Skip to main content
eScholarship
Open Access Publications from the University of California

Scholarly Works (6 results)

  • Thesis
  • Peer Reviewed
UC Irvine Electronic Theses and Dissertations (2020)

As genomic repositories increasingly grow with a variety of data from a multitude of organisms, the need to approach extracting and interpreting data also becomes increasingly difficult. Recent advances in protein annotation and structure prediction have improved, however the variety and sheer amount of data requires unique approaches from multiple different disciplines. Bioinformatics yields important functional sequence information and classification. Molecular dynamics (MD) simulation allows for the interrogation of biochemical systems at the atomistic level. Combined with machine learning, these disciplines can be equipped to investigate the complex functions and relationships of proteins within the current abundant genomic landscape.

The objective of this dissertation is to outline complementary methodologies from various fields - bioinformatics, molecular dynamics simulation, and machine learning - that together, can investigate vast genomic repositories, functional protein data.

Aim 1: The development of the bioinformatics and in silico maturation pipeline consists of gene annotation, MD simulation to equilibrate predicted proteins, and statistical methods adopted from graph theory in collaboration with the Butts lab. Proteins can be represented in graph theoretic terms allowing for the exploration of diverse protein structural features.

Aim 2: Molecular dynamics simulation gives rise to atomic level details of complex systems. A variety of protein systems - HIV Rev, short intrinsically disordered peptides, STXPB4, YAP-1 WW domain - explored are intrinsically disordered. MD simulations were used to simulate the complexities and difficulties encountered within these proteins as well as plant metabolic proteins.

Aim 3: After the aforementioned bioinformatics pipeline and \textit{in silico} molecular dynamics-based maturation of predicted proteins, methods to extract useful atomistic information from coarse protein structure networks (PSNs) were developed. A multi-layer perceptron was used to essentially upscale coarse PSNs into atomistic models. The significance of this technique permits for the simulation of coarse PSNs, and the exploration of complex protein structural conformations.

    Cover page: Investigation of protein sequence-structure dynamics using bioinformatics, molecular dynamics and machine learningCreative Commons 'BY' version 4.0 license
    • Article
    • Peer Reviewed
    UC Irvine Previously Published Works (2018)
    Frequently elusive to experimental characterizations, intrinsically disordered proteins (IDPs) can be probed using molecular dynamics to provide detailed insight into their complex structure, dynamics, and function. However, previous computational studies were often found to disagree with experiment due to either force field biases or insufficient sampling. In this study, nine unstructured short peptides and the HIV-1 Rev protein were simulated and extended to microseconds to assess these limitations in IDP simulations. In short peptide simulations, a tested IDP-specific force field ff14IDPSFF outperforms its generic counterpart ff14SB as agreement of simulated NMR observables with experiment improves, though its advantages are not clear-cut in apo Rev simulations. It is worth noting that sampling is probably still not sufficient in the ff14SB simulations of apo Rev even if 10 ms have been collected. This indicates that enhanced sampling techniques would greatly benefit IDP simulations. Finally, detailed structural analyses of apo Rev conformations demonstrate different secondary structural preferences between ff14SB (helical) and ff14IDPSFF (random coil). A natural next step is to ask a more quantitative question: whether ff14SB is too ordered or ff14IDPSFF is too disordered in simulations of more complex IDPs such as Rev. This requires further quantitative analyses both experimentally and computationally.
      Cover page: Computational Studies of Intrinsically Disordered Proteins
      • Article
      • Peer Reviewed
      UC Davis Previously Published Works (2014)
      A variety of quinoline-4-amines were synthesized from substituted 3-(2-nitrophenyl)isoxazoles utilizing Zn0 or Fe0 dust and HOAc via a reductive heterocyclization process. The starting isoxazoles were synthesized from readily available starting materials. A brief survey of functional groups tolerated in this reductive heterocyclization was performed and several 10-amino-3,4-dihydrobenzo[b][1,6]naphthyridin-1(2H)-one and 9-amino-3,4-dihydroacridin-1(2H)-one examples were synthesized.
        Cover page: Heterocycle‐to‐Heterocycle Route to Quinoline‐4‐amines: Reductive Heterocyclization of 3‐(2‐Nitrophenyl)isoxazoles
        • Article
        • Peer Reviewed
        UC Irvine Previously Published Works (2017)

        Background

        Carnivorous plants possess diverse sets of enzymes with novel functionalities applicable to biotechnology, proteomics, and bioanalytical research. Chitinases constitute an important class of such enzymes, with future applications including human-safe antifungal agents and pesticides. Here, we compare chitinases from the genome of the carnivorous plant Drosera capensis to those from related carnivorous plants and model organisms.

        Methods

        Using comparative modeling, in silico maturation, and molecular dynamics simulation, we produce models of the mature enzymes in aqueous solution. We utilize network analytic techniques to identify similarities and differences in chitinase topology.

        Results

        Here, we report molecular models and functional predictions from protein structure networks for eleven new chitinases from D. capensis, including a novel class IV chitinase with two active domains. This architecture has previously been observed in microorganisms but not in plants. We use a combination of comparative and de novo structure prediction followed by molecular dynamics simulation to produce models of the mature forms of these proteins in aqueous solution. Protein structure network analysis of these and other plant chitinases reveal characteristic features of the two major chitinase families.

        General significance

        This work demonstrates how computational techniques can facilitate quickly moving from raw sequence data to refined structural models and comparative analysis, and to select promising candidates for subsequent biochemical characterization. This capability is increasingly important given the large and growing body of data from high-throughput genome sequencing, which makes experimental characterization of every target impractical.
          Cover page: Structure prediction and network analysis of chitinases from the Cape sundew, Drosera capensis
          • Article
          • Peer Reviewed
          UC Irvine Previously Published Works (2018)
          Polyketides are a large class of bioactive natural products with a wide range of structures and functions. Polyketides are biosynthesized by large, multidomain enzyme complexes termed polyketide synthases (PKSs). One of the primary challenges when studying PKSs is the high reactivity of their poly-β-ketone substrates. This has hampered structural and mechanistic characterization of PKS-polyketide complexes, and, as a result, little is known about how PKSs position the unstable substrates for proper catalysis while displaying high levels of regio- and stereospecificity. As a first step toward a general plan to use oxetanes as carbonyl isosteres to broadly interrogate PKS chemistry, we describe the development and application of an oxetane-based PKS substrate mimic. This enabled the first structural determination of the acyl-enzyme intermediate of a ketosynthase (KS) in complex with an inert extender unit mimic. The crystal structure, in combination with molecular dynamics simulations, led to a proposed mechanism for the unique activity of DpsC, the priming ketosynthase for daunorubicin biosynthesis. The successful application of an oxetane-based polyketide mimic suggests that this novel class of probes could have wide-ranging applications to the greater biosynthetic community interested in the mechanistic enzymology of iterative PKSs.
            Cover page: An Oxetane-Based Polyketide Surrogate To Probe Substrate Binding in a Polyketide Synthase
            • Article
            • Peer Reviewed
            UC Irvine Previously Published Works (2020)
            The Hippo pathway, which plays a critical role in organ size control and cancer, features numerous WW domain-based protein-protein interactions. However, ~100 WW domains and 2,000 PY motif-containing peptide ligands are found in the human proteome, raising a "WW-PY" binding specificity issue in the Hippo pathway. In this study, we have established the WW domain binding specificity for Hippo pathway components and uncovered a unique amino acid sequence required for it. By using this criterion, we have identified a WW domain-containing protein, STXBP4, as a negative regulator of YAP. Mechanistically, STXBP4 assembles a protein complex comprising α-catenin and a group of Hippo PY motif-containing components/regulators to inhibit YAP, a process that is regulated by actin cytoskeleton tension. Interestingly, STXBP4 is a potential tumor suppressor for human kidney cancer, whose downregulation is correlated with YAP activation in clear cell renal cell carcinoma. Taken together, our study not only elucidates the WW domain binding specificity for the Hippo pathway, but also reveals STXBP4 as a player in actin cytoskeleton tension-mediated Hippo pathway regulation.
              Cover page: Elucidation of WW domain ligand binding specificities in the Hippo pathway reveals STXBP4 as YAP inhibitor
              Top