Immunogenicity of peptide-vaccine candidates predicted by molecular dynamics simulations

We present an in silico, structure-based approach for design and evaluation of conformationally restricted peptide-vaccines. In particular, we designed four cyclic peptides of ten or 11 residues mimicking the crystallographically observed beta-turn conformation of a predicted immunodominant loop of PorA from Neisseria meningitidis. Conformational correctness and stability of the peptide designs, as evaluated by molecular dynamics simulations, correctly predicted the immunogenicity of the peptides. We observed a peptide-induced functional antibody response that, remarkably, exceeded the response induced by the native protein in outer membrane vesicles, without losing specificity for related strains. The presented approach offers tools for a priori design and selection of peptide-vaccine candidates with full biological activity. This approach could be widely applicable: to outer membrane proteins of Gram-negative bacteria, and to other epitopes in a large range of pathogens.     

Dynamics of proteins predicted by molecular dynamics simulations and analytical approaches: application to alpha-amylase inhibitor

The dynamics of alpha-amylase inhibitors has been investigated using molecular dynamics (MD) simulations and two analytical approaches, the Gaussian network model (GNM) and anisotropic network model (ANM). MD simulations use a full atomic approach with empirical force fields, while the analytical approaches are based on a coarse-grained single-site-per-residue model with a single-parameter harmonic potential between sufficiently close (r 相似文献   

Multiple loop conformations of peptides predicted by molecular dynamics simulations are compatible with nuclear magnetic resonance

The affinity and selectivity of protein-protein interactions can be fine-tuned by varying the size, flexibility, and amino acid composition of involved surface loops. As a model for such surface loops, we study the conformational landscape of an octapeptide, whose flexibility is chemically steered by a covalent ring closure integrating an azobenzene dye into and by a disulfide bridge additionally constraining the peptide backbone. Because the covalently integrated azobenzene dyes can be switched by light between a bent cis state and an elongated trans state, six cyclic peptide models of strongly different flexibilities are obtained. The conformational states of these peptide models are sampled by NMR and by unconstrained molecular dynamics (MD) simulations. Prototypical conformations and the free-energy landscapes in the high-dimensional space spanned by the phi/psi angles at the peptide backbone are obtained by clustering techniques from the MD trajectories. Multiple open-loop conformations are shown to be predicted by MD particularly in the very flexible cases and are shown to comply with the NMR data despite the fact that such open-loop conformations are missing in the refined NMR structures.     

Structures of scrambled disulfide forms of the potato carboxypeptidase inhibitor predicted by molecular dynamics simulations with constraints

The structures of two species of potato carboxypeptidase inhibitor with nonnative disulfide bonds were determined by molecular dynamics simulations in explicit solvent using disulfide bond constraints that have been shown to work for the native species. Ten structures were determined; five for scrambled A (disulfide bonds between Cys8-Cys27, Cys12-Cys18, and Cys24-Cys34) and five for the scrambled C (disulfide bonds Cys8-Cys24, Cys12-Cys18, and Cys27-Cys34). The two scrambled species were both more solvent exposed than the native structure; the scrambled C species was more solvent exposed and less compact than the scrambled A species. Analysis of the loop regions indicates that certain loops in scrambled C are more nativelike than in scrambled A. These factors, combined with the fact that scrambled C has one native disulfide bond, may contribute to the observed faster conversion to the native structure from scrambled C than from scrambled A. Results from the PROCHECK program using the standard parameter database and a database specially constructed for small, disulfide-rich proteins indicate that the 10 scrambled structures have correct stereochemistry. Further, the results show that a characteristic feature of small, disulfide-rich proteins is that they score poorly using the standard PROCHECK parameter database. Proteins 2000;40:482-493.     

Experimental evaluation of single‐domain antibodies predicted by molecular dynamics simulations to have elevated thermal stability

Recently Bekker et al. [Bekker G‐J et al. Protein Sci. 2019;28:429–438.] described a computational strategy of applying molecular‐dynamics simulations to estimate the relative stabilities of single‐domain antibodies, and utilized their method to design changes with the aim of increasing the stability of a single‐domain antibody with a known crystal structure. The structure from which they generated potentially stabilizing mutations is an anti‐cholera toxin single domain antibody selected from a naïve library which has relatively low thermal stability, reflected by a melting point of 48°C. Their work was purely theoretical, so to examine their predictions, we prepared the parental and predicted stabilizing mutant single domain antibodies and examined their thermal stability, ability to refold and affinity. We found that the mutation that improved stability the most (~7°C) was one which changed an amino acid in CDR1 from an asparagine to an aspartic acid. This change unfortunately was also accompanied by a reduction in affinity. Thus, while their modeling did appear to successfully predict stabilizing mutations, introducing mutations in the binding regions is problematic. Of further interest, the mutations selected via their high temperature simulations, did improve refolding, suggesting that they were successful in stabilizing the structure at high temperatures and thereby decrease aggregation. Our result should permit them to reassess and refine their model and may one day lead to a usefulin silico approach to protein stabilization.     

Collective mechanical responses of cadherin-based adhesive junctions as predicted by simulations

Cadherin-based adherens junctions and desmosomes help stabilize cell-cell contacts with additional function in mechano-signaling, while clustered protocadherin junctions are responsible for directing neuronal circuits assembly. Structural models for adherens junctions formed by epithelial cadherin (CDH1) proteins indicate that their long, curved ectodomains arrange to form a periodic, two-dimensional lattice stabilized by tip-to-tip trans interactions (across junction) and lateral cis contacts. Less is known about the exact architecture of desmosomes, but desmoglein (DSG) and desmocollin (DSC) cadherin proteins are also thought to form ordered junctions. In contrast, clustered protocadherin (PCDH)-based cell-cell contacts in neuronal tissues are thought to be responsible for self-recognition and avoidance, and structural models for clustered PCDH junctions show a linear arrangement in which their long and straight ectodomains form antiparallel overlapped trans complexes. Here, we report all-atom molecular dynamics simulations testing the mechanics of minimalistic adhesive junctions formed by CDH1, DSG2 coupled to DSC1, and PCDHγB4, with systems encompassing up to 3.7 million atoms. Simulations generally predict a favored shearing pathway for the adherens junction model and a two-phased elastic response to tensile forces for the adhesive adherens junction and the desmosome models. Complexes within these junctions first unbend at low tensile force and then become stiff to unbind without unfolding. However, cis interactions in both the CDH1 and DSG2-DSC1 systems dictate varied mechanical responses of individual dimers within the junctions. Conversely, the clustered protocadherin PCDHγB4 junction lacks a distinct two-phased elastic response. Instead, applied tensile force strains trans interactions directly, as there is little unbending of monomers within the junction. Transient intermediates, influenced by new cis interactions, are observed after the main rupture event. We suggest that these collective, complex mechanical responses mediated by cis contacts facilitate distinct functions in robust cell-cell adhesion for classical cadherins and in self-avoidance signaling for clustered PCDHs.     

Three-dimensional model of a substrate-bound SARS chymotrypsin-like cysteine proteinase predicted by multiple molecular dynamics simulations: catalytic efficiency regulated by substrate binding

Severe acute respiratory syndrome (SARS) is a contagious and deadly disease caused by a new coronavirus. The protein sequence of the chymotrypsin-like cysteine proteinase (CCP) responsible for SARS viral replication has been identified as a target for developing anti-SARS drugs. Here, I report the ATVRLQ(p1)A(p1')-bound CCP 3D model predicted by 420 different molecular dynamics simulations (2.0 ns for each simulation with a 1.0-fs time step). This theoretical model was released at the Protein Data Bank (PDB; code: 1P76) before the release of the first X-ray structure of CCP (PDB code: 1Q2W). In contrast to the catalytic dyad observed in X-ray structures of CCP and other coronavirus cysteine proteinases, a catalytic triad comprising Asp187, His41, and Cys145 is found in the theoretical model of the substrate-bound CCP. The simulations of the CCP complex suggest that substrate binding leads to the displacement of a water molecule entrapped by Asp187 and His41, thus converting the dyad to a more efficient catalytic triad. The CCP complex structure has an expanded active-site pocket that is useful for anti-SARS drug design. In addition, this work demonstrates that multiple molecular dynamics simulations are effective in correcting errors that result from low-sequence-identity homology modeling.     

Bridging the gap: linking molecular simulations and systemic descriptions of cellular compartments

Metabolic processes in biological cells are commonly either characterized at the level of individual enzymes and metabolites or at the network level. Often these two paradigms are considered as mutually exclusive because concepts from neither side are suited to describe the complete range of scales. Additionally, when modeling metabolic or regulatory cellular systems, often a large fraction of the required kinetic parameters are unknown. This even applies to such simple and extensively studied systems like the photosynthetic apparatus of purple bacteria. Using the chromatophore vesicles of Rhodobacter sphaeroides as a model system, we show that a consistent kinetic model emerges when fitting the dynamics of a molecular stochastic simulation to a set of time dependent experiments even though about two thirds of the kinetic parameters in this system are not known from experiment. Those kinetic parameters that were previously known all came out in the expected range. The simulation model was built from independent protein units composed of elementary reactions processing single metabolites. This pools-and-proteins approach naturally compiles the wealth of available molecular biological data into a systemic model and can easily be extended to describe other systems by adding new protein or nucleic acid types. The automated parameter optimization, performed with an evolutionary algorithm, reveals the sensitivity of the model to the value of each parameter and the relative importances of the experiments used. Such an analysis identifies the crucial system parameters and guides the setup of new experiments that would add most knowledge for a systemic understanding of cellular compartments. The successful combination of the molecular model and the systemic parametrization presented here on the example of the simple machinery for bacterial photosynthesis shows that it is actually possible to combine molecular and systemic modeling. This framework can now straightforwardly be applied to other currently less well characterized but biologically more relevant systems.     

Ribonucleotide reductase inhibition by p-alkoxyphenols studied by molecular docking and molecular dynamics simulations

Ribonucleotide reductase (RNR) is necessary for production of the precursor deoxyribonucleotides for DNA synthesis. Class Ia RNR functions via a stable free radical in one of the two components protein R2. The enzyme mechanism involves long range (proton coupled) electron transfer between protein R1 and the tyrosyl radical in protein R2. Earlier experimental studies showed that p-alkoxyphenols inhibit RNR. Here, molecular docking and molecular dynamics simulations involving protein R2 suggest an inhibition mechanism for p-alkoxyphenols . A low energy binding pocket is identified in protein R2. The preferred configuration provides a structural basis explaining their specific binding to the Escherichia coli and mouse R2 proteins. Trp48 (E. coli numbering), on the electron transfer pathway, is involved in the interactions with the inhibitors. The relative order of the binding energies calculated for the phenol derivatives to protein R2 is correlated with earlier experimental data on inhibition efficiency, in turn related to increasing size of the hydrophobic alkyl substituents. Using the configuration identified by molecular docking as a starting point for molecular dynamics simulations, we find that the p-allyloxyphenol interrupts the catalytic electron transfer pathway of the R2 protein by forming hydrogen bonds with Trp48 and Asp237, thus explaining the inhibitory activity of p-alkoxyphenols.     

HLA-DP2 binding prediction by molecular dynamics simulations

Major histocompatibility complex (MHC) II proteins bind peptide fragments derived from pathogen antigens and present them at the cell surface for recognition by T cells. MHC proteins are divided into Class I and Class II. Human MHC Class II alleles are grouped into three loci: HLA-DP, HLA-DQ, and HLA-DR. They are involved in many autoimmune diseases. In contrast to HLA-DR and HLA-DQ proteins, the X-ray structure of the HLA-DP2 protein has been solved quite recently. In this study, we have used structure-based molecular dynamics simulation to derive a tool for rapid and accurate virtual screening for the prediction of HLA-DP2-peptide binding. A combinatorial library of 247 peptides was built using the "single amino acid substitution" approach and docked into the HLA-DP2 binding site. The complexes were simulated for 1 ns and the short range interaction energies (Lennard-Jones and Coulumb) were used as binding scores after normalization. The normalized values were collected into quantitative matrices (QMs) and their predictive abilities were validated on a large external test set. The validation shows that the best performing QM consisted of Lennard-Jones energies normalized over all positions for anchor residues only plus cross terms between anchor-residues.     

Dynamic exchange between stabilized conformations predicted for hyaluronan tetrasaccharides: comparison of molecular dynamics simulations with available NMR data

Studies of the hyaluronan (HA) tetrasaccharides are important for understanding hydrogen-bonding in the HA polymer, as they are probably the smallest oligomers in which characteristics of the constituent monosaccharides and the polymer are simultaneously exhibited. Here we present extensive molecular dynamics simulations of the two tetrasaccharides of HA in dilute aqueous solution. These simulations have confirmed the existence of intramolecular hydrogen-bonds between the neighboring sugar residues of HA in solution, as proposed by Scott (1989). However, our simulations predict that these intramolecular hydrogen-bonds are not static as previously proposed, but are in constant dynamic exchange on the sub-nanosecond time-scale. This process results in discrete internal motion of the HA tetrasaccharides where they rapidly move between low energy conformations. Specific interactions between water and intramolecular hydrogen-bonds involving the hydroxymethyl group were found to result in differing conformations and dynamics for the two alternative tetrasaccharides of HA. This new observation suggests that this residue may play a key role in the entropy and stability of HA in solution, allowing it to stay soluble up to high concentration. The vicinal coupling constants3 J NHCH of the acetamido groups have been calculated from our aqueous simulations of HA. We found that high values of 3J NHCH approximately 8 Hz, as experimentally measured for HA, are consistent with mixtures of both trans and cis conformations, and thus3 J NHCH cannot be used to imply a purely trans conformation of the acetamido. The rapid exchange of intramolecular hydrogen-bonds indicates that although the structure is at any moment stabilized by these hydrogen-bonds, no one hydrogen-bond exists for an extended period of time. This could explain why NMR often fails to provide evidence for intramolecular hydrogen-bonds in HA and other aqueous carbohydrate structures.      

Determination of membrane-insertion free energies by molecular dynamics simulations

The accurate prediction of membrane-insertion probability for arbitrary protein sequences is a critical challenge to identifying membrane proteins and determining their folded structures. Although algorithms based on sequence statistics have had moderate success, a complete understanding of the energetic factors that drive the insertion of membrane proteins is essential to thoroughly meeting this challenge. In the last few years, numerous attempts to define a free-energy scale for amino-acid insertion have been made, yet disagreement between most experimental and theoretical scales persists. However, for a recently resolved water-to-bilayer scale, it is found that molecular dynamics simulations that carefully mimic the conditions of the experiment can reproduce experimental free energies, even when using the same force field as previous computational studies that were cited as evidence of this disagreement. Therefore, it is suggested that experimental and simulation-based scales can both be accurate and that discrepancies stem from disparities in the microscopic processes being considered rather than methodological errors. Furthermore, these disparities make the development of a single universally applicable membrane-insertion free energy scale difficult.     

Hemolytic mechanism of dioscin proposed by molecular dynamics simulations

Saponins are a class of compounds containing a triterpenoid or steroid core with some attached carbohydrate modules. Many saponins cause hemolysis. However, the hemolytic mechanism of saponins at the molecular level is not yet fully understood. In an attempt to explore this issue, we have studied dioscin—a saponin with high hemolytic activity—through extensive molecular dynamics (MD) simulations. Firstly, all-atom MD simulations of 8 ns duration were conducted to study the stability of the dioscin–cholesterol complex and the cholesterol–cholesterol complex in water and in decane, respectively. MM-GB/SA computations indicate that the dioscin–cholesterol complex is energetically more favorable than the cholesterol–cholesterol complex in a non-polar environment. Next, several coarse-grained MD simulations of 400 ns duration were conducted to directly observe the distribution of multiple dioscin molecules on a DPPC-POPC-PSM-CHOL lipid bilayer. Our results indicate that dioscin can penetrate into the lipid bilayer, accumulate in the lipid raft micro-domain, and then bind cholesterol. This leads to the destabilization of lipid raft and consequent membrane curvature, which may eventually result in the hemolysis of red cells. This possible mechanism of hemolysis can well explain some experimental observations on hemolysis.     

Aggregation of small peptides studied by molecular dynamics simulations

Peptides and proteins tend to aggregate under appropriate conditions. The amyloid fibrils that are ubiquitously found among these structures are associated with major human diseases like Alzheimer's disease, type II diabetes, and various prion diseases. Lately, it has been observed that even very short peptides like tetra and pentapeptides can form ordered amyloid structures. Here, we present aggregation studies of three such small polypeptide systems, namely, the two amyloidogenic peptides DFNKF and FF, and a control (nonamyloidogenic) one, the AGAIL. The respective aggregation process is studied by all-atom Molecular Dynamics simulations, which allow to shed light on the fine details of the association and aggregation process. Our analysis suggests that naturally aggregating systems exhibit significantly diverse overall cluster shape properties and specific intermolecular interactions. Additional analysis was also performed on the previously studied NFGAIL system.     

Understanding beta-hairpin formation by molecular dynamics simulations of unfolding

We have studied the mechanism of formation of a 16-residue beta-hairpin from the protein GB1 using molecular dynamics simulations in an aqueous environment. The analysis of unfolding trajectories at high temperatures suggests a refolding pathway consisting of several transient intermediates. The changes in the interaction energies of residues are related with the structural changes during the unfolding of the hairpin. The electrostatic energies of the residues in the turn region are found to be responsible for the transition between the folded state and the hydrophobic core state. The van der Waals interaction energies of the residues in the hydrophobic core reflect the behavior of the radius of gyration of the core region. We have examined the opposing influences of the protein-protein (PP) energy, which favors the native state, and the protein-solvent (PS) energy, which favors unfolding, in the formation of the beta-hairpin structure. It is found that the behavior of the electrostatic components of PP and PS energies reflects the structural changes associated with the loss of backbone hydrogen bonding. Relative changes in the PP and PS van der Waals interactions are related with the disruption of the hydrophobic core of a protein. The results of the simulations support the hydrophobic collapse mechanism of beta-hairpin folding.     

Temperature dependence of protein-hydration hydrodynamics by molecular dynamics simulations

The dynamics of water molecules near the protein surface are different from those of bulk water and influence the structure and dynamics of the protein itself. To elucidate the temperature dependence hydration dynamics of water molecules, we present results from the molecular dynamic simulation of the water molecules surrounding two proteins (Carboxypeptidase inhibitor and Ovomucoid) at seven different temperatures (T=273 to 303 K, in increments of 5 K). Translational diffusion coefficients of the surface water and bulk water molecules were estimated from 2 ns molecular dynamics simulation trajectories. Temperature dependence of the estimated bulk water diffusion closely reflects the experimental values, while hydration water diffusion is retarded significantly due to the protein. Protein surface induced scaling of translational dynamics of the hydration waters is uniform over the temperature range studied, suggesting the importance protein-water interactions.     

Computer simulations of protein folding by targeted molecular dynamics

We have performed 128 folding and 45 unfolding molecular dynamics runs of chymotrypsin inhibitor 2 (CI2) with an implicit solvation model for a total simulation time of 0.4 microseconds. Folding requires that the three-dimensional structure of the native state is known. It was simulated at 300 K by supplementing the force field with a harmonic restraint which acts on the root-mean-square deviation and allows to decrease the distance to the target conformation. High temperature and/or the harmonic restraint were used to induce unfolding. Of the 62 folding simulations started from random conformations, 31 reached the native structure, while the success rate was 83% for the 66 trajectories which began from conformations unfolded by high-temperature dynamics. A funnel-like energy landscape is observed for unfolding at 475 K, while the unfolding runs at 300 K and 375 K as well as most of the folding trajectories have an almost flat energy landscape for conformations with less than about 50% of native contacts formed. The sequence of events, i.e., secondary and tertiary structure formation, is similar in all folding and unfolding simulations, despite the diversity of the pathways. Previous unfolding simulations of CI2 performed with different force fields showed a similar sequence of events. These results suggest that the topology of the native state plays an important role in the folding process.