Enhanced Lipid Diffusion and Mixing in Accelerated Molecular Dynamics

Improved Highly Mobile Membrane Mimetic Model for Investigating Protein-Cholesterol Interactions

Cholesterol (CHL) plays an integral role in modulating the function and activity of various mammalian membrane proteins. Due to the slow dynamics of lipids, conventional computational studies of protein-CHL interactions rely on either long-time scale atomistic simulations or coarse-grained approximations to sample the process. A highly mobile membrane mimetic (HMMM) has been developed to enhance lipid diffusion and thus used to facilitate the investigation of lipid interactions with peripheral membrane proteins and, with customized in silico solvents to replace phospholipid tails, with integral membrane proteins. Here, we report an updated HMMM model that is able to include CHL, a nonphospholipid component of the membrane, henceforth called HMMM-CHL. To this end, we had to optimize the effect of the customized solvents on CHL behavior in the membrane. Furthermore, the new solvent is compatible with simulations using force-based switching protocols. In the HMMM-CHL, both improved CHL dynamics and accelerated lipid diffusion are integrated. To test the updated model, we have applied it to the characterization of protein-CHL interactions in two membrane protein systems, the human β2-adrenergic receptor (β2AR) and the mitochondrial voltage-dependent anion channel 1 (VDAC-1). Our HMMM-CHL simulations successfully identified CHL binding sites and captured detailed CHL interactions in excellent consistency with experimental data as well as other simulation results, indicating the utility of the improved model in applications where an enhanced sampling of protein-CHL interactions is desired.

Investigation of nano- and microdomains formed by ceramide 1 phosphate in lipid bilayers

Biological membranes are renowned for their intricate complexity, with the formation of membrane domains being pivotal to the successful execution of numerous cellular processes. However, due to their nanoscale characteristics, these domains are often understudied, as the experimental techniques required for quantitative investigation present significant challenges. In this study we employ spot-variation z-scan fluorescence correlation spectroscopy (svzFCS) tailored for artificial lipid vesicles of varying composition and combine this approach with high-resolution imaging. This method has been harnessed to examine the lipid-segregation behavior of distinct types of ceramide-1-phosphate (C1P), a crucial class of signaling molecules, within these membranes. Moreover, we provide a quantitative portrayal of the lipid membranes studied and the domains induced by C1P at both nano and microscales. Given the lack of definitive conclusions from the experimental data obtained, it was supplemented with comprehensive in silico studies-including the analysis of diffusion coefficient via molecular dynamics and domain populations via Monte Carlo simulations. This approach enhanced our insight into the dynamic behavior of these molecules within model lipid membranes, confirming that nano- and microdomains can co-exist in lipid vesicles.

Sigmoid Accelerated Molecular Dynamics: An Efficient Enhanced Sampling Method for Biosystems

Gaussian accelerated molecular dynamics (GaMD) is recognized as a popular enhanced sampling method for tackling long-standing challenges in biomolecular simulations. Inspired by GaMD, Sigmoid accelerated molecular dynamics (SaMD) is proposed in this work by adding a Sigmoid boost potential to improve the balance between the highest acceleration and accurate reweighting. Compared with GaMD, SaMD extends the accessible time scale and improves the computational efficiency as tested in three tasks. In the alanine dipeptide task, SaMD can produce the free energy landscape with better accuracy and efficiency. In the chignolin folding task, the estimated Gibbs free energy difference can converge to the experimental value ∼30% faster. In the protein-ligand binding task, the bound conformations are closer to the crystal structure with a minimal ligand root-mean-square deviation of 1.7 Å. The binding of the ligand XK263 to the HIV protease is reproduced by SaMD in ∼60% less simulation time.

CHARMM-GUI Enhanced Sampler for various collective variables and enhanced sampling methods

Enhanced sampling methodologies modifying underlying Hamiltonians can be used for the systems with a rugged potential energy surface that makes it hard to observe convergence using conventional unbiased molecular dynamics (MD) simulations. We present CHARMM-GUI Enhanced Sampler, a web-based tool to prepare various enhanced sampling simulations inputs with user-selected collective variables (CVs). Enhanced Sampler provides inputs for the following nine methods: accelerated MD, Gaussian accelerated MD, conformational flooding, metadynamics, adaptive biasing force, steered MD, temperature replica exchange MD, replica exchange solute tempering 2, and replica exchange umbrella sampling for the method-implemented MD packages including AMBER, CHARMM, GENESIS, GROMACS, NAMD, and OpenMM. Users only need to select a group of atoms via intuitive web-implementation in order to define commonly used nine CVs of interest: center of mass based distance, angle, dihedral, root-mean-square-distance, radius of gyration, distance projected on axis, two types of angles projected on axis, and coordination numbers. The enhanced sampling methods are tested with several biological systems to illustrate their efficiency over conventional MD. Enhanced Sampler with carefully optimized system-dependent parameters will help users to get meaningful results from their enhanced sampling simulations.

Binding Analysis Using Accelerated Molecular Dynamics Simulations and Future Perspectives

Biomolecular recognition such as binding of small molecules, nucleic acids, peptides and proteins to their target receptors plays key roles in cellular function and has been targeted for therapeutic drug design. Molecular dynamics (MD) is a computational approach to analyze these binding processes at an atomistic level, which provides valuable understandings of the mechanisms of biomolecular recognition. However, the rather slow biomolecular binding events often present challenges for conventional MD (cMD), due to limited simulation timescales (typically over hundreds of nanoseconds to tens of microseconds). In this regard, enhanced sampling methods, particularly accelerated MD (aMD), have proven useful to bridge the gap and enable all-atom simulations of biomolecular binding events. Here, we will review the recent method developments of Gaussian aMD (GaMD), ligand GaMD (LiGaMD) and peptide GaMD (Pep-GaMD), which have greatly expanded our capabilities to simulate biomolecular binding processes. Spontaneous binding of various biomolecules to their receptors has been successfully simulated by GaMD. Microsecond LiGaMD and Pep-GaMD simulations have captured repetitive binding and dissociation of small-molecule ligands and highly flexible peptides, and thus enabled ligand/peptide binding thermodynamics and kinetics calculations. We will also present relevant application studies in simulations of important drug targets and future perspectives for rational computer-aided drug design.

Anti-TNF Alpha Antibody Humira with pH-dependent Binding Characteristics: A constant-pH Molecular Dynamics, Gaussian Accelerated Molecular Dynamics, and In Vitro Study

Humira is a monoclonal antibody that binds to TNF alpha, inactivates TNF alpha receptors, and inhibits inflammation. Neonatal Fc receptors can mediate the transcytosis of Humira-TNF alpha complex structures and process them toward degradation pathways, which reduces the therapeutic effect of Humira. Allowing the Humira-TNF alpha complex structures to dissociate to Humira and soluble TNF alpha in the early endosome to enable Humira recycling is crucial. We used the cytoplasmic pH (7.4), the early endosomal pH (6.0), and pKa of histidine side chains (6.0-6.4) to mutate the residues of complementarity-determining regions with histidine. Our engineered Humira (W1-Humira) can bind to TNF alpha in plasma at neutral pH and dissociate from the TNF alpha in the endosome at acidic pH. We used the constant-pH molecular dynamics, Gaussian accelerated molecular dynamics, two-dimensional potential mean force profiles, and in vitro methods to investigate the characteristics of W1-Humira. Our results revealed that the proposed Humira can bind TNF alpha with pH-dependent affinity in vitro. The W1-Humira was weaker than wild-type Humira at neutral pH in vitro, and our prediction results were close to the in vitro results. Furthermore, our approach displayed a high accuracy in antibody pH-dependent binding characteristics prediction, which may facilitate antibody drug design. Advancements in computational methods and computing power may further aid in addressing the challenges in antibody drug design.

CHARMM-GUI Supports Hydrogen Mass Repartitioning and Different Protonation States of Phosphates in Lipopolysaccharides

Hydrogen mass repartitioning (HMR) that permits time steps of all-atom molecular dynamics simulation up to 4 fs by increasing the mass of hydrogen atoms has been used in protein and phospholipid bilayers simulations to improve conformational sampling. Molecular simulation input generation via CHARMM-GUI now supports HMR for diverse simulation programs. In addition, considering ambiguous pH at the bacterial outer membrane surface, different protonation states, either -2e or -1e, of phosphate groups in lipopolysaccharides (LPS) are also supported in CHARMM-GUI LPS Modeler. To examine the robustness of HMR and the influence of protonation states of phosphate groups on LPS bilayer properties, eight different LPS-type all-atom systems with two phosphate protonation states are modeled and simulated utilizing both OpenMM 2-fs (standard) and 4-fs (HMR) schemes. Consistency in the conformational space sampled by standard and HMR simulations shows the reliability of HMR even in LPS, one of the most complex biomolecules. For systems with different protonation states, similar conformations are sampled with a PO41- or PO42- group, but different phosphate protonation states make slight impacts on lipid packing and conformational properties of LPS acyl chains. Systems with PO41- have a slightly smaller area per lipid and thus slightly more ordered lipid A acyl chains compared to those with PO42-, due to more electrostatic repulsion between PO42- even with neutralizing Ca2+ ions. HMR and different protonation states of phosphates of LPS available in CHARMM-GUI are expected to be useful for further investigations of biological systems of diverse origin.

The intrinsically disordered N-terminus of the voltage-dependent anion channel

The voltage-dependent anion channel (VDAC) is a critical β-barrel membrane protein of the mitochondrial outer membrane, which regulates the transport of ions and ATP between mitochondria and the cytoplasm. In addition, VDAC plays a central role in the control of apoptosis and is therefore of great interest in both cancer and neurodegenerative diseases. Although not fully understood, it is presumed that the gating mechanism of VDAC is governed by its N-terminal region which, in the open state of the channel, exhibits an α-helical structure positioned midway inside the pore and strongly interacting with the β-barrel wall. In the present work, we performed molecular simulations with a recently developed force field for disordered systems to shed new light on known experimental results, showing that the N-terminus of VDAC is an intrinsically disordered region (IDR). First, simulation of the N-terminal segment as a free peptide highlighted its disordered nature and the importance of using an IDR-specific force field to properly sample its conformational landscape. Secondly, accelerated dynamics simulation of a double cysteine VDAC mutant under applied voltage revealed metastable low conducting states of the channel representative of closed states observed experimentally. Related structures were characterized by partial unfolding and rearrangement of the N-terminal tail, that led to steric hindrance of the pore. Our results indicate that the disordered properties of the N-terminus are crucial to properly account for the gating mechanism of VDAC.

The voltage-dependent anion channel (VDAC) is a membrane protein playing a pivotal role in the transport of ions or ATP across the mitochondrial outer membrane as well as in the induction of apoptosis. At high enough membrane potential, VDAC is known to transition from an open state to multiple closed states, reducing the flow of ions through the channel and blocking the passage of large metabolites. While the structure of the open state was resolved more than a decade ago, a molecular description of the gating mechanism of the channel is still missing. Here we show that the N-terminus of VDAC is an intrinsically disordered region and that such a property has a profound impact on its dynamics either as a free peptide or as part of the channel. By taking disordered properties of the N-terminus into account, we managed to generate long-lived closed conformations of the channel at experimental values of the membrane potential. Our results provide new insights into the molecular mechanism driving the gating of VDAC.

Scalable molecular dynamics on CPU and GPU architectures with NAMD

NAMDis a molecular dynamics program designed for high-performance simulations of very large biological objects on CPU- and GPU-based architectures. NAMD offers scalable performance on petascale parallel supercomputers consisting of hundreds of thousands of cores, as well as on inexpensive commodity clusters commonly found in academic environments. It is written in C++ and leans on Charm++ parallel objects for optimal performance on low-latency architectures. NAMD is a versatile, multipurpose code that gathers state-of-the-art algorithms to carry out simulations in apt thermodynamic ensembles, using the widely popular CHARMM, AMBER, OPLS, and GROMOS biomolecular force fields. Here, we review the main features of NAMD that allow both equilibrium and enhanced-sampling molecular dynamics simulations with numerical efficiency. We describe the underlying concepts utilized by NAMD and their implementation, most notably for handling long-range electrostatics; controlling the temperature, pressure, and pH; applying external potentials on tailored grids; leveraging massively parallel resources in multiple-copy simulations; and hybrid quantum-mechanical/molecular-mechanical descriptions. We detail the variety of options offered by NAMD for enhanced-sampling simulations aimed at determining free-energy differences of either alchemical or geometrical transformations and outline their applicability to specific problems. Last, we discuss the roadmap for the development of NAMD and our current efforts toward achieving optimal performance on GPU-based architectures, for pushing back the limitations that have prevented biologically realistic billion-atom objects to be fruitfully simulated, and for making large-scale simulations less expensive and easier to set up, run, and analyze. NAMD is distributed free of charge with its source code at www.ks.uiuc.edu.

In silico identification of new inhibitors for βeta-2-glycoprotein I as a major antigen in antiphospholipid antibody syndrome

Beta 2 glycoprotein I (β2GPI) is a major antigen for autoantibodies present in antiphospholipid antibody syndrome (APS). β2GPI is a single polypeptide with five repeated domains and different conformations. The activated J-shaped conformation of β2GPI binds to negatively charged phospholipids in the membrane via the fifth domain and causes blood clotting reactions. We applied a drug repurposing strategy using virtual screening and molecular dynamics to find the best FDA drugs against the fifth domain of β2GPI. In the first phase, FDA drugs that had the most favorable ΔG with the fifth domain of β2GPI were selected by virtual screening. Among these drugs that had the most favorable ΔG, Vorapaxar and Antrafenine were selected for molecular dynamics (MD) simulation studies. MD simulation was performed to evaluate the stability of Vorapaxar and Antrafenine complexes and the effect of the two drugs on protein conformation. Also, MD simulation was done to investigate the effect of Antrafenine and Vorapaxar on the binding of β2GPI to the platelet model membrane. According to the results, Vorapaxar and Antrafenine were bound to the protein with the favorable binding energy (Vorapaxar and Antrafenine binding energies are - 49.641 and - 38.803 kcal/mol, respectively). In this study, it was shown that unlike protein alone and protein in the Antrafenine complex, the protein in the Vorapaxar complex was completely separated from the model membrane after 350 ns. Moreover, Vorapaxar led to more changes in the activated J-shape of β2GPI. Thus, Vorapaxar can be a suitable candidate for further investigations on the treatment of APS.

Computational modeling of cyclic peptide inhibitor-MDM2/MDMX binding through global docking and Gaussian accelerated molecular dynamics simulations

MDM2 and MDMX are potential targets for p53-dependent cancer therapy. Peptides are key in cellular immunology and oncology, and cyclic peptides generally have higher half-life than their linear counterparts. However, prediction of cyclic peptide-protein binding is challenging with normal molecular simulation approaches because of high peptide flexibility. Here, we used global peptide docking, normal molecular dynamics, Gaussian accelerated molecular dynamics (GaMD), two-dimensional (2D) potential of mean force (PMF) profiles, and solvated interaction energy (SIE) techniques to investigate the interactions of MDM2/MDMX with three N-to-C-terminal cyclic peptide-based inhibitors. We determined the possible cyclic peptide-MDM2/MDMX complex structures via 2D PMF profiles and SIE calculations. Our findings increase the accuracy of peptide-protein structural prediction, which may facilitate cyclic peptide drug design. Advancements in the computational methods and computing power may further aid in addressing the challenges in cyclic peptide drug design. Communicated by Ramaswamy H. Sarma.

Generalized Form for Finite-Size Corrections in Mutual Diffusion Coefficients of Multicomponent Mixtures Obtained from Equilibrium Molecular Dynamics Simulation

The system-size dependence of computed mutual diffusion coefficients of multicomponent mixtures is investigated, and a generalized correction term is derived. The generalized finite-size correction term was validated for the ternary molecular mixture chloroform/acetone/methanol as well as 28 ternary LJ systems. It is shown that only the diagonal elements of the Fick matrix show system-size dependency. The finite-size effects of these elements can be corrected by adding the term derived by Yeh and Hummer (J. Phys. Chem. B2004, 108, 15873–15879). By performing an eigenvalue analysis of the finite-size effects of the matrix of Fick diffusivities we show that the eigenvector matrix of Fick diffusivities does not depend on the size of the simulation box. Only eigenvalues, which describe the speed of diffusion, depend on the size of the system. An analytic relation for finite-size effects of the matrix of Maxwell–Stefan diffusivities was developed. All Maxwell–Stefan diffusivities depend on the system size, and the required correction depends on the matrix of thermodynamic factors.

Location, Orientation and Aggregation of Bardoxolone-ME, CDDO-ME, in a Complex Phospholipid Bilayer Membrane

Bardoxolone methyl (CDDO-Me), a synthetic derivative of the naturally occurring triterpenoid oleanolic acid, displays strong antioxidant, anticancer and anti-inflammatory activities, according to different bibliographical sources. However, the understanding of its molecular mechanism is missing. Furthermore, CDDO-Me has displayed a significant cytotoxicity against various types of cancer cells. CDDO-Me has a noticeable hydrophobic character and several of its effects could be attributed to its ability to be incorporated inside the biological membrane and therefore modify its structure and specifically interact with its components. In this study, we have used full-atom molecular dynamics to determine the location, orientation and interactions of CDDO-Me in phospholipid model membranes. Our results support the location of CDDO-Me in the middle of the membrane, it specifically orients so that the cyano group lean towards the phospholipid interface and it specifically interacts with particular phospholipids. Significantly, in the membrane the CDDO-Me molecules specifically interact with POPE and POPS. Moreover, CDDO-Me does not aggregates in the membrane but it forms a complex conglomerate in solution. The formation of a complex aggregate in solution might hamper its biological activity and therefore it should be taken into account when intended to be used in clinical assays. This work should aid in the development of these molecules opening new avenues for future therapeutic developments.

Accelerating Membrane Simulations with Hydrogen Mass Repartitioning

The time step of atomistic molecular dynamics (MD) simulations is determined by the fastest motions in the system and is typically limited to 2 fs. An increasingly popular approach is to increase the mass of the hydrogen atoms to ∼3 amu and decrease the mass of the parent atom by an equivalent amount. This approach, known as hydrogen-mass repartitioning (HMR), permits time steps up to 4 fs with reasonable simulation stability. While HMR has been applied in many published studies to date, it has not been extensively tested for membrane-containing systems. Here, we compare the results of simulations of a variety of membranes and membrane-protein systems run using a 2 fs time step and a 4 fs time step with HMR. For pure membrane systems, we find almost no difference in structural properties, such as area-per-lipid, electron density profiles, and order parameters, although there are differences in kinetic properties such as the diffusion constant. Conductance through a porin in an applied field, partitioning of a small peptide, hydrogen-bond dynamics, and membrane mixing show very little dependence on HMR and the time step. We also tested a 9 Å cutoff as compared to the standard CHARMM cutoff of 12 Å, finding significant deviations in many properties tested. We conclude that HMR is a valid approach for membrane systems, but a 9 Å cutoff is not.

Gaussian accelerated molecular dynamics for elucidation of drug pathways

INTRODUCTION

Understanding pathways and mechanisms of drug binding to receptors is important for rational drug design. Remarkable advances in supercomputing and methodological developments have opened a new era for application of computer simulations in predicting drug-receptor interactions at an atomistic level. Gaussian accelerated molecular dynamics (GaMD) is a computational enhanced sampling technique that works by adding a harmonic boost potential to reduce energy barriers. GaMD enables free energy calculations without the requirement of predefined collective variables. GaMD has proven useful in biomolecular simulations, in particular, the prediction of drug-receptor interactions. Areas covered: Herein, the authors review recent GaMD simulation studies that elucidated pathways of drug binding to proteins including the G-protein-coupled receptors and HIV protease. Expert opinion: GaMD is advantageous for enhanced simulations of, amongst many biological processes, drug binding to target receptors. Compared with conventional molecular dynamics, GaMD speeds up biomolecular simulations by orders of magnitude. GaMD enables routine drug binding simulations using personal computers with GPUs or common computing clusters. GaMD and, more broadly, enhanced sampling simulations are expected to dramatically increase our capabilities to determine the mechanisms of drug binding to a wide range of receptors in the near future. This will greatly facilitate computer-aided drug design.

A Computational Modeling Approach Predicts Interaction of the Antifungal Protein AFP from Aspergillus giganteus with Fungal Membranes via Its γ-Core Motif

Fungal pathogens kill more people per year globally than malaria or tuberculosis and threaten international food security through crop destruction. New sophisticated strategies to inhibit fungal growth are thus urgently needed. Among the potential candidate molecules that strongly inhibit fungal spore germination are small cationic, cysteine-stabilized proteins of the AFP family secreted by a group of filamentous Ascomycetes. Its founding member, AFP from Aspergillus giganteus, is of particular interest since it selectively inhibits the growth of filamentous fungi without affecting the viability of mammalian, plant, or bacterial cells. AFPs are also characterized by their high efficacy and stability. Thus, AFP can serve as a lead compound for the development of novel antifungals. Notably, all members of the AFP family comprise a γ-core motif which is conserved in all antimicrobial proteins from pro- and eukaryotes and known to interfere with the integrity of cytoplasmic plasma membranes. In this study, we used classical molecular dynamics simulations combined with wet laboratory experiments and nuclear magnetic resonance (NMR) spectroscopy to characterize the structure and dynamical behavior of AFP isomers in solution and their interaction with fungal model membranes. We demonstrate that the γ-core motif of structurally conserved AFP is the key for its membrane interaction, thus verifying for the first time that the conserved γ-core motif of antimicrobial proteins is directly involved in protein-membrane interactions. Furthermore, molecular dynamic simulations suggested that AFP does not destroy the fungal membrane by pore formation but covers its surface in a well-defined manner, using a multistep mechanism to destroy the membranes integrity.IMPORTANCE Fungal pathogens pose a serious danger to human welfare since they kill more people per year than malaria or tuberculosis and are responsible for crop losses worldwide. The treatment of fungal infections is becoming more complicated as fungi develop resistances against commonly used fungicides. Therefore, discovery and development of novel antifungal agents are of utmost importance.

A molecular dynamics simulation study decodes the Zika virus NS5 methyltransferase bound to SAH and RNA analogue

Since 2015, widespread Zika virus outbreaks in Central and South America have caused increases in microcephaly cases, and this acute problem requires urgent attention. We employed molecular dynamics and Gaussian accelerated molecular dynamics techniques to investigate the structure of Zika NS5 protein with S-adenosyl-L-homocysteine (SAH) and an RNA analogue, namely 7-methylguanosine 5'-triphosphate (m7GTP). For the binding motif of Zika virus NS5 protein and SAH, we suggest that the four Zika NS5 substructures (residue orders: 101-112, 54-86, 127-136 and 146-161) and the residues (Ser56, Gly81, Arg84, Trp87, Thr104, Gly106, Gly107, His110, Asp146, Ile147, and Gly148) might be responsible for the selectivity of the new Zika virus drugs. For the binding motif of Zika NS5 protein and m7GTP, we suggest that the three Zika NS5 substructures (residue orders: 11-31, 146-161 and 207-218) and the residues (Asn17, Phe24, Lys28, Lys29, Ser150, Arg213, and Ser215) might be responsible for the selectivity of the new Zika virus drugs.

Ordering of lipid membranes altered by boron nitride nanosheets

Boron nitride nanosheets are novel promising nanomaterials with a lower cytotoxicity than graphene making them a better candidate for biomedical applications.

Gaussian Accelerated Molecular Dynamics: Theory, Implementation, and Applications

A novel Gaussian Accelerated Molecular Dynamics (GaMD) method has been developed for simultaneous unconstrained enhanced sampling and free energy calculation of biomolecules. Without the need to set predefined reaction coordinates, GaMD enables unconstrained enhanced sampling of the biomolecules. Furthermore, by constructing a boost potential that follows a Gaussian distribution, accurate reweighting of GaMD simulations is achieved via cumulant expansion to the second order. The free energy profiles obtained from GaMD simulations allow us to identify distinct low energy states of the biomolecules and characterize biomolecular structural dynamics quantitatively. In this chapter, we present the theory of GaMD, its implementation in the widely used molecular dynamics software packages (AMBER and NAMD), and applications to the alanine dipeptide biomolecular model system, protein folding, biomolecular large-scale conformational transitions and biomolecular recognition.

Understanding the molecular basis of agonist/antagonist mechanism of human mu opioid receptor through gaussian accelerated molecular dynamics method

The most powerful analgesic and addictive properties of opiate alkaloids are mediated by the μ opioid receptor (MOR). The MOR has been extensively investigated as a drug target in the twentieth century, with numerous compounds of varying efficacy being identified. We employed molecular dynamics and Gaussian accelerated molecular dynamics techniques to identify the binding mechanisms of MORs to BU72 (agonist) and β-funaltrexamine (antagonist). Our approach theoretically suggests that the 34 residues (Lys209–Phe221 and Ile301–Cys321) of the MORs were the key regions enabling the two compounds to bind to the active site of the MORs. When the MORs were in the holo form, the key region was in the open conformation. When the MORs were in the apo form, the key region was in the closed conformation. The key region might be responsible for the selectivity of new MOR agonists and antagonists.

Non-active site mutations disturb the loop dynamics, dimerization, viral budding and egress of VP40 of the Ebola virus

The first account of the dynamic features of the loop region of VP40 of the Ebola virus (EboV) using accelerated molecular dynamics (aMD) simulations is reported herein. Due to its major role in the Ebola life cycle, VP40 is considered a promising therapeutic target. The available experimental data on the N-terminal domain (NTD) loop indicates that mutations K127A, T129A and N130A demonstrate an unrecognized role for NTD-plasma membrane (PM) interaction for efficient VP40-PM localization, oligomerization, matrix assembly and egress. Despite experimental results, the molecular description of VP40 and the information it can provide still remain vague. Therefore, to gain further molecular insight into the effect of mutations on the loop region of VP40 and its effects on the overall protein conformation and VP40 dimerization, aMD simulations and post-dynamic analyses were employed for wildtype (WT) and mutant systems. The results showed significant variations in the presence of mutations as per RMSF, RMSD, R_g, PCA and distance calculations in comparison to the WT. These results could provide researchers with insight with regards to the conformational aspects concerning VP40 and its close relation to the experimental data. We believe that the results presented in this study will ultimately provide a useful understanding of the structural landscape of the loop region of VP40, which would contribute towards the discovery of novel EboV inhibitors.

VP40 of the Ebola Virus as a Target for EboV Therapy: Comprehensive Conformational and Inhibitor Binding Landscape from Accelerated Molecular Dynamics

The first account of the dynamic features of the loop region of VP40 of the Ebola virus was studied using accelerated molecular dynamics simulations and reported herein. Among the proteins of the Ebola virus, the matrix protein (VP40) plays a significant role in the virus lifecycle thereby making it a promising therapeutic target. Of interest is the newly elucidated N-terminal domain loop region of VP40 comprising residues K127, T129, and N130 which when mutated to alanine have demonstrated an unrecognized role for N-terminal domain-plasma membrane interaction for efficient VP40-plasma membrane localization, oligomerization, matrix assembly, and egress. The molecular understanding of the conformational features of VP40 in complex with a known inhibitor still remains elusive. Using accelerated molecular dynamics approaches, we conducted a comparative study on VP40 apo and bound systems to understand the conformational features of VP40 at the molecular level and to determine the effect of inhibitor binding with the aid of a number of post-dynamic analytical tools. Significant features were seen in the presence of an inhibitor as per molecular mechanics/generalized born surface area binding free energy calculations. Results revealed that inhibitor binding to VP40 reduces the flexibility and mobility of the protein as supported by root mean square fluctuation and root mean square deviation calculations. The study revealed a characteristic "twisting" motion and coiling of the loop region of VP40 accompanied by conformational changes in the dimer interface upon inhibitor binding. We believe that results presented in this study will ultimately provide useful insight into the binding landscape of VP40 which could assist researchers in the discovery of potent Ebola virus inhibitors for anti-Ebola therapies.

Gaussian Accelerated Molecular Dynamics in NAMD

Gaussian accelerated molecular dynamics (GaMD) is a recently developed enhanced sampling technique that provides efficient free energy calculations of biomolecules. Like the previous accelerated molecular dynamics (aMD), GaMD allows for “unconstrained” enhanced sampling without the need to set predefined collective variables and so is useful for studying complex biomolecular conformational changes such as protein folding and ligand binding. Furthermore, because the boost potential is constructed using a harmonic function that follows Gaussian distribution in GaMD, cumulant expansion to the second order can be applied to recover the original free energy profiles of proteins and other large biomolecules, which solves a long-standing energetic reweighting problem of the previous aMD method. Taken together, GaMD offers major advantages for both unconstrained enhanced sampling and free energy calculations of large biomolecules. Here, we have implemented GaMD in the NAMD package on top of the existing aMD feature and validated it on three model systems: alanine dipeptide, the chignolin fast-folding protein, and the M₃ muscarinic G protein-coupled receptor (GPCR). For alanine dipeptide, while conventional molecular dynamics (cMD) simulations performed for 30 ns are poorly converged, GaMD simulations of the same length yield free energy profiles that agree quantitatively with those of 1000 ns cMD simulation. Further GaMD simulations have captured folding of the chignolin and binding of the acetylcholine (ACh) endogenous agonist to the M₃ muscarinic receptor. The reweighted free energy profiles are used to characterize the protein folding and ligand binding pathways quantitatively. GaMD implemented in the scalable NAMD is widely applicable to enhanced sampling and free energy calculations of large biomolecules.

Self-consistent molecular dynamics calculation of diffusion in higher n-alkanes

Diffusion is one of the key subjects of molecular modeling and simulation studies. However, there is an unresolved lack of consistency between Einstein-Smoluchowski (E-S) and Green-Kubo (G-K) methods for diffusion coefficient calculations in systems of complex molecules. In this paper, we analyze this problem for the case of liquid n-triacontane. The non-conventional long-time tails of the velocity autocorrelation function (VACF) are found for this system. Temperature dependence of the VACF tail decay exponent is defined. The proper inclusion of the long-time tail contributions to the diffusion coefficient calculation results in the consistency between G-K and E-S methods. Having considered the major factors influencing the precision of the diffusion rate calculations in comparison with experimental data (system size effects and force field parameters), we point to hydrogen nuclear quantum effects as, presumably, the last obstacle to fully consistent n-alkane description.

CHARMM-GUI HMMM Builder for Membrane Simulations with the Highly Mobile Membrane-Mimetic Model

Slow diffusion of the lipids in conventional all-atom simulations of membrane systems makes it difficult to sample large rearrangements of lipids and protein-lipid interactions. Recently, Tajkhorshid and co-workers developed the highly mobile membrane-mimetic (HMMM) model with accelerated lipid motion by replacing the lipid tails with small organic molecules. The HMMM model provides accelerated lipid diffusion by one to two orders of magnitude, and is particularly useful in studying membrane-protein associations. However, building an HMMM simulation system is not easy, as it requires sophisticated treatment of the lipid tails. In this study, we have developed CHARMM-GUI HMMM Builder (http://www.charmm-gui.org/input/hmmm) to provide users with ready-to-go input files for simulating HMMM membrane systems with/without proteins. Various lipid-only and protein-lipid systems are simulated to validate the qualities of the systems generated by HMMM Builder with focus on the basic properties and advantages of the HMMM model. HMMM Builder supports all lipid types available in CHARMM-GUI and also provides a module to convert back and forth between an HMMM membrane and a full-length membrane. We expect HMMM Builder to be a useful tool in studying membrane systems with enhanced lipid diffusion.

Accelerated molecular dynamics simulations of ligand binding to a muscarinic G-protein-coupled receptor

Elucidating the detailed process of ligand binding to a receptor is pharmaceutically important for identifying druggable binding sites. With the ability to provide atomistic detail, computational methods are well poised to study these processes. Here, accelerated molecular dynamics (aMD) is proposed to simulate processes of ligand binding to a G-protein-coupled receptor (GPCR), in this case the M3 muscarinic receptor, which is a target for treating many human diseases, including cancer, diabetes and obesity. Long-timescale aMD simulations were performed to observe the binding of three chemically diverse ligand molecules: antagonist tiotropium (TTP), partial agonist arecoline (ARc) and full agonist acetylcholine (ACh). In comparison with earlier microsecond-timescale conventional MD simulations, aMD greatly accelerated the binding of ACh to the receptor orthosteric ligand-binding site and the binding of TTP to an extracellular vestibule. Further aMD simulations also captured binding of ARc to the receptor orthosteric site. Additionally, all three ligands were observed to bind in the extracellular vestibule during their binding pathways, suggesting that it is a metastable binding site. This study demonstrates the applicability of aMD to protein-ligand binding, especially the drug recognition of GPCRs.

Accelerated molecular dynamics simulations of the octopamine receptor using GPUs: discovery of an alternate agonist-binding position

Octopamine receptors (OARs) perform key biological functions in invertebrates, making this class of G-protein coupled receptors (GPCRs) worth considering for insecticide development. However, no crystal structures and very little research exists for OARs. Furthermore, GPCRs are large proteins, are suspended in a lipid bilayer, and are activated on the millisecond timescale, all of which make conventional molecular dynamics (MD) simulations infeasible, even if run on large supercomputers. However, accelerated Molecular Dynamics (aMD) simulations can reduce this timescale to even hundreds of nanoseconds, while running the simulations on graphics processing units (GPUs) would enable even small clusters of GPUs to have processing power equivalent to hundreds of CPUs. Our results show that aMD simulations run on GPUs can successfully obtain the active and inactive state conformations of a GPCR on this reduced timescale. Furthermore, we discovered a potential alternate active-state agonist-binding position in the octopamine receptor which has yet to be observed and may be a novel GPCR agonist-binding position. These results demonstrate that a complex biological system with an activation process on the millisecond timescale can be successfully simulated on the nanosecond timescale using a simple computing system consisting of a small number of GPUs. Proteins 2016; 84:1480-1489. © 2016 Wiley Periodicals, Inc.

Unconstrained Enhanced Sampling for Free Energy Calculations of Biomolecules: A Review

Free energy calculations are central to understanding the structure, dynamics and function of biomolecules. Yet insufficient sampling of biomolecular configurations is often regarded as one of the main sources of error. Many enhanced sampling techniques have been developed to address this issue. Notably, enhanced sampling methods based on biasing collective variables (CVs), including the widely used umbrella sampling, adaptive biasing force and metadynamics, have been discussed in a recent excellent review (Abrams and Bussi, Entropy, 2014). Here, we aim to review enhanced sampling methods that do not require predefined system-dependent CVs for biomolecular simulations and as such do not suffer from the hidden energy barrier problem as encountered in the CV-biasing methods. These methods include, but are not limited to, replica exchange/parallel tempering, self-guided molecular/Langevin dynamics, essential energy space random walk and accelerated molecular dynamics. While it is overwhelming to describe all details of each method, we provide a summary of the methods along with the applications and offer our perspectives. We conclude with challenges and prospects of the unconstrained enhanced sampling methods for accurate biomolecular free energy calculations.

Markovian and Non-Markovian Modeling of Membrane Dynamics with Milestoning

We exploit atomically detailed simulations and the milestoning theory to extract coarse grained models of membrane kinetics and thermodynamics. Non-Markovian and Markovian theories for the phosphate group displacements are used to coarsely represent membrane motions. The construction of the two models makes it possible to examine their consistency and accuracy. The equilibrium and fluctuations of the phosphate groups along the normal to the membrane plane are estimated, and milestoning equations are constructed and solved. An optimal Markovian model is constructed that reproduces exactly the equilibrium and mean first passage time (MFPT) of the non-Markovian model. The equilibrium solution of both models is favorably compared to distributions obtained from straightforward molecular dynamics simulations. The picture for the kinetics is complex. Multiple local relaxation times of the mass density are illustrated emphasizing the non-Markovian characteristics of the process. In Markovian modeling, only a single relaxation time is assumed for a state. Mapping of particle dynamics to the dynamics of a field density offers a new way of coarse graining complex systems as membranes that may bridge between atomically detailed models and phenomenological descriptions of macroscopic membranes.

A Flexible Domain-Domain Hinge Promotes an Induced-fit Dominant Mechanism for the Loading of Guide-DNA into Argonaute Protein in Thermus thermophilus

Argonaute proteins (Ago) are core components of the RNA Induced Silencing Complex (RISC) that load and utilize small guide nucleic acids to silence mRNAs or cleave foreign DNAs. Despite the essential role of Ago in gene regulation and defense against virus, the molecular mechanism of guide-strand loading into Ago remains unclear. We explore such a mechanism in the bacterium Thermus thermophilus Ago (TtAgo), via a computational approach combining molecular dynamics, bias-exchange metadynamics, and protein-DNA docking. We show that apo TtAgo adopts multiple closed states that are unable to accommodate guide-DNA. Conformations able to accommodate the guide are beyond the reach of thermal fluctuations from the closed states. These results suggest an induced-fit dominant mechanism for guide-strand loading in TtAgo, drastically different from the two-step mechanism for human Ago 2 (hAgo2) identified in our previous study. Such a difference between TtAgo and hAgo2 is found to mainly originate from the distinct rigidity of their L1-PAZ hinge. Further comparison among known Ago structures from various species indicates that the L1-PAZ hinge may be flexible in general for prokaryotic Ago's but rigid for eukaryotic Ago's.

General trends of dihedral conformational transitions in a globular protein

Dihedral conformational transitions are analyzed systematically in a model globular protein, cytochrome P450cam, to examine their structural and chemical dependences through combined conventional molecular dynamics (cMD), accelerated molecular dynamics (aMD) and adaptive biasing force (ABF) simulations. The aMD simulations are performed at two acceleration levels, using dihedral and dual boost, respectively. In comparison with cMD, aMD samples protein dihedral transitions approximately two times faster on average using dihedral boost, and ∼ 3.5 times faster using dual boost. In the protein backbone, significantly higher dihedral transition rates are observed in the bend, coil, and turn flexible regions, followed by the β bridge and β sheet, and then the helices. Moreover, protein side chains of greater length exhibit higher transition rates on average in the aMD-enhanced sampling. Side chains of the same length (particularly Nχ = 2) exhibit decreasing transition rates with residues when going from hydrophobic to polar, then charged and aromatic chemical types. The reduction of dihedral transition rates is found to be correlated with increasing energy barriers as identified through ABF free energy calculations. These general trends of dihedral conformational transitions provide important insights into the hierarchical dynamics and complex free energy landscapes of functional proteins.

Molecular dynamics simulations of biological membranes and membrane proteins using enhanced conformational sampling algorithms

This paper reviews various enhanced conformational sampling methods and explicit/implicit solvent/membrane models, as well as their recent applications to the exploration of the structure and dynamics of membranes and membrane proteins. Molecular dynamics simulations have become an essential tool to investigate biological problems, and their success relies on proper molecular models together with efficient conformational sampling methods. The implicit representation of solvent/membrane environments is reasonable approximation to the explicit all-atom models, considering the balance between computational cost and simulation accuracy. Implicit models can be easily combined with replica-exchange molecular dynamics methods to explore a wider conformational space of a protein. Other molecular models and enhanced conformational sampling methods are also briefly discussed. As application examples, we introduce recent simulation studies of glycophorin A, phospholamban, amyloid precursor protein, and mixed lipid bilayers and discuss the accuracy and efficiency of each simulation model and method. This article is part of a Special Issue entitled: Membrane Proteins edited by J.C. Gumbart and Sergei Noskov.

Force Field Development for Lipid Membrane Simulations

With the rapid development of computer power and wide availability of modelling software computer simulations of realistic models of lipid membranes, including their interactions with various molecular species, polypeptides and membrane proteins have become feasible for many research groups. The crucial issue of the reliability of such simulations is the quality of the force field, and many efforts, especially in the latest several years, have been devoted to parametrization and optimization of the force fields for biomembrane modelling. In this review, we give account of the recent development in this area, covering different classes of force fields, principles of the force field parametrization, comparison of the force fields, and their experimental validation. This article is part of a Special Issue entitled: Biosimulations edited by Ilpo Vattulainen and Tomasz Róg.

Gaussian Accelerated Molecular Dynamics: Unconstrained Enhanced Sampling and Free Energy Calculation

A Gaussian accelerated molecular dynamics (GaMD) approach for simultaneous enhanced sampling and free energy calculation of biomolecules is presented. By constructing a boost potential that follows Gaussian distribution, accurate reweighting of the GaMD simulations is achieved using cumulant expansion to the second order. Here, GaMD is demonstrated on three biomolecular model systems: alanine dipeptide, chignolin folding, and ligand binding to the T4-lysozyme. Without the need to set predefined reaction coordinates, GaMD enables unconstrained enhanced sampling of these biomolecules. Furthermore, the free energy profiles obtained from reweighting of the GaMD simulations allow us to identify distinct low-energy states of the biomolecules and characterize the protein-folding and ligand-binding pathways quantitatively.

Accelerated molecular dynamics simulations of protein folding

Folding of four fast-folding proteins, including chignolin, Trp-cage, villin headpiece and WW domain, was simulated via accelerated molecular dynamics (aMD). In comparison with hundred-of-microsecond timescale conventional molecular dynamics (cMD) simulations performed on the Anton supercomputer, aMD captured complete folding of the four proteins in significantly shorter simulation time. The folded protein conformations were found within 0.2-2.1 Å of the native NMR or X-ray crystal structures. Free energy profiles calculated through improved reweighting of the aMD simulations using cumulant expansion to the second-order are in good agreement with those obtained from cMD simulations. This allows us to identify distinct conformational states (e.g., unfolded and intermediate) other than the native structure and the protein folding energy barriers. Detailed analysis of protein secondary structures and local key residue interactions provided important insights into the protein folding pathways. Furthermore, the selections of force fields and aMD simulation parameters are discussed in detail. Our work shows usefulness and accuracy of aMD in studying protein folding, providing basic references in using aMD in future protein-folding studies.

Functional loop dynamics of the streptavidin-biotin complex

Accelerated molecular dynamics (aMD) simulation is employed to study the functional dynamics of the flexible loop(3-4) in the strong-binding streptavidin-biotin complex system. Conventional molecular (cMD) simulation is also performed for comparison. The present study reveals the following important properties of the loop dynamics: (1) The transition of loop(3-4) from open to closed state is observed in 200 ns aMD simulation. (2) In the absence of biotin binding, the open-state streptavidin is more stable, which is consistent with experimental evidences. The free energy (ΔG) difference is about 5 kcal/mol between two states. But with biotin binding, the closed state is more stable due to electrostatic and hydrophobic interactions between the loop(3-4) and biotin. (3) The closure of loop(3-4) is concerted to the stable binding of biotin to streptavidin. When the loop(3-4) is in its open-state, biotin moves out of the binding pocket, indicating that the interactions between the loop(3-4) and biotin are essential in trapping biotin in the binding pocket. (4) In the tetrameric streptavidin system, the conformational change of the loop(3-4) in each monomer is independent of each other. That is, there is no cooperative binding for biotin bound to the four subunits of the tetramer.

Molecular modeling of peptides

This article presents a review of the field of molecular modeling of peptides. The main focus is on atomistic modeling with molecular mechanics potentials. The description of peptide conformations and solvation through potentials is discussed. Several important computer simulation methods are briefly introduced, including molecular dynamics, accelerated sampling approaches such as replica-exchange and metadynamics, free energy simulations and kinetic network models like Milestoning. Examples of recent applications for predictions of structure, kinetics, and interactions of peptides with complex environments are described. The reliability of current simulation methods is analyzed by comparison of computational predictions obtained using different models with each other and with experimental data. A brief discussion of coarse-grained modeling and future directions is also presented.

Microsecond molecular dynamics simulations of lipid mixing

Molecular dynamics (MD) simulations of membranes are often hindered by the slow lateral diffusion of lipids and the limited time scale of MD. In order to study the dynamics of mixing and characterize the lateral distribution of lipids in converged mixtures, we report microsecond-long all-atom MD simulations performed on the special-purpose machine Anton. Two types of mixed bilayers, POPE:POPG (3:1) and POPC:cholesterol (2:1), as well as a pure POPC bilayer, were each simulated for up to 2 μs. These simulations show that POPE:POPG and POPC:cholesterol are each fully miscible at the simulated conditions, with the final states of the mixed bilayers similar to a random mixture. By simulating three POPE:POPG bilayers at different NaCl concentrations (0, 0.15, and 1 M), we also examined the effect of salt concentration on lipid mixing. While an increase in NaCl concentration is shown to affect the area per lipid, tail order, and lipid lateral diffusion, the final states of mixing remain unaltered, which is explained by the largely uniform increase in Na(+) ions around POPE and POPG. Direct measurement of water permeation reveals that the POPE:POPG bilayer with 1 M NaCl has reduced water permeability compared with those at zero or low salt concentration. Our calculations provide a benchmark to estimate the convergence time scale of all-atom MD simulations of lipid mixing. Additionally, equilibrated structures of POPE:POPG and POPC:cholesterol, which are frequently used to mimic bacterial and mammalian membranes, respectively, can be used as starting points of simulations involving these membranes.

Acceleration of Lateral Equilibration in Mixed Lipid Bilayers Using Replica Exchange with Solute Tempering

The lateral heterogeneity of cellular membranes plays an important role in many biological functions such as signaling and regulating membrane proteins. This heterogeneity can result from preferential interactions between membrane components or interactions with membrane proteins. One major difficulty in molecular dynamics simulations aimed at studying the membrane heterogeneity is that lipids diffuse slowly and collectively in bilayers, and therefore, it is difficult to reach equilibrium in lateral organization in bilayer mixtures. Here, we propose the use of the replica exchange with solute tempering (REST) approach to accelerate lateral relaxation in heterogeneous bilayers. REST is based on the replica exchange method but tempers only the solute, leaving the temperature of the solvent fixed. Since the number of replicas in REST scales approximately only with the degrees of freedom in the solute, REST enables us to enhance the configuration sampling of lipid bilayers with fewer replicas, in comparison with the temperature replica exchange molecular dynamics simulation (T-REMD) where the number of replicas scales with the degrees of freedom of the entire system. We apply the REST method to a cholesterol and 1,2-dipalmitoyl-sn-glycero-3-phosphocholine (DPPC) bilayer mixture and find that the lateral distribution functions of all molecular pair types converge much faster than in the standard MD simulation. The relative diffusion rate between molecules in REST is, on average, an order of magnitude faster than in the standard MD simulation. Although REST was initially proposed to study protein folding and its efficiency in protein folding is still under debate, we find a unique application of REST to accelerate lateral equilibration in mixed lipid membranes and suggest a promising way to probe membrane lateral heterogeneity through molecular dynamics simulation.

Improved Reweighting of Accelerated Molecular Dynamics Simulations for Free Energy Calculation

Accelerated molecular dynamics (aMD) simulations greatly improve the efficiency of conventional molecular dynamics (cMD) for sampling biomolecular conformations, but they require proper reweighting for free energy calculation. In this work, we systematically compare the accuracy of different reweighting algorithms including the exponential average, Maclaurin series, and cumulant expansion on three model systems: alanine dipeptide, chignolin, and Trp-cage. Exponential average reweighting can recover the original free energy profiles easily only when the distribution of the boost potential is narrow (e.g., the range ≤20k_BT) as found in dihedral-boost aMD simulation of alanine dipeptide. In dual-boost aMD simulations of the studied systems, exponential average generally leads to high energetic fluctuations, largely due to the fact that the Boltzmann reweighting factors are dominated by a very few high boost potential frames. In comparison, reweighting based on Maclaurin series expansion (equivalent to cumulant expansion on the first order) greatly suppresses the energetic noise but often gives incorrect energy minimum positions and significant errors at the energy barriers (∼2–3k_BT). Finally, reweighting using cumulant expansion to the second order is able to recover the most accurate free energy profiles within statistical errors of ∼k_BT, particularly when the distribution of the boost potential exhibits low anharmonicity (i.e., near-Gaussian distribution), and should be of wide applicability. A toolkit of Python scripts for aMD reweighting “PyReweighting” is distributed free of charge at http://mccammon.ucsd.edu/computing/amdReweighting/.

Free energy landscape of G-protein coupled receptors, explored by accelerated molecular dynamics

G-protein coupled receptors (GPCRs) mediate cellular responses to various hormones and neurotransmitters and are important targets for treating a wide spectrum of diseases. They are known to adopt multiple conformational states (e.g., inactive, intermediate and active) during their modulation of various cell signaling pathways. Here, the free energy landscape of GPCRs is explored using accelerated molecular dynamics (aMD) simulations as demonstrated on the M2 muscarinic receptor, a key GPCR that regulates human heart rate and contractile forces of cardiomyocytes. Free energy profiles of important structural motifs that undergo conformational transitions upon GPCR activation and allosteric signaling are analyzed in detail, including the Arg(3.50)-Glu(6.30) ionic lock, the Trp(6.48) toggle switch and the hydrogen interactions between Tyr(5.58)-Tyr(7.53).

Lipid14: The Amber Lipid Force Field

The AMBER lipid force field has been updated to create Lipid14, allowing tensionless simulation of a number of lipid types with the AMBER MD package. The modular nature of this force field allows numerous combinations of head and tail groups to create different lipid types, enabling the easy insertion of new lipid species. The Lennard-Jones and torsion parameters of both the head and tail groups have been revised and updated partial charges calculated. The force field has been validated by simulating bilayers of six different lipid types for a total of 0.5 μs each without applying a surface tension; with favorable comparison to experiment for properties such as area per lipid, volume per lipid, bilayer thickness, NMR order parameters, scattering data, and lipid lateral diffusion. As the derivation of this force field is consistent with the AMBER development philosophy, Lipid14 is compatible with the AMBER protein, nucleic acid, carbohydrate, and small molecule force fields.

Surface-Tension Replica-Exchange Molecular Dynamics Method for Enhanced Sampling of Biological Membrane Systems

Conformational sampling is fundamentally important for simulating complex biomolecular systems. The generalized-ensemble algorithm, especially the temperature replica-exchange molecular dynamics method (T-REMD), is one of the most powerful methods to explore structures of biomolecules such as proteins, nucleic acids, carbohydrates, and also of lipid membranes. T-REMD simulations have focused on soluble proteins rather than membrane proteins or lipid bilayers, because explicit membranes do not keep their structural integrity at high temperature. Here, we propose a new generalized-ensemble algorithm for membrane systems, which we call the surface-tension REMD method. Each replica is simulated in the NPγT ensemble, and surface tensions in a pair of replicas are exchanged at certain intervals to enhance conformational sampling of the target membrane system. We test the method on two biological membrane systems: a fully hydrated DPPC (1,2-dipalmitoyl-sn-glycero-3-phosphatidylcholine) lipid bilayer and a WALP23-POPC (1-palmitoyl-2-oleoyl-sn-glycero-3-phosphocholine) membrane system. During these simulations, a random walk in surface tension space is realized. Large-scale lateral deformation (shrinking and stretching) of the membranes takes place in all of the replicas without collapse of the lipid bilayer structure. There is accelerated lateral diffusion of DPPC lipid molecules compared with conventional MD simulation, and a much wider range of tilt angle of the WALP23 peptide is sampled due to large deformation of the POPC lipid bilayer and through peptide-lipid interactions. Our method could be applicable to a wide variety of biological membrane systems.