Browsing by Author "Kolomeisky, Anatoly B"
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Item Electron correlation in extended systems via quantum embedding(2015-06-17) Bulik, Ireneusz W; Scuseria, Gustavo E.; Kolomeisky, Anatoly B; Hazzard, KadenThe pursuit of accurate and computationally efficient many-body tools capable of describing electron correlation is a major effort of the quantum chemistry community. The accuracy of chemical predictions strongly depends on the ability of the models to account for electron correlation. As the computational demand scales unfavourably with the size of the system, an efficient way of identifying relevant degrees of freedom may be an interesting avenue. In this thesis, a quantum embedding approach is employed to study lattice systems, polymers, and crystals. Numerical data shows the accuracy of the quantum embedding theory when combined with high-level many-body techniques. As the size of the units that are embedded grows, a more approximate and more computationally affordable tools are called for. In this thesis, we investigate the possibility of forming such methods in the framework of coupled cluster theory. We believe that the tools presented in this thesis could be important for accurate treatment of electron correlation in applications to realistic materials.Item Investigating Modular Structure and Function in Biology: from Immunology to Cognition(2020-12-04) Bonomo, Melia E.; Kolomeisky, Anatoly BModularity is the grouping of the components of a complex system into distinct units. Modular structure is pervasive in biology and has been especially studied in biological networks, including metabolic circuits, protein-protein interaction networks, ecological food webs, and human brain networks. However, beyond simply quantifying the organization of these different systems, modularity plays an important role in optimizing their functional capabilities. It affords a system greater evolvability, efficiency, and robustness to perturbation; however, depending on the function being carried out, lower modularity is sometimes more advantageous, as it does not constrain the system to a particular configuration. The interactions between system complexity, modularity, flexibility of module composition, task demand, and performance provide a versatile theoretical framework that can tackle a diverse set of problems. Under this generalized theoretical model, I have studied a broad range of biological systems: the CRISPR-Cas immune mechanism in bacteria, the human immune response to influenza, and the human brain both at rest and during task performance. This work has applications to increasing precision in genetic editing, improving flu vaccine selection and development, understanding music processing in the brain, and quantifying the cognitive health benefits of a therapeutic arts intervention.Item Microstructure and Interfacial Properties of Aqueous Mixtures(2014-11-07) Ballal, Deepti; Chapman, Walter G; Biswal, Sibani L; Kolomeisky, Anatoly BUnderstanding the properties of aqueous mixtures has important implications in applications ranging from enhanced oil recovery to biochemical processes. While there has been considerable effort invested in understanding the bulk properties of aqueous mixtures, very few studies have concentrated on their behavior in interfacial systems. Interfacial properties, which are important for applications like coatings and chemical separations, are defined by the molecular structuring of the fluid at the interface. The goal of this thesis is to understand and alter the wetting of solid surfaces by aqueous mixtures. In particular, we study the partitioning of aqueous mixtures of polar and non-polar molecules to different surfaces. What makes aqueous mixtures interesting is the hydrogen bonding nature of water that plays very different roles in the partitioning of polar and non-polar components of the aqueous mixtures. In this thesis, hydrogen bonding is modeled using a thermodynamic perturbation theory due to Wertheim. The theory, included in a classical Density Functional Theory framework, is used to study the molecular structure and interfacial properties of the system. We extend and apply the theory to study a number of aqueous mixtures. Key contributions of this thesis include 1. Predicting the interfacial properties of aqueous mixtures of short alcohols close to a hydrophobic surface 2. Extension of the first order perturbation theory to study the competition between intra and intermolecular hydrogen bonding of molecules in the presence of an explicit water-like solvent 3. Studying the effect of physical conditions and surface chemistry on the wetting of different surfaces by water-oil mixtures 4. Analyzing molecular simulation models for water-alkane interactions through a solubility studyItem Stochastic modeling of protein target search in different DNA topologies(2022-08-12) Felipe dos Anjos, Cayke; Kolomeisky, Anatoly BProtein-DNA interactions are fundamental not only for gene activity and transcription but also for the formation of different complexes that organize the genetic material. In order for the formation of these complexes or transcription to take place it is first necessary that the protein can find its target sequence in the midst of the nuclear environment that is heavily crowded with different molecules and presents tightly packed DNA. Our understanding of this search process has been extensively improved over the course of the last 40 years but open questions about the microscopic mechanism of target search or even how different structures in the DNA impact the search process still remain. The chapters of this thesis are committed to develop models for very different protein search processes. Since single-molecule experiments have been able to measure transition rates for sliding, associating and unbind from DNA, it is straightforward to adopt a discrete state stochastic model to obtain the target search time distribution for those cases and understand how these different scenarios impact the search dynamics. First, after recent investigations have completely explained the dynamics of the DNA loop formation process, we describe how the emergence of this protein-DNA structure happens when a fixed crowder molecule or obstacle that prevents protein sliding through or binding on that site is present in our system. Using this model, we are able to show that the obstacle causes the average target search time to diverge exponentially in one of the protein search regimes. We also connected the presence of this obstacle with an increase in stochastic noise. Second, we start analyzing how a fixed loop structure can accelerate the search process if we suppose that there is a probability of transition between its intersection sites. After that we increase the complexity of our system by introducing DNA spatial configuration transition rates and we explain the complex behaviour obtained with this model. Lastly, based on recent experimental measurements of association and unbinding dynamics of different transcription factors in nucleosomal and free DNA, we were able to develop a new model that accounts for how molecules known as pioneer transcription factors are able to invade and find their target sequences much faster than normal transcription factors in a compacted nucleosomal DNA region. This allows us to better understand how even silenced genes, inaccessible to most transcription factors, can still be expressed even when located in dense regions of the chromatin.Item Theoretical investigation of protein search for targets on DNA(2017-08-11) Kochugaeva, Maria; Kolomeisky, Anatoly BProtein-DNA interactions activate many biochemical transitions used by living systems for successful functioning. The starting point in this process is a protein search and recognition of specific target sequences on DNA among millions of non-specific sites. One of the most striking observations is the fact that some proteins can find their targets on DNA much faster than expected from 3D bulk diffusional estimates which follow from the famous theory developed by M.Smoluchovski. This phenomenon is known as facilitated diffusion. After extensive investigation via theoretical and experimental methods, it has been argued that the facilitated diffusion of proteins (also known as accelerated search) is possible due to combining 3D bulk motion with 1D sliding of non-specifically bound protein molecules along the DNA chain. The recent development of single-molecule techniques has allowed for direct visualization of protein sliding during its binding site search. Thus, although we now have a better understanding of protein search on DNA, there are still many unanswered questions and many features related to this complex biological phenomenon that are still not resolved at the molecular level. In this work we develop a theoretical method to explain the molecular picture behind these complex processes. Our approach is based on a discrete-state stochastic framework and utilizes a first-passage probability method that takes into account the most relevant physical-chemical processes. This allows us to explicitly evaluate the protein search for the targets on DNA for different conditions. Theoretical predictions are supported by Monte Carlo computer simulations, and obtained results are utilized for analysis of available experimental data.Item Theoretical Investigations of Mechanisms of Bacterial Clearance by Antimicrobial Peptides(2022-09-07) Nguyen, Thao N; Kolomeisky, Anatoly BThe discovery and subsequent clinical usage of antibiotics was a major breakthrough in 20th-century medicine, drastically improving healthcare standards while increasing the average human life expectancy. The antibiotic era, despite its considerable success, was unfortunately short-lived. Once again, the threat of potential lack of treatments for infectious diseases returns, this time due to the emergence of multidrug-resistant bacteria. Limitations in the number of bacterial targets remain among the main challenges in discovering new antibiotics. In order to overcome this shortage, a promising solution is using antimicrobial peptides (AMPs), a strong naturally occurring alternative. We developed a theoretical framework for the interactions of AMPs and bacteria on both the single-cell and population level, with and without considering the synergistic combination of different types of AMPs. Our methods explain the wide spectrum of efficiencies at which different types of AMPs operate while indicating the equivalent significance of the bacterial cell entrance and inhibition processes. Measures of minimal inhibitory concentration (MIC) as well as our cooperativity parameter in the 2-AMP cases were detailed, offering a physical-chemical description of the mechanisms of cooperativity and the overall bacterial clearance dynamics.Item Theoretical Investigations of Transcriptional Bursting(2020-04-22) Klindziuk, Alena; Kolomeisky, Anatoly BTranscriptional bursting, or the random alternation between periods of synthesis of messenger RNA molecules and cessation of the transfer of genetic information, is present in all cell types and is an important contributing factor to gene expression noise. Yet, its exact molecular mechanisms remain unclear. In response to an experimental observation that certain transcription systems have a spectrum of activity levels, we developed a phenomenological multi-state theoretical model of transcription. By solving the model exactly and analyzing the results, we found that the degree of stochastic fluctuations during transcription directly correlates with the number of independent biochemical states in the system. In response to studies that show that supercoiling plays an important role in bacterial transcription, we developed a more microscopic mechano-chemical model of transcription. Solving the model, we demonstrate that the interplay between chemical process of RNA synthesis and mechanical stress build up on the DNA strand can lead to transcriptional bursting dynamics. Also, the first-passage analysis was used to estimate the energy to produce an RNA when supercoiling is at play.