Characterization of the Structure and Dynamics of Biomimetic Peptides by Solid-State NMR

Thesis (Ph.D.)--University of Washington, 2016-05

Solution structure of O-glycosylated C-terminal leucine zipper domain of human salivary mucin (MUC7)

Solution structures of a 23 residue glycopeptide II (KIS* RFLLYMKNLLNRIIDDMVEQ, where * denotes the glycan Gal-beta-(1-3)-alpha-GalNAc) and its deglycosylated counterpart I derived from the C-terminal leucine zipper domain of low molecular weight human salivary mucin (MUC7) were studied using CD, NMR spectroscopy and molecular modeling. The peptide I was synthesized using the Fmoc chemistry following the conventional procedure and the glycopeptide II was synthesized incorporating the O-glycosylated building block (N alpha-Fmoc-Ser-[Ac-4,-beta-D-Gal-(1,3)-Ac(2)alpha-D-GalN(3)]-OPfp) at the appropriate position in stepwise assembly of peptide chain. Solution structures of these glycosylated and nonglycosylated peptides were studied in water and in the presence of 50% of an organic cosolvent, trifluoroethanol (TFE) using circular dichroism (CD), and in 50% TFE using two-dimensional proton nuclear magnetic resonance (2D H-1 NMR) spectroscopy. CD spectra in aqueous medium indicate that the apopeptide I adapts, mostly, a beta-sheet conformation whereas the glycopeptide II assumes helical structure. This transition in the secondary structure, upon glycosylation, demonstrates that the carbohydrate moiety exerts significant effect on the peptide backbone conformation. However, in 50% TFE both the peptides show pronounced helical structure. Sequential and medium range NOEs, C alpha H chemical shift perturbations, (3)J(NH:C alpha H) couplings and deuterium exchange rates of the amide proton resonances in water containing 50% TFE indicate that the peptide I adapts alpha-helical structure from Ile2-Val21 and the glycopeptide II adapts alpha-helical structure from Ser3-Glu22. The observation of continuous stretch of helix in both the peptides as observed by both NMR and CD spectroscopy strongly suggests that the C-terminal domain of MUC7 with heptad repeats of leucines or methionine residues may be stabilized by dimeric leucine zipper motif. The results reported herein may be invaluable in understanding the aggregation (or dimerization) of MUC7 glycoprotein which would eventually have implications in determining its structure-function relationship.

PEECE II mesocosm experiment: Dynamics of extracellular enzyme activities in seawater under changed atmospheric pCO2, 2011

As part of the PeECE II mesocosm project, we investigated the effects of pCO2 levels on the initial step of heterotrophic carbon cycling in the surface ocean. The activities of microbial extracellular enzymes hydrolyzing 4 polysaccharides were measured during the development of a natural phytoplankton bloom under pCO2 conditions representing glacial (190 µatm) and future (750 µatm) atmospheric pCO2. We observed that (1) chondroitin hydrolysis was variable throughout the pre-, early- and late-bloom phases, (2) fucoidanase activity was measurable only in the glacial mesocosm as the bloom developed, (3) laminarinase activity was low and constant, and (4) xylanase activity declined as the bloom progressed. Concurrent measurements of microbial community composition, using denaturing-gradient gel electrophoresis (DGGE), showed that the 2 mesocosms diverged temporally, and from one another, especially in the late-bloom phase. Enzyme activities correlated with bloom phase and pCO2, suggesting functional as well as compositional changes in microbial communities in the different pCO2 environments. These changes, however, may be a response to temporal changes in the development of phytoplankton communities that differed with the pCO2 environment. We hypothesize that the phytoplankton communities produced dissolved organic carbon (DOC) differing in composition, a hypothesis supported by changing amino acid composition of the DOC, and that enzyme activities responded to changes in substrates. Enzyme activities observed under different pCO2 conditions likely reflect both genetic and population-level responses to changes occurring among multiple components of the microbial loop.

Impact of CO2 enrichment on organic matter dynamics during nutrient induced coastal phytoplankton blooms

A mesocosm experiment was conducted to investigate the impact of rising fCO2 on the build-up and decline of organic matter during coastal phytoplankton blooms. Five mesocosms (~38 m³ each) were deployed in the Baltic Sea during spring (2009) and enriched with CO2 to yield a gradient of 355-862 µatm. Mesocosms were nutrient fertilized initially to induce phytoplankton bloom development. Changes in particulate and dissolved organic matter concentrations, including dissolved high-molecular weight (>1 kDa) combined carbohydrates, dissolved free and combined amino acids as well as transparent exopolymer particles (TEP), were monitored over 21 days together with bacterial abundance, and hydrolytic extracellular enzyme activities. Overall, organic matter followed well-known bloom dynamics in all CO2 treatments alike. At high fCO2, higher dPOC:dPON during bloom rise, and higher TEP concentrations during bloom peak, suggested preferential accumulation of carbon-rich components. TEP concentration at bloom peak was significantly related to subsequent sedimentation of particulate organic matter. Bacterial abundance increased during the bloom and was highest at high fCO2. We conclude that increasing fCO2 supports production and exudation of carbon-rich components, enhancing particle aggregation and settling, but also providing substrate and attachment sites for bacteria. More labile organic carbon and higher bacterial abundance can increase rates of oxygen consumption and may intensify the already high risk of oxygen depletion in coastal seas in the future.

Observation via one-dimensional 13Calpha NMR of local conformational substates in thermal unfolding equilibria of a synthetic analog of the GCN4 leucine zipper.

Synthesis of a 33-residue, capped leucine zipper analogous to that in GCN4 is reported. Histidine and arginine residues are mutated to lysine to reduce the unfolding temperature. CD and ultracentrifugation studies indicate that the molecule is a two-stranded coiled coil under benign conditions. Versions of the same peptide are made with 99% 13Calpha at selected sites. One-dimensional 13C NMR spectra are assigned by inspection and used to study thermal unfolding equilibria over the entire transition from 8 to 73 degrees C. Spectra at the temperature extremes establish the approximate chemical shifts for folded and unfolded forms at each labeled site. Resonances for each amino acid appear at both locations at intermediate T, indicating that folded and unfolded forms interconvert slowly (> >2 ms) on the NMR time scale. Moreover, near room temperature, the structured form's resonance is double at several, but not all, sites, indicating at least two slowly interconverting, structured, local conformational substates. Analysis of the dynamics is possible. For example, near room temperature at the Val-9, Ala-24, and Gly-31 positions, the equilibrium constant for interconversion of the two structured forms is near unity and the time scale is > or= 10-20 ms.

Identification of metastable states in peptide's dynamics

A recently developed spectral method for identifying metastable states in Markov chains is used to analyse the conformational dynamics of a four residue peptide Valine-Proline-Alanine-Leucine. We compare our results to empirically defined conformational states and show that the found metastable states correctly reproduce the conformational dynamics of the system.

Controlling protein molecular dynamics:how to accelerate folding while preserving the native state

The dynamics of peptides and proteins generated by classical molecular dynamics (MD) is described by using a Markov model. The model is built by clustering the trajectory into conformational states and estimating transition probabilities between the states. Assuming that it is possible to influence the dynamics of the system by varying simulation parameters, we show how to use the Markov model to determine the parameter values that preserve the folded state of the protein and at the same time, reduce the folding time in the simulation. We investigate this by applying the method to two systems. The first system is an imaginary peptide described by given transition probabilities with a total folding time of 1 micros. We find that only small changes in the transition probabilities are needed to accelerate (or decelerate) the folding. This implies that folding times for slowly folding peptides and proteins calculated using MD cannot be meaningfully compared to experimental results. The second system is a four residue peptide valine-proline-alanine-leucine in water. We control the dynamics of the transitions by varying the temperature and the atom masses. The simulation results show that it is possible to find the combinations of parameter values that accelerate the dynamics and at the same time preserve the native state of the peptide. A method for accelerating larger systems without performing simulations for the whole folding process is outlined.

Sensitivity of peptide conformational dynamics on clustering of a classical molecular dynamics trajectory

We investigate the sensitivity of a Markov model with states and transition probabilities obtained from clustering a molecular dynamics trajectory. We have examined a 500 ns molecular dynamics trajectory of the peptide valine-proline-alanine-leucine in explicit water. The sensitivity is quantified by varying the boundaries of the clusters and investigating the resulting variation in transition probabilities and the average transition time between states. In this way, we represent the effect of clustering using different clustering algorithms. It is found that in terms of the investigated quantities, the peptide dynamics described by the Markov model is sensitive to the clustering; in particular, the average transition times are found to vary up to 46%. Moreover, inclusion of nonphysical sparsely populated clusters can lead to serious errors of up to 814%. In the investigation, the time step used in the transition matrix is determined by the minimum time scale on which the system behaves approximately Markovian. This time step is found to be about 100 ps. It is concluded that the description of peptide dynamics with transition matrices should be performed with care, and that using standard clustering algorithms to obtain states and transition probabilities may not always produce reliable results.

Identifying and correcting non-Markov states in peptide conformational dynamics

Conformational transitions in proteins define their biological activity and can be investigated in detail using the Markov state model. The fundamental assumption on the transitions between the states, their Markov property, is critical in this framework. We test this assumption by analyzing the transitions obtained directly from the dynamics of a molecular dynamics simulated peptide valine-proline-alanine-leucine and states defined phenomenologically using clustering in dihedral space. We find that the transitions are Markovian at the time scale of ˜ 50 ps and longer. However, at the time scale of 30–40 ps the dynamics loses its Markov property. Our methodology reveals the mechanism that leads to non-Markov behavior. It also provides a way of regrouping the conformations into new states that now possess the required Markov property of their dynamics.