Browsing by Subject "Biophysics, General"

Gram-negative bacteria possess an asymmetric outer membrane in which the inner leaflet is composed primarily of phospholipids while the outer leaflet contains both phospholipids and lipopolysaccharide (LPS). LPS forms a structural barrier that protects Gram-negative bacteria from antibiotics and other environmental stressors. The lipid A anchor of LPS is a glucosamine-based saccharolipid that is further modified with core and O-antigen sugars. In addition to serving a structural role as the hydrophobic anchor of LPS, lipid A is recognized by the innate immune system in animal cells and macrophages. The enzymes of Lipid A biosynthesis are conserved in Gram-negative bacteria; in most species, a single copy of each bio-synthetic gene is present. The exception is lpxH, which is an essential gene encoding a membrane-associated UDP-2,3-diacylglucosamine hydrolase, which catalyzed the attack of water upon the alpha-phosphate of its substrate and the leaving of UMP, resulting in the formation of lipid X. Many Gram-negatives lack an lpxH orthologue, yet these species must possess an activity analogous to that of LpxH. We used bioinformatics approaches to identify a candidate gene, designated lpxI, encoding this activity in the model organism Caulobacter crescentus. We then demonstrated that lpxI can rescue Escherichia coli deficient in lpxH. Moreover, we have shown that LpxI possesses robust and specific UDP-2,3-diacylglucosamine hydrolase activity in vitro. We have developed high-yield purification schema for Caulobacter crescentus LpxI (CcLpxI) heterologously expressed in E. coli. We crystallized CcLpxI and determined its 2.6 Å x-ray crystal structure in complex with lipid X. CcLpxI, which has no known homologues, consists of two novel domains connected by a linker. Moreover, we have identified a point mutant of CcLpxI which co-purifies with its substrate in a 0.85:1 molar ratio. We have solved the x-ray crystal structure of this mutant to 3.0 Å; preliminary comparison with the product-complexed model reveals striking differences. The findings described herein set the stage for further mechanistic and structural characterization of this novel enzyme.

In this work, we also isolate and characterize LpxB, an essential lipid A biosynthetic gene which is conserved among all Gram-negative bacteria. We purify E. coli and Hemophilus influeznea LpxB to near-homogeneity on a 10 mg scale, and we determine that E. coli LpxB activity is dependent upon the bulk surface concentration of its substrates in a mixed micellar assay system, suggesting that catalysis occurs at the lipid interface. E. coli LpxB partitions with membranes, but this interaction is partially abolished in high-salt conditions, suggesting that a significant component of LpxB's membrane association is ionic in nature. E. coli LpxB (Mr ~ 43 kDa) is a peripheral membrane protein, and we demonstrate that it co-purifies with phospholipids. We estimate, by autoradiography and mass-spectrometry, molar ratios of phospholipids to purified enzyme of 1.6-3.5:1. Transmission electron microscopy reveals the accumulation of intra-cellular membranes when LpxB is massively over-expressed. Alanine-scanning mutagenesis of selected conserved LpxB residues identified two, D89A and R201A, for which no residual catalytic activity is detected. Our data support the hypothesis that LpxB performs catalysis at the cytoplasmic surface of the inner membrane, and provide a rational starting-point for structural studies. This work contributes to knowledge of the small but growing set of structurally and mechanistically characterized enzymes which perform chemistry upon lipids.

Many of the biological roles of proteins are modulated through protein-ligand interactions, making proteins important targets for drug therapies and diagnostic imaging probes. The discovery of novel ligands for a protein of interest often relies on the use of high throughput screening (HTS) technologies designed to detect protein-ligand binding. The basis of one such technology is a recently reported mass spectrometry-based assay termed SUPREX (stability of unpurified proteins from rates of H/D exchange). SUPREX is a technique that uses H/D exchange and MALDI-mass spectrometry for the measurement of protein stabilities and protein-ligand binding affinities. The single-point SUPREX assay is an abbreviated form of SUPREX that is capable of detecting protein-ligand interactions in a high throughput manner by exploiting the change in protein stability that occurs upon ligand binding.

This work is focused on the development and application of high throughput SUPREX protocols for the detection of protein-ligand binding. The first step in this process was to explore the scope of SUPREX for the analysis of non-two-state proteins to determine whether this large subset of proteins would be amenable to SUPREX analyses. Studies conducted on two model proteins, Bcl-xL and alanine:glyoxylate aminotransferase, indicate that SUPREX can be used to detect and quantify the strength of protein-ligand binding interactions in non-two-state proteins.

The throughput and efficiency of a high throughput SUPREX protocol (i.e., single-point SUPREX) was also evaluated in this work. As part of this evaluation, cyclophilin A, a protein target of diagnostic and therapeutic significance, was screened against the 880-member Prestwick Chemical Library to identify novel ligands that might be useful as therapeutics or imaging agents for lung cancer. This screening not only established the analytical parameters of the assay, but it revealed a limitation of the technique: the efficiency of the assay is highly dependent on the precision of each mass measurement, which generally decreases as protein size increases.

To overcome this limitation and improve the efficiency and generality of the assay, a new SUPREX protocol was developed that incorporated a protease digestion step into the single-point SUPREX protocol. This new protocol was tested on two model proteins, cyclophilin A and alanine:glyoxylate aminotransferase, and was found to result in a significant improvement in the efficiency of the SUPREX assay in HTS applications. This body of work resulted in advancements in the use of SUPREX for high throughput applications and laid the groundwork for future HTS campaigns on target proteins of medical significance.

Understanding the interconversion between the thermodynamically distinguishable states present in a protein folding pathway provides not only the kinetics and energetics of protein folding but also insights into the functional roles of these states in biological systems. The protein component of bacterial RNase P holoenzyme from Bacillus subtilis (P protein) was used as a model system to elucidate the general folding/unfolding of an intrinsically unstructured protein (IUP) both in the absence and presence of ligands.

P protein was previously characterized as an intrinsically unstructured protein, and it is predominantly unfolded in the absence of ligands. Addition of small anions can induce the protein to fold. Therefore, the folding and binding are tightly coupled. Trimethylamine-N oxide (TMAO), an osmolyte that stabilizes the unliganded folded form of the protein, enabled us to study the folding process of P protein in the absence of ligand. Transient stopped-flow kinetic time courses at various final TMAO concentrations showed multiphase kinetics. Equilibrium "cotitration" experiments were performed using both TMAO and urea to obtain a TMAO-urea titration surface of P protein. Both kinetic and equilibrium studies show evidence of an intermediate state in the P protein folding process. The intermediate state is significantly populated and the folding rate constants involved in the reaction are slow relative to similar size proteins.

NMR spectroscopy was used to characterize the structural properties of the folding intermediate of P protein. The results indicate that the N-terminal (residues 2-19) and C-terminal regions (residues 91-116, 118 is the last residue) are mostly unfolded. 1H-15N HSQC NMR spectra were collected at various pH values. The results suggest that His 22 may play a major role in the energetics of the equilibria between the unfolded, intermediate, and native states of P protein.

Ligand-induced folding kinetics were also investigated to elucidate the overall coupled folding and binding mechanism of P protein and the holoenzyme assembly process. Stopped flow fluorescence experiments were performed at various final ligand concentrations and the data were analyzed using a minimal complexity model that included three conformational states (unfolded, intermediate and folded) in each of three possible liganding states (0, 1 and 2 ligands). The kinetic and equilibrium model parameters that best fit the data were used to calculate the flux through each of the six possible folding/binding pathways. This novel flux-based analysis allows evaluation of the relative importance of pathways in which folding precedes binding or vice versa. The results indicate that the coupled folding and binding mechanism of P protein is strongly dependent on ligand concentration. This conclusion can be generalized to other protein systems for which ligand binding is coupled to conformational changes.

The physics of complex systems has grown considerably as a field in recent decades, largely due to improved computational technology and increased availability of systems level data. One area in which physics is of growing relevance is molecular biology. A new field, systems biology, investigates features of biological systems as a whole, a strategy of particular importance for understanding emergent properties that result from a complex network of interactions. Due to the complicated nature of the systems under study, the physics of complex systems has a significant role to play in elucidating the collective behavior.

In this dissertation, we explore three problems in the physics of complex systems, motivated in part by systems biology. The first of these concerns the applicability of Boolean models as an approximation of continuous systems. Studies of gene regulatory networks have employed both continuous and Boolean models to analyze the system dynamics, and the two have been found produce similar results in the cases analyzed. We ask whether or not Boolean models can generically reproduce the qualitative attractor dynamics of networks of continuously valued elements. Using a combination of analytical techniques and numerical simulations, we find that continuous networks exhibit two effects -- an asymmetry between on and off states, and a decaying memory of events in each element's inputs -- that are absent from synchronously updated Boolean models. We show that in simple loops these effects produce exactly the attractors that one would predict with an analysis of the stability of Boolean attractors, but in slightly more complicated topologies, they can destabilize solutions that are stable in the Boolean approximation, and can stabilize new attractors.

Second, we investigate ensembles of large, random networks. Of particular interest is the transition between ordered and disordered dynamics, which is well characterized in Boolean systems. Networks at the transition point, called critical, exhibit many of the features of regulatory networks, and recent studies suggest that some specific regulatory networks are indeed near-critical. We ask whether certain statistical measures of the ensemble behavior of large continuous networks are reproduced by Boolean models. We find that, in spite of the lack of correspondence between attractors observed in smaller systems, the statistical characterization given by the continuous and Boolean models show close agreement, and the transition between order and disorder known in Boolean systems can occur in continuous systems as well. One effect that is not present in Boolean systems, the failure of information to propagate down chains of elements of arbitrary length, is present in a class of continuous networks. In these systems, a modified Boolean theory that takes into account the collective effect of propagation failure on chains throughout the network gives a good description of the observed behavior. We find that propagation failure pushes the system toward greater order, resulting in a partial or complete suppression of the disordered phase.

Finally, we explore a dynamical process of direct biological relevance: asymmetric cell division in A. thaliana. The long term goal is to develop a model for the process that accurately accounts for both wild type and mutant behavior. To contribute to this endeavor, we use confocal microscopy to image roots in a SHORTROOT inducible mutant. We compute correlation functions between the locations of asymmetrically divided cells, and we construct stochastic models based on a few simple assumptions that accurately predict the non-zero correlations. Our result shows that intracellular processes alone cannot be responsible for the observed divisions, and that an intercell signaling mechanism could account for the measured correlations.

The overall goal of this project is to enhance the physical accuracy of individual models in macromolecular NMR (Nuclear Magnetic Resonance) structures and the realism of variation within NMR ensembles of models, while improving agreement with the experimental data. A secondary overall goal is to combine synergistically the best aspects of NMR and crystallographic methodologies to better illuminate the underlying joint molecular reality. This is accomplished by using the powerful method of all-atom contact analysis (describing detailed sterics between atoms, including hydrogens); new graphical representations and interactive tools in 3D and virtual reality; and structural bioinformatics approaches to the expanded and enhanced data now available.

The resulting better descriptions of macromolecular structure and its dynamic variation enhances the effectiveness of the many biomedical applications that depend on detailed molecular structure, such as mutational analysis, homology modeling, molecular simulations, protein design, and drug design.

Cellular dynamics arise from intricate interactions among diverse components, such as metabolites, RNAs, and proteins. An in-depth understanding of these interactions requires an integrated approach to the investigation of biological systems. This task can benefit from a combination of mathematical modeling and experimental validations, which is becoming increasingly indispensable for basic and applied biological research.

Utilizing a combination of modeling and experimentation, we investigate mammalian cell cycle entry. We begin our investigation by making predictions with a mathematical model, which is constructed based on the current knowledge of biology. To test these predictions, we develop experimental platforms for validations, which in turn can be used to further refine the model. Such iteration of model predictions and experimental validations has allowed us to gain an in-depth understanding of the cell cycle entry dynamics.

In this dissertation, we have focused on the Myc-Rb-E2F signaling pathway and its associated pathways, dysregulation of which is associated with virtually all cancers. Our analyses of these signaling pathways provide insights into three questions in biology: 1) regulation of the restriction point (R-point) in cell cycle entry, 2) regulation of the temporal dynamics in cell cycle entry, and 3) post-translational regulation of Myc by its upstream signaling pathways. The well-studied pathways can serve as a foundation for perturbations and tight control of cell cycle entry dynamics, which may be useful in developing cancer therapeutics.

We conclude by demonstrating how a combination of mathematical modeling and experimental validations provide mechanistic insights into the regulatory networks in cell cycle entry.

Instability in the propagation of nonlinear electro-chemical waves in the heart is responsible for life-threatening disease. This thesis describes an investigation of the effects of boundaries on cardiac wave propagation that arises from a site where an electrical stimulus is applied or from boundaries beyond which current does not flow. It is generally believed that the spatial scale for boundary effects is approximately equal to the passive length constant, lambda, of the tissue, the distance over which a a voltage pulse decays when it is below the threshold for wave generation. From the results of in vitro experiments with bullfrog cardiac tissue and through numerical simulations, I find that boundaries affect wave propagation over a much larger spatial scale and that the spatial variation in some cardiac restitution properties is correlated statistically with the onset of alternans, a possible precursor to fibrillation in the human heart.

An optical imaging system using novel illumination based on LEDs is used to determine the spatial dependence of action potential duration (APD) and the slope of the dynamic restitution curve S_DRC, which describes the relationship between steady-state APD and diastolic interval. For tissue with nearly identical cells, I find that APD is longest near the stimulus and shortest near the physical boundary with significant changes (~100 ms) over a distance of ~10lambda. S_DRC decreases with distance from the stimulus at a constant rate (~0.1-1.5 /mm) over the surface of the tissue. Simulations using a two-variable cardiac model confirm that spatial patterns of APD and S_DRC can be induced by boundaries.

Additional measurements with the simultaneous impalement of two microelectrodes are used to determine the spatial differences of other restitution properties. These studies indicate that APD and S_DRC, as well as the slopes of the constant-BCL and S1S2 restitution curves, vary in space and that the spatial differences and onset of alternans at rapid pacing are correlated. If similar correlations are evident in humans, such measurements may identify patients who are susceptible to arrhythmias and allow for early treatment.

Inositol Polyphosphate Multi-Kinase (IPMK, also known as ArgRIII, Arg82, and IPK2) is a central component of the inositol signaling system, catalyzing the phosphorylation of at least four different inositol polyphosphate species in vivo with in vitro activity observed for three more. Each of these IP species is sterically unique and the phosphorylation target varies between the 6'-, 3'-, or 5'-hydroxyls, classifying IPMK as a 6/3/5-kinase. The products of IPMK have been linked to multiple processes including cell cycle regulation, transcriptional control, telomere length regulation, mRNA export and various phenotypes including mouse embryonic and fly larvae development, and stress responses in plants and yeast. Linking specific IP species and cellular processes has been complicated by the inability to distinguish between the different effects of the various IP species generated by IPMK. Deletion of IPMK affects the IP populations of all its various substrates and products and therefore the role of a single IP species cannot be tracked. The goals of this work were to address the question of substrate selectivity and develop new tools to probe inositol signaling in vivo through a combination of structural, enzymatic, and genomic techniques.

The structure of Arabidopsis thaliana IPMK is reported at 2.9Å resolution and in conjunction with a new model of inositol selectivity has been used to design constructs with altered substrate profiles. In vitro and in vivo experiments have confirmed that IPMK identifies substrate inositol polyphosphate species through a recognition surface that requires phosphate groups occupy specific pockets and rejects those with axial phosphate groups in specific regions. In vivo experiments have linked specific inositol polyphosphate species to nitrogen metabolism and temperature sensitivity in yeast and established the potential for these constructs to be used to probe signaling in other organisms.

We study the comparison of computational simulations of biomolecules to experimental data. We study the convergence of these simulations to equilibrium and determine measures of variance of the data using statistical methods. We run replica-exchange molecular dynamics (REMD) simulations of eight helical peptides and compare the simulation helicity to the experimentally measured helicity of the peptides. We use one-way sensitivity analysis to determine which parameter changes have a large effect on helicity measurements and use Bayesian updating for a parameter of the AMBER potential. We then consider the theoretical convergence behavior of the REMD algorithm itself by evaluating the properties of the isothermal numerical integrators used in the underlying MD. The underlying constant-temperature integrators explored in this thesis represent a majority of the deterministic isothermal methods used with REMD simulations and we show that these methods either fail to be measure-invariant or are not ergodic. For each of the non-ergodic integrators we show that REMD fails to be ergodic when run with the integrator. We give computational results from examples to demonstrate the practical implications of non-ergodicity and describe hybrid Monte Carlo, a method that leads to ergodicity. Finally, we consider the use of stochastic Langevin dynamics to simulate isothermal MD. We show geometric ergodicity of the Langevin diffusion over a simplified system with the eventual goal of determining geometric ergodicity for Langevin dynamics over the full AMBER potential.

There were 2.5 million people newly infected with HIV in 2007, clearly motivating the need for additional novel prevention methods. In response, topical vaginal antimicrobials, or microbicides, are being developed. These products aim to stop HIV transmission through local, vaginal delivery of antiviral compounds. To succeed, microbicides require a potent active compound within a well-engineered delivery vehicle.

A well-engineered delivery vehicle provides an antiviral compound with the greatest opportunity to interact with HIV and/or infected cells, thereby increasing overall microbicide effectiveness. The theoretical and experimental investigations within this dissertation are concerned with the study of HIV and active compound transport within microbicide delivery vehicles and with the mechanisms by which these transport processes can be affected to maximize viral neutralization. To initially investigate the factors contributing to microbicide effectiveness, a combined pharmacokinetic and pharmacodynamic model of HIV transport and neutralization within a microbicide product was created. Model results suggested that thin (~100µm) layers of microbicide product may protect against HIV infection. Model results also indicated that a specific and engineerable property of delivery vehicles - the ability to restrict viral transport - may increase the overall effectiveness of a microbicide. Two new experimental assays were developed to test the hypothesis that delivery vehicles can slow viral transport. First, a novel methodology was created to measure particle diffusion over length scales relevant to microbicide delivery (50-500µm). Results showed that current vehicles significantly restrict the transport of small molecules and proteins. The second assay was designed to test HIV transport in a biologically relevant, layered (fluid-microbicide-tissue) configuration of a microbicide product in vivo; infectious HIV was placed above a thin layer of a microbicide delivery vehicle. Assay results showed that HIV transport is significantly slowed by two different placebo gels. This experimental confirmation of viral restriction in hydrogels, combined with the theoretical finding that viral restriction increased microbicide effectiveness, strongly motivates the future development of new delivery vehicles that intentionally slow viral transport. These new experimental methodologies can also be used to screen and compare future delivery vehicles to produce optimal microbicide products.

Finally, a two-dimensional, computational finite-element vaginal model was created to evaluate the transport of drugs from an intravaginal ring. This model determined that while IVRs may be effective in the delivery of antiviral compound, their performance is influenced by the flow of vaginal fluid. The analysis also warns about the potential for local toxicity.

Well-engineered delivery vehicles are an essential component to microbicide performance because they maximize the opportunities for active compounds to interact with and neutralize HIV. The studies in this dissertation demonstrate that delivery vehicles have a significant effect on active compound and HIV transport. To create an effective microbicide, vehicle effects on transport processes must be well understood, purposefully engineered, and carefully optimized to ensure maximal interactions between antiviral compounds and virus. Directed engineering of delivery vehicles contribute to the foundation for microbicide success.