PACE Force Field for Protein Simulations. 2. Folding Simulations of Peptides

Simulations of Functional Motions of Super Large Biomolecules with a Mixed-Resolution Model

Many large protein machines function through an interplay between large-scale movements and intricate conformational changes. Understanding functional motions of these proteins through simulations becomes challenging for both all-atom and coarse-grained (CG) modeling techniques because neither approach alone can readily capture the full details of these motions. In this study, we develop a multiscale model by employing the popular MARTINI CG model to represent a heterogeneous environment and structurally stable proteins and using the united-atom (UA) model PACE to describe proteins undergoing subtle conformational changes. PACE was previously developed to be compatible with the MARTINI solvent and membrane. Here, we couple the protein descriptions of the two models by directly mixing UA and CG interaction parameters to greatly simplify parameter determination. Through extensive validations with diverse protein systems in solution or membrane, we demonstrate that only additional parameter rescaling is needed to enable the resulting model to recover the stability of native structures of proteins under mixed representation. Moreover, we identify the optimal scaling factors that can be applied to various protein systems, rendering the model potentially transferable. To further demonstrate its applicability for realistic systems, we apply the model to a mechanosensitive ion channel Piezo1 that has peripheral arms for sensing membrane tension and a central pore for ion conductance. The model can reproduce the coupling between Piezo1's large-scale arm movement and subtle pore opening in response to membrane stress while consuming much less computational costs than all-atom models. Therefore, our model shows promise for studying functional motions of large protein machines.

Developing Hybrid All-Atom and Ultra-Coarse-Grained Models to Investigate Taxol-Binding and Dynein Interactions on Microtubules

Simulating the conformations and functions of biological macromolecules by using all-atom (AA) models is a challenging task due to expensive computational costs. One possible strategy to solve this problem is to develop hybrid all-atom and ultra-coarse-grained (AA/UCG) models of the biological macromolecules. In the AA/UCG scheme, the interest regions are described by AA models, while the other regions are described in the UCG representation. In this study, we develop the hybrid AA/UCG models and apply them to investigate the conformational changes of microtubule-bound tubulins. The simulation results of the hybrid models elucidated the mechanism of why the taxol molecules selectively bound microtubules but not tubulin dimers. In addition, we also explore the interactions of the microtubules and dyneins. Our study shows that the hybrid AA/UCG model has great application potential in studying the function of complex biological systems.

Performance efficient macromolecular mechanics via sub-nanometer shape based coarse graining

Dimensionality reduction via coarse grain modeling is a valuable tool in biomolecular research. For large assemblies, ultra coarse models are often knowledge-based, relying on a priori information to parameterize models thus hindering general predictive capability. Here, we present substantial advances to the shape based coarse graining (SBCG) method, which we refer to as SBCG2. SBCG2 utilizes a revitalized formulation of the topology representing network which makes high-granularity modeling possible, preserving atomistic details that maintain assembly characteristics. Further, we present a method of granularity selection based on charge density Fourier Shell Correlation and have additionally developed a refinement method to optimize, adjust and validate high-granularity models. We demonstrate our approach with the conical HIV-1 capsid and heteromultimeric cofilin-2 bound actin filaments. Our approach is available in the Visual Molecular Dynamics (VMD) software suite, and employs a CHARMM-compatible Hamiltonian that enables high-performance simulation in the GPU-resident NAMD3 molecular dynamics engine.

Effect of Slp4-a on Membrane Bending During Prefusion of Vesicles in Blood-Brain Barrier

Vesicle exocytosis is a promising pathway for brain drug delivery through the blood-brain barrier to treat neurodegenerative diseases. In vesicle exocytosis, the membrane fusion process is initiated by the calcium sensor protein named synaptotagmin-like protein4-a (Slp4-a). Understanding conformational changes of Slp4-a during the prefusion stage of exocytosis will help to develop vesicle-based drug delivery to the brain. In this work, we use molecular dynamics (MD) simulations with a hybrid force field coupling united-atom protein model with MARTINI coarse-grained (CG) solvent to capture the conformational changes of Slp4-a during the prefusion stage. These hybrid coarse-grained simulations are more efficient than all-atom MD simulations and can capture protein interactions and conformational changes. Our simulation results show that the calcium ions play critical roles during the prefusion stage. Only one calcium ion can remain in each calcium-binding pocket of Slp4-a C2 domains. The C2B domain of calcium-unbound Slp4-a remains parallel to the endothelial membrane, while the C2B domain of calcium-bound Slp4-a rotates perpendicular to the endothelial membrane to approach the vesicular membrane. For the calcium-bound case, three Slp4-a proteins can effectively bend lipid membranes at the prefusion stage, which could later trigger lipid stalk between membranes. This work provides a better understanding how C2 domains of Slp4-a operate during vesicle exocytosis from an endothelial cell.

Early Stages of RNA-Mediated Conversion of Human Prions

Prion diseases are characterized by the conversion of prion proteins from a PrPC fold into a disease-causing PrPSC form that is self-replicating. A possible agent to trigger this conversion is polyadenosine RNA, but both mechanism and pathways of the conversion are poorly understood. Using coarse-grained molecular dynamic simulations we study the time evolution of PrPC over 600 μs. We find that both the D178N mutation and interacting with polyadenosine RNA reduce the helicity of the protein and encourage formation of segments with strand-like motifs. We conjecture that these transient β-strands nucleate the conversion of the protein to the scrapie conformation PrPSC.

Accurate and Efficient Estimation of Lennard-Jones Interactions for Coarse-Grained Particles via a Potential Matching Method

The Lennard-Jones (LJ) energy functions are commonly used to describe the nonbonded interactions in bulk coarse-grained (CG) models, which contribute significantly to the stabilization of a local binding configuration or a self-assembly system. In many cases, systematic development of the LJ interaction parameters in a CG model requires a comprehensive sampling of the objective molecules at the all-atom (AA) level, which is therefore extremely time-consuming for large systems. Inspired by the concept of electrostatic potential (ESP), we define the LJ static potential (LJSP), by which the embedding potential energy surface can be constructed analytically. A semianalytic approach, namely, the LJSP matching method, is developed here to derive the CG parameters by minimizing the LJSP difference between the AA and the CG models, which provides a universal way to derive the CG LJ parameters from the AA models without doing presampling. The LJSP matching method is successful not only in deriving the LJ interaction energy landscape in the CG models for proteins, lipids, and DNA but also in reproducing the critical properties such as intermediate structures and enthalpy contributions as exemplified in simulating the self-assembly process of the dipalmitoylphosphatidylcholine (DPPC) lipids.

Resolution exchange with tunneling for enhanced sampling of protein landscapes

Simulations of protein folding and protein association happen on timescales that are orders of magnitude larger than what can typically be covered in all-atom molecular dynamics simulations. Use of low-resolution models alleviates this problem but may reduce the accuracy of the simulations. We introduce a replica-exchange-based multiscale sampling technique that combines the faster sampling in coarse-grained simulations with the potentially higher accuracy of all-atom simulations. After testing the efficiency of our Resolution Exchange with Tunneling (ResET) in simulations of the Trp-cage protein, an often used model to evaluate sampling techniques in protein simulations, we use our approach to compare the landscape of wild-type and A2T mutant Aβ_{1-42} peptides. Our results suggest a mechanism by that the mutation of a small hydrophobic alanine (A) into a bulky polar threonine (T) may interfere with the self-assembly of Aβ fibrils.

Development of a Hybrid-Resolution Force Field for Peptide Self-Assembly Simulations: Optimizing Peptide-Peptide and Peptide-Solvent Interactions

Atomic descriptions of peptide self-assembly are crucial to an understanding of disease-related peptide aggregation and the design of peptide-assembled materials. Obtaining these descriptions through computer simulation is challenging because current force fields, which were not designed for this process and are often unable to describe correctly peptide self-assembly behavior and the sequence dependence. Here, we developed a framework using dipeptide aggregation as a model system to improve force fields for simulations of self-assembly. Aggregation-related structural properties were designed and used to guide the optimization of peptide-peptide and peptide-solvent interactions. With this framework, we developed a self-assembly force field, termed PACE-ASM, by reoptimizing a hybrid-resolution force field that was originally developed for folding simulation. With its applicability in folding simulations, the new PACE was used to simulate the self-assembly of two disease-related short peptides, Aβ_16-21 and PHF6, into β-sheet-rich cross-β amyloids. These simulations reproduced the crystal structures of Aβ_16-21 and PHF6 amyloids at near-atomic resolution and captured the difference in packing orientations between the two sequences, a task which is challenging even with all-atom force fields. Apart from cross-β amyloids, the self-assembly of emerging helix-rich cross-α amyloids by another peptide PSMα3 can also be correctly described with the new PACE, manifesting the versatility of the force field. We demonstrated that the ability of the PACE-ASM to model peptide self-assembly is based largely on its improved description of peptide-peptide and peptide-solvent interactions. This was achieved with our optimization framework that can readily identify and address the deficiency in describing these interactions.

SPICA Force Field for Proteins and Peptides

A coarse-grained (CG) model for peptides and proteins was developed as an extension of the Surface Property fItting Coarse grAined (SPICA) force field (FF). The model was designed to examine membrane proteins that are fully compatible with the lipid membranes of the SPICA FF. A preliminary version of this protein model was created using thermodynamic properties, including the surface tension and density in the SPICA (formerly called SDK) FF. In this study, we improved the CG protein model to facilitate molecular dynamics (MD) simulations with a reproduction of multiple properties from both experiments and all-atom (AA) simulations. An elastic network model was adopted to maintain the secondary structure within a single chain. The side-chain analogues reproduced the transfer free energy profiles across the lipid membrane and demonstrated reasonable association free energy (potential of mean force) in water compared to those from AA MD. A series of peptides/proteins adsorbed onto or penetrated into the membrane simulated by the CG MD correctly predicted the penetration depths and tilt angles of peripheral and transmembrane peptides/proteins as comparable to those in the orientations of proteins in membranes (OPM) database. In addition, the dimerization free energies of several transmembrane helices within a lipid bilayer were comparable to those from experimental estimation. Application studies on a series of membrane protein assemblies, scramblases, and poliovirus capsids demonstrated the good performance of the SPICA FF.

Kirkwood-Buff-Derived Force Field for Peptides and Proteins: Applications of KBFF20

Here, we perform structural, thermodynamic, and kinetics tests of the Kirkwood-Buff-derived force field, KBFF20, for peptides and proteins developed in the previous article. The physical/structural tests measure the ability of KBFF20 to capture the experimental J-couplings for small peptides, to keep globular monomeric and oligomeric proteins folded, and to produce the experimentally relevant expanded conformational ensembles of intrinsically disordered proteins. The thermodynamic-based tests probe KBFF20's ability to quantify the preferential interactions of sodium chloride around native β-lactoglobulin and urea around native lysozyme, to reproduce the melting curves for small helix- and sheet-based peptides, and to fold the small proteins Trp-cage and Villin. The kinetics-based tests quantify how well KBFF20 can match the experimental contact formation rates of small, repeat-sequence peptides of variable lengths and the rotational diffusion coefficients of globular proteins. The results suggest that KBFF20 is naturally able to reproduce properties of both folded and disordered proteins, which we attribute to the use of the Kirkwood-Buff theory as the foundation of the force field's development. However, we show that KBFF20 tends to lose some well-defined secondary structural elements and increases the percentage of coil regions, indicating that the perfect balance of all interactions remains elusive. Nevertheless, we argue that KBFF20 is an improvement over recently modified force fields that require ad hoc interventions to prevent the collapse of intrinsically disordered proteins.

Ligand-protein interactions in lysozyme investigated through a dual-resolution model

A fully atomistic (AT) modeling of biological macromolecules at relevant length- and time-scales is often cumbersome or not even desirable, both in terms of computational effort required and a posteriori analysis. This difficulty can be overcome with the use of multiresolution models, in which different regions of the same system are concurrently described at different levels of detail. In enzymes, computationally expensive AT detail is crucial in the modeling of the active site in order to capture, for example, the chemically subtle process of ligand binding. In contrast, important yet more collective properties of the remainder of the protein can be reproduced with a coarser description. In the present work, we demonstrate the effectiveness of this approach through the calculation of the binding free energy of hen egg white lysozyme with the inhibitor di-N-acetylchitotriose. Particular attention is payed to the impact of the mapping, that is, the selection of AT and coarse-grained residues, on the binding free energy. It is shown that, in spite of small variations of the binding free energy with respect to the active site resolution, the separate contributions coming from different energetic terms (such as electrostatic and van der Waals interactions) manifest a stronger dependence on the mapping, thus pointing to the existence of an optimal level of intermediate resolution.

Substrate-dependent transport mechanism in AcrB of multidrug resistant bacteria

The multidrug resistance (MDR) system effectively expels antibiotics out of bacteria causing serious issues during bacterial infection. In addition to drug, indole, a common metabolic waste of bacteria, is expelled by MDR system of gram-negative bacteria for their survival. Experimental results suggest that AcrB, one of the key components of MDR system, undergoes large scale conformation changes during the pumping due to proton-motive process. However, due to extremely short time scale, it is difficult to observe (experimentally) those changes in the AcrB, which might facilitate the pumping process. Molecular simulations can shed light to understand the conformational changes for transport of indole in AcrB. Examination of conformational changes using all-atom simulation is, however, impractical. Here, we develop a hybrid coarse-grained force field to study the conformational changes of AcrB in presence of indole in the porter domain of monomer II. Using the coarse-grained force field, we investigated the conformational changes of AcrB for a number of model systems considering the effect of protonation in aspartic acid (Asp) residues Asp407 and Asp408 in the transmembrane domain of monomer II. Our results show that in the presence of indole, protonation of Asp408 or Asp407 residue causes conformational changes from binding state to extrusion state in monomer II, while remaining two monomers (I and III) approach access state in AcrB protein. We also observed that all three AcrB monomers prefer to go back to access state in the absence of indole. Steered molecular dynamics simulations were performed to demonstrate the feasibility of indole transport mechanism for protonated systems. Identification of indole transport pathway through AcrB can be very helpful in understanding the drug efflux mechanism used by the MDR bacteria.

Exploration of the Misfolding Mechanism of Transthyretin Monomer: Insights from Hybrid-Resolution Simulations and Markov State Model Analysis

Misfolding and aggregation of transthyretin (TTR) is widely known to be responsible for a progressive systemic disorder called amyloid transthyretin (ATTR) amyloidosis. Studies suggest that TTR aggregation is initiated by a rate-limiting dissociation of the homo-tetramer into its monomers, which can rapidly misfold and self-assemble into amyloid fibril. Thus, exploring conformational change involved in TTR monomer misfolding is of vital importance for understanding the pathogenesis of ATTR amyloidosis. In this work, microsecond timescale hybrid-resolution molecular dynamics (MD) simulations combined with Markov state model (MSM) analysis were performed to investigate the misfolding mechanism of the TTR monomer. The results indicate that a macrostate with partially unfolded conformations may serve as the misfolded state of the TTR monomer. This misfolded state was extremely stable with a very large equilibrium probability of about 85.28%. With secondary structure analysis, we found the DAGH sheet in this state to be significantly destroyed. The CBEF sheet was relatively stable and sheet structure was maintained. However, the F-strand in this sheet was likely to move away from E-strand and reform a new β-sheet with the H-strand. This observation is consistent with experimental finding that F and H strands in the outer edge drive the misfolding of TTR. Finally, transition pathways from a near native state to this misfolded macrostate showed that the conformational transition can occur either through a native-like β-sheet intermediates or through partially unfolded intermediates, while the later appears to be the main pathway. As a whole, we identified a potential misfolded state of the TTR monomer and elucidated the misfolding pathway for its conformational transition. This work can provide a valuable theoretical basis for understanding of TTR aggregation and the pathogenesis of ATTR amyloidosis at the atomic level.

Computational Nanoscopy of Tight Junctions at the Blood-Brain Barrier Interface

The selectivity of the blood-brain barrier (BBB) is primarily maintained by tight junctions (TJs), which act as gatekeepers of the paracellular space by blocking blood-borne toxins, drugs, and pathogens from entering the brain. The BBB presents a significant challenge in designing neurotherapeutics, so a comprehensive understanding of the TJ architecture can aid in the design of novel therapeutics. Unraveling the intricacies of TJs with conventional experimental techniques alone is challenging, but recently developed computational tools can provide a valuable molecular-level understanding of TJ architecture. We employed the computational methods toolkit to investigate claudin-5, a highly expressed TJ protein at the BBB interface. Our approach started with the prediction of claudin-5 structure, evaluation of stable dimer conformations and nanoscale assemblies, followed by the impact of lipid environments, and posttranslational modifications on these claudin-5 assemblies. These led to the study of TJ pores and barriers and finally understanding of ion and small molecule transport through the TJs. Some of these in silico, molecular-level findings, will need to be corroborated by future experiments. The resulting understanding can be advantageous towards the eventual goal of drug delivery across the BBB. This review provides key insights gleaned from a series of state-of-the-art nanoscale simulations (or computational nanoscopy studies) performed on the TJ architecture.

Hybrid Atomistic and Coarse-Grained Model for Surfactants in Apolar Solvents

Here, we develop and verify the performance of a hybrid molecular modeling approach that combines coarse-grained apolar solvent and atomistic solute or polar solvent description, for example, for description of reverse micellar systems. The coarse-grained solvent model is directly applicable to organic solvents encompassing alkane, alkene, and fatty acid ester functional groups and connects directly to both standard united-atom GROMOS 53A6 and all-atom CHARMM27 force fields, as well as the atomistic detail water models compatible with these force fields. The different levels of description are coupled via explicit, unscaled electrostatics, and scaled mixing rules for dispersive interactions. The hybrid model is in near-quantitative agreement with fully atomistic simulations when combined with the CHARMM27 model but underestimates modestly surfactant aggregation when using GROMOS 53A6 united-atom description. The use of truncated electrostatics affords up to a 9-fold increase in computational speed without significant loss of accuracy. However, long-range electrostatic calculations and load imbalance at high core counts can significantly degrade the performance. We demonstrate the usability of the hybrid model by assessing the reverse micelle formation of a homologous series of nonionic glycerolipids via large-scale self-assembly simulations. The presented model is demonstrated here for accurate description of surfactant systems in apolar solvents, with and without also polar solvent (water) in the system. The formulation can be expected to describe well also other solute species or interfaces with an apolar solvent in an apolar environment.

Characterization of Lipid-Protein Interactions and Lipid-Mediated Modulation of Membrane Protein Function through Molecular Simulation

The cellular membrane constitutes one of the most fundamental compartments of a living cell, where key processes such as selective transport of material and exchange of information between the cell and its environment are mediated by proteins that are closely associated with the membrane. The heterogeneity of lipid composition of biological membranes and the effect of lipid molecules on the structure, dynamics, and function of membrane proteins are now widely recognized. Characterization of these functionally important lipid-protein interactions with experimental techniques is however still prohibitively challenging. Molecular dynamics (MD) simulations offer a powerful complementary approach with sufficient temporal and spatial resolutions to gain atomic-level structural information and energetics on lipid-protein interactions. In this review, we aim to provide a broad survey of MD simulations focusing on exploring lipid-protein interactions and characterizing lipid-modulated protein structure and dynamics that have been successful in providing novel insight into the mechanism of membrane protein function.

Conformation Dependence of Diphenylalanine Self-Assembly Structures and Dynamics: Insights from Hybrid-Resolution Simulations

The molecular design of peptide-assembled nanostructures relies on extensive knowledge pertaining to the relationship between conformational features of peptide constituents and their behavior regarding self-assembly, and characterizing the conformational details of peptides during their self-assembly is experimentally challenging. Here, we demonstrate that a hybrid-resolution modeling method can be employed to investigate the role that conformation plays during the assembly of terminally capped diphenylalanines (FF) through microsecond simulations of hundreds or thousands of peptides. Our simulations discovered tubular or vesicular nanostructures that were consistent with experimental observation while reproducing critical self-assembly concentration and secondary structure contents in the assemblies that were measured in our experiments. The atomic details provided by our method allowed us to uncover diverse FF conformations and conformation dependence of assembled nanostructures. We found that the assembled morphologies and the molecular packing of FFs in the observed assemblies are linked closely with side-chain angle and peptide bond orientation, respectively. Of various conformations accessible to soluble FFs, only a select few are compatible with the assembled morphologies in water. A conformation resembling a FF crystal, in particular, became predominant due to its ability to permit highly ordered and energetically favorable FF packing in aqueous assemblies. Strikingly, several conformations incompatible with the assemblies arose transiently as intermediates, facilitating key steps of the assembly process. The molecular rationale behind the role of these intermediate conformations were further explained. Collectively, the structural details reported here advance the understanding of the FF self-assembly mechanism, and our method shows promise for studying peptide-assembled nanostructures and their rational design.

A revisit of the conformational dynamics of SNARE protein rYkt6

N-ethylmaleimide-sensitive factor attachment protein receptor (SNARE) proteins are involved in the fusion of vesicles with their target membranes. R-SNARE protein Ykt6 is one of the most conserved SNARE in eukaryotes. The conformational state of Ykt6 is regulated by the lipidations at its C-terminal motif. Previous studies show that the binding of dodecylphosphocholine (DPC) can stabilize a closed conformation of rat Ykt6 (rYkt6) and mimic the farnesylated rYkt6. Despite this model, the detailed conformational dynamics of Ykt6 is still unclear. Here, we combined smFRET and MD simulation to demonstrate that the un-lipidated rYkt6 adopts five major conformational states. DPC binding shifts the conformational distribution toward the more closed states. At the same time, there remain considerable fractions of open and semi-open conformations in the presence of DPC. These newly revealed dynamic features of rYkt6 are consistent with its unique functional diversity in neuronal cells.

Coarse-grained simulations of conformational changes in the multidrug efflux transporter AcrB

The multidrug resistance (MDR) system actively pumps antibiotics out of cells causing serious health problems. During the pumping, AcrB (one of the key components of MDR) undergoes a series of large-scale and proton-motive conformational changes. Capturing the conformational changes through all-atom simulations is challenging. Here, we implement a hybrid coarse-grained force field to investigate the conformational changes of AcrB in the porter domain under different protonation states of Asp407/Asp408 in the trans-membrane domain. Our results show that protonation of Asp408 in monomer III (extrusion) stabilizes the asymmetric structure of AcrB; deprotonation of Asp408 induces clear opening of the entrance and closing of the exit leading to the transition from extrusion to access state. The structural changes in the porter domain of AcrB are strongly coupled with the proton translocation stoichiometry in the trans-membrane domain. Moreover, our simulations support the postulation that AcrB should adopt the symmetric resting state in a substrate-free situation.

Exploration of conformational changes in lactose permease upon sugar binding and proton transfer through coarse-grained simulations

Escherichia coli lactose permease (LacY) actively transports lactose and other galactosides across cell membranes through lactose/H⁺ symport process. Lactose/H⁺ symport is a highly complex process that involves sugar translocation, H⁺ transfer, and large-scale protein conformational changes. The complete picture of lactose/H⁺ symport is largely unclear due to the complexity and multiscale nature of the process. In this work, we develop the force field for sugar molecules compatible with PACE, a hybrid and coarse-grained force field that couples the united-atom protein models with the coarse-grained MARTINI water/lipid. After validation, we implement the new force field to investigate the binding of a β-d-galactopyranosyl-1-thio- β-d-galactopyranoside (TDG) molecule to a wild-type LacY. Results show that the local interactions between TDG and LacY at the binding pocket are consistent with the X-ray experiment. Transitions from inward-facing to outward-facing conformations upon TDG binding and protonation of Glu269 have been achieved from ∼5.5 µs simulations. Both the opening of the periplasmic side and closure of the cytoplasmic side of LacY are consistent with double electron-electron resonance and thiol cross-linking experiments. Our analysis suggests that the conformational changes of LacY are a cumulative consequence of interdomain H-bonds breaking at the periplasmic side, interdomain salt-bridge formation at the cytoplasmic side, and the TDG orientational changes during the transition.

Multiscale simulations for understanding the evolution and mechanism of hierarchical peptide self-assembly

Multiscale molecular simulations that combine and systematically link several hierarchies can provide insights into the evolution and dynamics of hierarchical peptide self-assembly from the molecular level to the mesoscale.

How Does Hyperphopsphorylation Promote Tau Aggregation and Modulate Filament Structure and Stability?

Tau proteins are hyperphosphorylated at common sites in their N- and C-terminal domains in at least three neurodegenerative diseases, Parkinson, dementia with Lewy bodies, and Alzheimer's, suggesting specific pathology but general mechanism. Full-length human tau filament comprises a rigid core and a two-layered fuzzy coat. Tau is categorized into two groups of isoforms, with either four repeats (R1-R4) or three repeats (R1, R3, and R4); their truncated constructs are respectively called K18 and K19. Using multiscale molecular dynamics simulations, we explored the conformational consequences of hyperhposphorylation on tau's repeats. Our lower conformational energy filament models suggest a rigid filament core with a radius of ∼30 to 40 Å and an outer layer with a thickness of ∼140 Å consisting of a double-layered polyelectrolyte. The presence of the phosphorylated terminal domains alters the relative stabilities in the K18 ensemble, thus shifting the populations of the full-length filaments. However, the structure with the straight repeats in the core region is still the most stable, similar to the truncated K18 peptide species without the N- and C-terminus. Our simulations across different scales of resolution consistently reveal that hyperphosphorylation of the two terminal domains decreases the attractive interactions among the N- and C-terminus and repeat domain. To date, the relationship on the conformational level between phosphorylation and aggregation has not been understood. Our results suggest that the exposure of the repeat domain upon hyperphosphorylation could enhance tau filament aggregation. Thus, we discovered that even though these neurodegenerative diseases vary and their associated tau filaments are phosphorylated to different extents, remarkably, the three pathologies appear to share a common tau aggregation mechanism.

Coarse-grained simulations of proton-dependent conformational changes in lactose permease

During lactose/H(+) symport, the Escherichia coli lactose permease (LacY) undergoes a series of global conformational transitions between inward-facing (open to cytoplasmic side) and outward-facing (open to periplasmic side) states. However, the exact local interactions and molecular mechanisms dictating those large-scale structural changes are not well understood. All-atom molecular dynamics simulations have been performed to investigate the molecular interactions involved in conformational transitions of LacY, but the simulations can only explore early or partial global structural changes because of the computational limits (< 100 ns). In this work, we implement a hybrid force field that couples the united-atom protein models with the coarse-grained MARTINI water/lipid, to investigate the proton-dependent dynamics and conformational changes of LacY. The effects of the protonation states on two key glutamate residues (Glu325 and Glu269) have been studied. Our results on the salt-bridge dynamics agreed with all-atom simulations at early short time period, validating our simulations. From our microsecond simulations, we were able to observe the complete transition from inward-facing to outward-facing conformations of LacY. Our results showed that all helices have participated during the global conformational transitions and helical movements of LacY. The inter-helical distances measured in our simulations were consistent with the double electron-electron resonance experiments at both cytoplasmic and periplasmic sides. Our simulations indicated that the deprotonation of Glu325 induced the opening of the periplasmics side and partial closure of the cytoplasmic side of LacY, while protonation of the Glu269 caused a stable cross-domain salt-bridge (Glu130-Arg344) and completely closed the cytoplasmic side. Proteins 2016; 84:1067-1074. © 2016 Wiley Periodicals, Inc.

Efficient preparation and analysis of membrane and membrane protein systems

Molecular dynamics (MD) simulations have become a highly important technique to consider lipid membrane systems, and quite often they provide considerable added value to laboratory experiments. Rapid development of both software and hardware has enabled the increase of time and size scales reachable by MD simulations to match those attainable by several accurate experimental techniques. However, until recently, the quality and maturity of software tools available for building membrane models for simulations as well as analyzing the results of these simulations have seriously lagged behind. Here, we discuss the recent developments of such tools from the end-users' point of view. In particular, we review the software that can be employed to build lipid bilayers and other related structures with or without embedded membrane proteins to be employed in MD simulations. Additionally, we provide a brief critical insight into force fields and MD packages commonly used for membrane and membrane protein simulations. Finally, we list analysis tools that can be used to study the properties of membrane and membrane protein systems. In all these points we comment on the respective compatibility of the covered tools. We also share our opinion on the current state of the available software. We briefly discuss the most commonly employed tools and platforms on which new software can be built. We conclude the review by providing a few ideas and guidelines on how the development of tools can be further boosted to catch up with the rapid pace at which the field of membrane simulation progresses. This includes improving the compatibility between software tools and promoting the openness of the codes on which these applications rely. This article is part of a Special Issue entitled: Biosimulations edited by Ilpo Vattulainen and Tomasz Róg.

Coarse-Grained Modeling of Nucleic Acids Using Anisotropic Gay-Berne and Electric Multipole Potentials

In this work, we attempt to apply a coarse-grained (CG) model, which is based on anisotropic Gay-Berne and electric multipole (EMP) potentials, to the modeling of nucleic acids. First, a comparison has been made between the CG and atomistic models (AMBER point-charge model) in the modeling of DNA and RNA hairpin structures. The CG results have demonstrated a good quality in maintaining the nucleic acid hairpin structures, in reproducing the dynamics of backbone atoms of nucleic acids, and in describing the hydrogen-bonding interactions between nucleic acid base pairs. Second, the CG and atomistic AMBER models yield comparable results in modeling double-stranded DNA and RNA molecules. It is encouraging that our CG model is capable of reproducing many elastic features of nucleic acid base pairs in terms of the distributions of the interbase pair step parameters (such as shift, slide, tilt, and twist) and the intrabase pair parameters (such as buckle, propeller, shear, and stretch). Finally, The GBEMP model has shown a promising ability to predict the melting temperatures of DNA duplexes with different lengths.

Nanobubbles, cavitation, shock waves and traumatic brain injury

Shock wave induced cavitation denaturates blood–brain barrier tight junction proteins; this may result in various neurological complications.

Fibril elongation by Aβ(17-42): kinetic network analysis of hybrid-resolution molecular dynamics simulations

A critical step of β-amyloid fibril formation is fibril elongation in which amyloid-β monomers undergo structural transitions to fibrillar structures upon their binding to fibril tips. The atomic detail of the structural transitions remains poorly understood. Computational characterization of the structural transitions is limited so far to short Aβ segments (5–10 aa) owing to the long time scale of Aβ fibril elongation. To overcome the computational time scale limit, we combined a hybrid-resolution model with umbrella sampling and replica exchange molecular dynamics and performed altogether ∼1.3 ms of molecular dynamics simulations of fibril elongation for Aβ_17–42. Kinetic network analysis of biased simulations resulted in a kinetic model that encompasses all Aβ segments essential for fibril formation. The model not only reproduces key properties of fibril elongation measured in experiments, including Aβ binding affinity, activation enthalpy of Aβ structural transitions and a large time scale gap (τ_lock/τ_dock = 10³–10⁴) between Aβ binding and its structural transitions, but also reveals detailed pathways involving structural transitions not seen before, namely, fibril formation both in hydrophobic regions L17-A21 and G37-A42 preceding fibril formation in hydrophilic region E22-A30. Moreover, the model identifies as important kinetic intermediates strand–loop–strand (SLS) structures of Aβ monomers, long suspected to be related to fibril elongation. The kinetic model suggests further that fibril elongation arises faster at the fibril tip with exposed L17-A21, rather than at the other tip, explaining thereby unidirectional fibril growth observed previously in experiments.

CHARMM-GUI PACE CG Builder for solution, micelle, and bilayer coarse-grained simulations

Coarse-grained (CG) and multiscale simulations are widely used to study large biological systems. However, preparing the simulation system is time-consuming when the system has multiple components, because each component must be arranged carefully as in protein/micelle or protein/bilayer systems. We have developed CHARMM-GUI PACE CG Builder for building solution, micelle, and bilayer systems using the PACE force field, a united-atom (UA) model for proteins, and the Martini CG force field for water, ions, and lipids. The robustness of PACE CG Builder is validated by simulations of various systems in solution (α3D, fibronectin, and lysozyme), micelles (Pf1, DAP12-NKG2C, OmpA, and DHPC-only micelle), and bilayers (GpA, OmpA, VDAC, MscL, OmpF, and lipid-only bilayers for six lipids). The micelle’s radius of gyration, the bilayer thickness, and the per-lipid area in bilayers are comparable to the values from previous all-atom and CG simulations. Most tested proteins have root-mean squared deviations of less than 3 Å. We expect PACE CG Builder to be a useful tool for modeling/refining large, complex biological systems at the mixed UA/CG level.

An Anisotropic Coarse-Grained Model for Proteins Based On Gay-Berne and Electric Multipole Potentials

Gay–Berne anisotropic potential has been widely used to evaluate the nonbonded interactions between coarse-grained particles being described as elliptical rigid bodies. In this paper, we are presenting a coarse-grained model for twenty kinds of amino acids and proteins, based on the anisotropic Gay–Berne and point electric multipole (EMP) potentials. We demonstrate that the anisotropic coarse-grained model, namely GBEMP model, is able to reproduce many key features observed from experimental protein structures (Dunbrack Library), as well as from atomistic force field simulations (using AMOEBA, AMBER, and CHARMM force fields), while saving the computational cost by a factor of about 10–200 depending on specific cases and atomistic models. More importantly, unlike other coarse-grained approaches, our framework is based on the fundamental intermolecular forces with explicit treatment of electrostatic and repulsion-dispersion forces. As a result, the coarse-grained protein model presented an accurate description of nonbonded interactions (particularly electrostatic component) between hetero/homodimers (such as peptide–peptide, peptide–water). In addition, the encouraging performance of the model was reflected by the excellent correlation between GBEMP and AMOEBA models in the calculations of the dipole moment of peptides. In brief, the GBEMP model given here is general and transferable, suitable for simulating complex biomolecular systems.

The intrinsic conformational features of amino acids from a protein coil library and their applications in force field development

The local conformational (φ, ψ, χ) preferences of amino acid residues remain an active research area, which are important for the development of protein force fields. In this perspective article, we first summarize spectroscopic studies of alanine-based short peptides in aqueous solution. While most studies indicate a preference for the P(II) conformation in the unfolded state over α and β conformations, significant variations are also observed. A statistical analysis from various coil libraries of high-resolution protein structures is then summarized, which gives a more coherent view of the local conformational features. The φ, ψ, χ distributions of the 20 amino acids have been obtained from a protein coil library, considering both backbone and side-chain conformational preferences. The intrinsic side-chain χ(1) rotamer preference and χ(1)-dependent Ramachandran plot can be generally understood by combining the interaction of the side-chain Cγ/Oγ atom with two neighboring backbone peptide groups. Current all-atom force fields such as AMBER ff99sb-ILDN, ff03 and OPLS-AA/L do not reproduce these distributions well. A method has been developed by combining the φ, ψ plot of alanine with the influence of side-chain χ(1) rotamers to derive the local conformational features of various amino acids. It has been further applied to improve the OPLS-AA force field. The modified force field (OPLS-AA/C) reproduces experimental (3)J coupling constants for various short peptides quite well. It also better reproduces the temperature-dependence of the helix-coil transition for alanine-based peptides. The new force field can fold a series of peptides and proteins with various secondary structures to their experimental structures. MD simulations of several globular proteins using the improved force field give significantly less deviation (RMSD) to experimental structures. The results indicate that the local conformational features from coil libraries are valuable for the development of balanced protein force fields.

Characterization of folding mechanisms of Trp-cage and WW-domain by network analysis of simulations with a hybrid-resolution model

In this study, we apply a hybrid-resolution model, namely, PACE, to characterize the free energy surfaces (FESs) of Trp-cage and a WW-domain variant along with the respective folding mechanisms. Unbiased, independent simulations with PACE are found to achieve together multiple folding and unfolding events for both proteins, allowing us to perform network analysis of the FESs to identify folding pathways. PACE reproduces for both proteins expected complexity hidden in the folding FESs, in particular metastable non-native intermediates. Pathway analysis shows that some of these intermediates are, actually, on-pathway folding intermediates and that intermediates kinetically closest to the native states can be either critical on-pathway or off-pathway intermediates, depending on the protein. Apart from general insights into folding, specific folding mechanisms of the proteins are resolved. We find that Trp-cage folds via a dominant pathway in which hydrophobic collapse occurs before the N-terminal helix forms; full incorporation of Trp6 into the hydrophobic core takes place as the last step of folding, which, however, may not be the rate-limiting step. For the WW-domain variant studied, we observe two main folding pathways with opposite orders of formation of the two hairpins involved in the structure; for either pathway, formation of hairpin 1 is more likely to be the rate-limiting step. Altogether, our results suggest that PACE combined with network analysis is a computationally efficient and valuable tool for the study of protein folding.

PRIMO: A Transferable Coarse-grained Force Field for Proteins

We describe here the PRIMO (PRotein Intermediate Model) force field, a physics-based fully transferable additive coarse-grained potential energy function that is compatible with an all-atom force field for multi-scale simulations. The energy function consists of standard molecular dynamics energy terms plus a hydrogen-bonding potential term and is mainly parameterized based on the CHARMM22/CMAP force field in a bottom-up fashion. The solvent is treated implicitly via the generalized Born model. The bonded interactions are either harmonic or distance-based spline interpolated potentials. These potentials are defined on the basis of all-atom molecular dynamics (MD) simulations of dipeptides with the CHARMM22/CMAP force field. The non-bonded parameters are tuned by matching conformational free energies of diverse set of conformations with that of CHARMM all-atom results. PRIMO is designed to provide a correct description of conformational distribution of the backbone (ϕ/ψ) and side chains (χ1) for all amino acids with a CMAP correction term. The CMAP potential in PRIMO is optimized based on the new CHARMM C36 CMAP. The resulting optimized force field has been applied in MD simulations of several proteins of 36-155 amino acids and shown that the root-mean-squared-deviation of the average structure from the corresponding crystallographic structure varies between 1.80 and 4.03 Å. PRIMO is shown to fold several small peptides to their native-like structures from extended conformations. These results suggest the applicability of the PRIMO force field in the study of protein structures in aqueous solution, structure predictions as well as ab initio folding of small peptides.

Mixing MARTINI: electrostatic coupling in hybrid atomistic-coarse-grained biomolecular simulations

Hybrid molecular dynamics simulations of atomistic (AA) solutes embedded in coarse-grained (CG) environment can substantially reduce the computational cost with respect to fully atomistic simulations. However, interfacing both levels of resolution is a major challenge that includes a balanced description of the relevant interactions. This is especially the case for polar solvents such as water, which screen the electrostatic interactions and thus require explicit electrostatic coupling between AA and CG subsystems. Here, we present and critically test computationally efficient hybrid AA/CG models. We combined the Gromos atomistic force field with the MARTINI coarse-grained force field. To enact electrostatic coupling, two recently developed CG water models with explicit electrostatic interactions were used: the polarizable MARTINI water model and the BMW model. The hybrid model was found to be sensitive to the strength of the AA-CG electrostatic coupling, which was adjusted through the relative dielectric permittivity εr(AA-CG). Potentials of mean force (PMFs) between pairs of amino acid side chain analogues in water and partitioning free enthalpies of uncharged amino acid side chain analogues between apolar solvent and water show significant differences between the hybrid simulations and the fully AA or CG simulations, in particular for charged and polar molecules. For apolar molecules, the results obtained with the hybrid AA/CG models are in better agreement with the fully atomistic results. The structures of atomistic ubiquitin solvated in CG water and of a single atomistic transmembrane α-helix and the transmembrane portion of an atomistic mechanosensitive channel in CG lipid bilayers were largely maintained during 50-100 ns of AA/CG simulations, partly due to an overstabilization of intramolecular interactions. This work highlights some key challenges on the way toward hybrid AA/CG models that are both computationally efficient and sufficiently accurate for biomolecular simulations.

Further optimization of a hybrid united-atom and coarse-grained force field for folding simulations: Improved backbone hydration and interactions between charged side chains

PACE, a hybrid force field which couples united-atom protein models with coarse-grained (CG) solvent, has been further optimized, aiming to improve itse ciency for folding simulations. Backbone hydration parameters have been re-optimized based on hydration free energies of polyalanyl peptides through atomistic simulations. Also, atomistic partial charges from all-atom force fields were combined with PACE in order to provide a more realistic description of interactions between charged groups. Using replica exchange molecular dynamics (REMD), ab initio folding using the new PACE has been achieved for seven small proteins (16 - 23 residues) with different structural motifs. Experimental data about folded states, such as their stability at room temperature, melting point and NMR NOE constraints, were also well reproduced. Moreover, a systematic comparison of folding kinetics at room temperature has been made with experiments, through standard MD simulations, showing that the new PACE may speed up the actual folding kinetics 5-10 times. Together with the computational speedup benefited from coarse-graining, the force field provides opportunities to study folding mechanisms. In particular, we used the new PACE to fold a 73-residue protein, 3D, in multiple 10 - 30 μs simulations, to its native states (C(α) RMSD ~ 0.34 nm). Our results suggest the potential applicability of the new PACE for the study of folding and dynamics of proteins.

A generic force field for protein coarse-grained molecular dynamics simulation

Coarse-grained (CG) force fields have become promising tools for studies of protein behavior, but the balance of speed and accuracy is still a challenge in the research of protein coarse graining methodology. In this work, 20 CG beads have been designed based on the structures of amino acid residues, with which an amino acid can be represented by one or two beads, and a CG solvent model with five water molecules was adopted to ensure the consistence with the protein CG beads. The internal interactions in protein were classified according to the types of the interacting CG beads, and adequate potential functions were chosen and systematically parameterized to fit the energy distributions. The proposed CG force field has been tested on eight proteins, and each protein was simulated for 1000 ns. Even without any extra structure knowledge of the simulated proteins, the Cα root mean square deviations (RMSDs) with respect to their experimental structures are close to those of relatively short time all atom molecular dynamics simulations. However, our coarse grained force field will require further refinement to improve agreement with and persistence of native-like structures. In addition, the root mean square fluctuations (RMSFs) relative to the average structures derived from the simulations show that the conformational fluctuations of the proteins can be sampled.