Analysis of the Contrasting Pathogenicities Induced by the D222G Mutation in 1918 and 2009 Pandemic Influenza A Viruses.

In 2009, the D222G mutation in the hemagglutinin (HA) glycoprotein of pandemic H1N1 influenza A virus was found to correlate with fatal and severe human infections. Previous static structural analysis suggested that, unlike the H1N1 viruses prevalent in 1918, the mutation did not compromise binding to human α2,6-linked glycan receptors, allowing it to transmit efficiently. Here we investigate the interconversion mechanism between two predicted binding modes in both 2009 and 1918 HAs, introducing a highly parallel intermediate network search scheme to construct kinetically relevant pathways efficiently. Accumulated mutations at positions 183 and 224 that alter the size of the binding pocket are identified with the fitness of the 2009 pandemic virus carrying the D222G mutation. This result suggests that the pandemic H1N1 viruses could gain binding affinity to the α2,3-linked glycan receptors in the lungs, usually associated with highly pathogenic avian influenza, without compromising viability.This work was supported by the ERC and the EPSRC.This is the final version of the article. It first appeared from ACS via http://pubs.acs.org/doi/abs/10.1021/ct5010565

Energy landscapes of a hairpin peptide including NMR chemical shift restraints.

Methods recently introduced to improve the efficiency of protein structure prediction simulations by adding a restraint potential to a molecular mechanics force field introduce additional input parameters that can affect the performance. Here we investigate the changes in the energy landscape as the relative weight of the two contributions, force field and restraint potential, is systematically altered, for restraint functions constructed from calculated nuclear magnetic resonance chemical shifts. Benchmarking calculations were performed on a 12-residue peptide, tryptophan zipper 1, which features both secondary structure (a β-hairpin) and specific packing of tryptophan sidechains. Basin-hopping global optimization was performed to assess the efficiency with which lowest-energy structures are located, and the discrete path sampling approach was employed to survey the energy landscapes between unfolded and folded structures. We find that inclusion of the chemical shift restraints improves the efficiency of structure prediction because the energy landscape becomes more funnelled and the proportion of local minima classified as native increases. However, the funnelling nature of the landscape is reduced as the relative contribution of the chemical shift restraint potential is increased past an optimal value.This research was supported by the EPSRC and the ERC.This is the final version of the article. It first appeared from the Royal Society of Chemistry via http://dx.doi.org/10.1039/C5CP01259

Thermodynamics and kinetics of aggregation for the GNNQQNY peptide.

The energy landscape of the monomer and dimer are explored for the amyloidogenic heptapeptide GNNQQNY from the N-terminal prion-determining domain of the yeast protein Sup35. The peptide is modeled by a united-atom potential and an implicit solvent representation. Replica exchange molecular dynamics is used to explore the conformational space, and discrete path sampling is employed to investigate the pathways that interconvert the most populated minima on the free energy surfaces. For the monomer, we find a rapid fluctuation between four different conformations, where a geometry intermediate between compact and extended structures is the most thermodynamically favorable. The GNNQQNY dimer forms three stable sheet structures, namely in-register parallel, off-register parallel, and antiparallel. The antiparallel dimer is stabilized by strong electrostatic interactions resulting from interpeptide hydrogen bonds, which restrict its conformational flexibility. The in-register parallel dimer, which is close to the amyloid beta-sheet structure, has fewer interpeptide hydrogen bonds, making hydrophobic interactions more important and increasing the conformational entropy compared to the antiparallel sheet. The estimated two-state rate constants indicate that the formation of dimers from monomers is fast and that the dimers are kinetically stable against dissociation at room temperature. Interconversions between the different dimers are feasible processes and are more likely than dissociation

Research data supporting "Energy landscapes of a hairpin peptide including NMR chemical shift restraints"

In the top-level directory, there are two input files for CHARMM: (1) orderparams.inp -> to calculate quantities for a given structure used to obtain the structural order parameters (2) charmm_md.inp -> to run molecular dynamics simulations in two parts: an initial heating phase (commands commented out) and a constant-temperature production phaseThe four subdirectories alpha0/ alpha0.3/ alpha0.5/ and alpha0.7/ contain input and output files for the kinetic transition networks assembled using discrete path sampling for the four different overall potentials. These directories contain: (1) min.data -> database of minima in the kinetic transition network (2) ts.data -> database of transition states in the kinetic transition network (3) points.min -> coordinates of the minima in min.data (direct access, unformatted file) (4) points.ts -> coordinates of the transition states in ts.data (direct access, unformatted file) (5) min.A, min.B -> input files for PATHSAMPLE required for certain types of run (6) pathdata -> input file for the PATHSAMPLE program for discrete path sampling (7) odata.connect -> input file for running double-ended connections using the OPTIM program with CHARMM interfaced (8) 1le0_extended.pdb -> PDB file for an extended structure of the trpzip1 peptide, used as input to CHARMM and OPTIM with CHARMM interfaced (9) perm.allow -> input file used by OPTIM and PATHSAMPLE for the optimal alignment of pairs of structures with respect to overall translation, rotation and permutational isomerization (10) input.crd -> template input coordinates file based on CHARMM card format* (11) chemshifts.dat -> input file for OPTIM, containing the reference CamShift chemical shifts (NOT needed for forcefield only calculations, i.e. directory alpha0/) (12) dinfo -> input file for plotting disconnectivity graphs using the disconnectionDPS program Subdirectory basinhopping/ (1) data -> input file for the GMIN program with CHARMM interfaced, to show the options used (2) [1,2,3,4,5,6,7,8,9,10].dbase.1 -> output coordinate files, based on CHARMM card format*, containing the lowest-energy minimum found by GMIN in the 10 independent runs starting from different configurations (labelled by the run number) Running PATHSAMPLE with the current keywords will compute the "fastest" path through the network between the minima whose indices are specified in the min.A and min.B files, at 298K. The binary files can be read using the PATHSAMPLE program compiled with the NAG Fortran Compiler Release 6.0 (64 bit). * Input and output CHARMM coordinate files are formatted based on the CHARMM card format, for free-field reading, but with modifications to the source code to allow greater precision in the coordinates and longer line lengths (120 characters), found to be essential to our work.For the meaning and operation of specific keywords in the input files please refer to the user manuals (see http://www-wales.ch.cam.ac.uk/software.html and http://www.charmm.org/documentation/chmdoc.html). For further enquiries please email Prof. David J. Wales .This work was supported by the EPSRC [grant number EP/H042660/1] and ERC [grant number 267369]

A Local Rigid Body Framework for Global Optimization of Biomolecules

We present a local rigid body framework for simulations of biomolecules. In this framework, arbritrary sets of atoms may be treated as rigid bodies. Such groupings reduce the number of degrees of freedom, which can result in a significant reduction of computational time. As benchmarks, we consider global optimization for the tryptophan zipper (trpzip 1, 1LE0; using the CHARMM force field) and chignolin (1UAO; using the AMBER force field). We use a basin-hopping algorithm to find the global minima and compute the mean first encounter time from random starting configurations with and without the local rigid body framework. Minimal groupings are used, where only peptide bonds, termini, and side chain rings are considered rigid. Finding the global minimum is 4.2 and 2.5 times faster, respectively, for trpzip 1 and chignolin, within the local rigid body framework. We further compare <i>O</i>(10⁵) low-lying local minima to the fully relaxed unconstrained representation for trpzip 1 at different levels of rigidification. The resulting Pearson correlation coefficients, and thus the apparent intrinsic rigidity of the various groups, appear in the following order: side chain rings > termini > trigonal planar centers ≥ peptide bonds ≫ side chains. This approach is likely to be even more beneficial for structure prediction in larger biomolecules

A Local Rigid Body Framework for Global Optimization of Biomolecules

We present a local rigid body framework for simulations of biomolecules. In this framework, arbritrary sets of atoms may be treated as rigid bodies. Such groupings reduce the number of degrees of freedom, which can result in a significant reduction of computational time. As benchmarks, we consider global optimization for the tryptophan zipper (trpzip 1, 1LE0; using the CHARMM force field) and chignolin (1UAO; using the AMBER force field). We use a basin-hopping algorithm to find the global minima and compute the mean first encounter time from random starting configurations with and without the local rigid body framework. Minimal groupings are used, where only peptide bonds, termini, and side chain rings are considered rigid. Finding the global minimum is 4.2 and 2.5 times faster, respectively, for trpzip 1 and chignolin, within the local rigid body framework. We further compare <i>O</i>(10⁵) low-lying local minima to the fully relaxed unconstrained representation for trpzip 1 at different levels of rigidification. The resulting Pearson correlation coefficients, and thus the apparent intrinsic rigidity of the various groups, appear in the following order: side chain rings > termini > trigonal planar centers ≥ peptide bonds ≫ side chains. This approach is likely to be even more beneficial for structure prediction in larger biomolecules

A Local Rigid Body Framework for Global Optimization of Biomolecules

We present a local rigid body framework for simulations of biomolecules. In this framework, arbritrary sets of atoms may be treated as rigid bodies. Such groupings reduce the number of degrees of freedom, which can result in a significant reduction of computational time. As benchmarks, we consider global optimization for the tryptophan zipper (trpzip 1, 1LE0; using the CHARMM force field) and chignolin (1UAO; using the AMBER force field). We use a basin-hopping algorithm to find the global minima and compute the mean first encounter time from random starting configurations with and without the local rigid body framework. Minimal groupings are used, where only peptide bonds, termini, and side chain rings are considered rigid. Finding the global minimum is 4.2 and 2.5 times faster, respectively, for trpzip 1 and chignolin, within the local rigid body framework. We further compare <i>O</i>(10⁵) low-lying local minima to the fully relaxed unconstrained representation for trpzip 1 at different levels of rigidification. The resulting Pearson correlation coefficients, and thus the apparent intrinsic rigidity of the various groups, appear in the following order: side chain rings > termini > trigonal planar centers ≥ peptide bonds ≫ side chains. This approach is likely to be even more beneficial for structure prediction in larger biomolecules

Research data supporting "Energy Landscapes and Persistent Minima"

Kinetic transition networks (databases of connected stationary points on the potential energy surface) for dialanine and tetraalanine peptides, the 38-atom Lennard-Jones cluster, a 60-atom binary Lennard-Jones mixture, a 69-bead model protein, binding modes for influenza virus, and a UUCG RNA tetraloop. These networks, obtained in previous work, are analysed here using topological persistence, to obtain subsets of local minima and hence a reduced description of the underlying energy landscape.This work was supported by the ERC [grant number 267369]

Virulence-Associated Substitution D222G in the Hemagglutinin of 2009 Pandemic Influenza A(H1N1) Virus Affects Receptor Binding

The clinical impact of the 2009 pandemic influenza A(H1N1) virus (pdmH1N1) has been relatively low. However, amino acid substitution D222G in the hemagglutinin of pdmH1N1 has been associated with cases of severe disease and fatalities. D222G was introduced in a prototype pdmH1N1 by reverse genetics, and the effect on virus receptor binding, replication, antigenic properties, and pathogenesis and transmission in animal models was investigated. pdmH1N1 with D222G caused ocular disease in mice without further indications of enhanced virulence in mice and ferrets. pdmH1N1 with D222G retained transmissibility via aerosols or respiratory droplets in ferrets and guinea pigs. The virus displayed changes in attachment to human respiratory tissues in vitro, in particular increased binding to macrophages and type II pneumocytes in the alveoli and to tracheal and bronchial submucosal glands. Virus attachment studies further indicated that pdmH1N1 with D222G acquired dual receptor specificity for complex alpha 2,3- and alpha 2,6-linked sialic acids. Molecular dynamics modeling of the hemagglutinin structure provided an explanation for the retention of alpha 2,6 binding. Altered receptor specificity of the virus with D222G thus affected interaction with cells of the human lower respiratory tract, possibly explaining the observed association with enhanced disease in human