Matching Items (6)
Filtering by
- All Subjects: Biophysics
- Creators: Hariadi, Rizal
Description
The properties of materials depend heavily on the spatial distribution and connectivity of their constituent parts. This applies equally to materials such as diamond and glasses as it does to biomolecules that are the product of billions of years of evolution. In science, insight is often gained through simple models with characteristics that are the result of the few features that have purposely been retained. Common to all research within in this thesis is the use of network-based models to describe the properties of materials. This work begins with the description of a technique for decoupling boundary effects from intrinsic properties of nanomaterials that maps the atomic distribution of nanomaterials of diverse shape and size but common atomic geometry onto a universal curve. This is followed by an investigation of correlated density fluctuations in the large length scale limit in amorphous materials through the analysis of large continuous random network models. The difficulty of estimating this limit from finite models is overcome by the development of a technique that uses the variance in the number of atoms in finite subregions to perform the extrapolation to large length scales. The technique is applied to models of amorphous silicon and vitreous silica and compared with results from recent experiments. The latter part this work applies network-based models to biological systems. The first application models force-induced protein unfolding as crack propagation on a constraint network consisting of interactions such as hydrogen bonds that cross-link and stabilize a folded polypeptide chain. Unfolding pathways generated by the model are compared with molecular dynamics simulation and experiment for a diverse set of proteins, demonstrating that the model is able to capture not only native state behavior but also partially unfolded intermediates far from the native state. This study concludes with the extension of the latter model in the development of an efficient algorithm for predicting protein structure through the flexible fitting of atomic models to low-resolution cryo-electron microscopy data. By optimizing the fit to synthetic data through directed sampling and context-dependent constraint removal, predictions are made with accuracies within the expected variability of the native state.
ContributorsDe Graff, Adam (Author) / Thorpe, Michael F. (Thesis advisor) / Ghirlanda, Giovanna (Committee member) / Matyushov, Dmitry (Committee member) / Ozkan, Sefika B. (Committee member) / Treacy, Michael M. J. (Committee member) / Arizona State University (Publisher)
Created2011
Description
Nanosphere lithography is a high throughput procedure that has important implications
for facile, low cost scaling of nanostructures. However, current benchtop experiments have
limitations based on the placement of molecular species that exhibit greater than singlemolecular binding. In addition, reliance upon bottom-up self-assembly of close-packed
nanospheres makes it problematic to resolve images using low-cost light microscopes due to the
spacing limitations smaller in magnitude than light wavelength. One method that is created to
resolve this issue is iterative size reduction (ISR), where repetitive ‘iterative’ processes are
employed in order to increase the precision at which single molecules bind to a given substrate.
ISR enables inherent separation of nanospheres and therefore any subsequent single molecule
binding platforms. In addition, ISR targets and encourages single-molecule binding by
systematically reducing binding site size. Results obtained pursuing iteratively reduced
nanostructures showed that many factors are needed to be taken into consideration, including
functionalization of nanosphere particles, zeta potential, and protonation-buffer reactions.
Modalities used for observation of nanoscale patterning and single-molecule binding included
atomic force microscopy (AFM) and ONI super-resolution and fluorescence microscopy. ISR
was also used in conjunction with zero mode waveguides, which are nanoapertures enabling realtime single molecule observation at zeptoliter volumes. Although current limitations and
obstacles still exist with reproducibility and scalability of ISR, it nonetheless exhibits limitless
potential and flexibility in nanotechnology applications.
for facile, low cost scaling of nanostructures. However, current benchtop experiments have
limitations based on the placement of molecular species that exhibit greater than singlemolecular binding. In addition, reliance upon bottom-up self-assembly of close-packed
nanospheres makes it problematic to resolve images using low-cost light microscopes due to the
spacing limitations smaller in magnitude than light wavelength. One method that is created to
resolve this issue is iterative size reduction (ISR), where repetitive ‘iterative’ processes are
employed in order to increase the precision at which single molecules bind to a given substrate.
ISR enables inherent separation of nanospheres and therefore any subsequent single molecule
binding platforms. In addition, ISR targets and encourages single-molecule binding by
systematically reducing binding site size. Results obtained pursuing iteratively reduced
nanostructures showed that many factors are needed to be taken into consideration, including
functionalization of nanosphere particles, zeta potential, and protonation-buffer reactions.
Modalities used for observation of nanoscale patterning and single-molecule binding included
atomic force microscopy (AFM) and ONI super-resolution and fluorescence microscopy. ISR
was also used in conjunction with zero mode waveguides, which are nanoapertures enabling realtime single molecule observation at zeptoliter volumes. Although current limitations and
obstacles still exist with reproducibility and scalability of ISR, it nonetheless exhibits limitless
potential and flexibility in nanotechnology applications.
ContributorsLe, Eric K (Author) / Hariadi, Rizal (Thesis director) / Kishnan, Devika (Committee member) / School of Molecular Sciences (Contributor) / Barrett, The Honors College (Contributor)
Created2020-05
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
The propulsion matrix provides a compact description of the locomotion of a single flagella molecular motor in a low Reynolds number environment. The locomotion properties of individual flagellar motors are central to bacterial behavior, including chemotaxis, pathogenesis, and biofilm formation. However, because conventional hydrodynamic measurement approaches require applied forces, torques, or fluid flows, it is not possible to directly measure the propulsion matrix for an individual microscale helical filament. Here, the limitations inherent to conventional measurement approaches are overcome using a combination of theoretical, experimental, and computational advancements. First, the relationship between the elements of the propulsion matrix with translational and rotational Brownian motion is derived using the fluctuation-dissipation theorem. Next, a volumetric fluorescent imaging using high resolution oblique plane microscopy with sufficient spatio-temporal resolution is conducted to resolve both translation and rotation of individual helical filaments isolated from E.coli's flagellar motor. Finally, a computational framework is developed to track individual helical filaments across six degrees of freedom, extract diffusion coefficients, and quantify the temporal correlation between translation and rotation. This study computed the maximum propulsion efficiency to be around 1.7%. Direct measurement of propulsion efficiency generally agrees with the ensemble and large-scale measurements previously performed using conventional hydrodynamic measurements. The findings suggest that the approach described here can be extended to more complex in-vitro experiments that evaluate microscale molecular motors. For example, evaluating sperm motility without inducing chemotaxis or utilizing a microfluidic setup.
ContributorsDjutanta, Franky (Author) / Hariadi, Rizal (Thesis advisor) / Wang, Robert (Thesis advisor) / Yurke, Bernard (Committee member) / Herrmann, Marcus (Committee member) / Huang, Huei-Ping (Committee member) / Arizona State University (Publisher)
Created2022
Description
Proteins, the machinery of life, perform a vast array of essential biochemical functions, evolving over time to acquire diverse roles within biological systems. This evolution, primarily driven by mutations within protein sequences, can profoundly impact protein function, potentially leading to various diseases. This thesis aims to dissect the intricate mechanisms through which genetic mutations influence protein functionality, focusing on the dynamic alterations induced by single and combined mutations. Employing a suite of computational tools, including molecular dynamics (MD) simulations and proven analysis metrics like the Dynamic Flexibility Index (DFI) and Dynamic Coupling Index (DCI), I analyze protein dynamics to uncover the common dynamic effects associated with disease causation and compensatory mechanisms. This analysis extends to exploring the concept of epistasis through the lens of protein dynamics, showing how combinations of mutations interact within the protein's 3D structure to either exacerbate or mitigate the functional impacts of individual mutations. The use of EpiScore, a computational tool designed to quantify the epistatic effects of mutations, provides insight on the combined dynamic effects two mutations might have. This is particularly evident in the analysis of rare alleles within human populations, where certain allele combinations, despite their individual rarity, frequently co-occur, suggesting a mechanism of dynamic compensation. This phenomenon is further investigated in the context of the SARS-CoV-2 spike protein, providing insights into viral evolution and the adaptive significance of specific mutations. Additionally, I delve into the role of Intrinsically Disordered Regions (IDRs) in protein function and mutation compensation, highlighting the need for sophisticated dynamics analysis tools to capture the full spectrum of mutation effects. By integrating these analyses, this thesis unveils a complex picture of how proteins' dynamic properties, shaped by mutations, underpin their functional evolution and disease outcomes.
ContributorsOse, Nicholas James (Author) / Ozkan, Sefika Banu (Thesis advisor) / Hariadi, Rizal (Committee member) / Beckstein, Oliver (Committee member) / Vaiana, Sara (Committee member) / Arizona State University (Publisher)
Created2024
Description
Proteins are the machines of living systems that carry out a diverse set of essential biochemical functions. Furthermore, the diversity of their functions has grown overtime via molecular evolution. This thesis aims to explore fundamental questions in protein science regarding the mechanisms of protein evolution particularly addressing how substitutions in sequence modulate function through structure and structural dynamics. In the work presented here, the first goal is to develop a set of tools which connect the sequence-structure relationship which are implemented in two major projects of protein structural refinement and protein structural design. Both of these two works highlight the importance of capturing important pairwise interactions within a given protein system.The second major goal of this work is to understand how sequence and structural dynamics give rise to protein function, and, importantly, how Nature can utilize allostery to evolve towards a new function. Here I employ several in-house and novel computational tools to shed light onto the mechanisms of allostery, and, particularly dynamic allostery in the absence of structural rearrangements. This analysis is applied to several different protein systems including Pin1, LacI, CoV-1 and CoV-2 and TEM-1. I show that the dynamics of protein systems may be altered fundamentally by distal perturbations such as ligand binding or point mutations. These peturbations lead to change in local interactions which cascade within the 3-D network of interaction of a protein and give rise to flexibility changes of distal sites, particularly those of functional/active residues positions thereby altering the protein function.
This networking picture of the protein is further explored through asymmetric dynamic coupling which shows to be a marker of allosteric interactions between distal residue pairs. Within the networking picture, the concept of sequence context dependence upon mutation becomes critical in understanding the functional outcome of these mutations. Here I design a computational tool, EpiScore, which is able to capture these effects and correlate them to measured experimental epistasis in two protein systems, dihydrofolate reductase (DHFR) and TEM-1. Ultimately, the work provided in this thesis shows that both allostery and epistasis may be considered, and accurately modeled, as intrinsic properties of anisotropic networks.
Contributorscampitelli, paul (Author) / Ozkan, Banu (Thesis advisor) / Ghirlanda, Giovanna (Committee member) / Hariadi, Rizal (Committee member) / Thorpe, Michael (Committee member) / Arizona State University (Publisher)
Created2021