Testing of the GROMOS Force-Field Parameter Set 54A8: Structural Properties of Electrolyte Solutions, Lipid Bilayers, and Proteins

Reif, Maria M.; Winger, Moritz; Oostenbrink, Chris

doi:10.1021/ct300874c

Cited by 95 publications

(108 citation statements)

References 104 publications

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“…19 The analysis was performed with both libraries of DISICL (summarized in Table 5), as well as DSSP and STRIDE (Tables S9 and S10, Supporting Information). While differing greatly for individual proteins, the overall content of structural elements was similar to the analysis of the PDB data sets for all three algorithms and the same holds for their correlations.…”

Section: Resultsmentioning

confidence: 99%

Dihedral-Based Segment Identification and Classification of Biopolymers I: Proteins

Nagy

Oostenbrink

2014

J. Chem. Inf. Model.

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A new structure classification scheme for biopolymers is introduced, which is solely based on main-chain dihedral angles. It is shown that by dividing a biopolymer into segments containing two central residues, a local classification can be performed. The method is referred to as DISICL, short for Dihedral-based Segment Identification and Classification. Compared to other popular secondary structure classification programs, DISICL is more detailed as it offers 18 distinct structural classes, which may be simplified into a classification in terms of seven more general classes. It was designed with an eye to analyzing subtle structural changes as observed in molecular dynamics simulations of biomolecular systems. Here, the DISICL algorithm is used to classify two databases of protein structures, jointly containing more than 10 million segments. The data is compared to two alternative approaches in terms of the amount of classified residues, average occurrence and length of structural elements, and pair wise matches of the classifications by the different programs. In an accompanying paper (Nagy, G.; Oostenbrink, C. Dihedral-based segment identification and classification of biopolymers II: Polynucleotides. J. Chem. Inf. Model. 2013, DOI: 10.1021/ci400542n), the analysis of polynucleotides is described and applied. Overall, DISICL represents a potentially useful tool to analyze biopolymer structures at a high level of detail.

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Section: Resultsmentioning

confidence: 99%

Dihedral-Based Segment Identification and Classification of Biopolymers I: Proteins

Nagy

Oostenbrink

2014

J. Chem. Inf. Model.

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“…Potential candidates are, e.g., discrepancies in the ion models [109][110][111] , incomplete treatment of electronic polarizability 112 , and inaccuracies in the lipid headgroup description 45 .…”

Section: Cation Binding In Different Simulation Modelsmentioning

confidence: 99%

Molecular electrometer and binding of cations to phospholipid bilayers

Catte

Girych

Javanainen

et al. 2016

Phys. Chem. Chem. Phys.

256

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Despite the vast amount of experimental and theoretical studies on the binding affinity of cations -especially the biologically relevant Na + and Ca 2+ -for phospholipid bilayers, there is no consensus in the literature. Here we show that by interpreting changes in the choline headgroup order parameters according to the 'molecular electrometer' concept [Seelig et al., Biochemistry, 1987, 26, 7535], one can directly compare the ion binding affinities between simulations and experiments. Our findings strongly support the view that in contrast to Ca 2+ and other multivalent ions, Na + and other monovalent ions (except Li + ) do not specifically bind to phosphatidylcholine lipid bilayers at sub-molar concentrations. However, the Na + binding affinity was overestimated by several molecular dynamics simulation models, resulting in artificially positively charged bilayers and exaggerated structural effects in the lipid headgroups. While qualitatively correct headgroup order parameter response was observed with Ca 2+ binding in all the tested models, no model had sufficient quantitative accuracy to interpret the Ca 2+ :lipid stoichiometry or the induced atomistic resolution structural changes. All scientific contributions to this open collaboration work were made publicly, using nmrlipids.blogspot.fi as the main communication platform.

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“…The validity of this assumption was tested explicitly in numerous simulations of complex molecular systems, including solvated biomolecules. 67,[78][79][80][81][82][83] The most recent major reparametrization of the GROMOS force field 63 has led to two distinct parameter sets labelled 53A5 and 53A6, exclusively differing in the atomic partial charges within polar functional groups. Set 53A5, which was calibrated to reproduce the densities and vaporization enthalpies of pure liquids, was recommended for the simulation of organic liquids and liquid mixtures.…”

Section: Introductionmentioning

confidence: 99%

A GROMOS-Compatible Force Field for Small Organic Molecules in the Condensed Phase: The 2016H66 Parameter Set

Horta

Merz

Fuchs

et al. 2016

J. Chem. Theory Comput.

147

287

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This article reports on the calibration and validation of a new GROMOS-compatible parameter set 2016H66 for small organic molecules in the condensed phase. The calibration is based on 62 organic molecules spanning the chemical functions alcohol, ether, aldehyde, ketone, carboxylic acid, ester, amine, amide, thiol, sulfide, and disulfide, as well as aromatic compounds and nucleic-acid bases. For 57 organic compounds, the calibration targets are the experimental pure-liquid density ρliq and the vaporization enthalpy ΔHvap, as well as the hydration free energy ΔGwat and the solvation free energy ΔGche in cyclohexane, at atmospheric pressure and at (or close to) room temperature. The final root-mean-square deviations (RMSD) for these four quantities over the set of compounds are 32.4 kg m(-3), 3.5 kJ mol(-1), 4.1 kJ mol(-1), and 2.1 kJ mol(-1), respectively, and the corresponding average deviations (AVED) are 1.0 kg m(-3), 0.2 kJ mol(-1), 2.6 kJ mol(-1), and 1.0 kJ mol(-1), respectively. For the five nucleic-acid bases, the parametrization is performed by transferring the final 2016H66 parameters from analogous organic compounds followed by a slight readjustment of the charges to reproduce the experimental water-to-chloroform transfer free energies ΔGtrn. The final RMSD for this quantity over the five bases is 1.7 kJ mol(-1), and the corresponding AVED is 0.8 kJ mol(-1). As an initial validation of the 2016H66 set, seven additional thermodynamic, transport, and dielectric properties are calculated for the 57 organic compounds in the liquid phase. The agreement with experiment in terms of these additional properties is found to be reasonable, with significant deviations typically affecting either a specific chemical function or a specific molecule. This suggests that in most cases, a classical force-field description along with a careful parametrization against ρliq, ΔHvap, ΔGwat, and ΔGche results in a model that appropriately describes the liquid in terms of a wide spectrum of its physical properties.

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Testing of the GROMOS Force-Field Parameter Set 54A8: Structural Properties of Electrolyte Solutions, Lipid Bilayers, and Proteins

Cited by 95 publications

References 104 publications

Dihedral-Based Segment Identification and Classification of Biopolymers I: Proteins

Dihedral-Based Segment Identification and Classification of Biopolymers I: Proteins

Molecular electrometer and binding of cations to phospholipid bilayers

A GROMOS-Compatible Force Field for Small Organic Molecules in the Condensed Phase: The 2016H66 Parameter Set

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