Browsing by Author "Wolynes, Peter G"

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    Evolutionary Fitness of Non-Coding Genetic Elements
    (2024-04-19) Jaafari, Hana; Wolynes, Peter G
    Proper protein structure and function are integral to cellular homeostasis. The wide array of known natural protein sequences are a product of millions of years of evolutionary pressure maintaining physical stability and biological function. The evolutionary process occurs via random instances of structural and sequence variations in the genome. While typically neutral in protein-coding genes, such variations can result in the loss of function of a protein-coding gene or produce a novel protein-coding gene. A former protein-coding gene can behave as a reservoir for novel protein-coding genes or variants of known proteins. This dissertation features work that examines the evolutionary fitness of two classes of genetic elements, pseudogenes and exons, that may encode functional amino acid sequences. In Chapter 1 of this dissertation, we introduce the concepts and tools employed in later chapters. We provide a conceptual overview of pseudogenes and exons, as well as review past works that examine the physical stabilities of their encoded amino acid sequences. We also discuss the energy landscape theory and the physical energy function-- the Associative Memory, Water Mediated, Structure and Energy Model (AWSEM)--informed by the theory's principles. We finally discuss the Direct Coupling Analysis (DCA) model, which, when used alongside the AWSEM Hamiltonian, provides information on the physical stability and biological function of a protein sequence. In Chapter 2 of this dissertation, we present work characterizing the physical and evolutionary energy landscapes of pseudogenes, former protein coding genes found in many eukaryotes that cannot be translated due to debilitating mutations. Given these genetic elements previously experienced selection pressure to fold, pseudogenes are an intriguing example of protein devolution. We systematically studied pseudogenes associated with an array of proteins varying in biological function and size. We found that, if translated, pseudogene sequences are typically destabilized relative to their former native state as a function of evolutionary time. Pseudogene sequences that inversely become more physically stable as a result of their mutations have diminished or altered functional abilities that may result in pathological conditions. In Chapter 3 of this dissertation, we present work that evaluates the physical energy landscapes of exons, genetic elements that encode amino acid sequences in eukaryotic genes. If exons encode independently foldable structural units, naturally occurring or engineered exon shuffling can quickly produce novel protein coding genes. Using publicly available databases of annotated protein sequences and gene structures, we identify conserved exons in multiple protein families. We find that conserved exons tend to be minimally frustrated, with these exons' boundaries coinciding with secondary structural element boundaries. Our findings support previous works suggesting exons can encode physically stable protein segments.
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    Exploring the mechanism of functional binding & disease-related self-assembly of biomolecules using energy landscape theory
    (2022-04-15) Chen, Xun; Wolynes, Peter G
    Proteins are large biomolecules that consist of one or multiple chains of amino acid residues. They play vital roles in biological function in the biosystem, including transcription, DNA replication, transporting, etc. It is believed that the structure determines the function. Here we explores the mechanism of functional binding and disease-related self-assembly of biomolecules using energy landscape theory from three aspects: Tau aggregation, PU.1 transcription process, and Heme in protein. First, we used energy landscape theory to investigate the mechanisms of tau aggregation. Tau isoforms, involved in Alzheimer's and Pick's disease, often aggregate to amorphous phase separation and firbilization. The free energy distributions of these Tau isoforms showed two channels in the aggregation: one leading to more ordered amyloid fibrils and the other non-fibrillar channels leading to an amorphous phase. The different structural properties of the species in the two channels suggest that the interconversion between the two channels will act as a backtrack, suggesting that the two channels are kinetically independent. Then, we focus on the indirect readout role in PU.1 DNA recognition. The accurate recognition of the binding site is essential for transcription. Many proteins recognize the binding region through "indirect readout in the transcription factor family." The indirect readout is subtle and acts as a long-range function. Here, we investigate the origin of the binding specificity of the PU.1. A nonspecific electrostatically driven DNA mechanism mainly achieves the binding specificity of PU.1. The electrostatic interactions between PU.1 and DNA cause both changes in elastic properties of the DNA and complex DNA conformational/dynamics. PU.1 affects the elastic properties of DNA through second-order mechanical effects. When PU.1 binds to the non-binding region of the DNA, the DNA becomes stiffer. Then, PU.1 then slides along the DNA, which becomes softer as the protein recognizes its specific binding site. This recognition process is driven by configurational entropy effects, suggesting a general mechanism for indirect readout. At last, we focus on heme proteins, where heme act as an active center of proteins. Here, we explore the role of the heme in protein folding and protein structure computationally. First, we model heme proteins using a hybrid model, which combines the AWSEM Hamiltonian for the protein, and coarse-grained forcefield, with AMBER Hamiltonian for the heme, an all-atom forcefield. Here, we show that both heme b and heme c improve protein structure predictions' accuracy. In the folding process, coordinated covalent bonds for both heme b and heme c drive the heme toward the native pocket. Thioester covalent bonds also drive heme c to the binding pocket. In addition, electrostatics also helps to search binding sites. We explore the mechanism of functional binding and disease-related self-assembly of biomolecules using energy landscape theory from these three aspects.
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    Multi-scale computational modeling of an RNA-binding prion, CPEB3, reveals its molecular mechanisms underlying the formation of long-term memory
    (2022-12-02) Gu, Xinyu; Wolynes, Peter G
    The growth and stabilization of dendritic spines is thought to be essential for strengthening the connections between neurons, and thereby memories. Actin cytoskeleton remodeling in spines is the basis of this growth and stabilization. CPEB proteins were first identified as a group of RNA-binding proteins regulating the translation of their target mRNAs, like actin mRNAs. Intriguingly, one isoform in CPEB family, CPEB3, has been recently reported as a functional prion that interacts with actin cytoskeleton. These observations make CPEB3 a seductively plausible candidate as a synaptic tag to strengthen the actin cytoskeleton and long-term memory by forming stable aggregates, and simultaneously regulate the local translation of synaptic proteins in spines. Numerous gene knockout experiments have been conducted about CPEB3 and its homologs to investigate CPEB3's function in memories. However, it is challenging for experimentalists to collect structural information of CPEB3 due to the conformational flexibility of prion-like proteins, and the picture of CPEB3's role in synaptic plasticity is still unclear at molecular level. In this thesis, to fill in the missing pieces in the molecular mechanisms of CPEB3, we utilized multi-scale computational modeling by conducting bioinformatic searches, setting up reaction-diffusion systems, and mainly by running molecular dynamics simulations using a coarse-grained protein force field - the Associative memory, Water-mediated, Structure and Energy Model (AWSEM). In the first part, we studied the interaction between actin and CPEB3 and proposed a molecular model for the complex structure of CPEB3 bound to an actin filament (F-actin). Our model gives insights into the molecular details of the F-actin/CPEB3 positive feedback loop underlying long-term memory which involves CPEB3's binding to F-actin, its aggregation triggered by F-actin, and its regulation by SUMOylation. The soluble CPEB3 monomers repress translation, whereas CPEB3 aggregates activate the translation of its target mRNAs. The CPEB3 aggregates, however, that act as long-lasting prions providing "conformational memory", may raise the problem of the consequent translational activation being unregulated. In the second part of the thesis, I propose a computational model of the complex structure between CPEB3 RNA-binding domain (CPEB3-RBD) and small ubiquitin-like modifier protein 2 (SUMO2). Free energy calculations suggest that the allosteric binding of CPEB3 with SUMO2 can confine the CPEB3-RBD to a conformation that favors RNA-binding, and thereby can amplify its RNA-binding affinity. Combining this model with previous experiments showing that CPEB3 monomers are SUMOylated in basal synapses but become deSUMOylated and start to aggregate upon stimulation, we suggest a way in which the translational control of CPEB3 can be switched back to a repressive mode after a stimulation pulse, through an RNA binding shift from binding to CPEB3 fibers to binding to SUMOylated CPEB3 monomers in basal synapses. In the last part, inspired by the specific geometry and polarity of the assembly of mRNAs and CPEB3 aggregates, a vectorial channeling mechanism is proposed to describe the local translational regulation by general mRNA/protein assemblies including functional prions and condensates. The analysis shows that the vectorial processive nature of translation can couple to transport via diffusion so as to repress or activate translation depending on the structure of the RNA protein assembly. We find that multiple factors including diffusivity changes and free energy biases in the assemblies can regulate the translation rate of mRNA by changing the balance between substrate recycling and competition between mRNAs.
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    Observation of antiferromagnetic correlations in the Fermi-Hubbard model
    (2014-11-26) Duarte-Gelvez, Pedro M; Hulet , Randall G; Killian, Thomas C; Wolynes, Peter G
    The Hubbard model contains only the essential ingredients to describe the behavior of strongly interacting electrons moving in a periodic lattice. It describes particles that can tunnel between sites in the lattice and that acquire an on-site interaction energy when two of them occupy the same lattice site. This simple model is a prominent example of how strongly correlated phases emerge from simple Hamiltonians. It gives rise to a Mott-metal insulator transition, and at a density of one particle per site shows an antiferromagnetic ground state. It is also considered to contain the essence of high-temperature superconductivity as observed in the cuprates, a question that remains open due to the difficulty in numerically accessing the solutions of the model at densities different than one particle per site. In this work we have realized the Hubbard model with a spin mixture of ultracold atoms in a simple cubic optical lattice. Atoms in lattices have emerged in the last decade as promising systems in which to perform quantum simulations of condensed matter Hamiltonians. In the laboratory we can create defect-free optical lattice potentials with laser light, and we can control the interactions between the atoms using a magnetic Feshbach resonance. For this work we implemented a novel compensated optical lattice setup, which allows us to control the density of the sample and mitigate the non-adiabaticity in the lattice loading process which often leads to heating of the sample or to out of equilibrium distributions. Using the compensated optical lattice we are able to get closer to the ground state of the Hubbard model than anybody before us has been able to do so with ultracold atoms. To demonstrate this achievement we use spin-sensitive Bragg scattering of light to measure the spin-structure factor, a measure of the antiferromagnetic correlations in the collection of spins. Measurements of the spin-structure factor are compared to theoretical calculations to establish precise thermometry of the atoms in the lattice. We have also studied the in-situ density distribution of the system, which confirms that the temperature of our sample is in a regime where most of the remaining entropy in the system resides in the spin degree of freedom. The results presented here represent an important step in the field of quantum simulation with ultracold atoms. In the future, we expect to further explore and exploit the experimental possibilities opened up by the compensated lattice potential and by light scattering thermometry, with the ultimate goal of addressing the existence of d-wave superfluidity in the Hubbard model.
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    Protein folding, unfolding, and phase diagrams with coarse-grained models
    (2017-09-11) Sirovetz, Brian Joseph; Wolynes, Peter G
    A protein can exhibit a variety of behaviors depending on its environment. Under physiological conditions, proteins spontaneously fold into functional structures. Exposing proteins to extreme temperatures or pressures often results in their denaturation. Single molecule force spectroscopy experiments have shown how mechanical forces can also disrupt a protein’s structure. In the research highlighted in this thesis, we used coarse-grained models of proteins and the principles of energy landscape theory to better understand these complex physical phenomena. Each chapter deals with a different aspect of protein folding behavior. We first discuss a study on protein folding. During evolution, protein sequences within a family undergo random mutation but are also under selection pressure to maintain their ability to fold into their common native structure. These processes together leave an imprint of the structure in the form of strong covariation between pairs of sites on the resulting family of evolved sequences. We leveraged these “evolutionary restraints” (ER) to improve the Associative memory, Water mediated, Structure and Energy Model (AWSEM), making it AWSEM-ER. The results from the AWSEM-ER model demonstrate that adding contacts predicted from sequence covariation significantly improves the quality of the predicted protein structures. In another study, we augmented the AWSEM model to allow for the exploration of protein folding and unfolding behavior as a function of temperature and pressure. The resulting model exhibits an elliptical phase diagram in the temperature-pressure plane for the two proteins studied, consistent with previously reported experimental findings. Finally, we predicted misfolded structures of a tandem construct of the designed protein Top7 using AWSEM. We then unfolded the predicted misfolded structures using steered molecular dynamics simulations of a structure based model to compare the force vs. extension curves with experiment. Non-trivial agreement was found between the number and extension length of unfolding transitions when unfolding the misfolded structures. This agreement suggests that AWSEM can accurately predict misfolded structures of proteins, which is a potentially important application where other models are typically either too costly (e.g., all-atom models) or just not applicable (e.g., native-centric models).
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    Single-molecule conformational dynamics of a transcription factor reveals a continuum of binding modes controlling association and dissociation
    (Oxford University Press, 2021) Chen, Wei; Lu, Wei; Wolynes, Peter G; Komives, Elizabeth A; Center for Theoretical Biological Physics
    Binding and unbinding of transcription factors to DNA are kinetically controlled to regulate the transcriptional outcome. Control of the release of the transcription factor NF-κB from DNA is achieved through accelerated dissociation by the inhibitor protein IκBα. Using single-molecule FRET, we observed a continuum of conformations of NF-κB in free and DNA-bound states interconverting on the subseconds to minutes timescale, comparable to in vivo binding on the seconds timescale, suggesting that structural dynamics directly control binding kinetics. Much of the DNA-bound NF-κB is partially bound, allowing IκBα invasion to facilitate DNA dissociation. IκBα induces a locked conformation where the DNA-binding domains of NF-κB are too far apart to bind DNA, whereas a loss-of-function IκBα mutant retains the NF-κB conformational ensemble. Overall, our results suggest a novel mechanism with a continuum of binding modes for controlling association and dissociation of transcription factors.
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    Symbolic solution for computational quantum many-body theory development
    (2018-03-02) Zhao, Jinmo; Scuseria, Gustavo E; Wolynes, Peter G; Várilly-Alvarado, Anthony
    Computational many-body theories in quantum chemistry, condensed matter, and nuclear physics aim to provide sufficiently accurate description of and insights into the motion of many interacting particles. Due to their intrinsic complexity, the development of such theories generally involves very complex, tedious, and error-prone symbolic manipulations. Here a complete solution to automate the symbolics in many-body theory development is attempted. General data structures based on an existing computer algebra system are designed to specifically address the symbolic problems for which there is currently no satisfactory handling. Based on the data structures, algorithms are given to accomplish common symbolic manipulations and simplifications. Noncommutative algebraic systems, tensors with symmetry, and symbolic summations can all enjoy deep simplifications efficient enough for theories of very complex form. After the symbolic derivation, novel algorithms for automatic optimization of tensor contractions and their sums are devised, which can be used together with automatic code generation tools. In this way, the burden of symbolic tasks in theory development can be vastly reduced, with the potential to spare scientists more time and energy for the actual art and science of many-body theories.