Solvation Effects on the Conformational Behaviour of Gellan and Calcium Ion Binding to Gellan Double Helices

The contribution of the presence of solvent to the conformations adopted by disaccharide fragments within the repeat unit of gellan have been studied by molecular modelling techniques. Initial conformational energy searches, using a dielectric continuum to represent the solvent, provided starting geometries for a series of molecular dynamics simulations. The solution behaviour from these simulations was subsequently compared to fibre diffraction data of the potassium gellan salt. The present calculations indicate considerable flexibility of the glycosidic linkages, and this is discussed in relation to its effect on gel formation. One of the fragments was solvated with explicit water molecules. These calculations showed the same conformational behaviour as those simulations conducted in implicit solvent.Finally, a series of molecular dynamics (MD) simulations were performed to study the calcium binding to gellan. The results from this clearly showed a well defined binding site for this ion.Abbreviations MM molecular mechanics - MD molecular dynamics     

Toward the understanding of the structure and dynamics of protein-carbohydrate interactions: molecular dynamics studies of the complexes between hevein and oligosaccharidic ligands

Herein we study, through all atom molecular dynamics simulations, the complex between hevein and two N-acetylated chitin oligomers, namely N,N(')-diacetylchitobiose and N,N('),N(")-triacetylchitotriose. The results of the simulations for two disaccharide complexes and one trisaccharide complex show that a carbohydrate oligomer is able to move on the surface of the relatively flat binding pocket of hevein, therefore occupying different binding subpockets. Statistical analysis methods were also applied in order to define the principal overall motions in the complexes, showing how the different ligands in the simulations modulate the protein motions. The oligosaccharide binding can be considered as defined by a subtle balance between enthalpic (formation of intermolecular interactions between the ligand and the receptor) and entropic (due mainly to the possibility for the sugar to move on the surface of the protein domain) effects, determining multiple binding conformations. This structural and dynamical view could parallel the results obtained by regularly used restrained MD simulations based on NOE NMR data that provide a well defined structure for both the disaccharide and trisaccharide complexes, and agrees with the observations for longer oligosaccharide chains.     

Molecular dynamics-solvated interaction energy studies of protein-protein interactions: the MP1-p14 scaffolding complex

Using the MP1-p14 scaffolding complex from the mitogen-activated protein kinase signaling pathway as model system, we explored a structure-based computational protocol to probe and characterize binding affinity hot spots at protein-protein interfaces. Hot spots are located by virtual alanine-scanning consensus predictions over three different energy functions and two different single-structure representations of the complex. Refined binding affinity predictions for select hot-spot mutations are carried out by applying first-principle methods such as the molecular mechanics generalized Born surface area (MM-GBSA) and solvated interaction energy (SIE) to the molecular dynamics (MD) trajectories for mutated and wild-type complexes. Here, predicted hot-spot residues were actually mutated to alanine, and crystal structures of the mutated complexes were determined. Two mutated MP1-p14 complexes were investigated, the p14(Y56A)-mutated complex and the MP1(L63A,L65A)-mutated complex. Alternative ways to generate MD ensembles for mutant complexes, not relying on crystal structures for mutated complexes, were also investigated. The SIE function, fitted on protein-ligand binding affinities, gave absolute binding affinity predictions in excellent agreement with experiment and outperformed standard MM-GBSA predictions when tested on the MD ensembles of Ras-Raf and Ras-RalGDS protein-protein complexes. For wild-type and mutant MP1-p14 complexes, SIE predictions of relative binding affinities were supported by a yeast two-hybrid assay that provided semiquantitative relative interaction strengths. Results on the MP1-mutated complex suggested that SIE predictions deteriorate if mutant MD ensembles are approximated by just mutating the wild-type MD trajectory. The SIE data on the p14-mutated complex indicated feasibility for generating mutant MD ensembles from mutated wild-type crystal structure, despite local structural differences observed upon mutation. For energetic considerations, this would circumvent costly needs to produce and crystallize mutated complexes. The sensitized protein-protein interface afforded by the p14(Y56A) mutation identified here has practical applications in screening-based discovery of first-generation small-molecule hits for further development into specific modulators of the mitogen-activated protein kinase signaling pathway.     

Molecular dynamics simulation of oligosaccharides containing N-acetyl neuraminic acid

αD -N-acetyl neuraminic acid (Neu5Ac, sialic acid) is a commonly occurring carbohydrate residue in various cell surface glycolipids and glycoproteins. This residue is linked terminally or internally to Gal residues via an α(2 → 3) or α(2 → 6) linkage. In the cell surface receptor, sialyl-Lewis^X, a terminal α(2 → 3) linkage is present. Previous studies from our laboratory have shown that in solution Lewis^X adopts a relatively rigid structure. In order to model the Neu5Ac residue, vacuum molecular dynamics of this monosaccharide were compared with simulations that explicitly include solvent water. The dynamical average of the monosaccharide conformation obtained from the two simulations was similar. Vacuum calculations for the disaccharide Neu5Ac α(2 → 3) Gal β-O-methyl show that a number of low energy minima are accessible to this disaccharide. Molecular dynamics simulations starting from the low energy minima show conformational transitions with a time scale of 10–50 ps among several of the minima while large barriers between other minima prevent transitions on the time scale studied. Simulations of this disaccharide in the presence of solvent show fewer conformational transitions, illustrating a dampening effect of the solvent that has been observed in some other studies. Our results are most consistent with an equilibrium among multiple conformations for the Neu5Ac α(2 → 3) Gal β linkage. © 1994 John Wiley & Sons, Inc.     

Subtle functional collective motions in pancreatic-like ribonucleases: from ribonuclease A to angiogenin

The analysis of the dynamic behavior of enzymes is fundamental to structural biology. A direct relationship between protein flexibility and biological function has been shown for bovine pancreatic ribonuclease (RNase A) (Rasmussen et al., Nature 1992;357:423-424). More recently, crystallographic studies have shown that functional motions in RNase A involve the enzyme beta-sheet regions that move concertedly on substrate binding and release (Vitagliano et al., Proteins 2002;46:97-104). These motions have been shown to correspond to intrinsic dynamic properties of the native enzyme by molecular dynamics (MD) simulations. To unveil the occurrence of these collective motions in other members of pancreatic-like superfamily, we carried out MD simulations on human angiogenin (Ang). Essential dynamics (ED) analyses performed on the trajectories reveal that Ang exhibits collective motions similar to RNase A, despite the limited sequence identity (33%) of the two proteins. Furthermore, we show that these collective motions are also present in ensembles of experimentally determined structures of both Ang and RNase A. Finally, these subtle concerted beta-sheet motions were also observed for other two members of the pancreatic-like superfamily by comparing the ligand-bound and ligand-free structures of these enzymes. Taken together, these findings suggest that pancreatic-like ribonucleases share an evolutionary conserved dynamic behavior consisting of subtle beta-sheet motions, which are essential for substrate binding and release.     

Molecular dynamics study of Pseudomonas aeruginosa lectin-II complexed with monosaccharides

We present the results of a series of 10-ns molecular dynamics simulations on Pseudomonas aeruginosa lectin-II (PA-IIL) and its complexes with four different monosaccharides. We compare the saccharide-free, saccharide-occupied, and saccharide- and ion-free forms of the lectin. The results are coupled with analysis of the water density map and calcium coordination. The water density pattern around the binding site in the free lectin molecular dynamics was fitted with that in the X-ray and with the hydroxyl groups of the monosaccharide within the lectin/monosaccharide complexes and the best ligand was predicted based on the best fit. Interestingly, the water density pattern around the binding site in the uncomplexed lectin exactly fitted the O2, O3, and O4 hydroxyl groups of the fucose complex with the lectin. This observation could lead to a hypothesis that the replacement of these three water molecules from the binding site by the monosaccharide decreases the entropy of the complex and increases the entropy of the water molecules, which favors the binding. It suggests that the high density peaks of the solvent around the binding site in the free protein could be the tool to predict hydroxyl group orientation of the sugar in the protein/sugar complexes. The high affinity of PA-IIL binding site is also attributed to the presence of two calcium ions, each of them making five to six coordinations with the protein part and two coordinations with either water or the monosaccharide. When the calcium ions are removed from the simulated system, they are replaced by sodium ions from the solvent. These observations rationalize the high binding affinity of PA-IIL towards fucose.     

Dynamical allosterism in the mechanism of action of DNA mismatch repair protein MutS

The multidomain protein Thermus aquaticus MutS and its prokaryotic and eukaryotic homologs recognize DNA replication errors and initiate mismatch repair. MutS actions are fueled by ATP binding and hydrolysis, which modulate its interactions with DNA and other proteins in the mismatch-repair pathway. The DNA binding and ATPase activities are allosterically coupled over a distance of ∼70 Å, and the molecular mechanism of coupling has not been clarified. To address this problem, all-atom molecular dynamics simulations of ∼150 ns including explicit solvent were performed on two key complexes—ATP-bound and ATP-free MutS⋅DNA(+T bulge). We used principal component analysis in fluctuation space to assess ATP ligand-induced changes in MutS structure and dynamics. The molecular dynamics-calculated ensembles of thermally accessible structures showed markedly small differences between the two complexes. However, analysis of the covariance of dynamical fluctuations revealed a number of potentially significant interresidue and interdomain couplings. Moreover, principal component analysis revealed clusters of correlated atomic fluctuations linking the DNA and nucleotide binding sites, especially in the ATP-bound MutS⋅DNA(+T) complex. These results support the idea that allosterism between the nucleotide and DNA binding sites in MutS can occur via ligand-induced changes in motion, i.e., dynamical allosterism.     

Molecular dynamics and binding specificity analysis of the bovine immunodeficiency virus BIV Tat-TAR complex

We have performed molecular dynamics (MD) simulations, with particle-mesh Ewald, explicit waters, and counterions, and binding specificity analyses using combined molecular mechanics and continuum solvent (MM-PBSA) on the bovine immunodeficiency virus (BIV) Tat peptide-TAR RNA complex. The solution structure for the complex was solved independently by Patel and co-workers and Puglisi and co-workers. We investigated the differences in both structures and trajectories, particularly in the formation of the U-A-U base triple, the dynamic flexibility of the Tat peptide, and the interactions at the binding interface. We observed a decrease in RMSD in comparing the final average RNA structures and initial RNA structures of both trajectories, which suggests the convergence of the RNA structures to a MD equilibrated RNA structure. We also calculated the relative binding of different Tat peptide mutants to TAR RNA and found qualitative agreement with experimental studies.     

Weight average approaches for predicting dynamical properties of biomolecules

Recent advances in atomistic molecular dynamics (MD) simulations of biomolecules allow us to explore their conformational spaces widely, observing large-scale conformational fluctuations or transitions between distinct structures. To reproduce or refine experimental data using MD simulations, structure ensembles, which are characterized by multiple structures and their statistical weights on the rugged free-energy landscapes, are often used. Here, we summarize weight average approaches for various experimental measurements. Weight average approaches are now applied to hybrid quantum mechanics/molecular mechanics MD simulations to predict fast vibrational motions in a protein with a high accuracy for better understanding of molecular functions from atomic structures.     

Molecular dynamics re-refinement of two different small RNA loop structures using the original NMR data suggest a common structure

Restrained molecular dynamics simulations are a robust, though perhaps underused, tool for the end-stage refinement of biomolecular structures. We demonstrate their utility-using modern simulation protocols, optimized force fields, and inclusion of explicit solvent and mobile counterions-by re-investigating the solution structures of two RNA hairpins that had previously been refined using conventional techniques. The structures, both domain 5 group II intron ribozymes from yeast ai5γ and Pylaiella littoralis, share a nearly identical primary sequence yet the published 3D structures appear quite different. Relatively long restrained MD simulations using the original NMR restraint data identified the presence of a small set of violated distance restraints in one structure and a possibly incorrect trapped bulge nucleotide conformation in the other structure. The removal of problematic distance restraints and the addition of a heating step yielded representative ensembles with very similar 3D structures and much lower pairwise RMSD values. Analysis of ion density during the restrained simulations helped to explain chemical shift perturbation data published previously. These results suggest that restrained MD simulations, with proper caution, can be used to "update" older structures or aid in the refinement of new structures that lack sufficient experimental data to produce a high quality result. Notable cautions include the need for sufficient sampling, awareness of potential force field bias (such as small angle deviations with the current AMBER force fields), and a proper balance between the various restraint weights.     

Protein solution structure calculations in solution: Solvated molecular dynamics refinement of calbindin D9k

The three-dimensional solution structures of proteins determinedwith NMR-derived constraints are almost always calculated in vacuo. Thesolution structure of (Ca²⁺)_{_2}-calbindinD_9k has been redetermined by new restrained molecular dynamics(MD) calculations that include Ca²⁺ ions and explicit solventmolecules. Four parallel sets of MD refinements were run to provide accuratecomparisons of structures produced in vacuo, in vacuo withCa²⁺ ions, and with two different protocols in a solvent bathwith Ca²⁺ ions. The structural ensembles were analyzed interms of structural definition, molecular energies, packing density,solvent-accessible surface, hydrogen bonds, and the coordination of calciumions in the two binding loops. Refinement including Ca²⁺ ionsand explicit solvent results in significant improvements in the precisionand accuracy of the structure, particularly in the binding loops. Theseresults are consistent with results previously obtained in free MDsimulations of proteins in solution and show that the rMD refinedNMR-derived solution structures of proteins, especially metalloproteins, canbe significantly improved by these strategies.     

Combining NMR ensembles and molecular dynamics simulations provides more realistic models of protein structures in solution and leads to better chemical shift prediction

While chemical shifts are invaluable for obtaining structural information from proteins, they also offer one of the rare ways to obtain information about protein dynamics. A necessary tool in transforming chemical shifts into structural and dynamic information is chemical shift prediction. In our previous work we developed a method for 4D prediction of protein ¹H chemical shifts in which molecular motions, the 4th dimension, were modeled using molecular dynamics (MD) simulations. Although the approach clearly improved the prediction, the X-ray structures and single NMR conformers used in the model cannot be considered fully realistic models of protein in solution. In this work, NMR ensembles (NMRE) were used to expand the conformational space of proteins (e.g. side chains, flexible loops, termini), followed by MD simulations for each conformer to map the local fluctuations. Compared with the non-dynamic model, the NMRE+MD model gave 6–17% lower root-mean-square (RMS) errors for different backbone nuclei. The improved prediction indicates that NMR ensembles with MD simulations can be used to obtain a more realistic picture of protein structures in solutions and moreover underlines the importance of short and long time-scale dynamics for the prediction. The RMS errors of the NMRE+MD model were 0.24, 0.43, 0.98, 1.03, 1.16 and 2.39 ppm for ¹Hα, ¹HN, ¹³Cα, ¹³Cβ, ¹³CO and backbone ¹⁵N chemical shifts, respectively. The model is implemented in the prediction program 4DSPOT, available at .     

Human Lactate Dehydrogenase A Inhibitors: A Molecular Dynamics Investigation

Lactate dehydrogenase A (LDHA) is an important enzyme in fermentative glycolysis, generating most energy for cancer cells that rely on anaerobic respiration even under normal oxygen concentrations. This renders LDHA a promising molecular target for the treatment of various cancers. Several efforts have been made recently to develop LDHA inhibitors with nanomolar inhibition and cellular activity, some of which have been studied in complex with the enzyme by X-ray crystallography. In this work, we present a molecular dynamics (MD) study of the binding interactions of selected ligands with human LDHA. Conventional MD simulations demonstrate different binding dynamics of inhibitors with similar binding affinities, whereas steered MD simulations yield discrimination of selected LDHA inhibitors with qualitative correlation between the in silico unbinding difficulty and the experimental binding strength. Further, our results have been used to clarify ambiguities in the binding modes of two well-known LDHA inhibitors.     

Molecular Dynamics Simulations on the Complexes of Glucoamylase II (471) from Aspergillus awamori var. X100 with 1-Deoxynojirimycin and Lentiginosine

Molecular dynamics (MD) simulations on the complexes of glucoamylase II (471) from Aspergillus awamori var. X100 with two powerful inhibitors, 1-deoxynojirimycin and (+)-lentiginosine, have been performed, in order to build a model for these complexes in solution and to clarify the structure-activity relationship. MD calculations were carried out for 105 ps, over a 15 Å sphere centered on the inhibitors. A 8 Å residue-based cut-off was used, and the calculations were performed with explicit inclusion of solvent molecules. The MD structure of the complex 1-deoxynojirimycin-glucoamylase shows only minor deviations from the available X-ray structure. The MD structure of the complex of (+)-lentiginosine-glucoamylase, obtained by docking the inhibitor into the active site, suggests us a suitable orientation for the molecule into the enzyme cavity, which can rationalize the high inhibition activity found for (+)-lentiginosine towards amyloglucosidase from A. niger.     

Enhanced sampling simulations to construct free-energy landscape of protein–partner substrate interaction

Molecular dynamics (MD) simulations using all-atom and explicit solvent models provide valuable information on the detailed behavior of protein–partner substrate binding at the atomic level. As the power of computational resources increase, MD simulations are being used more widely and easily. However, it is still difficult to investigate the thermodynamic properties of protein–partner substrate binding and protein folding with conventional MD simulations. Enhanced sampling methods have been developed to sample conformations that reflect equilibrium conditions in a more efficient manner than conventional MD simulations, thereby allowing the construction of accurate free-energy landscapes. In this review, we discuss these enhanced sampling methods using a series of case-by-case examples. In particular, we review enhanced sampling methods conforming to trivial trajectory parallelization, virtual-system coupled multicanonical MD, and adaptive lambda square dynamics. These methods have been recently developed based on the existing method of multicanonical MD simulation. Their applications are reviewed with an emphasis on describing their practical implementation. In our concluding remarks we explore extensions of the enhanced sampling methods that may allow for even more efficient sampling.     

Calculation of protein ionization equilibria with conformational sampling: pK(a) of a model leucine zipper, GCN4 and barnase.

The use of conformational ensembles provided by nuclear magnetic resonance (NMR) experiments or generated by molecular dynamics (MD) simulations has been regarded as a useful approach to account for protein motions in the context of pK(a) calculations, yet the idea has been tested occasionally. This is the first report of systematic comparison of pK(a) estimates computed from long multiple MD simulations and NMR ensembles. As model systems, a synthetic leucine zipper, the naturally occurring coiled coil GCN4, and barnase were used. A variety of conformational averaging and titration curve-averaging techniques, or combination thereof, was adopted and/or modified to investigate the effect of extensive global conformational sampling on the accuracy of pK(a) calculations. Clustering of coordinates is proposed as an approach to reduce the vast diversity of MD ensembles to a few structures representative of the average electrostatic properties of the system in solution. Remarkable improvement of the accuracy of pK(a) predictions was achieved by the use of multiple MD simulations. By using multiple trajectories the absolute error in pK(a) predictions for the model leucine zipper was reduced to as low as approximately 0.25 pK(a) units. The validity, advantages, and limitations of explicit conformational sampling by MD, compared with the use of an average structure and a high internal protein dielectric value as means to improve the accuracy of pK(a) calculations, are discussed.     

Conformation of a trimannoside bound to mannose-binding protein by nuclear magnetic resonance and molecular dynamics simulations

A model of the carbohydrate recognition domain of the serum form of mannose-binding protein (MBP) from rat complexed with methyl 3,6-di-O-(alpha-D-mannopyranosyl)-alpha-D-mannopyranoside is presented. Allowed conformations for the bound sugar were derived from simulated annealing protocols incorporating distance restraints computed from transferred NOESY spectra. The resulting sugar conformations were then modeled into the MBP binding site, and these models of the complex were refined using molecular dynamics (MD) simulations in the presence of solvent water. These studies indicate that only one of the two major conformations of the alpha(1-->6) linkage found in solution is significantly populated in the bound state (omega = 60 degrees ), whereas the alpha(1-->3) linkage samples at least two states, similar to its behavior in free solution. The bound conformation allows direct hydrogen bonds to form between the sugar and K182 of MBP, in addition to other water-mediated hydrogen bonds. Estimates of binding constants of candidate complexes based on changes in solvent-accessible surface areas upon binding support the NMR and MD results. These estimates further suggest that the enthalpic gains of the additional sugar-MBP interactions in a trisaccharide as opposed to a monosaccharide are offset by entropic penalties, offering an explanation for previous binding data.     

Interpretation of Solution X-Ray Scattering by Explicit-Solvent Molecular Dynamics

Small- and wide-angle x-ray scattering (SWAXS) and molecular dynamics (MD) simulations are complementary approaches that probe conformational transitions of biomolecules in solution, even in a time-resolved manner. However, the structural interpretation of the scattering signals is challenging, while MD simulations frequently suffer from incomplete sampling or from a force-field bias. To combine the advantages of both techniques, we present a method that incorporates solution scattering data as a differentiable energetic restraint into explicit-solvent MD simulations, termed SWAXS-driven MD, with the aim to direct the simulation into conformations satisfying the experimental data. Because the calculations fully rely on explicit solvent, no fitting parameters associated with the solvation layer or excluded solvent are required, and the calculations remain valid at wide angles. The complementarity of SWAXS and MD is illustrated using three biological examples, namely a periplasmic binding protein, aspartate carbamoyltransferase, and a nuclear exportin. The examples suggest that SWAXS-driven MD is capable of refining structures against SWAXS data without foreknowledge of possible reaction paths. In turn, the SWAXS data accelerates conformational transitions in MD simulations and reduces the force-field bias.     

Structural predictions of protein–DNA binding: MELD-DNA

Structural, regulatory and enzymatic proteins interact with DNA to maintain a healthy and functional genome. Yet, our structural understanding of how proteins interact with DNA is limited. We present MELD-DNA, a novel computational approach to predict the structures of protein–DNA complexes. The method combines molecular dynamics simulations with general knowledge or experimental information through Bayesian inference. The physical model is sensitive to sequence-dependent properties and conformational changes required for binding, while information accelerates sampling of bound conformations. MELD-DNA can: (i) sample multiple binding modes; (ii) identify the preferred binding mode from the ensembles; and (iii) provide qualitative binding preferences between DNA sequences. We first assess performance on a dataset of 15 protein–DNA complexes and compare it with state-of-the-art methodologies. Furthermore, for three selected complexes, we show sequence dependence effects of binding in MELD predictions. We expect that the results presented herein, together with the freely available software, will impact structural biology (by complementing DNA structural databases) and molecular recognition (by bringing new insights into aspects governing protein–DNA interactions).