Physics
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Item Understanding Allosteric Communication in Biological Systems using Molecular Dynamics Simulations(2024) Samanta, Riya; Matysiak, Silvina; Biophysics (BIPH); Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)Allostery is critical to survival in living organisms due to its biological relevance in signal transduction, metabolism, and drug discovery. However, the molecular details of this phenomenon remain unclear. In this thesis, I present my work on two allosteric protein systems, each representative of structure-based (E. coli Biotin Protein Ligase) and dynamics-based (B. taurus S100B) allostery. I examined the structural and dynamic features of the proteins and associated variants subjected to various allosteric triggers (ligand/salt/mutations) to study how external/internal perturbations transmit across large distances using Molecular Dyanmic simulations in conjunction with the experiments carried out by our collaborators. Additionally, I carried out Network analyses on the two systems to characterize communication pathways on the protein/ protein family levels. Together, the structural and dynamic features would help us elucidate the underlying mechanism of allostery. The first chapter introduces the two systems with a brief dive into the history of allostery. In the second chapter, my work on E. coli Biotin Protein Ligase and its variants reveal one possible mechanism by which disorder-to-order transitions at the functional surfaces transmit via local changes around the critical residues in the allosteric network. The third chapter explores how the protein network reconfigures to adopt a new allosteric function by studying the allosteric and non-allosteric Biotin Protein Ligases. The fourth chapter elucidates the structural and dynamical markers in bovine S100B, which help to relay information about an allosteric signal by varying two allosteric triggers - ionic strength and target peptide. The final chapter sums up my conclusions, where I propose additional experiments and computational analyses that could be carried out to further our understanding of allostery.Item THE ROLE OF TRANSCRIPTION FACTOR DYNAMICS IN GENE EXPRESSION: DOES TIME MATTER?(2021) Garcia Grisales, David A; Upadhyaya, Arpita; Hager, Gordon L; Physics; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)Different proteins and complexes work together at multiple time scales to orchestrate the activation and silencing of genes in a process called transcription. Understanding transcriptional regulation is of utmost importance to reveal mechanisms behind cell homeostasis and pathologies. The transcription machinery needs to be perfectly tuned in space and time to control the expression of genes to carry out cellular and physiological processes in the noisy and highly heterogeneous nuclear microenvironment. Transcription factors (TF), specialized proteins that bind to specific DNA sequences to regulate mRNA production, are central players in transcriptional regulation. TFs need to navigate the intricate nuclear microenvironment to bind to specific regulatory elements with binding times critically determining their regulatory functions. Recent advances in super-resolution microscopy have allowed us to investigate the dynamics of the transcriptional machinery at the single molecule level, revealing the essential features of transcriptional control. However, how TFs dynamically navigate the nuclear microenvironment and interact with chromatin to activate or silence genes remains poorly understood. I used state of the art microscopy and genomic techniques to show that binding times of TFs to chromatin are power-law distributed. I proposed a new theoretical framework to demonstrate the broad distribution of binding affinity arises from heterogeneity in TF-chromatin interactions and the nuclear microenvironment, contrary to the current paradigm of well-defined and distinguishable TF binding times to specific and non-specific chromatin sites. These studies reconciled discrepancies between genomics, gene expression and TF mobility. I used statistical modeling to show that TFs exhibit two distinguishable low mobility states in the nucleus. One state is related to chromatin binding while the second arises due to protein-protein interactions mediated by intrinsically disordered regions of the TF and potentially controls the initiation rate of transcription. Finally, I studied transcriptional regulation on substrates of different stiffness revealing a connection between the physical properties of the cell microenvironment and TF dynamics. I demonstrated that substrate stiffness activates the estrogen receptor even in the absence of its ligand, with implications for our understanding and treatment of breast cancer. The evidence presented here shows that TF binding times are finely tuned to regulate gene expression.Item DISSECTING THE GENE REGULATORY FUNCTION OF THE MYC ONCOGENE WITH SINGLE-MOLECULE IMAGING(2020) Patange, Simona; Larson, Daniel R; Girvan, Michelle; Biophysics (BIPH); Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)The MYC oncogene contributes to an estimated 100,000 cancer-related deaths annually in the United States and is associated with aggressive tumor progression and poor clinical outcome. MYC is a nuclear transcription factor that regulates a myriad of cellular activities and has direct interactions with hundreds of proteins, which has made a unified understanding of its function historically difficult. In recent years, several groups have put forth a new hypothesis that questions the prevailing view of MYC as a gene-specific transcription factor and instead envision it as a global amplifier of gene expression. Instead of being an on/off switch for transcription, MYC is proposed to act as a `volume knob' to amplify and sustain the active gene expression program in a cell. The scope of the amplifier model remains controversial in part because studies of MYC largely consist of cell population-based measurements obtained at fixed timepoints, which makes distinguishing direct from indirect consequences on gene expression difficult. A high-temporal, high-spatial precision viewpoint of how MYC acts in single living cells does not exist. To evaluate the competing hypotheses of MYC function, we developed a single-cell assay for precisely controlling MYC and interrogating the effects on transcription in living cells. We engineered `Pi-MYC,' an optogenetic variant of MYC that is biologically active, can be visualized under the microscope, and can be controlled with light. We combined Pi-MYC with single-molecule imaging methods to obtain the first real-time observations of how MYC affects RNA production and transcription factor mobility in single cells. We show that MYC increases the duration of active periods of genes population-wide, and globally affects the binding dynamics of core transcription factors involved in RNA Polymerase II transcription complex assembly and productive elongation. These findings provide living, single-cell evidence of MYC as a global amplifier of gene expression, and suggests the mechanism is by stabilizing the active period of a gene through interactions with core transcription machinery.Item Theoretical Studies of the Workings of Processive Molecular Motors(2017) Vu, Huong Thuy; Thirumalai, Devarajan; Biophysics (BIPH); Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)Processive molecular motors, such as kinesins, myosins and helicases, take multiple discrete steps on linear polar tracks such as microtubules, filamentous actin, and DNA/RNA substrates. Insights into the mechanisms and functions of this important class of biological motors have been obtained through observations from single-molecule experiments and structural studies. Such information includes the distribution of n, the number of steps motors take before dissociating, and v, the motor velocity, in the presence and absence of an external resistive force from single molecule experiments; and different structures of different states of motors at different conditions. Based on those available data, this thesis focuses on using both analytical and computational theoretical tools to investigate the workings of processive motors. Two examples of processive motors considered here are kinesins that walk on microtubules while transporting vesicles, and helicases which translocate on DNA/RNA substrate while unwinding the helix substrate. New physical principles and predictions related to their motility emerge from the proposed theories. The most significant results reported in this thesis are: Exact and approximate equations for velocity distribution, P(v), and runlength distribution, P(n), have been derived. Application of the theory to kinesins shows that P(v) is non-Gaussian and bimodal at high resistive forces. This unexpected behavior is a consequence of the discrete spacing between the alpha/beta tubulins, the building blocks of microtubule. In the case of helicases, we demonstrate that P(v) of typical helicases T7 and T4 shows signatures of heterogeneity, inferred from large variations in the velocity from molecule to molecule. The theory is used to propose experiments in order to distinguish between different physical basis for heterogeneity. We generated a one-microsecond atomic simulation trajectory capturing the docking process of the neck-linker, a crucial element deemed to be important in the motility of Kinesin-1. The conformational change in the neck linker is important in the force generation in this type of motor. The simulations revealed new conformations of the neck-linker that have not been noted in previous structural studies of Kinesin-1, but which are demonstrated to be relevant to another superfamily member, Kinesin-5. By comparing the simulation results with currently available data, we suggest that the two superfamilies might actually share more similarities in the neck-linker docking process than previously thought.Item Making Predictions and Handling Errors in Reconstructed Biological Networks(2013) Platig, John; Girvan, Michelle; Physics; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)In this thesis we present methods for applying techniques from complex network theory to analyze and interpret inferred biological interactions. With the advent of high throughput technologies such as gene microarrays and genome-wide sequencing, it is now possible to measure the activity of every gene in a cancer cell population under different conditions. How to extract important interactions from these experiments remains an outstanding question. Here we present a method to identify these key interactions by focusing on short paths in a transcription factor network. We use a mutual information-based approach to infer the transcription factor network from gene expression microarrays, which measure perturbations in a Diffuse Large B Cell Lymphoma cell line. By focusing on the number of short paths between transcription factors and signature genes in the inferred network, we find a set of transcription factors whose biology is crucial to the continued survival of these lymphoma cells and also show that a subset of these factors have a distinct expression pattern in patient tumors as well. As many networks of interest are reconstructed from data containing errors, we introduce two simple models of false and missing links to characterize the effects of network misinformation on three commonly used centrality measures: degree centrality, betweenness centrality, and dynamical importance. We show that all three measures are especially robust to both false and missing links when the network has a power law in the tail of its degree distribution.