Membrane partitioning of peptide aggregates: coarse-grained molecular dynamics simulations

Abstract

Coarse-grained molecular dynamics (CGMD) simulation technique (MARTINI force field) is applied to monitor the aggregation of helical peptides representing the transmembrane sequence and its extension of bone marrow stromal cell antigen 2 (BST-2). One of the peptides is coupled with a protein transducing domain (PTD) of nine arginine residues (R9) at its N-terminal side as well as a peptide, pep11**, which has been shown to bind to human papilloma virus 16 (HPV16) E6 oncoprotein. A short hydrophobic stretch of the transmembrane domain (TMD) of BST-2 aggregates the fastest and inserts into a lipid membrane. An aggregate of R9-pep11** attaches to the membrane via simultaneous contact of many arginine residues. Monomers from the aggregates of the shortest of the hydrophobic TMDs dissolve into the opposing leaflet when the aggregate spans the bilayer. A ‘flipping’ of the individual monomeric peptides is not observed.

Communicated by Ramaswamy H. Sarma     

Study of the Villin headpiece folding dynamics by combining coarse-grained Monte Carlo evolution and all-atom molecular dynamics

The folding mechanism of the Villin headpiece (HP36) is studied by means of a novel approach which entails an initial coarse-grained Monte Carlo (MC) scheme followed by all-atom molecular dynamics (MD) simulations in explicit solvent. The MC evolution occurs in a simplified free-energy landscape and allows an efficient selection of marginally-compact structures which are taken as viable initial conformations for the MD. The coarse-grained MC structural representation is connected to the one with atomic resolution through a "fine-graining" reconstruction algorithm. This two-stage strategy is used to select and follow the dynamics of seven different unrelated conformations of HP36. In a notable case the MD trajectory rapidly evolves towards the folded state, yielding a typical root-mean-square deviation (RMSD) of the core region of only 2.4 A from the closest NMR model (the typical RMSD over the whole structure being 4.0 A). The analysis of the various MC-MD trajectories provides valuable insight into the details of the folding and mis-folding mechanisms and particularly about the delicate influence of local and nonlocal interactions in steering the folding process.     

Sop‐GPU: Accelerating biomolecular simulations in the centisecond timescale using graphics processors

Theoretical exploration of fundamental biological processes involving the forced unraveling of multimeric proteins, the sliding motion in protein fibers and the mechanical deformation of biomolecular assemblies under physiological force loads is challenging even for distributed computing systems. Using a C_α‐based coarse‐grained self organized polymer (SOP) model, we implemented the Langevin simulations of proteins on graphics processing units (SOP‐GPU program). We assessed the computational performance of an end‐to‐end application of the program, where all the steps of the algorithm are running on a GPU, by profiling the simulation time and memory usage for a number of test systems. The ～90‐fold computational speedup on a GPU, compared with an optimized central processing unit program, enabled us to follow the dynamics in the centisecond timescale, and to obtain the force‐extension profiles using experimental pulling speeds (v_f = 1–10 μm/s) employed in atomic force microscopy and in optical tweezers‐based dynamic force spectroscopy. We found that the mechanical molecular response critically depends on the conditions of force application and that the kinetics and pathways for unfolding change drastically even upon a modest 10‐fold increase in v_f. This implies that, to resolve accurately the free energy landscape and to relate the results of single‐molecule experiments in vitro and in silico, molecular simulations should be carried out under the experimentally relevant force loads. This can be accomplished in reasonable wall‐clock time for biomolecules of size as large as 10⁵ residues using the SOP‐GPU package. Proteins 2010; © 2010 Wiley‐Liss, Inc.     

Configuration and validation of an analytical model predicting secondary neutron radiation in proton therapy using Monte Carlo simulations and experimental measurements

PurposeThis study focuses on the configuration and validation of an analytical model predicting leakage neutron doses in proton therapy.MethodsUsing Monte Carlo (MC) calculations, a facility-specific analytical model was built to reproduce out-of-field neutron doses while separately accounting for the contribution of intra-nuclear cascade, evaporation, epithermal and thermal neutrons. This model was first trained to reproduce in-water neutron absorbed doses and in-air neutron ambient dose equivalents, H*(10), calculated using MCNPX. Its capacity in predicting out-of-field doses at any position not involved in the training phase was also checked. The model was next expanded to enable a full 3D mapping of H*(10) inside the treatment room, tested in a clinically relevant configuration and finally consolidated with experimental measurements.ResultsFollowing the literature approach, the work first proved that it is possible to build a facility-specific analytical model that efficiently reproduces in-water neutron doses and in-air H*(10) values with a maximum difference less than 25%. In addition, the analytical model succeeded in predicting out-of-field neutron doses in the lateral and vertical direction. Testing the analytical model in clinical configurations proved the need to separate the contribution of internal and external neutrons. The impact of modulation width on stray neutrons was found to be easily adjustable while beam collimation remains a challenging issue. Finally, the model performance agreed with experimental measurements with satisfactory results considering measurement and simulation uncertainties.ConclusionAnalytical models represent a promising solution that substitutes for time-consuming MC calculations when assessing doses to healthy organs.     

RASPA: molecular simulation software for adsorption and diffusion in flexible nanoporous materials

A new software package, RASPA, for simulating adsorption and diffusion of molecules in flexible nanoporous materials is presented. The code implements the latest state-of-the-art algorithms for molecular dynamics and Monte Carlo (MC) in various ensembles including symplectic/measure-preserving integrators, Ewald summation, configurational-bias MC, continuous fractional component MC, reactive MC and Baker's minimisation. We show example applications of RASPA in computing coexistence properties, adsorption isotherms for single and multiple components, self- and collective diffusivities, reaction systems and visualisation. The software is released under the GNU General Public License.     

Lattice simulations of cotranslational folding of single domain proteins

We use lattice protein models and Monte Carlo simulations to study cotranslational folding of small single domain proteins. We show that the assembly of native structure begins during late extrusion stages, but final formation of native state occurs during de novo folding, when all residues are extruded. There are three main results in our study. First, for the sequences displaying two-state refolding mechanism de novo cotranslational folding pathway differs from that sampled in in vitro refolding. The change in folding pathways is due to partial assembly of native interactions during extrusion that results in different starting conditions for in vitro refolding and for de novo cotranslational folding. For small single domain proteins cotranslational folding is slower than in vitro refolding, but is generally fast enough to be completed before the release from a ribosome. Second, we found that until final stages of biosynthesis cotranslational folding is essentially equilibrium. This observation is explained by low stability of structured states for partially extruded chains. Finally, our data suggest that the proteins, which refold in vitro slowly via intermediates, complete their de novo folding after the release from a ribosome. Comparison of our lattice cotranslational simulations with recent experimental and computational studies is discussed.     

Homogeneous vs. patient specific breast models for Monte Carlo evaluation of mean glandular dose in mammography

PurposeTo compare, via Monte Carlo simulations, homogeneous and non-homogenous breast models adopted for mean glandular dose (MGD) estimates in mammography vs. patient specific digital breast phantoms.MethodsWe developed a GEANT4 Monte Carlo code simulating four homogenous cylindrical breast models featured as follows: (1) semi-cylindrical section enveloped in a 5-mm adipose layer; (2) semi-elliptical section with a 4-mm thick skin; (3) semi-cylindrical section with a 1.45-mm skin layer; (4) semi-cylindrical section in a 1.45-mm skin layer and 2-mm subcutaneous adipose layer. Twenty patient specific digital breast phantoms produced from a dedicated CT scanner were assumed as reference in the comparison. We simulated two spectra produced from two anode/filter combinations. An additional digital breast phantom was produced via BreastSimulator software.ResultsWith reference to the results for patient-specific breast phantoms and for W/Al spectra, models #1 and #3 showed higher MGD values by about 1% (ranges [–33%; +28%] and [−31%; +30%], respectively), while for model #4 it was 2% lower (range [−34%; +26%]) and for model #2 –11% (range [−39%; +14%]), on average. On the other hand, for W/Rh spectra, models #1 and #4 showed lower MGD values by 2% and 1%, while for model #2 and #3 it was 14% and 8% lower, respectively (ranges [−43%; +13%] and [−41%; +21%]). The simulation with the digital breast phantom produced with BreastSimulator showed a MGD overestimation of +33%.ConclusionsThe homogeneous breast models led to maximum MGD underestimation and overestimation of 43% and 28%, respectively, when compared to patient specific breast phantoms derived from clinical CT scans.     

Grid computing and molecular simulations: the vision of the eMinerals project

This paper discusses a number of aspects of using grid computing methods in support of molecular simulations, with examples drawn from the eMinerals project. A number of components for a useful grid infrastructure are discussed, including the integration of compute and data grids, automatic metadata capture from simulation studies, interoperability of data between simulation codes, management of data and data accessibility, management of jobs and workflow, and tools to support collaboration. Use of a grid infrastructure also brings certain challenges, which are discussed. These include making use of boundless computing resources, the necessary changes, and the need to be able to manage experimentation.     

Motional timescale predictions by molecular dynamics simulations: Case study using proline and hydroxyproline sidechain dynamics

We propose a new approach for force field optimizations which aims at reproducing dynamics characteristics using biomolecular MD simulations, in addition to improved prediction of motionally averaged structural properties available from experiment. As the source of experimental data for dynamics fittings, we use ¹³C NMR spin‐lattice relaxation times T₁ of backbone and sidechain carbons, which allow to determine correlation times of both overall molecular and intramolecular motions. For structural fittings, we use motionally averaged experimental values of NMR J couplings. The proline residue and its derivative 4‐hydroxyproline with relatively simple cyclic structure and sidechain dynamics were chosen for the assessment of the new approach in this work. Initially, grid search and simplexed MD simulations identified large number of parameter sets which fit equally well experimental J couplings. Using the Arrhenius‐type relationship between the force constant and the correlation time, the available MD data for a series of parameter sets were analyzed to predict the value of the force constant that best reproduces experimental timescale of the sidechain dynamics. Verification of the new force‐field (termed as AMBER99SB‐ILDNP) against NMR J couplings and correlation times showed consistent and significant improvements compared to the original force field in reproducing both structural and dynamics properties. The results suggest that matching experimental timescales of motions together with motionally averaged characteristics is the valid approach for force field parameter optimization. Such a comprehensive approach is not restricted to cyclic residues and can be extended to other amino acid residues, as well as to the backbone. Proteins 2014; 82:195–215. © 2013 Wiley Periodicals, Inc.     

CGDB: A database of membrane protein/lipid interactions by coarse-grained molecular dynamics simulations

Membrane protein function and stability has been shown to be dependent on the lipid environment. Recently, we developed a high-throughput computational approach for the prediction of membrane protein/lipid interactions. In the current study, we enhanced this approach with the addition of a new measure of the distortion caused by membrane proteins on a lipid bilayer. This is illustrated by considering the effect of lipid tail length and headgroup charge on the distortion caused by the integral membrane proteins MscS and FLAP, and by the voltage sensing domain from the channel KvAP. Changing the chain length of lipids alters the extent but not the pattern of distortion caused by MscS and FLAP; lipid headgroups distort in order to interact with very similar but not identical regions in these proteins for all bilayer widths investigated. Introducing anionic lipids into a DPPC bilayer containing the KvAP voltage sensor does not affect the extent of bilayer distortion.     

Activation of Bax by joint action of tBid and mitochondrial outer membrane: Monte Carlo simulations

The mitochondrial pathway of apoptosis proceeds when molecules, such as cytochrome c, sequestered between the outer and inner mitochondrial membranes are released to the cytosol by mitochondrial outer membrane (MOM) permeabilization. Bax, a member of the Bcl-2 protein family, plays a pivotal role in mitochondrion-mediated apoptosis. In response to apoptotic stimuli, Bax integrates into the MOM, where it mediates the release of cytochrome c from the intermembrane space into the cytosol, leading to caspase activation and cell death. The pro-death action of Bax is regulated by interactions with both other prosurvival proteins, such as tBid, and the MOM, but the exact mechanisms remain largely unclear. Here, the mechanisms of integration of Bax into a model membrane mimicking the MOM were studied by Monte Carlo simulations preceded by a computer prediction of the docking of tBid with Bax. A novel model of Bax activation by tBid was predicted by the simulations. In this model, tBid binds to Bax at an interaction site formed by Bax helices α1, α2, α3 and α5 leading, due to interaction of the positively charged N-terminal fragment of tBid with anionic lipid headgroups, to Bax reorientation such that a hydrogen-bonded pair of residues, Asp98 and Ser184, is brought into close proximity with negatively charged lipid headgroups. The interaction with these headgroups destabilizes the hydrogen bond which results in the release of helix α9 from the Bax-binding groove, its insertion into the membrane, followed by insertion into the membrane of the α5–α6 helical hairpin. Electronic supplementary material  The online version of this article (doi:) contains supplementary material, which is available to authorized users.     

Protein conformational transitions coupled to binding in molecular recognition of unstructured proteins: hierarchy of structural loss from all-atom Monte Carlo simulations of p27Kip1 unfolding-unbinding and structural determinants of the binding mechanism

Conformational transitions coupled to binding are studied for the p27(Kip1) protein which undergoes a functional disorder-to-order folding transition during tertiary complex formation with the phosphorylated cyclin A-cyclin-dependent kinase 2 (Cdk2) binary complex. Temperature-induced Monte Carlo simulations of p27(Kip1) unfolding-unbinding carried out from the crystal structure of the tertiary complex have revealed a systematic trend in the hierarchy of structural loss for p27(Kip1) and a considerable difference in mobility of p27(Kip1) secondary structure elements. The most persistent interactions of p27(Kip1) at the intermolecular interface during unfolding-unbinding simulations are formed by beta-hairpin and beta-strand that on average maintain their structural integrity considerably longer than other p27(Kip1) elements. We have found that the ensemble of unfolded p27(Kip1) conformations is characterized by transitions between mostly unbound, collapsed conformations and entropically favorable p27(Kip1) conformations, which are weakly bound to the cyclin A side of the binary complex. The results of this study are consistent with the experimental evidence pointing to this region of the intermolecular interface as a potential initiation docking site during binding reaction and may reconcile conflicting experimental hypotheses on the recognition of substrate recruitment motifs.     

Effect of temperature on adsorption of mixtures in porous materials

The effect of temperature on the adsorption of a simple mixture (Ar/Kr) in disordered porous materials is investigated by means of molecular simulation. In the larger mesopores of porous silica glasses, capillary condensation occurs upon decreasing the temperature. At temperatures above the capillary condensation temperature, Kr is preferentially adsorbed at the pore surface and Ar adsorption occurs in regions of low Kr density. For temperatures below the capillary condensation temperature, Ar density surprisingly increases as temperature increases, the behaviour that is consistent with an over-solubility effect. In contrast, in the disordered sub-nanoporous carbon, filling of the pores occurs in a reversible and continuous way upon decreasing the temperature, owing to the small size and amorphous shape of the pores. These results show that the crossover between capillary condensation and continuous reversible filling observed for pure fluids in pores also exists for mixtures. We also show that the Kr selectivity exhibits a minimum in the disordered porous silica that is located at the capillary condensation temperature. In contrast, in the disordered porous carbon where no capillary condensation occurs, the selectivity decreases monotonically with increasing the temperature. These results shed light on low-temperature adsorption of mixtures confined in porous materials and provide a guide to design efficient phase separation processes.     

Kinetics of cytochrome C folding: atomically detailed simulations

The vast range of time scales (from nanoseconds to seconds) during protein folding is a challenge for experiments and computations. To make concrete predictions on folding mechanisms, atomically detailed simulations of protein folding, using potentials derived from chemical physics principles, are desired. However, due to their computational complexity, straightforward molecular dynamics simulations of protein folding are impossible today. An alternative algorithm is used that makes it possible to compute approximate atomically detailed long time trajectories (the Stochastic Difference Equation in Length). This algorithm is used to compute 26 atomically detailed folding trajectories of cytochrome c (a millisecond process). The early collapse of the protein chain (with marginal formation of secondary structure), and the earlier formation of the N and C helices (compare to the 60's helix) are consistent with the experiment. The existence of an energy barrier upon entry to the molten globule is examined as well. In addition to (favorable) comparison to experiments, we show that non-native contacts drive the formation of the molten globule. In contrast to popular folding models, the non-native contacts do not form off-pathway kinetic traps in cytochrome c.     

Molecular dynamics simulations of Factor Xa: insight into conformational transition of its binding subsites

Protein flexibility and conformational diversity is well known to be a key characteristic of the function of many proteins. Human blood coagulation proteins have multiple substrates, and various protein-protein interactions are required for the smooth functioning of the coagulation cascade to maintain blood hemostasis. To address how a protein may cope with multiple interactions with its structurally diverse substrates and the accompanied structural changes that may drive these changes, we studied human Factor X. We employed 20 ns of molecular dynamics (MD) and steered molecular dynamics (SMD) simulations on two different conformational forms of Factor X, open and closed, and observed an interchangeable conformational transition from one to another. This work also demonstrates the roles of various aromatic residues involved in aromatic-aromatic interactions, which make this dynamic transition possible.     

Adsorption into the MFI zeolite of aromatic molecule of biological relevance. Investigations by Monte Carlo simulations

Adsorption of paracresol and water into the silicalite-1 (MFI) zeolite has been investigated using canonical and grand-canonical Monte Carlo simulations. The most stable sites of adsorption of paracresol are found to be located at the channel intersections. Grand-canonical simulations have shown that at low loading, water molecules adsorb preferably at the vicinity of paracresol molecules, whereas they are also located in the sinusoidal channels as the loading increases. In order to explain the experimental adsorption isotherm observed for the coadsorption of water and paracresol in the MFI zeolite we propose a new concept of apparent adsorption enthalpy that varies with the concentration of the solution. The mathematical expression for the apparent enthalpy is introduced in an adsorption isotherm model. We shall refer to this theoretical isotherm as a non-langmuirian isotherm. The non-linear expression for the apparent adsorption enthalpy accounts for a variable accessibility of the sites of adsorption with respect to the concentration of the solution. Figure Co-adsorption of paracresol and water in silicalite-1 zeolite and comparison between experimental and modelled adsorption isotherms.     

Application of statistical potentials to protein structure refinement from low resolution ab initio models

Recently ab initio protein structure prediction methods have advanced sufficiently so that they often assemble the correct low resolution structure of the protein. To enhance the speed of conformational search, many ab initio prediction programs adopt a reduced protein representation. However, for drug design purposes, better quality structures are probably needed. To achieve this refinement, it is natural to use a more detailed heavy atom representation. Here, as opposed to costly implicit or explicit solvent molecular dynamics simulations, knowledge-based heavy atom pair potentials were employed. By way of illustration, we tried to improve the quality of the predicted structures obtained from the ab initio prediction program TOUCHSTONE by three methods: local constraint refinement, reduced predicted tertiary contact refinement, and statistical pair potential guided molecular dynamics. Sixty-seven predicted structures from 30 small proteins (less than 150 residues in length) representing different structural classes (alpha, beta, alpha;/beta) were examined. In 33 cases, the root mean square deviation (RMSD) from native structures improved by more than 0.3 A; in 19 cases, the improvement was more than 0.5 A, and sometimes as large as 1 A. In only seven (four) cases did the refinement procedure increase the RMSD by more than 0.3 (0.5) A. For the remaining structures, the refinement procedures changed the structures by less than 0.3 A. While modest, the performance of the current refinement methods is better than the published refinement results obtained using standard molecular dynamics.