. Taking an alternative approach, this dissertation will discuss an analytical coarse-graining method for synthetic polymer chains of specific chemical structure, where a group of atoms on a polymer chain are represented by a variable number of soft interacting effective sites. The approach is based in liquid-state theory, providing a theoretical framework to address questions of thermodynamic consistency. It will be shown that the proposed method of coarse-graining maintains thermodynamic consistency for a variety of polymer models. In a multi-scale modeling scheme simulations of the same system represented by several different levels of detail may be joined to provide a complete description of the system at all length and time scales of interest. This dissertation includes previously published and unpublished co-authored material.