No description available.

No description available.

Membrane proteins are critical to many biological processes, including molecular transport, signal transduction, and cellular interactions. Through the use of molecular dynamics (MD) simulations, we are able to model this environment at an atomistic scale. However, traditionally used nonpolarizable force fields (FF) are thought to model the unique dielectric gradient posed by the lipid environment with a limited accuracy due to the mean field approximation of charge. Advancements in polarizable FFs and computing efficiency has enabled the explicit modeling of polarization responses and charge distribution, enabling a deeper understanding of the electrostatics driving these processes. Through the use of the Drude FF, we study three specific model systems to understand where explicit polarization is important in describing membranes and membrane proteins. These studies sought to answer the questions: (1) How does explicit electronic polarization impact small molecule permeation and localization preference?, (2) What electrostatic interactions underlie membrane protein secondary structure?, and (3) How do conformational changes propagate between microswitches in G-Protein Coupled Receptors? In this work, we show small molecule dipole moments changing as a function of localization in the bilayer. Additionally, we show differences in the free energy surfaces of permeation for aromatic, polar, and negatively charged species reliant upon force field used. For secondary structure, we showed key interactions which aided to stabilize model helices in bilayers. Finally, we showed potential inductive effects of key microswitch residues underlying prototypical G-Protein coupled receptor activation. This dissertation has helped to show the importance of including explicit polarization in membrane protein systems, especially when considering interactions at the interface and modeling species with charge. This work enables a refined view of the electrostatics occurring in membranes and membrane protein systems, and in the future, can be used as a basis for methodologies in computer aided drug design efforts. / Doctor of Philosophy / Deepening our understandings of membranes and membrane proteins enable better informed and more efficient drug design. In order to do this, biological processes can be simulated through molecular dynamics (MD) simulations. MD simulations use mathematical models known as force fields (FF) to represent the physics of biological systems at an atomistic scale. This enables the study of key interactions which can be leveraged for drug discovery efforts. However, traditional FF neglect electronic structural changes which are crucial for accurately describing the membrane environment and the influence it has on surrounding and embedded molecules. Using enhanced FFs, known as polarizable FFs, we can model this response and gain an entirely new perspective on membranes and membrane proteins. This work helps to define when these FFs are most important to be used when studying membranes and membrane proteins, and in the future, serve as a basis for further simulations in drug discovery efforts.

<p>Eukaryotic Topoisomerase 2 is an essential enzyme that solves DNA topological problems such as DNA knotting, catenation, and supercoiling. It alters the DNA topology by introducing transient double strand break in one DNA duplex as a gate for the passage of another DNA duplex. Two different aspects of studies about eukaryotic Topoisomerase 2 will be covered in this thesis. In the first half of the thesis, we investigated conformational changes of human Topoisomerase 2&#61537; (hsTop2&#61537;) in the presence of cofactors and inhibitors. In the second half, we focused on an unknown regulatory function in the C-terminal domain (CTD) of Drosophila Topoisomerase 2 (Top2).</p><p>In the project of studying enzyme conformational changes, we adapted a previously developed methodology, Pulse-Alkylation Mass Spectrometry, with monobromobimane to study the protein dynamics of hsTop2&#61537;. Using this method, we captured the evidence of conformational changes in the presence of ATP and Mg2+ or the Top2 inhibitor, ICRF-193 which were not previously observed. Last, by using CTD truncated hsTop2&#61537;, the increasing reactivity of Cys427 suggested the CTD domain might be tethered adjacent to the core enzyme.</p><p>Following the study of enzyme conformational changes, we switched gear to examine an interaction between Drosophila Top2 and Mus101, homolog of human TopBP1. We first found that Mus101 interacts with CTD of Top2 in a phosphorylation-dependent manner. Next, in the co-immunoprecipitation and pull-down experiments using truncated or mutant Top2 with various Ser to Ala substitutions, we mapped the binding motif to the last amino acids of Top2 and identified that phosphorylation of Ser1428 and Ser1443 is important for Top2 to interact with the N-terminus of Mus101, which contains BRCT1/2 domains (BRCT, BRCA1 C-terminus). The binding affinity of the N-terminal Mus101 with a synthetic phosphorylated peptide covering the last 25 amino acids of Top2 (with pS1428 and pS1443) was determined by surface plasmon resonance with a Kd of 0.57 &#956;M. In an in vitro decatenation assay, Mus101 can specifically reduce the decatenation activity of Top2, and dephosphorylation of Top2 attenuates this response to Mus101. Next, we endeavored to establish a cellular system for testing the biological function of Top2-Mus101 interaction. Top2-silenced S2 cells rescued by Top2&#61508;20, truncation of 20 amino acids from the C-terminus of Top2, developed abnormally high chromosome numbers, which implies an infidelity in chromosome segregation during mitosis. Lastly, Top2-null flies rescued by Top2 with S1428A and S1443A were found to be viable but sterile. After investigating spermatogenesis, telophase of meiosis I was delayed, indicating Top2-Mus101 interaction is also important in segregating DNA in meiosis.</p> / Dissertation

At the time of writing this thesis, the complete genomes of more than 180 organisms have been sequenced and more than 80000 biological macromolecular structures are available in the Protein Data Bank (PDB). While the number of sequenced genomes and solved three-dimensional structures are rapidly increasing, the functional annotation of protein sequences and structures is a much slower process, mostly because the experimental de-termination of protein function is expensive and time-consuming. A major class of in silico methods used for protein function prediction aim to transfer annotations between proteins based on sequence or structural similarities. These approaches rely on the assumption that homologous proteins of similar primary sequences and three-dimensional structures also have similar functions. While in most cases this assumption appears to be valid, an increasing number of examples show that proteins of highly similar sequences and/or structures can have different biochemical functions. Thus the relationship between the divergence of protein sequence, structure and function is more complex than previously anticipated. On the other hand, there is mounting evidence suggesting that minor changes of the sequences and structures of proteins can cause large differences in their conformational dynamics. As the intrinsic fluctuations of many proteins are key to their biochemical functions, the fact that very similar (almost identical) sequences or structures can have entirely different dynamics might be important for understanding the link between sequence, structure and function. In other words, the dynamic similarity of proteins could often serve as a better indicator of functional similarity than the similarity of their sequences or structures alone. Currently, little is known about how proteins are distributed in the 'dynamics space' and how protein motions depend on structure and sequence. These problems are relevant in the field of protein design, studying protein evolution and to better understand the functional differences of proteins. To address these questions, one needs a precise definition of dynamic similarity, which is not trivial given the complexity of protein motions. This thesis is intended to explore the possibilities of describing the similarity of proteins in the 'dynamics space'. To this end, novel methods of characterizing and comparing protein motions based on molecular dynamics simulation data were introduced. The generally applicable approach was tested on the family of PDZ domains; these small protein-protein interaction domains play key roles in many signalling pathways. The methodology was successfully used to characterize the dynamic dissimilarities of PDZ domains and helped to explain differences of their functional properties (e.g. binding promiscuity) also relevant for drug design studies. The software tools developed to implement the analysis are also introduced in the thesis. Finally, a network analysis study is presented to reveal dynamics-mediated intramolecular signalling pathways in an allosteric PDZ domain.

How an enzyme achieves such high rates of catalysis in comparison to its solution counterpart reaction has baffled scientists for many decades. Much of our understanding of enzyme function is derived from research devoted to enzyme chemical reactions and analysis of static three-dimensional images of individual enzyme molecules. However, more recently, a role of protein dynamics in facilitating enzyme catalysis has emerged. It is often challenging to probe how protein motions are correlated to and impact on the catalytic cycle of enzymes. Nevertheless, this subject must be addressed to further our understanding of the roots of enzyme catalysis. Herein, this research question is approached by studying the link between protein domain dynamics and electron transfer chemistry in the diflavin oxidoreductase family of enzymes. Previous studies conducted on the diflavin oxidoreductases have implied a role of protein domain dynamics in catalysing electron transfer chemistry. However, diflavin oxidoreductase motions have not been experimentally correlated with mechanistic steps in the reaction cycle. To address these shortcomings, a 'real-time' analysis of diflavin oxidoreductase domain dynamics that occur during enzyme catalysis was undertaken. The methodology involved specific labelling of diflavin oxidoreductases (cytochrome P450 reductase, CPR, and neuronal nitric oxide synthase, nNOS) with external donor-acceptor fluorophores that were further used for time-resolved stopped-flow Förster resonance energy transfer (FRET) spectroscopy measurements. This approach to study enzyme dynamics was further linked with traditional UV-visible stopped-flow approaches that probed enzymatic electron transfer chemistry. Results showed a tight coupling between the kinetics of electron transfer chemistry and domain dynamics in the two diflavin oxidoreductase systems studied. Moreover, through the use of a flavin analogue (5-deazaflavin mononucleotide) and isotopically labelled nicotinamide coenzymes (pro-S/R NADP2H), key steps in the reaction mechanism were correlated with dynamic events in calmodulin, the partner protein of nNOS.The approaches developed in this project should find wider application in related studies of complex electron-transfer enzymes. Altogether, this research emphasises the key link between protein domain motions and electron transfer chemistry and provides a framework to describe the relationship between domain dynamics and diflavin oxidoreductase function.

The relationship between protein structure, motions, and catalytic activity is an evolving perspective in enzymology. An interactive approach, where experimental and theoretical studies examine the same catalytic mechanism, is instrumental in addressing this issue. We combine various techniques, including steady state and pre-steady state kinetics, temperature dependence of kinetic isotope effects (KIEs), site-directed mutagenesis, X-ray crystallography, and quantum mechanics/molecular mechanics (QM/MM) calculations, to study the catalytic mechanisms of thymidylate synthase (TSase). Since TSase catalyzes the last step of the sole intracellular de novo synthesis of thymidylate (i.e. the DNA base T), it is a common target for antibiotic and anticancer drugs. The proposed catalytic mechanism for TSase comprises a series of bond cleavages and formations including activation of two C-H bonds: a rate-limiting C-H→C hydride transfer and a faster C-H→O proton transfer. This provides an excellent model system to examine the structural and dynamic effects of the enzyme on different C-H cleavage steps in the same catalyzed reaction. Our experiments found that the KIE on the hydride transfer is temperature independent while the KIE on the proton transfer is temperature dependent, implying the protein environment is better organized for H-tunneling in the former. Our QM/MM calculations revealed that the hydride transfer has a transition state (TS) that is invariable with temperature while the proton transfer has multiple subsets of TS structures, which corroborates with our experimental results. The calculations also suggest that collective protein motions rearrange the network of H-bonds to accompany structural changes in the ligands during and between chemical transformations. These computational results not only illustrate functionalities of specific protein residues that reconcile many previous experimental observations, but also provide guidance for future experiments to verify the proposed mechanisms. In addition, we conducted experiments to examine the importance of long-range interactions in TSase-catalyzed reaction, using both kinetic and structural analysis. Those experiments found that a remote mutation affects the hydride transfer by disrupting concerted protein motions, and Mg2+ binds to the surface of TSase and affects the hydride transfer at the interior active site. Both our experiments and computations have exposed interesting features of ecTSase that can potentially provide new targets for antibiotic drugs targeting DNA biosynthesis. The relationship between protein structure, motions, and catalytic activity learned from this project may have general implications to the question of how enzymes work.

Protein motions are complex, including occurring at different time scales, and their roles in enzyme-catalyzed reactions have always been of great interest among enzymologists. In order to characterize the potential factors that play a role on the chemical step of enzymatic reactions, variants of dihydrofolate reductase have been used as a benchmark system to study the motions of proteins correlated with the chemical step. A “global dynamic network” of coupled residues in Escherichia coli dihydrofolate reductase (ecDHFR), which assists in catalyzing the chemical step, has been demonstrated through quantum mechanical/molecular mechanical and molecular dynamic (QM/MM/MD) simulations, as well as bioinformatic analyses. A few specific residues — M42, G121, and I14 — were shown to function synergistically with measurements of single turnover rates and the temperature dependence of intrinsic kinetic isotope effects (KIEsint) of site-directed mutants. Although similar networks have been found in other enzymes, the general features of these networks are still unclear. This project focuses on exploring homologous residues of the proposed global network in human DHFR through computer simulations and measurements of the temperature dependence of KIEsint. The mutants M53W and S145V, both remote residues, showed significant decreases in catalytic efficiency. Non-additive isotope effects on activation energy were observed between M53 and S145, indicating their synergistic effect on hydride transfer in human DHFR. Apart from the effects of the conserved residues, we also extend our studies to exploring three potential phylogenetic events that account for the discrepancies between E. coli and human DHFR. They are L28, PP insertion and PEKN insertions by phylogenetic sequence analysis. Two of them (N23PP and G51PEKN E. coli DHFR) have been proved to be important both by MD simulation and experimental probe of KIEs measurement. The experiments have found that PP insertion itself rigidified the M20 loop and motions coupled to hydride transfer were impaired, however, loop rigidification was improved after incorporating PEKN. Furthermore, deletion of PP and PEKN of the engineered human enzyme also show a similar outcome. However, the effect of the key residue of L28 is not clear. In this project, we have step-wise engineered the human DHFR to be like hagfish (F31M) and E. coli (F32L). And it is found out that there is an increase in the temperature dependence of KIEs when the enzyme was bacterilized into a more primitive variant. This indicates that not only is residue F32 important and correlated with the chemical step as indicated by bioinformatic studies, but it is possible to trace the evolutionary trajectory. A triple mutation F32L-PP26N-PEKN62G on the human DHFR was also conducted, and it is not surprising to find out that the temperature dependence of KIEs has retained its behavior like wild-type human DHFR. These results suggest that the three predicted phylogenetically coherent events coevolved together to maintain the evolutionary preservation of the protein dynamics to enable H-tunneling from well-reorganized active sites. As has been indicated by the previous project, as the enzyme evolves, the active site of the enzyme will “reorganize” to form the optimal transition state for chemical step (from F32L-F32M-wild type DHFR). Here in this project, we aimed to systematically address this point of view through a series of cyclic permutation DHFR from directed evolutions. As this primitive enzyme is 7 orders of magnitude less efficient than the well-evolved human DHFR, together with four generations of evolved variants (cp, cp’ and cp”), this provides a good model system for explorations of the molecular basis of enzyme evolution. It is found that the organizations of transition state are improved before the catalytic efficiency is enhanced as the enzyme evolves.

No description available.

Enzymes are extraordinary molecules that can accelerate chemical reactions by several orders of magnitude. With recent advancements in structural biology together with classical enzymology the mechanism of many enzymes has become understood at the molecular level. During the last ten years significant efforts have been invested to understand the structure and dynamics of the actual catalyst (i. e. the enzyme). There has been a tremendous development in NMR spectroscopy (both hardware and pulse programs) that have enabled detailed studies of protein dynamics. In many cases there exists a strong coupling between enzyme dynamics and function. Here I have studied the conformational dynamics and thermodynamics of three model systems: adenylate kinase (Adk), Peroxiredoxin Q (PrxQ) and the structural protein S16. By developing a novel chemical shift-based method we show that Adk binds its two substrates AMP and ATP with an extraordinarily dynamic mechanism. For both substrate-saturated states the nucleotide-binding subdomains exchange between open and closed states, with the populations of these states being approximately equal. This finding contrasts with the traditional view of enzyme-substrate complexes as static low entropy states. We are also able to show that the individual subdomains in Adk fold and unfold in a non-cooperative manner. This finding is relevant from a functional perspective, since it allows a change in hydrogen bonding pattern upon substrate-binding without provoking global unfolding of the entire enzyme (as would be expected from a two-state folding mechanism). We also studied the structure and dynamics of the plant enzyme PrxQ in both reduced and oxidized states. Experimentally validated structural models were generated for both oxidation states. The reduced state displays unprecedented μs-ms conformational dynamics and we propose that this dynamics reflects local and functional unfolding of an α-helix in the active site. Finally, we solved the structure of S16 from Aquifex aeolicus and propose a model suggesting a link between thermostability and structure for a mesophilic and hyperthermophilic protein pair. A connection between the increased thermostability in the thermophilic S16 and residual structure in its unfolded state was discovered, persistent at high denaturant concentrations, thereby affecting the difference in heat capacity difference between the folded and unfolded state. In summary, we have contributed to the understanding of protein dynamics and to the coupling between dynamics and catalytic activity in enzymes.