Role of aspartic acid in collagen structure and stability: A molecular dynamics investigation

A molecular dynamics (MD) simulation study has been carried out to understand the stability of the triple helical collagen models. The calculations show that the presence of the aspartic acid residue in different positions leads to the local variation in the structure. Analyses of root-mean-square deviation (RMSD), radial distribution function (RDF), puckering effect, dihedral angle variation, hydrogen bond (H-bond), and conformational changes during molecular dynamics simulation reveal that the local perturbation in the sequences, increase in chain flexibility due to removal of five membered rings in the collagen by aspartic acid, change of intermolecular H-bonding pattern, and differences in the association of water are mainly influencing the nature of stabilization of collagen by aspartic acid.     

Polymer Structures and Glass Transition: A Molecular Dynamics Simulation Study

Full atomistic molecular dynamics (MD) simulations on five polymers with different chain backbone (C—C, Si—O, and C—O) and different side groups (—H, one —CH₃, and two —CH₃) are performed to study the effects of chain flexibility and side groups on the glass transition of polymers. Molecular dynamics simulations of NPT (constant pressure and constant temperature) dynamics are carried out to obtain specific volume as a function of temperature for polyethylene (PE), poly(propylene) (PP), polyisobutylene (PIB), poly(oxymethylene) (POM), and poly(dimethylsiloxane) (PDMS). The volumetric glass transition temperature has been determined as the temperature marking the discontinuity in slope of the plots of V–T simulation data. Various energy components at different temperatures of the polymers are investigated and their roles played in the glass transition process are analyzed. In order to understand the polymer chain conformations above and below the glass transition temperature, dihedral angle distributions of polymer chains at various temperatures are also studied.     

Application of torsion angle molecular dynamics for efficient sampling of protein conformations

We investigate the application of torsion angle molecular dynamics (TAMD) to augment conformational sampling of peptides and proteins. Interesting conformational changes in proteins mainly involve torsional degrees of freedom. Carrying out molecular dynamics in torsion space does not only explicitly sample the most relevant degrees of freedom, but also allows larger integration time steps with elimination of the bond and angle degrees of freedom. However, the covalent geometry needs to be fixed during internal coordinate dynamics, which can introduce severe distortions to the underlying potential surface in the extensively parameterized modern Cartesian-based protein force fields. A "projection" approach (Katritch et al. J Comput Chem 2003, 24, 254-265) is extended to construct an accurate internal coordinate force field (ICFF) from a source Cartesian force field. Torsion crossterm corrections constructed from local molecular fragments, together with softened van der Waals and electrostatic interactions, are used to recover the potential surface and incorporate implicit bond and angle flexibility. MD simulations of dipeptide models demonstrate that full flexibility in both the backbone phi/psi and side chain chi1 angles are virtually restored. The efficacy of TAMD in enhancing conformational sampling is then further examined by folding simulations of small peptides and refinement experiments of protein NMR structures. The results show that an increase of several fold in conformational sampling efficiency can be reliably achieved. The current study also reveals some complicated intrinsic properties of internal coordinate dynamics, beyond energy conservation, that can limit the maximum size of the integration time step and thus the achievable gain in sampling efficiency.     

A Method to Explore Protein Side Chain Conformational Variability Using Experimental Data

Experimentally measured values of molecular properties or observables of biomolecules such as proteins are generally averages over time and space, which do not contain su?cient information to determine the underlying conformational distribution of the molecules in solution. The relationship between experimentally measured NMR ³J‐coupling values and the corresponding dihedral angle values is a particularly complicated case due to its nonlinear, multiple‐valued nature. Molecular dynamics (MD) simulations at constant temperature can generate Boltzmann ensembles of molecular structures that are free from a priori assumptions about the nature of the underlying conformational distribution. They suffer, however, from limited sampling with respect to time and conformational space. Moreover, the quality of the obtained structures is dependent on the choice of force ?eld and solvation model. A recently proposed method that uses time‐averaging with local‐elevation (LE) biasing of the conformational search provides an elegant means of overcoming these three problems. Using a set of side chain ³J‐coupling values for the FK506 binding protein (FKBP), we ?rst investigate the uncertainty in the angle values predicted theoretically. We then propose a simple MD‐based technique to detect inconsistencies within an experimental data set and identify degrees of freedom for which conformational averaging takes place or for which force ?eld parameters may be de?cient. Finally, we show that LE MD is the best method for producing ensembles of structures that, on average, ?t the experimental data.     

Predictive power of molecular dynamics receptor structures in virtual screening

Molecular dynamics (MD) simulation is a well-established method for understanding protein dynamics. Conformations from unrestrained MD simulations have yet to be assessed for blind virtual screening (VS) by docking. This study presents a critical analysis of the predictive power of MD snapshots to this regard, evaluating two well-characterized systems of varying flexibility in ligand-bound and unbound configurations. Results from such VS predictions are discussed with respect to experimentally determined structures. In all cases, MD simulations provide snapshots that improve VS predictive power over known crystal structures, possibly due to sampling more relevant receptor conformations. Additionally, MD can move conformations previously not amenable to docking into the predictive range.     

Molecular dynamics with the united-residue model of polypeptide chains. II. Langevin and Berendsen-bath dynamics and tests on model alpha-helical systems

The implementation of molecular dynamics (MD) with our physics-based protein united-residue (UNRES) force field, described in the accompanying paper, was extended to Langevin dynamics. The equations of motion are integrated by using a simplified stochastic velocity Verlet algorithm. To compare the results to those with all-atom simulations with implicit solvent in which no explicit stochastic and friction forces are present, we alternatively introduced the Berendsen thermostat. Test simulations on the Ala(10) polypeptide demonstrated that the average kinetic energy is stable with about a 5 fs time step. To determine the correspondence between the UNRES time step and the time step of all-atom molecular dynamics, all-atom simulations with the AMBER 99 force field and explicit solvent and also with implicit solvent taken into account within the framework of the generalized Born/surface area (GBSA) model were carried out on the unblocked Ala(10) polypeptide. We found that the UNRES time scale is 4 times longer than that of all-atom MD simulations because the degrees of freedom corresponding to the fastest motions in UNRES are averaged out. When the reduction of the computational cost for evaluation of the UNRES energy function is also taken into account, UNRES (with hydration included implicitly in the side chain-side chain interaction potential) offers about at least a 4000-fold speed up of computations relative to all-atom simulations with explicit solvent and at least a 65-fold speed up relative to all-atom simulations with implicit solvent. To carry out an initial full-blown test of the UNRES/MD approach, we ran Berendsen-bath and Langevin dynamics simulations of the 46-residue B-domain of staphylococcal protein A. We were able to determine the folding temperature at which all trajectories converged to nativelike structures with both approaches. For comparison, we carried out ab initio folding simulations of this protein at the AMBER 99/GBSA level. The average CPU time for folding protein A by UNRES molecular dynamics was 30 min with a single Alpha processor, compared to about 152 h for all-atom simulations with implicit solvent. It can be concluded that the UNRES/MD approach will enable us to carry out microsecond and, possibly, millisecond simulations of protein folding and, consequently, of the folding process of proteins in real time.     

Interpreting protein structural dynamics from NMR chemical shifts

In this investigation, semiempirical NMR chemical shift prediction methods are used to evaluate the dynamically averaged values of backbone chemical shifts obtained from unbiased molecular dynamics (MD) simulations of proteins. MD-averaged chemical shift predictions generally improve agreement with experimental values when compared to predictions made from static X-ray structures. Improved chemical shift predictions result from population-weighted sampling of multiple conformational states and from sampling smaller fluctuations within conformational basins. Improved chemical shift predictions also result from discrete changes to conformations observed in X-ray structures, which may result from crystal contacts, and are not always reflective of conformational dynamics in solution. Chemical shifts are sensitive reporters of fluctuations in backbone and side chain torsional angles, and averaged (1)H chemical shifts are particularly sensitive reporters of fluctuations in aromatic ring positions and geometries of hydrogen bonds. In addition, poor predictions of MD-averaged chemical shifts can identify spurious conformations and motions observed in MD simulations that may result from force field deficiencies or insufficient sampling and can also suggest subsets of conformational space that are more consistent with experimental data. These results suggest that the analysis of dynamically averaged NMR chemical shifts from MD simulations can serve as a powerful approach for characterizing protein motions in atomistic detail.     

Enhanced sampling method in molecular simulations using genetic algorithm for biomolecular systems

We propose a molecular simulation method using genetic algorithm (GA) for biomolecular systems to obtain ensemble averages efficiently. In this method, we incorporate the genetic crossover, which is one of the operations of GA, to any simulation method such as conventional molecular dynamics (MD), Monte Carlo, and other simulation methods. The genetic crossover proposes candidate conformations by exchanging parts of conformations of a target molecule between a pair of conformations during the simulation. If the candidate conformations are accepted, the simulation resumes from the accepted ones. While conventional simulations are based on local update of conformations, the genetic crossover introduces global update of conformations. As an example of the present approach, we incorporated genetic crossover to MD simulations. We tested the validity of the method by calculating ensemble averages and the sampling efficiency by using two kinds of peptides, ALA3 and (AAQAA)₃. The results show that for ALA3 system, the distribution probabilities of backbone dihedral angles are in good agreement with those of the conventional MD and replica-exchange MD simulations. In the case of (AAQAA)₃ system, our method showed lower structural correlation of α-helix structures than the other two methods and more flexibility in the backbone ψ angles than the conventional MD simulation. These results suggest that our method gives more efficient conformational sampling than conventional simulation methods based on local update of conformations. © 2018 Wiley Periodicals, Inc.     

Coarse-grained protein molecular dynamics simulations

A limiting factor in biological science is the time-scale gap between experimental and computational trajectories. At this point, all-atom explicit solvent molecular dynamics (MD) are clearly too expensive to explore long-range protein motions and extract accurate thermodynamics of proteins in isolated or multimeric forms. To reach the appropriate time scale, we must then resort to coarse graining. Here we couple the coarse-grained OPEP model, which has already been used with activated methods, to MD simulations. Two test cases are studied: the stability of three proteins around their experimental structures and the aggregation mechanisms of the Alzheimer's Abeta16-22 peptides. We find that coarse-grained isolated proteins are stable at room temperature within 50 ns time scale. Based on two 220 ns trajectories starting from disordered chains, we find that four Abeta16-22 peptides can form a three-stranded beta sheet. We also demonstrate that the reptation move of one chain over the others, first observed using the activation-relaxation technique, is a kinetically important mechanism during aggregation. These results show that MD-OPEP is a particularly appropriate tool to study qualitatively the dynamics of long biological processes and the thermodynamics of molecular assemblies.     

Influence of electrostatic interactions on the properties of cyanobiphenyl liquid crystals predicted from atomistic molecular dynamics simulations

The influence of force field details in all-atom molecular dynamics (MD) simulations on the predicted thermodynamic, structural, and dynamic properties of bulk 4-cyano-4?-pentylbiphenyl (5CB) systems have been investigated in the 292–368 K temperature range. The effect of the molecular dipole moment and the details of dihedral potential for biphenyl unit were investigated using both polarisable (POL) and non-polarisable (NP) versions of the quantum chemistry-based force field. The predicted densities for the nematic and isotropic phases of bulk 5CB were found to be in excellent agreement with available experimental data. The nematic-isotropic transition temperature (T_NI) showed strong sensitivity to the force field details, MD simulations with partial atomic charge distributions and molecular dipole moment corresponding to high-level quantum chemistry calculations predicted an overestimation of the T_NI by about 30 K. Rescaling the charges to allow the molecular dipole to be closer to experimentally reported values of 5CB dipole in condensed phases, significantly improved the prediction of T_NI as well as other thermodynamic and dynamic properties of 5CB. We also discuss how the structural, thermodynamic, and dynamic properties of bulk 5CB are affected by the flexibility of the central biphenyl dihedral and the inclusion of induced polarisation effects.     

Computational algorithmic and molecular dynamics study of functional and structural impacts of non-synonymous single nucleotide polymorphisms in human DHFR gene

Human dihydrofolate reductase (DHFR) is a conserved enzyme that is central to folate metabolism and is widely targeted in pathogenic diseases as well as cancers. Although studies have reported the fact that genetic mutations in DHFR leads to a rare autosomal recessive inborn error of folate metabolism and drug resistance, there is a lack of an extensive study on how the deleterious non-synonymous SNPs (nsSNPs) disrupt its phenotypic effects. In this study, we aim at discovering the structural and functional consequences of nsSNPs in DHFR by employing a combined computational approach consisting of ten recently developed in silico tools for identification of damaging nsSNPs and molecular dynamics (MD) simulation for getting deeper insights into the magnitudes of damaging effects. Our study revealed the presence of 12 most deleterious nsSNPs affecting the native phenotypic effects, with three (R71T, G118D, Y122D) identified in the co-factor and ligand binding active sites. MD simulations also suggested that these three SNPs particularly Y122D, alter the overall structural flexibility and dynamics of the native DHFR protein which can provide more understandings into the crucial roles of these mutants in influencing the loss of DHFR function.     

The MM2QM tool for combining docking,molecular dynamics,molecular mechanics,and quantum mechanics†

The use of the MM2QM tool in a combined docking + molecular dynamics (MD) + molecular mechanics (MM) + quantum mechanical (QM) binding affinity prediction study is presented, and the tool itself is discussed. The system of interest is Mycobacterium tuberculosis (MTB) pantothenate synthetase in complexes with three highly similar sulfonamide inhibitors, for which crystal structures are available. Starting from the structure of MTB pantothenate synthetase in the “open” conformation and following the combined docking + MD + MM + QM procedure, we were able to capture the closing of the enzyme binding pocket and to reproduce the position of the ligands with an average root mean square deviation of 1.6 Å. Protein–ligand interaction energies were reproduced with an average error lower than 10%. The discussion on the MD part and a protein flexibility importance is carried out. The presented approach may be useful especially for finding analog inhibitors or improving drug candidates. © 2012 Wiley Periodicals, Inc.     

Solvation dynamics of Hoechst 33258 in water: an equilibrium and nonequilibrium molecular dynamics study

Integrated within an appropriate theoretical framework, molecular dynamics (MD) simulations are a powerful tool to complement experimental studies of solvation dynamics. Together, experiment, theory, and simulation have provided substantial insight into the dynamic behavior of polar solvents. MD investigations of solvation dynamics are especially valuable when applied to the heterogeneous environments found in biological systems, where the calculated response of the environment to the electrostatic perturbation of the probe molecule can easily be decomposed by component (e.g., aqueous solvent, biomolecule, ions), greatly aiding the molecular-level interpretation of experiments. A comprehensive equilibrium and nonequilibrium MD study of the solvation dynamics of the fluorescent dye Hoechst 33258 (H33258) in aqueous solution is presented. Many fluorescent probes employed in experimental studies of solvation dynamics in biological systems, such as the DNA minor groove binder H33258, have inherently more conformational flexibility than prototypical fused-ring chromophores. The role of solute flexibility was investigated by developing a fully flexible force-field for the H33258 molecule and by simulating its solvation response. While the timescales for the total solvation response calculated using both rigid (0.16 and 1.3 ps) and flexible (0.17 and 1.4 ps) models of the probe closely matched the experimentally measured solvation response (0.2 and 1.2 ps), there were subtle differences in the response profiles, including the presence of significant oscillations for the flexible probe. A decomposition of the total response of the flexible probe revealed that the aqueous solvent was responsible for the overall decay, while the oscillations result from fluctuations in the electrostatic terms in the solute intramolecular potential energy. A comparison of equilibrium and nonequilibrium approaches for the calculation of the solvation response confirmed that the solvation dynamics of H33258 in water is well-described by linear response theory for both rigid and flexible models of the probe.     

Temperature‐shuffled parallel cascade selection molecular dynamics accelerates the structural transitions of proteins

Parallel cascade selection molecular dynamics (PaCS‐MD) is an enhanced conformational sampling method for searching structural transition pathways from a given reactant to a product. Recently, a temperature‐aided PaCS‐MD (Vinod et al., Eur. Biophys. J. 2016, 45, 463) has been proposed as its extension, in which the temperatures were introduced as additional parameters in conformational resampling, whereas the temperature is fixed in the original PaCS‐MD. In the present study, temperature‐shuffled PaCS‐MD is proposed as a further extension of temperature‐aided PaCS‐MD in which the temperatures are shuffled among different replicas at the beginning of each cycle of conformational resampling. To evaluate their conformational sampling efficiencies, the original, temperature‐aided, and temperature‐shuffled PaCS‐MD were applied to a protein‐folding process of Trp‐cage, and their minimum computational costs to identify the native state were addressed. Through the evaluation, it was confirmed that temperature‐shuffled PaCS‐MD remarkably accelerated the protein‐folding process of Trp‐cage compared with the other methods. © 2017 Wiley Periodicals, Inc.     

Studies on Single Chain Structure of Konjac Glucomannan

1INTRODUCTION The single chain structure of KGM is the ele-mentary acting unit of its biological function and viscoelasticity of mechanical properties.The re-search method of saccharide chain and the com-plexity of its structure have restricted the study on structure-activity relationship.Therefore,the studies concerning KGM both at home and abroad mainly focus on its application,whereas less on its structure.Previous researches were only related to the determination and distribution as…     

A GRID-derived water network stabilizes molecular dynamics computer simulations of a protease

Structural water molecules are crucial for the stability and function of proteins. Recently, we presented a molecular dynamics (MD) study on blood coagulation factor Xa (fXa) to investigate the effect of water molecules on the flexibility of the protein structure. We showed that neglecting important water positions at the outset of the simulation leads to severe structural distortions during the MD simulations: A stable trajectory was obtained with a water set that was derived from all 73 X-ray structures of the protein. However, for many proteins of interest, only limited structural data is available, which precludes the merging of information from many X-ray structures. Here, we show that an in silico assembled water network, derived from molecular interaction fields generated with the GRID program, is a viable alternative to X-ray data. MD simulations with the GRID water set show a significantly improved stability over alternative setups without water or the X-ray resolved water molecules in the starting structure. The performance is comparable to a water setup derived from a recently presented clustering approach.     

A hybrid method of molecular dynamics and harmonic dynamics for docking of flexible ligand to flexible receptor

We have developed a new docking method to consider receptor flexibility, a hybrid method of molecular dynamics and harmonic dynamics. The global motions of the whole receptor were approximately introduced into those of the receptor in the docking simulation as harmonic dynamics. On the other hand, the local flexibility of the side chains was also considered by conventional molecular dynamics. We confirmed that this new method can reproduce the fluctuations of the whole receptor by making a comparison of the directions and amplitudes of the global fluctuations. Then this method was applied to the docking of HIV-1 protease and its ligand. As a result, we observed a docking process where the ligand enters into the binding pocket well, which implies that this method is effective enough to reproduce a molecular complex formation.     

Side chain dynamics in unfolded protein states: an NMR based 2H spin relaxation study of delta131delta

NMR relaxation data on disordered proteins can provide insight into both structural and dynamic properties of these molecules. Because of chemical shift degeneracy in correlation spectra, detailed site-specific analyses of side chain dynamics have not been possible. Here, we present new experiments for the measurement of side chain dynamics in methyl-containing residues in unfolded protein states. The pulse schemes are similar to recently proposed methods for measuring deuterium spin relaxation rates in (13)CH(2)D methyl groups in folded proteins.(1) However, because resolution in (1)H-(13)C correlation maps of unfolded proteins is limiting, relaxation data are recorded as a series of (1)H-(15)N spectra. The methodology is illustrated with an application to the study of side chain dynamics in delta131delta, a large disordered fragment of staphylococcal nuclease containing residues 1-3 and 13-140 of the wide-type protein. A good correlation between the order parameters of the symmetry axes of the methyl groups and the backbone (1)H-(15)N bond vectors of the same residue is observed. Simulations establish that such a correlation is only possible if the unfolded state is comprised of an ensemble of structures which are not equiprobable. A motional model, which combines wobbling-in-a-cone and Gaussian axial fluctuations, is proposed to estimate chi(1) torsion angle fluctuations, sigma(chi)()1, of Val and Thr residues on the basis of the backbone and side chain order parameters. Values of sigma(chi)()1 are approximately 10 degrees larger than what has previously been observed in folded proteins. Of interest, the value of sigma(chi)()1 for Val 104 is considerably smaller than for other Val or Thr residues, suggesting that it may be part of a hydrophobic cluster. Notably large (15)N transverse relaxation rates are observed in this region. To our knowledge, this is the first time that side chain dynamics in an unfolded state have been studied in detail by NMR.