Molecular Dynamics Software Package Research Articles

OpenMSCG: A Software Tool for Bottom-Up Coarse-Graining.

The "bottom-up" approach to coarse-graining, for building accurate and efficient computational models to simulate large-scale and complex phenomena and processes, is an important approach in computational chemistry, biophysics, and materials science. As one example, the Multiscale Coarse-Graining (MS-CG) approach to developing CG models can be rigorously derived using statistical mechanics applied to fine-grained, i.e., all-atom simulation data for a given system. Under a number of circumstances, a systematic procedure, such as MS-CG modeling, is particularly valuable. Here, we present the development of the OpenMSCG software, a modularized open-source software that provides a collection of successful and widely applied bottom-up CG methods, including Boltzmann Inversion (BI), Force-Matching (FM), Ultra-Coarse-Graining (UCG), Relative Entropy Minimization (REM), Essential Dynamics Coarse-Graining (EDCG), and Heterogeneous Elastic Network Modeling (HeteroENM). OpenMSCG is a high-performance and comprehensive toolset that can be used to derive CG models from large-scale fine-grained simulation data in file formats from common molecular dynamics (MD) software packages, such as GROMACS, LAMMPS, and NAMD. OpenMSCG is modularized in the Python programming framework, which allows users to create and customize modeling "recipes" for reproducible results, thus greatly improving the reliability, reproducibility, and sharing of bottom-up CG models and their applications.

An implementation of the Martini coarse-grained force field in OpenMM

We describe a complete implementation of Martini 2 and Martini 3 in the OpenMM molecular dynamics software package. Martini is a widely used coarse-grained force field with applications in biomolecular simulation, materials, and broader areas of chemistry. It is implemented as a force field but makes extensive use of facilities unique to the GROMACS software, including virtual sites and bonded terms that are not commonly used in standard atomistic force fields. OpenMM is a flexible molecular dynamics package widely used for methods development and is competitive in speed on GPUs with other commonly used packages. OpenMM has facilities to easily implement new force field terms, external forces and fields, and other nonstandard features, which we use to implement all force field terms used in Martini 2 and Martini 3. This allows Martini simulations, starting with GROMACS topology files that are processed by custom scripts, with all the added flexibility of OpenMM. We provide a GitHub repository with test cases, compare accuracy and performance between GROMACS and OpenMM, and discuss the limitations of our implementation in terms of direct comparison with GROMACS. We describe a use case that implements the Modeling Employing Limited Data method to apply experimental constraints in a Martini simulation to efficiently determine the structure of a protein complex. We also discuss issues and a potential solution with the Martini 2 topology for cholesterol.

Peridynamics method for problems solve of solids destruction

Abstract. The article investigates the method of peridynamics, which is an alternative approach to solving destruction problems based on integral equations. It is assumed that particles in a continuum interact with each other at a finite distance, as in molecular dynamics. Damage is part of the theory at the level of two-particle interactions, so damage finding and destruction occurs when solving the equation of motion. During this work, bondbased and state-based peridynamics models of destruction used in the Sandia Laboratory were described and implemented within the framework of the MoDyS molecular dynamics software package. In the bond-based model, the defining relationship is the bond stiffness function, which corrects the force of particle-particle interaction and imposes a restriction on the use of the Poisson’s ratio. The state-based model generalizes the bond-based approach and may be applied to materials with any Poisson’s ratio. The relationship of both models is ascertained. Calculation convergence is demonstrated on the example of a one-dimensional elasticity problem. The possibility of using the implemented models for fracture problems is also shown.

Interaction of KRSR Peptide with Titanium Dioxide Anatase (100) Surface: A Molecular Dynamics Simulation Study.

Due to its tensile strength and excellent biocompatibility, titanium (Ti) is commonly used as an implant material in medicine and dentistry. The success of dental implants depends on the formation of a contact between the oxidized surface of Ti implant and the surrounding bone tissue. The adsorption of proteins and peptides to the implant surface allows the bone-forming osteoblast cells to adhere to such modified surfaces. Recently, it has been observed that tetrapeptide KRSR (Lys-Arg-Ser-Arg) functionalization could promote osteoblast adhesion to implant surfaces. This may facilitate the establishment of an efficient bone-to implant contact and improve implant stability during the healing process. GROMACS, a molecular dynamics software package was used to perform a 200 ns simulation of adsorption of the KRSR peptide to the TiO2 (anatase) surface in an aqueous environment. The molecule conformations were mapped with Replica Exchange Molecular Dynamics (REMD) simulations to assess the possible peptide conformations on the anatase surface, and the umbrella sampling method was used to calculate the binding energy of the most common conformation. The simulations have shown that the KRSR peptide migrates and attaches to the surface in a stable position. The dominant amino acid residue interacting with the TiO2 surface was the N-terminal charged lysine (K) residue. REMD indicated that there is a distinct conformation that is taken by the KRSR peptide. In this conformation the surface interacts only with the lysine residue while the ser (S) and arg (R) residues interact with water molecules farther from the surface. The binding free energy of the most common conformation of KRSR peptide to the anatase (100) surface was ΔG = −8.817 kcal/mol. Our result suggests that the N-terminal lysine residue plays an important role in the adhesion of KRSR to the TiO2 surface and may influence the osseointegration of dental implants.

Enhancing the Accuracy of Ab Initio Molecular Dynamics by Fine Tuning of Effective Two-Body Interactions: Acetonitrile as a Test Case.

Grimme's dispersion-corrected density functional theory (DFT-D) methods have emerged among the most practical approaches to perform accurate quantum mechanical calculations on molecular systems ranging from small clusters to microscopic and mesoscopic samples, i.e., including hundreds or thousands of molecules. Moreover, DFT-D functionals can be easily integrated into popular ab initio molecular dynamics (MD) software packages to carry out first-principles condensed-phase simulations at an affordable computational cost. Here, starting from the well-established D3 version of the dispersion-correction term, we present a simple protocol to improve the accurate description of the intermolecular interactions of molecular clusters of growing size, considering acetonitrile as a test case. Optimization of the interaction energy was performed with reference to diffusion quantum Monte Carlo calculations, successfully reaching the same inherent accuracy of the latter (statistical error of ∼0.1 kcal/mol per molecule). The refined DFT-D3 model was then used to perform ab initio MD simulations of liquid acetonitrile, again showing significant improvements toward available experimental data with respect to the default correction.

CAN: A new program to streamline preparation of molecular coordinate files for molecular dynamics simulations.

Preparing molecular coordinate files for molecular dynamics (MD) simulations can be a very time-consuming process. Herein we present the development of a user-friendly program that drastically reduces the time required to prepare these molecular coordinate files for MD software packages such as AmberTools. Our program, known as charge atomtype naming (CAN), creates and uses a library of structures such as amino acid monomers to update the charge, atom type, and name of atoms in any molecular structure (mol2) file. We demonstrate the utility of this new program by rapidly preparing structural files for MD simulations for polypeptides ranging from small molecules to large protein structures. Both native and non-native amino acid residues are easily handled by this new program.

Molecular dynamics simulations of phospholipid bilayer mechanoporation under different strain states—a comparison between GROMACS and LAMMPS

Nanoscale deformation mechanisms of cellular structures could render drastically different results depending on the molecular dynamics (MD) simulator chosen. Due to different available settings, the comparison of these different MD simulators is typically an intricate task, requiring that all configurations be converted appropriately with a variety of reasonable parameter choices. The current study aims to perform and compare MD simulations of biomolecules between two common MD software packages (GROMACS and LAMMPS), in which a phospholipid bilayer is deformed under different strain states (equibiaxial, 2:1 non-equibiaxial, 4:1 non-equibiaxial, strip biaxial and uniaxial tension). The results for the stress–strain, pore nucleation and growth, and damage behavior are compared between the respective GROMACS and LAMMPS simulations. In general, GROMACS and LAMMPS produced similar deformation behavior, including damage evolution and the effect of strain state on phospholipid bilayer failure. However, GROMACS nucleated a greater number of pores at lower strains, produced lower stress values and higher damage values than LAMMPS. Multiple different setting options between GROMACS and LAMMPS, including algorithm variations, have been considered as possible explanations for the observed differences. Overall, this study will aid in the cross-check of parameter settings and simulation results in future MD research, particularly on the mechanical damage of phospholipid bilayers and other biological systems. Based on that, with future efforts, GROMACS and LAMMPS, as well as other MD programs, could be exploited synchronously with better comparability and reproducibility.

Computer simulations of lipid regulation by molecular semigrand canonical ensembles

The plasma membrane is the interface between cells and exterior media. Although its existence has been known for a long time, organization of its constituent lipids remain a challenge. Recently, we have proposed that lipid populations may be controlled by chemical potentials of different lipid species, resulting in semigrand canonical thermodynamic ensembles. However, the currently available molecular dynamics software packages do not facilitate the control of chemical potentials at the molecular level. Here, we propose a variation of existing algorithms that efficiently characterizes and controls the chemical nature of each lipid. Additionally, we allow coupling with collective variables and show that it can be used to dynamically create asymmetric membranes. This algorithm is openly available as a plugin for the HOOMD-Blue molecular dynamics engine.

GROMACS implementation of free energy calculations with non-pairwise Variationally derived Intermediates

Gradients in free energies are the driving forces of physical and biochemical systems. To predict free energy differences with high accuracy, Molecular Dynamics (MD) and other methods based on atomistic Hamiltonians conduct sampling simulations in intermediate thermodynamic states that bridge the configuration space densities between two states of interest (’alchemical transformations’). For uncorrelated sampling, the recent Variationally derived Intermediates (VI) method yields optimal accuracy. The form of the VI intermediates differs fundamentally from conventional ones in that they are non-pairwise, i.e., the total force on a particle in an intermediate states cannot be split into additive contributions from the surrounding particles. In this work, we describe the implementation of VI into the widely used GROMACS MD software package (2020, version 1). Furthermore, a variant of VI is developed that avoids numerical instabilities for vanishing particles. The implementation allows the use of previous non-pairwise potential forms in the literature, which have so far not been available in GROMACS. Example cases on the calculation of solvation free energies, and accuracy assessments thereof, are provided. Program summaryProgram Title: GROMACS-VI-ExtensionCPC Library link to program files:https://doi.org/10.17632/7yvc8mmnyv.1Developer’s repository link:https://www.mpibpc.mpg.de/gromacs-vi-extension and https://www.gitlab.gwdg.de/martin.reinhardt/gromacs-vi-extensionLicensing provisions: LGPLProgramming language: C++14, CUDANature of problem: The free energy difference between two states of a thermodynamic system is calculated using samples generated by simulations based on atomistic Hamiltonians. Due to the high dimensionality of many applications as in, e.g., biophysics, only a small part of the configuration space can be sampled. The choice of the sampling scheme critically affects the accuracy of the final free energy estimate. The challenge is, therefore, to find the optimal sampling scheme that provides best accuracy for given computational effort.Solution method: Sampling is commonly conducted in intermediate states, whose Hamiltonians are defined based on the Hamiltonians of the two states of interest. Here, sampling is conducted in the variationally derived intermediate states that, under the assumption of uncorrelated sample points, yield optimal accuracy. These intermediates differ fundamentally from the common intermediates in that they are non-pairwise, i.e., the forces on a particle are only additive in the end state, whereas the total force in the intermediate states cannot be split into additive contributions from the surrounding particles.

Luteolin and abyssinone II as potential inhibitors of SARS-CoV-2: an in silico molecular modeling approach in battling the COVID-19 outbreak

BackgroundAt present, the entire world is in a war against COVID-19 pandemic which has gradually led us toward a more compromised “new normal” life. SARS-CoV-2, the pathogenic microorganism liable for the recent COVID-19 outbreak, is extremely contagious in nature resulting in an unusual number of infections and death globally. The lack of clinically proven therapeutic intervention for COVID-19 has dragged the world’s healthcare system into the biggest challenge. Therefore, development of an efficient treatment scheme is now in great demand. Screening of different biologically active plant-based natural compounds could be a useful strategy for combating this pandemic. In the present research, a collection of 43 flavonoids of 7 different classes with previously recorded antiviral activity was evaluated via computational and bioinformatics tools for their impeding capacity against SARS-CoV-2. In silico drug likeness, pharmacophore and Absorption, Distribution, Metabolism, Excretion and Toxicity (ADMET) profile analysis of the finest ligands were carried out using DataWarrior, DruLiTo and admetSAR programs, respectively. Molecular docking was executed by AutoDock Vina, while molecular dynamics simulation of the target protein–ligand bound complexes was done using nanoscalable molecular dynamics and visual molecular dynamics software package. Finally, the molecular target analysis of the selected ligands within Homo sapiens was conducted with SwissTargetPredcition web server.ResultsOut of the forty-three flavonoids, luteolin and abyssinone II were found to develop successful docked complex within the binding sites of target proteins in terms of lowest binding free energy and inhibition constant. The root mean square deviation and root mean square fluctuation values of the docked complex displayed stable interaction and efficient binding between the ligands and target proteins. Both of the flavonoids were found to be safe for human use and possessed good drug likeness properties and target accuracy.ConclusionsConclusively, the current study proposes that luteolin and abyssinone II might act as potential therapeutic candidates for SARS-CoV-2 infection. In vivo and in vitro experiments, however, should be taken under consideration to determine the efficiency and to demonstrate the mechanism of action.

ReaxFF/AMBER—A Framework for Hybrid Reactive/Nonreactive Force Field Molecular Dynamics Simulations

Combined quantum mechanical/molecular mechanical (QM/MM) models using semiempirical and ab initio methods have been extensively reported on over the past few decades. These methods have been shown to be capable of providing unique insights into a range of problems, but they are still limited to relatively short time scales, especially QM/MM models using ab initio methods. An intermediate approach between a QM based model and classical mechanics could help fill this time-scale gap and facilitate the study of a range of interesting problems. Reactive force fields represent the intermediate approach explored in this paper. A widely used reactive model is ReaxFF, which has largely been applied to materials science problems and is generally used as a stand-alone (i.e., the full system is modeled using ReaxFF). We report a hybrid ReaxFF/AMBER molecular dynamics (MD) tool, which introduces ReaxFF capabilities to capture bond breaking and formation within the AMBER MD software package. This tool enables us to study local reactive events in large systems at a fraction of the computational costs of QM/MM models. We describe the implementation of ReaxFF/AMBER, validate this implementation using a benzene molecule solvated in water, and compare its performance against a range of similar approaches. To illustrate the predictive capabilities of ReaxFF/AMBER, we carried out a Claisen rearrangement study in aqueous solution. In a first for ReaxFF, we were able to use AMBER's potential of mean force (PMF) capabilities to perform a PMF study on this organic reaction. The ability to capture local reaction events in large systems using combined ReaxFF/AMBER opens up a range of problems that can be tackled using this model to address both chemical and biological processes.

PySpawn: Software for Nonadiabatic Quantum Molecular Dynamics.

The ab initio multiple spawning (AIMS) method enables nonadiabatic quantum molecular dynamics simulations in an arbitrary number of dimensions, with potential energy surfaces provided by electronic structure calculations performed on-the-fly. However, the intricacy of the AIMS algorithm complicates software development, deployment on modern shared computer resources, and postsimulation data analysis. PySpawn is a nonadiabatic molecular dynamics software package that addresses these issues. The program is designed to be easily interfaced with electronic structure software, and an interface to the TeraChem software package is described here. PySpawn introduces a task-based reorganization of the AIMS algorithm, allowing fine-grained restart capability and setting the stage for efficient parallelization in a future release. PySpawn includes a user-friendly and interactive Python analysis module that will enable novice users to painlessly adopt AIMS. As a demonstration of PySpawn's simulation capability and analysis module, we report complete active space self-consistent field-based AIMS simulations of the 1,2-dithienyl-1,2-dicyanoethene molecule, a promising molecular photoswitch.

Infinite switch simulated tempering in force (FISST).

Many proteins in cells are capable of sensing and responding to piconewton-scale forces, a regime in which conformational changes are small but significant for biological processes. In order to efficiently and effectively sample the response of these proteins to small forces, enhanced sampling techniques will be required. In this work, we derive, implement, and evaluate an efficient method to simultaneously sample the result of applying any constant pulling force within a specified range to a molecular system of interest. We start from simulated tempering in force, whereby force is added as a linear bias on a collective variable to the system's Hamiltonian, and the coefficient is taken as a continuous auxiliary degree of freedom. We derive a formula for an average collective-variable-dependent force, which depends on a set of weights learned on-the-fly throughout a simulation, that reflect the limit where force varies infinitely quickly. Simulation data can then be used to retroactively compute averages of any observable at any force within the specified range. This technique is based on recent work deriving similar equations for infinite switch simulated tempering in temperature, which showed that the infinite switch limit is the most efficient for sampling. Here, we demonstrate that our method accurately samples molecular systems at all forces within a user defined force range simultaneously and show how it can serve as an enhanced sampling tool for cases where the pulling direction destabilizes states that have low free-energy at zero-force. This method is implemented in and freely distributed with the PLUMED open-source sampling library, and hence can be readily applied to problems using a wide range of molecular dynamics software packages.

Molecular dynamics calculations of collision-induced absorption in a gas mixture of neon and krypton.

We continue the development of the in-house molecular dynamics software package SpaCIAL and test it for the computation of the collision-induced absorption coefficients for a neon (Ne) and krypton (Kr) gas mixture. An apodization procedure for the dipole autocorrelation function is implemented and tested. We also carry out a statistical study of the convergence rate with respect to ensemble size. The resulting absorption coefficients show a good accordance with quantum mechanical results. Comparison with laboratory measurements shows agreement within 10%-20% at T = 295 K. At T = 480 K, a larger difference of 40%-80% is observed, which can presumably be explained by experimental uncertainties. For the study, an empirical (Barker, Fisher, and Watts) interaction-potential [Mol. Phys. 21, 657 (1971)] for Ne-Kr has been developed. Ab initio {coupled cluster with singles and doubles (triples) [CCSD(T)]} potentials for Ne-Ne, Kr-Kr, and Ne-Kr have been computed, as well as the CCSD(T) interaction-induced Ne-Kr dipole moment curve.

TeraChem: Accelerating electronic structure and ab initio molecular dynamics with graphical processing units.

Developed over the past decade, TeraChem is an electronic structure and ab initio molecular dynamics software package designed from the ground up to leverage graphics processing units (GPUs) to perform large-scale ground and excited state quantum chemistry calculations in the gas and the condensed phase. TeraChem's speed stems from the reformulation of conventional electronic structure theories in terms of a set of individually optimized high-performance electronic structure operations (e.g., Coulomb and exchange matrix builds, one- and two-particle density matrix builds) and rank-reduction techniques (e.g., tensor hypercontraction). Recent efforts have encapsulated these core operations and provided language-agnostic interfaces. This greatly increases the accessibility and flexibility of TeraChem as a platform to develop new electronic structure methods on GPUs and provides clear optimization targets for emerging parallel computing architectures.

CP2K: An electronic structure and molecular dynamics software package - Quickstep: Efficient and accurate electronic structure calculations.

CP2K is an open source electronic structure and molecular dynamics software package to perform atomistic simulations of solid-state, liquid, molecular, and biological systems. It is especially aimed at massively parallel and linear-scaling electronic structure methods and state-of-the-art ab initio molecular dynamics simulations. Excellent performance for electronic structure calculations is achieved using novel algorithms implemented for modern high-performance computing systems. This review revisits the main capabilities of CP2K to perform efficient and accurate electronic structure simulations. The emphasis is put on density functional theory and multiple post-Hartree-Fock methods using the Gaussian and plane wave approach and its augmented all-electron extension.

Comparative Molecular Dynamics Simulations Provide Insight Into Antibiotic Interactions: A Case Study Using the Enzyme L,L-Diaminopimelate Aminotransferase (DapL).

The L,L-diaminopimelate aminotransferase (DapL) pathway, a recently discovered variant of the lysine biosynthetic pathway, is an attractive pipeline to identify targets for the development of novel antibiotic compounds. DapL is a homodimer that catalyzes the conversion of tetrahydrodipicolinate to L,L-diaminopimelate in a single transamination reaction. The penultimate and ultimate products of the lysine biosynthesis pathway, meso-diaminopimelate and lysine, are key components of the Gram-negative and Gram-positive bacterial peptidoglycan cell wall. Humans are not able to synthesize lysine, and DapL has been identified in 13% of bacteria whose genomes have been sequenced and annotated to date, thus it is an attractive target for the development of narrow spectrum antibiotics through the prevention of both lysine biosynthesis and peptidoglycan crosslinking. To address the common lack of structural information when conducting compound screening experiments and provide support for the use of modeled structures, our analyses utilized inferred structures from related homologous enzymes. Using a comprehensive and comparative molecular dynamics (MD) software package—DROIDS (Detecting Relative Outlier Impacts in Dynamic Simulations) 2.0, we investigated the binding dynamics of four previously identified antagonistic ligands of DapL from Verrucomicrobium spinosum, a non-pathogenic relative of Chlamydia trachomatis. Here, we present putative docking positions of the four ligands and provide confirmatory comparative molecular dynamics simulations supporting the conformations. The simulations performed in this study can be applied to evaluate putative targets to predict compound effectiveness prior to in vivo and in vitro experimentation. Moreover, this approach has the potential to streamline the process of antibiotic development.

Record Atomistic Simulation of Crystalline Silicon: Bridging Microscale Structures and Macroscale Properties.

Based on the molecular dynamics software package CovalentMD 2.0, the fastest molecular dynamics simulation for covalent crystalline silicon with bond-order potentials has been implemented on the third highest performance supercomputer "Sunway TaihuLight" in the world (before June 2019), and already obtained 16.0 Pflops (1015 floating point operation per second) in double precision for the simulation of crystalline silicon, which is recordly high for rigorous atomistic simulation of covalent materials. The simulations used up to 160,768 64-core processors, totally nearly 10.3 million cores, to simulate more than 137 billion silicon atoms, where the parallel efficiency is over 80% on the whole machine. The running performance on a single processor reached 15.1% of its theoretical peak at highest. The longitudinal dimension of the simulated system is far beyond the range with scale-dependent properties, while the lateral dimension significantly exceeds the experimentally measurable range. Our simulation enables virtual experiments on real-world nanostructured materials and devices for predicting macroscale properties and behaviors from microscale structures directly, bringing about many exciting new possibilities in nanotechnology, information technology, electronics and renewable energies, etc. © 2019 Wiley Periodicals, Inc.

Using Molecular Dynamics Simulations to Evaluate Ligand Binding of L, L‐diaminopimelate Aminotransferase, an Enzyme Involved in Protein and Peptidoglycan Biosynthesis

A common protocol, Site Directed Mutagenesis (SDM) experiments facilitate the alterations to a gene sequence to study downstream effects on its product. In addition, inhibitor/antagonistic studies investigate the potential of common ligands to inhibit or inactivate enzymes. Both approaches have seen minor updates in recent years, but methods to streamline these processes are highly desired. For example, a rate‐limiting step in SDM lies in choosing key nucleotides that will subsequently affect enzymatic activity. To facilitate SDM studies and subsequent analyses to save time and resources, a comprehensive and comparative molecular dynamics (MD) software package – DROIDS (Detecting Relative Outlier Impacts in Dynamic Simulations) 2.0 – has been applied. Here, we use a novel aminotransferase, L, L‐diaminopimelate aminotransferase (DapL) as a test to propose a method of augmenting SDM and related experiments using MD simulations. DapL is involved in peptidoglycan and protein metabolism. As such, the essentiality of the dapL gene in eubacteria is currently a key question yet to be answered. Information to supplement knowledge of this enzyme will aid in evaluating its potential as a narrow spectrum antibiotic target. We have used DROIDS 2.0 to investigate the impact of different point mutations and putative antagonistic ligands on the activity of the DapL enzyme, identifying those that most significantly impact its dynamic behavior. In addition, the DROIDS 2.0 protocol was taken further to predict mutations that lessen binding affinity to chosen inhibitors, which may have the potential to guide the rational design of inhibitory ligands. Comparative dynamics in DROIDS 2.0 can be visualized (Figure 1) in a variety of statistical plots, colored structures, and colored movies of protein movement, enhancing interpretation and communication to a broad audience.Support or Funding InformationNational Institutes of Health (NIH) award (R15GM120653)This abstract is from the Experimental Biology 2019 Meeting. There is no full text article associated with this abstract published in The FASEB Journal.

Coarse-Grained Molecular Dynamics Simulation of Methane Interacting with Intracytoplasmic Membranes

Intracytoplasmic membranes (ICMs) are a common structural element found in almost all methanotrophic bacteria. They house the particulate methane monooxygenase (pMMO), which is the initial enzyme in the metabolism of methane. To study the interaction of methane with these membranes we present coarse-grained molecular dynamics simulations using MARTINI force fields in the GROMACS molecular dynamics software package. All model lipid membrane were composed of a mixture of DOPG and DOPE. In some cases model hopanoids were added to the membrane. The study has three main considerations. First, in single membranes, both the partitioning of methane to the membrane and its effect on the fluidity of the bilayer was evaluated. Second, stacked membranes were created to model intracytoplasmic membrane layers and analyze the permeability of methane between these layers. Third, increasing amounts of model hopanoids were used to evaluate their effect on methane permeability and lipid mobility in the membranes.