A Critical Comparison of Biomembrane Force Fields: Structure and Dynamics of Model DMPC, POPC, and POPE Bilayers

Pluháčková, Kristýna; Kirsch, Sonja A.; Han, Jing; Sun, Liping; Jiang, Zhenyan; Unruh, Tobias; Böckmann, Rainer A.

doi:10.1021/acs.jpcb.6b01870

Cited by 148 publications

(216 citation statements)

References 106 publications

Supporting

Mentioning

177

Contrasting

Order By: Relevance

“…We note that this is the same approach as described by Pluhackova et al when testing a proposed work-around for known problems within the GROMACS program g_order (also termed gmx order in recent GROMACS versions). 42 We also note here that the CHARMM36 force field simulation was first processed with the GROMACS program trjconv to ensure none of the lipids were split across the periodic boundary, as some of the tools tested (e.g., the calc_op.tcl script and the g_lomepro program) produced slightly incorrect results if this were the case (data not shown).…”

Section: ■ Methodsmentioning

confidence: 99%

On the Calculation of Acyl Chain Order Parameters from Lipid Simulations

Piggot

Allison

Sessions

et al. 2017

J. Chem. Theory Comput.

117

111

View full text Add to dashboard Cite

For molecular dynamics simulations of biological membrane systems to live up to the potential of providing accurate atomic level detail into membrane properties and functions, it is essential that the force fields used to model such systems are as accurate as possible. One membrane property that is often used to assess force field accuracy is the carbon−hydrogen (or carbon−deuterium) order parameters of the lipid tails, which can be accurately measured using experimental NMR techniques. There are a variety of analysis tools available to calculate these order parameters from simulations and it is essential that these computational tools work correctly to ensure the accurate assessment of the simulation force fields. In this work we compare many of these computational tools for calculating the order parameters of POPC membranes. While tools that work on all-atom systems and tools that work on saturated lipid tails in general work extremely well, we demonstrate that the majority of the tested tools that calculate the order parameters for unsaturated united-atom lipid tails do so incorrectly. We identify tools that do perform accurate calculations and include one such program with this work, enabling rapid and accurate calculation of unitedatom lipid order parameters. Furthermore, we discuss cases in which it is nontrivial to appropriately predict the unsaturated carbon order parameters in united-atom systems. Finally, we examine order parameter splitting for carbon 2 in sn-2 lipid chains, demonstrating substantial deviations from experimental values in several all-atom and united-atom lipid force fields.

show abstract

Section: ■ Methodsmentioning

confidence: 99%

On the Calculation of Acyl Chain Order Parameters from Lipid Simulations

Piggot

Allison

Sessions

et al. 2017

J. Chem. Theory Comput.

117

111

View full text Add to dashboard Cite

show abstract

“…The particle mesh Ewald summation [64] was applied to compute the long-range electrostatics. For further simulation details see Pluhackova et al [65]. A summary of all atomistic simulations is given in Table 2.…”

Section: Methodsmentioning

confidence: 99%

Dynamic Cholesterol-Conditioned Dimerization of the G Protein Coupled Chemokine Receptor Type 4

et al. 2016

Self Cite

View full text Add to dashboard Cite

G protein coupled receptors (GPCRs) allow for the transmission of signals across biological membranes. For a number of GPCRs, this signaling was shown to be coupled to prior dimerization of the receptor. The chemokine receptor type 4 (CXCR4) was reported before to form dimers and their functionality was shown to depend on membrane cholesterol. Here, we address the dimerization pattern of CXCR4 in pure phospholipid bilayers and in cholesterol-rich membranes. Using ensembles of molecular dynamics simulations, we show that CXCR4 dimerizes promiscuously in phospholipid membranes. Addition of cholesterol dramatically affects the dimerization pattern: cholesterol binding largely abolishes the preferred dimer motif observed for pure phospholipid bilayers formed mainly by transmembrane helices 1 and 7 (TM1/TM5-7) at the dimer interface. In turn, the symmetric TM3,4/TM3,4 interface is enabled first by intercalating cholesterol molecules. These data provide a molecular basis for the modulation of GPCR activity by its lipid environment.

show abstract

“…The sources of error include an algorithmic implementation (Section 3.1.1), appropriate choice of constant temperature scheme (Section 3. 105 and Pluhackova et al 106 were unable to reproduce previously published results using the GROMOS 54A7 lipid force field with recent versions of the GROMACS simulation package (versions 4.5, 4.6 and 5.1.2) 69,107 , suggesting that this model may not reproduce the experimentally observed phase properties of phosphatidylcholine lipid bilayers modelled under certain hydration and temperature conditions. Specifically, it was found that the area per lipid was lower and the degree of acyl chain order greater than expected.…”

Section: Discussionmentioning

confidence: 85%

“…This made the reproduction of previous work with later versions of the code no longer possible and led to false claims regarding the performance of the GROMOS 54A7 lipid parameters. 106 We note that Botan et al 105 recognised the discrepancy between different versions of the code and went to considerable lengths to trace the source of the discrepancy as well as highlighted the problem to the developers of the code. That the true cause of the problem was not identified and addressed points to general challenges in the reference conditions used within both the code development community as well as those involved in force-field development and validation.…”

Section: Discussionmentioning

confidence: 89%

“…Clearly the failure of Botan et al 105 and Pluhackova et al 106 to obtain appropriate values for AL and other properties of a fluid-phase DPPC bilayer at 323 K using the GROMOS 54A7 lipid force field is not due to errors in the original parameterisation, but changes in the integration algorithm within GROMACS. Specifically, with the change in the multiple-time-step algorithm, it is no longer possible to update the long-range forces every 10 fs without severely affecting the outcomes of the simulations.…”

Section: Discussionmentioning

confidence: 99%

See 1 more Smart Citation

Improving the accuracy of molecular dynamics simulations: parameterisation of interaction potentials for small molecules

Stroet¹

View full text Add to dashboard Cite

The ability to accurately describe molecular systems with classical molecular dynamics (MD) is critically dependent on an understanding of the sources of error in the design, evaluation and analysis of the underlying model. One significant source of error is in the degree to which the equations and parameters used to represent atomic interaction can reproduce the experimental properties relevant to a particular application. While highly optimised and well-validated interaction parameters are available for common biomolecules (amino acids, sugars, lipids etc.), this is not the case for heterogeneous small molecules such as co-factors, substrates and drugs. The enormity of the chemical space covered by small molecules necessitates the development of automated approaches to parameterising and validating interaction parameters. Several tools are available that can be used to generate interaction parameters for small molecules compatible with a particular existing (bio)molecular force field. Despite their popularity, many are poorly validated, while some have been shown to be inappropriate for many applications. In other cases, validation studies have demonstrated reasonable performance, however, they also suggest significant improvements can be made. One such tool is the Automated Topology Builder (ATB, http://atb.uq.edu.au/) which provides interaction parameters for small molecules compatible with the GROMOS biomolecular force field.As part of this work, a fully automated protocol for the calculation of solvation energy by thermodynamic integration has been developed and applied to the large-scale validation of the ATB against experimental solvation data in water and hexane. It is shown that the largest errors are due to the Lennard-Jones parameters used for functional groups not present in common biomolecules. Other sources of error included the atomic charges assigned by the ATB for the united atom carbons and incompatibilities between GROMOS Lennard-Jones parameters and the ATB charge model. Significant sources of error were also identified in the evaluation of MD models, both for the calculation of solvation energy as well as for MD simulations of lipid membranes. In particular, the use of multiple-time-step algorithms as a time-saving technique. For the calculation of solvation energy by TI, the twin-range cutoff scheme-commonly used in simulations with the GROMOS force field-was found to introduce a systematic error of about 1 kJ/mol. While for lipid systems, various III changes made to the integration algorithm of the GROMACS simulation code were found to significantly alter the properties of lipid membranes when simulated with identical force fields.Finally, a method for parameterising transferrable interaction potentials with respect to a wide range of target properties is presented. The method is based on an analysis of surfaces corresponding to the difference between calculated and target data as a function of alternative combinations of parameters.The consideration of surfaces in parameter space...

show abstract

A Critical Comparison of Biomembrane Force Fields: Structure and Dynamics of Model DMPC, POPC, and POPE Bilayers

Cited by 148 publications

References 106 publications

On the Calculation of Acyl Chain Order Parameters from Lipid Simulations

On the Calculation of Acyl Chain Order Parameters from Lipid Simulations

Dynamic Cholesterol-Conditioned Dimerization of the G Protein Coupled Chemokine Receptor Type 4

Improving the accuracy of molecular dynamics simulations: parameterisation of interaction potentials for small molecules

Contact Info

Product

Resources

About