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- Genre: Doctoral Dissertation
Description
Proteins are a fundamental unit in biology. Although proteins have been extensively studied, there is still much to investigate. The mechanism by which proteins fold into their native state, how evolution shapes structural dynamics, and the dynamic mechanisms of many diseases are not well understood. In this thesis, protein folding is explored using a multi-scale modeling method including (i) geometric constraint based simulations that efficiently search for native like topologies and (ii) reservoir replica exchange molecular dynamics, which identify the low free energy structures and refines these structures toward the native conformation. A test set of eight proteins and three ancestral steroid receptor proteins are folded to 2.7Å all-atom RMSD from their experimental crystal structures. Protein evolution and disease associated mutations (DAMs) are most commonly studied by in silico multiple sequence alignment methods. Here, however, the structural dynamics are incorporated to give insight into the evolution of three ancestral proteins and the mechanism of several diseases in human ferritin protein. The differences in conformational dynamics of these evolutionary related, functionally diverged ancestral steroid receptor proteins are investigated by obtaining the most collective motion through essential dynamics. Strikingly, this analysis shows that evolutionary diverged proteins of the same family do not share the same dynamic subspace. Rather, those sharing the same function are simultaneously clustered together and distant from those functionally diverged homologs. This dynamics analysis also identifies 77% of mutations (functional and permissive) necessary to evolve new function. In silico methods for prediction of DAMs rely on differences in evolution rate due to purifying selection and therefore the accuracy of DAM prediction decreases at fast and slow evolvable sites. Here, we investigate structural dynamics through computing the contribution of each residue to the biologically relevant fluctuations and from this define a metric: the dynamic stability index (DSI). Using DSI we study the mechanism for three diseases observed in the human ferritin protein. The T30I and R40G DAMs show a loss of dynamic stability at the C-terminus helix and nearby regulatory loop, agreeing with experimental results implicating the same regulatory loop as a cause in cataracts syndrome.
ContributorsGlembo, Tyler J (Author) / Ozkan, Sefika B (Thesis advisor) / Thorpe, Michael F (Committee member) / Ros, Robert (Committee member) / Kumar, Sudhir (Committee member) / Shumway, John (Committee member) / Arizona State University (Publisher)
Created2011
Interactions driving the collapse of islet amyloid polypeptide: implications for amyloid aggregation
Description
Human islet amyloid polypeptide (hIAPP), also known as amylin, is a 37-residue intrinsically disordered hormone involved in glucose regulation and gastric emptying. The aggregation of hIAPP into amyloid fibrils is believed to play a causal role in type 2 diabetes. To date, not much is known about the monomeric state of hIAPP or how it undergoes an irreversible transformation from disordered peptide to insoluble aggregate. IAPP contains a highly conserved disulfide bond that restricts hIAPP(1-8) into a short ring-like structure: N_loop. Removal or chemical reduction of N_loop not only prevents cell response upon binding to the CGRP receptor, but also alters the mass per length distribution of hIAPP fibers and the kinetics of fibril formation. The mechanism by which N_loop affects hIAPP aggregation is not yet understood, but is important for rationalizing kinetics and developing potential inhibitors. By measuring end-to-end contact formation rates, Vaiana et al. showed that N_loop induces collapsed states in IAPP monomers, implying attractive interactions between N_loop and other regions of the disordered polypeptide chain . We show that in addition to being involved in intra-protein interactions, the N_loop is involved in inter-protein interactions, which lead to the formation of extremely long and stable β-turn fibers. These non-amyloid fibers are present in the 10 μM concentration range, under the same solution conditions in which hIAPP forms amyloid fibers. We discuss the effect of peptide cyclization on both intra- and inter-protein interactions, and its possible implications for aggregation. Our findings indicate a potential role of N_loop-N_loop interactions in hIAPP aggregation, which has not previously been explored. Though our findings suggest that N_loop plays an important role in the pathway of amyloid formation, other naturally occurring IAPP variants that contain this structural feature are incapable of forming amyloids. For example, hIAPP readily forms amyloid fibrils in vitro, whereas the rat variant (rIAPP), differing by six amino acids, does not. In addition to being highly soluble, rIAPP is an effective inhibitor of hIAPP fibril formation . Both of these properties have been attributed to rIAPP's three proline residues: A25P, S28P and S29P. Single proline mutants of hIAPP have also been shown to kinetically inhibit hIAPP fibril formation. Because of their intrinsic dihedral angle preferences, prolines are expected to affect conformational ensembles of intrinsically disordered proteins. The specific effect of proline substitutions on IAPP structure and dynamics has not yet been explored, as the detection of such properties is experimentally challenging due to the low molecular weight, fast reconfiguration times, and very low solubility of IAPP peptides. High-resolution techniques able to measure tertiary contact formations are needed to address this issue. We employ a nanosecond laser spectroscopy technique to measure end-to-end contact formation rates in IAPP mutants. We explore the proline substitutions in IAPP and quantify their effects in terms of intrinsic chain stiffness. We find that the three proline mutations found in rIAPP increase chain stiffness. Interestingly, we also find that residue R18 plays an important role in rIAPP's unique chain stiffness and, together with the proline residues, is a determinant for its non-amyloidogenic properties. We discuss the implications of our findings on the role of prolines in IDPs.
ContributorsCope, Stephanie M (Author) / Vaiana, Sara M (Thesis advisor) / Ghirlanda, Giovanna (Committee member) / Ros, Robert (Committee member) / Lindsay, Stuart M (Committee member) / Ozkan, Sefika B (Committee member) / Arizona State University (Publisher)
Created2013
Description
Molecular dynamics simulations were used to study properties of water at the interface with nanometer-size solutes. We simulated nonpolar attractive Kihara cavities given by a Lennard-Jones potential shifted by a core radius. The dipolar response of the hydration layer to a uniform electric field substantially exceeds that of the bulk. For strongly attractive solutes, the collective dynamics of the hydration layer become slow compared to bulk water, as the solute size is increased. The statistics of electric field fluctuations at the solute center are Gaussian and tend toward the dielectric continuum limit with increasing solute size. A dipolar probe placed at the center of the solute is sensitive neither to the polarity excess nor to the slowed dynamics of the hydration layer. A point dipole was introduced close to the solute-water interface to further study the statistics of electric field fluctuations generated by the water. For small dipole magnitudes, the free energy surface is single-welled, with approximately Gaussian statistics. When the dipole is increased, the free energy surface becomes double-welled, before landing in an excited state, characterized again by a single-welled surface. The intermediate region is fairly broad and is characterized by electrostatic fluctuations significantly in excess of the prediction of linear response. We simulated a solute having the geometry of C180 fullerene, with dipoles introduced on each carbon. For small dipole moments, the solvent response follows the results seen for a single dipole; but for larger dipole magnitudes, the fluctuations of the solute-solvent energy pass through a second maximum. The juxtaposition of the two transitions leads to an approximately cubic scaling of the chemical potential with the dipole strengh. Umbrella sampling techniques were used to generate free energy surfaces of the electric potential fluctuations at the heme iron in Cytochrome B562. The results were unfortunately inconclusive, as the ionic background was not effectively represented in the finite-size system.
ContributorsFriesen, Allan Dwayne (Author) / Matyushov, Dmitry V (Thesis advisor) / Angell, C Austen (Thesis advisor) / Beckstein, Oliver (Committee member) / Mujica, Vladimiro (Committee member) / Arizona State University (Publisher)
Created2012
Description
Disordered many-body systems are ubiquitous in condensed matter physics, materials science and biological systems. Examples include amorphous and glassy states of matter, granular materials, and tissues composed of packings of cells in the extra-cellular matrix (ECM). Understanding the collective emergent properties in these systems is crucial to improving the capability for controlling, engineering and optimizing their behaviors, yet it is extremely challenging due to their complexity and disordered nature. The main theme of the thesis is to address this challenge by characterizing and understanding a variety of disordered many-body systems via unique statistical geometrical and topological tools and the state-of-the-art simulation methods. Two major topics of the thesis are modeling ECM-mediated multicellular dynamics and understanding hyperuniformity in 2D material systems. Collective migration is an important mode of cell movement for several biological processes, and it has been the focus of a large number of studies over the past decades. Hyperuniform (HU) state is a critical state in a many-particle system, an exotic property of condensed matter discovered recently. The main focus of this thesis is to study the mechanisms underlying collective cell migration behaviors by developing theoretical/phenomenological models that capture the features of ECM-mediated mechanical communications in vitro and investigate general conditions that can be imposed on hyperuniformity-preserving and hyperuniformity-generating operations, as well as to understand how various novel transport physical properties arise from the unique hyperuniform long-range correlations.
ContributorsZheng, Yu (Author) / Jiao, Yang (Thesis advisor) / Zhuang, Houlong (Committee member) / Beckstein, Oliver (Committee member) / Ros, Robert (Committee member) / Arizona State University (Publisher)
Created2022
Description
Transportation of material across a cell membrane is a vital process for maintaininghomeostasis. Na+/H+ antiporters, for instance, help maintain cell volume and regulate
intracellular sodium and proton concentrations. They are prime drug targets, since
dysfunction of these crucial proteins in humans is linked to heart and neurodegenerative
diseases. Due to their placement in a cell membrane, their study is particularly difficult
compared to globular proteins, which is likely the reason the transport mechanisms
for these proteins are not entirely known. This work focuses on the electrogenic
bacterial homologs Thermus thermophilus NapA (TtNapA) and Echerichia coli NhaA
(EcNhaA), each transporting one sodium from the interior of the cell for two protons
on outside of the cell. Even though X-ray crystal structures for both of these systems
have been resolved, their study through molecular dynamics (MD) simulations is
limited. The dynamic protonation and deprotonation of the binding site residues is
a fundamental process in the transport cycle, which currently cannot be explored
intuitively with standard MD methodologies. Apart from this limitation, simulation
performance is only a fraction of what is needed to understand the full transport
process, particularly when it comes to global conformational changes. This work
seeks to overcome these limitations through the development and application of a
multiscale thermodynamic and kinetic framework for constructing models capable of
predicting experimental observables, such as the dependence of transporter turnover
on membrane voltage. These models allow interpretation of the effects of individual
processes on the function as a whole. This procedure is demonstrated for TtNapA and
the connection between structure and function is shown by computing cycle turnover
across a range of non-equilibrium conditions.
ContributorsKenney, Ian Michael (Author) / Beckstein, Oliver (Thesis advisor) / Ozkan, Sefika Banu (Committee member) / Heyden, Matthias (Committee member) / Vaiana, Sara (Committee member) / Arizona State University (Publisher)
Created2022
Description
In this thesis, applications of sparsity, specifically sparse-tensors are motivated in physics.An algorithm is introduced to natively compute sparse-tensor's partial-traces, along with direct implementations in popular python libraries for immediate use. These applications include the infamous exponentially-scaling (with system size) Quantum-Many-Body problems (both Heisenberg/spin-chain-like and Chemical Hamiltonian models). This sparsity aspect is stressed as an important and essential feature in solving many real-world physical problems approximately-and-numerically. These include the original motivation of solving radiation-damage questions for ultrafast light and electron sources.
ContributorsCandanedo, Julio (Author) / Beckstein, Oliver (Thesis advisor) / Arenz, Christian (Thesis advisor) / Keeler, Cynthia (Committee member) / Erten, Onur (Committee member) / Arizona State University (Publisher)
Created2023
Description
Protein interactions with the environment are crucial for proper function, butinteraction mechanisms are not always understood. In G protein-coupled receptors
(GPCRs), cholesterol modulates the function in some, but not all, GPCRs. Coarse
grained molecular dynamics was used to determine a set of contact events for each
residue and fit to a biexponential to determine the time scale of the long contacts
observed in simulation. Several residues of interest were indicated in CCK1 R near
Y140, which is known to render CCK1 R insensitive to cholesterol when mutated to
alanine. A difference in the overall residence time between CCK1 R and its cholesterol
insensitive homologue CCK2 R was also observed, indicating the ability to predict
relative cholesterol binding for homologous proteins.
Occasionally large errors and poor fits to the data were observed, so several
improvements were made, including generalizing the model to include K exponential
components. The sets of residence times in the improved method were analyzed using
Bayesian nonparametrics, which allowed for error estimations and the classification of
contact events to the individual components. Ten residues in three GPCRs bound to
cholesterol in experimental structures had large tau. Slightly longer overall interaction
time for the cholesterol sensitive CB1 R over its insensitive homologue CB2 R was also
observed.
The interactions between the cystic fibrosis transmembrane conductance regulator
(CFTR) and GlyH-101, an open-channel blocker, were analyzed using molecular
dynamics. The results showed the bromine in GlyH-101 was in constant contact with
F337, which is just inside the extracellular gate. The simulations also showed an
insertion of GlyH-101 between TM1 and TM6 deeper than the starting binding pose.
Once inserted deeper between TMs 1 and 6, the number of persistent contacts also
increased. This proposed binding pose may help in future investigations of CFTR
and help determine an open-channel structure for the protein, which in turn may help
in the development of treatments for various medical conditions. Overall, the use
of molecular dynamics and state of the art analysis tools can be useful in the study
of membrane proteins and eventuallyin the development of treatments for ailments
stemming from their atypical function.
ContributorsSexton, Ricky (Author) / Beckstein, Oliver (Thesis advisor) / Presse, Steve (Committee member) / Ozkan, Sefika B. (Committee member) / Hariadi, Rizal (Committee member) / Arizona State University (Publisher)
Created2022
Description
This thesis explores a diverse array of topics related to the role of dynamic allostery in regulating protein functions. Allostery is the phenomenon where a catalytic pocket responds to perturbations caused by binding at another distant site. This response often involves a conformational change resulting in a protein function alteration. However, it is essential to note the existence of dynamic allostery mechanisms that regulate protein function without relying on conformational changes but on dynamic motions. Within this thesis, position-specific equilibrium dynamics-based metrics like Dynamic Flexibility Index and Dynamic Coupling Index are employed to quantify the contributions of specific residues to protein dynamics. I investigated the role of dynamics in protein binding of the WW domain. In particular, I focused on how the mutations of distal positions modulate the binding site dynamics. By employing Dynamic Flexibility Index, I discovered that a residue, 10T, located distally from the binding pocket, plays a significant role in the observed dynamics difference between two variants: N21 (a native folded WW domain not binding Group I peptide) and CC16_N21 (an artificial WW domain binding Group I peptide). The T10H variant, created by exchanging the position 10 residue, enhances flexibility at positions 10 and 16. Consequently, this modification has led to an enhancement in the binding function of N21, enabling it to bind to Group I peptide effectively. Moreover, I investigated the influence of dynamic allostery on protein binding specificity, specifically in the PDZ domain PSD95. To gain insights into the binding process and accurately measure binding affinity, I employed two parallel computational approaches: Adaptive BP-docking and Steered Molecular Dynamics. These methods allowed me to model the binding interactions and quantify the binding strength robustly and comprehensively. The significance of allostery can serve as foundational knowledge in Deep Learning models, enabling the efficient mapping of protein sequences to their corresponding functionalities. One particular metric, Dynamic Coupling Index asymmetry, offers valuable insights into how the three-dimensional network of interactions facilitates communication within a protein structure. Leveraging these interactions, I developed a deep neural network architecture demonstrating enhanced capability in capturing epistatic interactions within Beta-lactamase and protein G function.
ContributorsLu, Jin (Author) / Ozkan, Banu (Thesis advisor) / Mills, Jeremy (Committee member) / Hariadi, Rizal (Committee member) / Beckstein, Oliver (Committee member) / Arizona State University (Publisher)
Created2023
Description
Transition metal ions such as Zn2+, Mn2+, Co2+, and Fe2+ play crucial roles in organisms from all kingdoms of life. The homeostasis of these ions is mainly regulated by a group of secondary transporters from the cation diffusion facilitator (CDF) family. The mammalian zinc transporters (ZnTs), a subfamily of CDF, have been an important target for study as they are associated with several diseases, such as diabetes, delayed growth and osteopenia, Alzheimer’s disease, and Parkinsonism. The bacterial homolog of ZnTs, YiiP, is the first CDF transporter with a determined structure and is used as a model for studying the structural and mechanistic properties of CDF transporters. On the other hand, Molecular dynamics simulation has emerged as a valuable computational tool for exploring the physical basis of biological macromolecules' structure and function with atomic precision at femtosecond resolution. This work aims to elucidate the roles of the three Zn$2+ binding sites found on each YiiP protomer and the role of protons in the transport process of CDFs, which remain under debate despite previous thermodynamic and structural studies on YiiP. Cryo-EM, microscale thermophoresis (MST) and molecular dynamics (MD) simulations were used to address these questions. With a Zn2+ model that accurately reproduces experimental structures of the binding clusters, the dynamical influence of zinc binding on the transporter was accessed through MD simulations, which was consistent with the new cryo-EM structures. Zinc binding affinities obtained through MST were used to infer the stoichiometry of Zn2+/H+ antiport in combination with a microscopic thermodynamic model and constant pH simulations. The most likely microstates of H$^+$ and Zn2+ binding indicated a transport stoichiometry of 1 Zn2+ to 2-3 H+ depending on the external pH. A model describing the entire transport cycle of YiiP was finally built on these findings, providing insight into the structural and mechanistic properties of CDF transporters.
ContributorsFan, Shujie (Author) / Beckstein, Oliver (Thesis advisor) / Ozkan, Banu (Committee member) / Heyden, Matthias (Committee member) / Van Horn, Wade (Committee member) / Arizona State University (Publisher)
Created2023
Description
Natures hardworking machines, proteins, are dynamic beings. Comprehending the role of dynamics in mediating allosteric effects is paramount to unraveling the intricate mechanisms underlying protein function and devising effective protein design strategies. Thus, the essential objective of this thesis is to elucidate ways to use protein dynamics based tools integrated with evolution and docking techniques to investigate the effect of distal allosteric mutations on protein function and further rationally design proteins. To this end, I first employed molecular dynamics (MD) simulations, Dynamic Flexibility Index (DFI) and Dynamic Coupling Index (DCI) on PICK1 PDZ, Butyrylcholinesterase (BChE), and Dihydrofolate reductase (DHFR) to uncover how these proteins utilize allostery to tune activity. Moreover, a new classification technique (“Controller”/“Controlled”) based on asymmetry in dynamic coupling is developed and applied to DHFR to elucidate the effect of allosteric mutations on enzyme activity. Subsequently, an MD driven dynamics design approach is applied on TEM-1 β-lactamase to tailor its activity against β-lactam antibiotics. New variants were created, and using a novel analytical approach called "dynamic distance analysis" (DDA) the degree of dynamic similarity between these variants were quantified. The experimentally confirmed results of these studies showed that the implementation of MD driven dynamics design holds significant potential for generating variants that can effectively modulate activity and stability. Finally, I introduced an evolutionary guided molecular dynamics driven protein design approach, integrated co-evolution and dynamic coupling (ICDC), to identify distal residues that modulate binding site dynamics through allosteric mechanisms. After validating the accuracy of ICDC with a complete mutational data set of β-lactamase, I applied it to Cyanovirin-N (CV-N) to identify allosteric positions and mutations that can modulate binding affinity. To further investigate the impact of mutations on the identified allosteric sites, I subjected putative mutants to binding analysis using Adaptive BP-Dock. Experimental validation of the computational predictions demonstrated the efficacy of integrating MD, DFI, DCI, and evolution to guide protein design. Ultimately, the research presented in this thesis demonstrates the effectiveness of using evolutionary guided molecular dynamics driven design alongside protein dynamics based tools to examine the significance of allosteric interactions and their influence on protein function.
ContributorsKazan, Ismail Can (Author) / Ozkan, Sefika Banu (Thesis advisor) / Ghirlanda, Giovanna (Thesis advisor) / Mills, Jeremy (Committee member) / Beckstein, Oliver (Committee member) / Arizona State University (Publisher)
Created2023