Michael E. Colvin

University of California, Merced, Merced, California, United States

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Publications (85)292.22 Total impact

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    ABSTRACT: The transport of cargo across the nuclear membrane is highly selective and accomplished by a poorly understood mechanism involving hundreds of nucleoporins lining the inside of the nuclear pore complex (NPC). Currently, there is no clear picture of the overall structure formed by this collection of proteins within the pore, primarily due to their disordered nature. We perform coarse-grained simulations of both individual nucleoporins and grafted rings of nups mimicking the in vivo geometry of the NPC and supplement this with polymer brush modeling. Our results indicate that different regions or blocks of an individual NPC protein can have distinctly different forms of disorder and that this property appears to be a conserved functional feature. Furthermore, this block structure at the individual protein level is critical to the formation of a unique higher-order polymer brush architecture that can exist in distinct morphologies depending on the effective interaction energy between the phenylalanine glycine (FG) domains of different nups. Because the interactions between FG domains may be modulated by certain forms of transport factors, our results indicate that transitions between brush morphologies could play an important role in regulating transport across the NPC, suggesting novel forms of gated transport across membrane pores with wide biomimetic applicability.
    Biophysical Journal 05/2014; 106(9):1997-2007. · 3.67 Impact Factor
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    ABSTRACT: The transport of cargo across the nuclear membrane is highly selective and accomplished by a poorly understood mechanism involving hundreds of nucleoporins within the nuclear pore complex (NPC). Currently, there is no clear picture of the overall structure formed by this collection of proteins within the pore, primarily due to their disordered nature. We perform coarse grained simulations of both individual nucleoporins and grafted rings of nups mimicking the in vivo geometry and supplement this with polymer brush modeling. Our results indicate that different regions or ``blocks'' of an individual NPC protein can have distinctly different forms of disorder and properties and that this appears to be a conserved feature. Furthermore, this block structure at the individual protein level is critical to the formation of a unique higher-order polymer brush architecture. Our results indicate that there exist transitions between distinct brush morphologies (open and closed states of the gate), which can be triggered by the presence of cargo with specific surface properties. The resulting transport mechanism, that we propose, is fundamentally different from existing models and points to a novel form of gated transport in operation within the NPC.
    03/2013;
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    ABSTRACT: The Nuclear Pore Complex (NPC) gates the only channel through which cells exchange material between the nucleus and cytoplasm. Traffic is regulated by transport receptors bound to cargo which interact with numerous of disordered phenylalanine glycine (FG) repeat containing proteins (FG nups) that line this channel. The precise physical mechanism of transport regulation has remained elusive primarily due to the difficulty in understanding the structure and dynamics of such a large assembly of interacting disordered proteins. Here we have performed a comprehensive bioinformatic analysis, specifically tailored towards disordered proteins, on thousands of nuclear pore proteins from a variety of species revealing a set of highly conserved features in the sequence structure among FG nups. Contrary to the general perception that these proteins are functionally equivalent to homogeneous polymers, we show that biophysically important features within individual nups like the separation, spatial localization and ordering along the chain of FG and charge domains are highly conserved. Our current understanding of NPC structure and function should therefore be revised to account for these common features that are functionally relevant for the underlying physical mechanism of NPC gating.
    03/2013;
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    ABSTRACT: Electroporation is the formation of permeabilizing structures in the cell membrane under the influence of an externally imposed electric field. The resulting increased permeability of the membrane enables a wide range of biological applications, including the delivery of normally excluded substances into cells. While electroporation is used extensively in biology, biotechnology, and medicine, its molecular mechanism is not well understood. This lack of knowledge limits the ability to control and fine-tune the process. In this article we propose a novel molecular mechanism for the electroporation of a lipid bilayer based on energetics analysis. Using molecular dynamics simulations we demonstrate that pore formation is driven by the reorganization of the interfacial water molecules. Our energetics analysis and comparisons of simulations with and without the lipid bilayer show that the process of poration is driven by field-induced reorganization of water dipoles at the water-lipid or water-vacuum interfaces into more energetically favorable configurations, with their molecular dipoles oriented in the external field. Although the contributing role of water in electroporation has been noted previously, here we propose that interfacial water molecules are the main players in the process, its initiators and drivers. The role of the lipid layer, to a first-order approximation, is then reduced to a relatively passive barrier. This new view of electroporation simplifies the study of the problem, and opens up new opportunities in both theoretical modeling of the process and experimental research to better control or to use it in new, innovative ways.
    PLoS ONE 01/2013; 8(4):e61111. · 3.53 Impact Factor
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    ABSTRACT: Bioinformatics of disordered proteins is especially challenging given high mutation rates for homologous proteins and that functionality may not be strongly related to sequence. Here we have performed a novel bioinformatic analysis, based on the spatial clustering of physically relevant features such as binding motifs and charges within disordered proteins, on thousands of Nuclear Pore Complex (NPC) FG motif containing proteins (FG nups). The biophysical mechanism by which FG nups regulate nucleocytoplasmic transport has remained elusive. Our analysis revealed a set of highly conserved spatial features in the sequence structure of individual FG nups, such as the separation, localization, and ordering of FG motifs and charged residues along the protein chain. These functionally conserved features provide insight into the particular biophysical mechanisms responsible for regulation of nucleocytoplasmic traffic in the NPC, strongly constraining current models. Additionally this method allows us to identify potentially functionally analogous disordered proteins across distantly related species.
    PLoS ONE 01/2013; 8(9):e73831. · 3.53 Impact Factor
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    ABSTRACT: Although targeting of cancer cells using drug-delivering nanocarriers holds promise for improving therapeutic agent specificity, the strategy of maximizing ligand affinity for receptors overexpressed on cancer cells is suboptimal. To determine design principles that maximize nanocarrier specificity for cancer cells, we studied a generalized kinetics-based theoretical model of nanocarriers with one or more ligands that specifically bind these overexpressed receptors. We show that kinetics inherent to the system play an important role in determining specificity and can in fact be exploited to attain orders of magnitude improvement in specificity. In contrast to the current trend of therapeutic design, we show that these specificity increases can generally be achieved by a combination of low rates of endocytosis and nanocarriers with multiple low-affinity ligands. These results are broadly robust across endocytosis mechanisms and drug-delivery protocols, suggesting the need for a paradigm shift in receptor-targeted drug-delivery design.
    PLoS ONE 01/2013; 8(6):e65623. · 3.53 Impact Factor
  • Biophysical Journal 01/2013; 104(2):233-. · 3.67 Impact Factor
  • Biophysical Journal 01/2012; 102(3):451-. · 3.67 Impact Factor
  • Biophysical Journal 01/2012; 102(3):622-. · 3.67 Impact Factor
  • Biophysical Journal 01/2012; 102(3):632-. · 3.67 Impact Factor
  • Biophysical Journal 01/2012; 102(3):2-. · 3.67 Impact Factor
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    Joshua L Phillips, Michael E Colvin, Shawn Newsam
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    ABSTRACT: Molecular dynamics (MD) simulation is a powerful technique for sampling the meta-stable and transitional conformations of proteins and other biomolecules. Computational data clustering has emerged as a useful, automated technique for extracting conformational states from MD simulation data. Despite extensive application, relatively little work has been done to determine if the clustering algorithms are actually extracting useful information. A primary goal of this paper therefore is to provide such an understanding through a detailed analysis of data clustering applied to a series of increasingly complex biopolymer models. We develop a novel series of models using basic polymer theory that have intuitive, clearly-defined dynamics and exhibit the essential properties that we are seeking to identify in MD simulations of real biomolecules. We then apply spectral clustering, an algorithm particularly well-suited for clustering polymer structures, to our models and MD simulations of several intrinsically disordered proteins. Clustering results for the polymer models provide clear evidence that the meta-stable and transitional conformations are detected by the algorithm. The results for the polymer models also help guide the analysis of the disordered protein simulations by comparing and contrasting the statistical properties of the extracted clusters. We have developed a framework for validating the performance and utility of clustering algorithms for studying molecular biopolymer simulations that utilizes several analytic and dynamic polymer models which exhibit well-behaved dynamics including: meta-stable states, transition states, helical structures, and stochastic dynamics. We show that spectral clustering is robust to anomalies introduced by structural alignment and that different structural classes of intrinsically disordered proteins can be reliably discriminated from the clustering results. To our knowledge, our framework is the first to utilize model polymers to rigorously test the utility of clustering algorithms for studying biopolymers.
    BMC Bioinformatics 11/2011; 12:445. · 3.02 Impact Factor
  • Michael A. Sprague, Michael E. Colvin
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    ABSTRACT: The ideal cooking process would heat food to a sufficient temperature throughout to kill bacteria without heating the food to temperatures that promote formation of toxic or carcinogenic compounds. Experimentally validated computer models have an important role to play in designing cooking processes since they allow rapid evaluations of different conditions without the confounding effects of experimental variation. In this paper we derive a mathematical model governing the heat and water transport in a cylindrical pan-fried beef patty. The continuum temperature model stems from a mixture-enthalpy formulation that accommodates the liquid and vapor states of water along with fat and protein. The governing equations were spatially discretized with Legendre spectral finite elements. All but two of the model properties were taken from the literature, with the remaining two determined through a comparison of numerical and physical experiments. These parameters were shown to produce solutions in agreement with a different set of experimental results. The model was used to calculate the formation of heterocyclic-amine (HA) compounds (known DNA mutagens and carcinogens). Results provide an explanation based on patty temperature for previous experimental studies showing that frequent patty flipping yields a dramatic reduction in HAs.
    Food Research International 04/2011; 44(3):789-797. · 3.05 Impact Factor
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    Biophysical Journal 01/2011; 100(3). · 3.67 Impact Factor
  • Biophysical Journal 01/2011; 100. · 3.67 Impact Factor
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    ABSTRACT: Nuclear pore complexes (NPCs) gate the only conduits for nucleocytoplasmic transport in eukaryotes. Their gate is formed by nucleoporins containing large intrinsically disordered domains with multiple phenylalanine-glycine repeats (FG domains). In combination, these are hypothesized to form a structurally and chemically homogeneous network of random coils at the NPC center, which sorts macromolecules by size and hydrophobicity. Instead, we found that FG domains are structurally and chemically heterogeneous. They adopt distinct categories of intrinsically disordered structures in non-random distributions. Some adopt globular, collapsed coil configurations and are characterized by a low charge content. Others are highly charged and adopt more dynamic, extended coil conformations. Interestingly, several FG nucleoporins feature both types of structures in a bimodal distribution along their polypeptide chain. This distribution functionally correlates with the attractive or repulsive character of their interactions with collapsed coil FG domains displaying cohesion toward one another and extended coil FG domains displaying repulsion. Topologically, these bipartite FG domains may resemble sticky molten globules connected to the tip of relaxed or extended coils. Within the NPC, the crowding of FG nucleoporins and the segregation of their disordered structures based on their topology, dimensions, and cohesive character could force the FG domains to form a tubular gate structure or transporter at the NPC center featuring two separate zones of traffic with distinct physicochemical properties.
    Molecular &amp Cellular Proteomics 04/2010; 9(10):2205-24. · 7.25 Impact Factor
  • Biophysical Journal 01/2010; 98(3). · 3.67 Impact Factor
  • Biophysical Journal 01/2010; 98(3). · 3.67 Impact Factor
  • Biophysical Journal 01/2010; 98(3). · 3.67 Impact Factor
  • Biophysical Journal 01/2010; 98(3). · 3.67 Impact Factor

Publication Stats

862 Citations
292.22 Total Impact Points

Institutions

  • 2004–2014
    • University of California, Merced
      • • Department of Chemistry and Chemical Biology
      • • Center for Computational Biology
      • • School of Natural Sciences
      Merced, California, United States
  • 1997–2006
    • Lawrence Livermore National Laboratory
      • Biosciences and Biotechnology Division
      Livermore, California, United States
  • 2005
    • CSU Mentor
      Long Beach, California, United States
  • 2002–2004
    • University of California, Davis
      • Department of Chemistry
      Davis, CA, United States
  • 1998–2004
    • Duke University Medical Center
      • Duke Comprehensive Cancer Center
      Durham, NC, United States
  • 1992–1997
    • Sandia National Laboratories
      • Computational Materials Science and Engineering Department
      Albuquerque, New Mexico, United States