Lipid14: The Amber Lipid Force Field

Dickson, Callum J.; Madej, Benjamin D.; Skjevik, Åge A.; Betz, Robin M.; Teigen, Knut; Gould, Ian R.; Walker, Ross C.

doi:10.1021/ct4010307

Cited by 1,081 publications

(1,068 citation statements)

References 108 publications

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“…Other examples of yet different simulation approaches reported a value of 62.3 ± 0.4 Å 2 for POPE at 30°C based on transferable potentials for phase equilibria, 22 and 55.5 ± 0.2 Å 2 at 37°C using Lipid14 of the AMBER lipid force field. 24 Among experimental studies, Pabst et al 68 derived an area of 52 ± 1Å 2 for DPPE at 75°C. However, this value is low compared to our estimated area of 60.3 Å 2 for DLPE bilayers extrapolated to the same temperature (see Figure 6).…”

Section: ■ Materials and Methodsmentioning

confidence: 99%

Molecular Structures of Fluid Phosphatidylethanolamine Bilayers Obtained from Simulation-to-Experiment Comparisons and Experimental Scattering Density Profiles

et al. 2014

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Vous avez des questions? Nous pouvons vous aider. Pour communiquer directement avec un auteur, consultez la première page de la revue dans laquelle son article a été publié afin de trouver ses coordonnées. Si vous n'arrivez pas à les repérer, communiquez avec nous à PublicationsArchive-ArchivesPublications@nrc-cnrc.gc.ca. Questions? Contact the NRC Publications Archive team atPublicationsArchive-ArchivesPublications@nrc-cnrc.gc.ca. If you wish to email the authors directly, please see the first page of the publication for their contact information. NRC Publications Archive Archives des publications du CNRCThis publication could be one of several versions: author's original, accepted manuscript or the publisher's version. / La version de cette publication peut être l'une des suivantes : la version prépublication de l'auteur, la version acceptée du manuscrit ou la version de l'éditeur. For the publisher's version, please access the DOI link below./ Pour consulter la version de l'éditeur, utilisez le lien DOI ci-dessous.http://doi.org/10.1021/jp511159qAccess and use of this website and the material on it are subject to the Terms and Conditions set forth at NRC Publications Record / Notice d'Archives des publications de CNRC:http://nparc.cisti-icist.nrc-cnrc.gc.ca/eng/view/object/?id=9f16af25-9d91-47f7-b19b-387fe4c4022b http://nparc.cisti-icist.nrc-cnrc.gc.ca/fra/voir/objet/?id=9f16af25-9d91-47f7-b19b-387fe4c4022b ABSTRACT: Following our previous efforts in determining the structures of commonly used PC, PG, and PS bilayers, we continue our studies of fully hydrated, fluid phase PE bilayers. The newly designed parsing scheme for PE bilayers was based on extensive MD simulations, and is utilized in the SDP analysis of both X-ray and neutron (contrast varied) scattering measurements. Obtained experimental scattering form factors are directly compared to our simulation results, and can serve as a benchmark for future developed force fields. Among the evaluated structural parameters, namely, area per lipid A, overall bilayer thickness D B , and hydrocarbon region thickness 2D C , the PE bilayer response to changing temperature is similar to previously studied bilayers with different headgroups. On the other hand, the reduced hydration of PE headgroups, as well as the strong hydrogen bonding between PE headgroups, dramatically affects lateral packing within the bilayer. Despite sharing the same glycerol backbone, a markedly smaller area per lipid distinguishes PE from other bilayers (i.e., PC, PG, and PS) studied to date. Overall, our data are consistent with the notion that lipid headgroups govern bilayer packing, while hydrocarbon chains dominate the bilayer's response to temperature changes. ■ INTRODUCTIONMembranes that surround cells and separate their contents from the external environment are ubiquitous in nature. Biological membranes consist mainly of lipids and proteins, where it is widely accepted that the membrane's underlying structure is imparted by the lipid bilayer. As such, tremendous effort has been expe...

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Section: ■ Materials and Methodsmentioning

confidence: 99%

Molecular Structures of Fluid Phosphatidylethanolamine Bilayers Obtained from Simulation-to-Experiment Comparisons and Experimental Scattering Density Profiles

et al. 2014

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“…21 We should note that Lipid14 was tested and validated for several models of lipid membranes, including the one used here, the DOPC bilayer. Four copies of the previously equilibrated Penetratin were taken, randomly rotated, and placed in a TIP3P water box, maximally away from each other and from the membrane.…”

Section: A Molecular Dynamicsmentioning

confidence: 99%

Structure and dynamics of Penetratin’s association and translocation to a lipid bilayer

General

Asciutto

2017

AIP Advances

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Penetratin belongs to the important class of small and positively charged peptides, capable of entering cells. The determination of the optimal peptidic structure for translocation is challenging; results obtained so far are varied and dependent on several factors. In this work, we review the dynamics of association of Penetratin with a modeled dioleoyl-phosphatidylcholine (DOPC) lipid membrane using molecular dynamics simulations with last generation force fields. Penetratin’s structural preferences are determined using a Markov state model. It is observed that the peptide retains a helical form in the membrane associated state, just as in water, with the exception of both termini which lose helicity, facilitating the interaction of terminal residues with the phosphate groups on the membrane’s outer layer. The optimal orientation for insertion is found to be with the peptide’s axis forming a small angle with the interface, and with R1 stretching toward the bilayer. The interaction between arginine side-chains and phosphate groups is found to be greater than the corresponding to lysine, mainly due to a higher number of hydrogen bonds between them. The free energy profile of translocation is qualitatively studied using Umbrella Sampling. It is found that there are different paths of penetration, that greatly differ in size of free energy barrier. The lowest path is compatible with residues R10 to K13 leading the way through the membrane and pulling the rest of the peptide. When the other side is reached, the C-terminus overtakes those residues, and finally breaks out of the membrane. The peptide’s secondary structure during this traversal suffers some changes with respect to the association structure but, overall, conserves its helicity, with both termini in a more disordered state.

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“…Geometrically, these equations define two planes with the vectors u⃗1 and u⃗2 which are orthogonal to the corresponding plane. The GA solutions align along a three-dimensional line formed by the intersection of these two planes ( Figure 4A) which is defined by the cross product vector u⃗3 = u⃗1 × u⃗2: (18) where t is a free parameter, the vector q⃗0 is a set of point charges that satisfies eqs 16 and 17. Projections of this three-dimensional line give three pairwise linear relationships between each pair of the atomic charges ( Figure 4B, Figure S3 in the Supporting Information); for example, a projection on the (qC, qH) plane results in a linear correlation between qC and qH.…”

Section: Ga Charge Fitting For Small Modelsmentioning

confidence: 99%

Genetic Algorithm Optimization of Point Charges in Force Field Development: Challenges and Insights

2015

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Evolutionary methods, such as genetic algorithms (GAs), provide powerful tools for optimization of the force field parameters, especially in the case of simultaneous fitting of the force field terms against extensive reference data. However, GA fitting of the nonbonded interaction parameters that includes point charges has not been explored in the literature, likely due to numerous difficulties with even a simpler problem of the least-squares fitting of the atomic point charges against a reference molecular electrostatic potential (MEP), which often demonstrates an unusually high variation of the fitted charges on buried atoms. Here, we examine the performance of the GA approach for the least-squares MEP point charge fitting, and show that the GA optimizations suffer from a magnified version of the classical buried atom effect, producing highly scattered yet correlated solutions. This effect can be understood in terms of the linearly independent, natural coordinates of the MEP fitting problem defined by the eigenvectors of the least-squares sum Hessian matrix, which are also equivalent to the eigenvectors of the covariance matrix evaluated for the scattered GA solutions. GAs quickly converge with respect to the high-curvature coordinates defined by the eigenvectors related to the leading terms of the multipole expansion, but have difficulty converging with respect to the low-curvature coordinates that mostly depend on the buried atom charges. The performance of the evolutionary techniques dramatically improves when the point charge optimization is performed using the Hessian or covariance matrix eigenvectors, an approach with a significant potential for the evolutionary optimization of the fixed-charge biomolecular force fields.

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Lipid14: The Amber Lipid Force Field

Cited by 1,081 publications

References 108 publications

Molecular Structures of Fluid Phosphatidylethanolamine Bilayers Obtained from Simulation-to-Experiment Comparisons and Experimental Scattering Density Profiles

Molecular Structures of Fluid Phosphatidylethanolamine Bilayers Obtained from Simulation-to-Experiment Comparisons and Experimental Scattering Density Profiles

Structure and dynamics of Penetratin’s association and translocation to a lipid bilayer

Genetic Algorithm Optimization of Point Charges in Force Field Development: Challenges and Insights

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