Browsing by Author "Onuchic, José N"

Now showing 1 - 5 of 5
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    Investigating the role of biological modularity and stochasticity in cancer metastasis
    (2022-08-25) Galbraith, Madeline Lee; Onuchic, José N
    Metastasis is the leading cause of cancer-related deaths. While cancer and metastasis have been studied for many years there is still much to learn, particularly with regards to how various biological pathways interact to instigate or prevent metastasis. The multitude of gene regulatory networks that govern cancer metastasis can be studied individually as “modules” that represent individual networks. While biological networks are not isolated in nature, using modules is a necessary first step to understand the mechanism of cancer metastasis. This thesis will discuss the core network of the epithelial-mesenchymal transition (EMT), the glucose metabolism pathway, the stemness network, and the Notch signaling pathway. The dysregulation of these networks leads to phenotypes with high metastatic potential. For instance, a partial EMT transition can allow cells to gain the ability to collectively migrate while metabolic reprogramming can increase the ability of cells to survive in differing microenvironments. By coupling the EMT and metabolism networks, we noticed the phenotypes with high metastatic potential are correlated. While coupling networks can bring insight into the crosstalk between the modules governing cancer, another key aspect of cancer is cellular heterogeneity. We utilized random circuit perturbation, a way to generate an ensemble of heterogeneous phenotypes, to understand the hierarchical decision making of the stemness network. Lastly, rather than incorporating cellular heterogeneity via changing kinetic parameters, we can introduce stochasticity to adjust the stability of cellular states. We used stochastic fluctuations to model extrinsic noise, such as signals in the tumor microenvironment, and determined they can promote ordered pattern formation in Notch-Delta mediated systems. Additionally, noise alters the stability of the cellular states and potentially destabilizes a phenotype associated with therapy resistance in the Notch-Delta-Jagged pathway. These projects show the importance of not stopping at a modular viewpoint of biology. Instead, models should incorporate crosstalk, cellular heterogeneity, and could even incorporate noise when the effect of the microenvironment is unknown.
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    On the role of conformational flexibility in viral fusion mechanisms - fusion by disorder
    (2018-04-20) Eddy, Nathanial Reed; Onuchic, José N
    Viral diseases continue to contribute to leading causes of death around the world and are annually responsible for significant morbidity and mortality. Many envelope viruses infect cells through the use of fusion proteins, surface proteins which are responsible for fusing the viral and host membranes through large scale conformational transitions. Although pre-fusion and post-fusion structures have been experimentally determined for many viral fusion proteins, specific structural details about how they transition between these states have remained challenging to probe both experimentally and computationally. Even with recent computational advances, acquiring equilibrium distributions of the entire functional landscape through standard molecular dynamics calculations is not currently feasible. In this body of work, we employ structure based models to analyze the conformational dynamics of a range of viral fusion proteins. Structure based models have rigorous mathematical roots in the language of energy landscape theory and have been successfully applied to many problems in folding, allostery, and functional motions of biomolecules. These models take experimental structures as an input and make them explicit energy minima in the Hamiltonian. We construct energy functions for several viral fusion proteins which simultaneously include all interactions from the pre- and post-fusion structures and observe their time evolution. We first analyze Influenza A Hemagglutinin, where we show that Hemagglutinin can transition by two dominant pathways. Both pathways are characterized by an early order-disorder transition in a characteristic hairpin region and breaking of the threefold symmetry present in the prefusion structure. Late stage N-C terminal zipping completes the transition. This picture is in contrast with the standard spring-loaded view of Hemagglutinin mediated fusion, where an early loop to helix transition drives the transition. We extend this analysis to a survey of other Class I viral fusion proteins and show that they all share the same global mechanistic features observed in Hemagglutinin. Finally, we employ a similar model to investigate Class II Dengue Envelope dimers and show that symmetry in the potential gives rise to a dynamic, entropically stabilized intermediate state. Collectively, these results are suggestive that viruses take advantage of conformational flexibility and disordered intermediate ensembles to facilitate viral entry.
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    Optimization of predictive energy landscapes for membrane and globular protein structure prediction
    (2015-10-09) Kim, Bobby Lee; Wolynes, Peter G.; Onuchic, José N; Clementi, Cecilia
    This thesis discusses recent results using the Associative-memory, Water-mediated, Structure and Energy Model (AWSEM), an optimized, coarse-grained molecular dynamics model. AWSEM and its membrane protein extension, AWSEM-membrane, are capable of de novo protein structure prediction and through the use of statistical estimators, allow construction of free energy landscapes which can provide insight about the dynamics of protein systems. We review the origins of energy landscape theory and how one can learn energy functions using the results of spin glass-inspired statistical mechanics models. We explore the similarities and differences between the energy landscapes of proteins that have been selected by nature and those of some proteins designed by humans. We also study how robust the folding of these designs would be to the simplification of the sequences using fewer amino acid types. Using an optimized extension of AWSEM, AWSEM-membrane, we explore the hypothesis that the folding landscapes of membrane proteins are funneled once the proteins’ topology within the membrane is established. We also show that the AWSEM-membrane force field is able to sample near native binding interfaces of several oligomeric systems.
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    Uncovering Protein Structure from Genomic Data
    (2022-04-26) Mehrabiani, Kareem M; Onuchic, José N
    Reliable three-dimensional structures of proteins serve as a necessary starting point for a mechanistic understanding of how those proteins function in living systems. Yet only a small fraction of known proteins also have experimentally determined structures, necessitating the development of structure prediction algorithms, especially in cases where there is limited or no experimentally determined structures available. In particular, it has been shown that information encoded in amino acid sequence data can directly be used to infer structural contacts in a folded protein or protein complex that have been preserved over natural selection. Throughout evolution, favorable random amino acid mutations that were selected for in sequence space have shaped the protein’s functional structure, connecting the sequence and folding landscapes through a process called amino acid coevolution. In particular, statistical methodologies such as the Direct Coupling Analysis (DCA) approach have been used to quantify the amount of amino acid coevolution between residue pairs, allowing for the inference of spatial proximity between these pairs. Here, we refine the structure-prediction approach using DCA for the prediction of dimer interfaces and higher-order protein-protein interactions. We develop a measure of statistical significance for DCA predictions based on the Z-score, allowing for high quality predictions to be distinguished from noisy predictions. We also explore the number of protein sequences necessary to make accurate predictions of spatial contacts in a folded protein, e.g., how much sequence information is necessary to reliably make predictions using DCA? Finally, we will conclude with a discussion of some of the applications of DCA to specific systems, such as the prediction of the actin fiber.
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    Uncovering the Molecular Mechanism Underpinning the Function of Influenza Hemagglutinin
    (2018-04-19) Lin, Xingcheng; Onuchic, José N; Levine, Herbert; Clementi, Cecilia
    Influenza Hemagglutinin (HA) is a homotrimeric viral fusion protein critical for the invasion of flu viruses. It is composed of two domains, a receptor-binding domain called HA1 and a viral fusion stem domain called HA2. HA assists in the invasion of viruses through an HA2 induced membrane fusion process under a lowered pH environment. The crystal structures of HA2 before and after the membrane fusion were solved previously. A comparison between them reveals a dramatic structural rearrangement of HA2 during the viral invasion process. In spite of the solved structures, dynamic details about how this structural transition happens are still missing. This thesis focuses on the investigation of the molecular mechanism underlying this structural transition and understanding how this transition induces the subsequent membrane fusion process. In Chapter Two, we used a coarse-grained dual-basin structure-based model for investigating the overall structural transition of HA2. We find two disparate routes on this transition landscape and multiple metastable intermediates. Specifically, our simulations feature an early ``cracking'' process initializing the HA2 transition and a ``symmetry-breaking'' process leading to a functional bending structure of HA2. In Chapter Three, we employed detailed explicit-solvent simulations with transferrable force fields to probe the initial phase of HA2 transition. Specifically, we focused on the role of a lowered pH in the release of fusion peptides. Our results indicate that a buried salt bridge locks the fusion peptides in the pre-fusion structure, and the breaking of it is crucial for releasing fusion peptides and the subsequent HA2 transition. Further, our detailed simulations reproduce the cracking and symmetry-breaking processes as we observed in the simulations with the structure-based model. In Chapter Four, we focused on a loop-to-coiled-coil transition of the B-loop domain of HA2, which was presumed to be a critical step in the structural transition of HA2. We implemented explicit-solvent simulations together with enhanced sampling techniques and showed that the post-fusion state of the B-loop by itself is unstable. A buried hydrophilic residue, Thr59, is shown to cause the instability. A further study indicates that Thr59 is the only residue of the B-loop that strictly differentiates between two taxonomic groups of HAs. Our simulations support previous studies by showing that the functional motion of HA2 is dynamic. The slow transition of the B-loop allows for more degrees of freedom for choosing the transition pathways. Overall, our simulations indicate a dynamic motion of HAs in its functional transition, which encourages different pathways HAs utilized to induce the membrane fusion process.