Limits...
COFFDROP: A Coarse-Grained Nonbonded Force Field for Proteins Derived from All-Atom Explicit-Solvent Molecular Dynamics Simulations of Amino Acids.

Andrews CT, Elcock AH - J Chem Theory Comput (2014)

Bottom Line: In a first test of the force field, it was used to predict the clustering behavior of concentrated amino acid solutions; the predictions were directly compared with the results of corresponding all-atom explicit-solvent MD simulations and found to be in excellent agreement.The anomalously strong intermolecular interactions seen in the MD study were reproduced in the COFFDROP simulations; a simple scaling of COFFDROP's nonbonded parameters, however, produced results in better accordance with experiment.Overall, our results suggest that potential functions derived from simulations of pairwise amino acid interactions might be of quite broad applicability, with COFFDROP likely to be especially useful for modeling unfolded or intrinsically disordered proteins.

View Article: PubMed Central - PubMed

Affiliation: Department of Biochemistry, University of Iowa , Iowa City, Iowa 52242, United States.

ABSTRACT
We describe the derivation of a set of bonded and nonbonded coarse-grained (CG) potential functions for use in implicit-solvent Brownian dynamics (BD) simulations of proteins derived from all-atom explicit-solvent molecular dynamics (MD) simulations of amino acids. Bonded potential functions were derived from 1 μs MD simulations of each of the 20 canonical amino acids, with histidine modeled in both its protonated and neutral forms; nonbonded potential functions were derived from 1 μs MD simulations of every possible pairing of the amino acids (231 different systems). The angle and dihedral probability distributions and radial distribution functions sampled during MD were used to optimize a set of CG potential functions through use of the iterative Boltzmann inversion (IBI) method. The optimized set of potential functions-which we term COFFDROP (COarse-grained Force Field for Dynamic Representation Of Proteins)-quantitatively reproduced all of the "target" MD distributions. In a first test of the force field, it was used to predict the clustering behavior of concentrated amino acid solutions; the predictions were directly compared with the results of corresponding all-atom explicit-solvent MD simulations and found to be in excellent agreement. In a second test, BD simulations of the small protein villin headpiece were carried out at concentrations that have recently been studied in all-atom explicit-solvent MD simulations by Petrov and Zagrovic (PLoS Comput. Biol. 2014, 5, e1003638). The anomalously strong intermolecular interactions seen in the MD study were reproduced in the COFFDROP simulations; a simple scaling of COFFDROP's nonbonded parameters, however, produced results in better accordance with experiment. Overall, our results suggest that potential functions derived from simulations of pairwise amino acid interactions might be of quite broad applicability, with COFFDROP likely to be especially useful for modeling unfolded or intrinsically disordered proteins.

No MeSH data available.


Translationaldiffusion coefficients and association kinetics ofamino acids calculated from all-atom MD simulations. (A) Translationaldiffusion coefficients of 12 amino acids calculated from MD and comparedto experimental data from Longsworth.97 Each symbol is labeled using the one letter amino acid code. (B)Plot showing the correlation between the calculated effective associationrate constant (kon) and the sum of theindividual amino acid translational diffusion coefficients. Each symbolrepresents a different amino acid pair.
© Copyright Policy
Related In: Results  -  Collection

License
getmorefigures.php?uid=PMC4230375&req=5

fig1: Translationaldiffusion coefficients and association kinetics ofamino acids calculated from all-atom MD simulations. (A) Translationaldiffusion coefficients of 12 amino acids calculated from MD and comparedto experimental data from Longsworth.97 Each symbol is labeled using the one letter amino acid code. (B)Plot showing the correlation between the calculated effective associationrate constant (kon) and the sum of theindividual amino acid translational diffusion coefficients. Each symbolrepresents a different amino acid pair.

Mentions: We deal with kinetic aspects first. In previouswork we showed that the effective association rate constants of smallaliphatic hydrocarbons appear to be diffusion-limited.82 To determine if the same is true for the cappedamino acids studied here, we first computed the translational diffusioncoefficients of the isolated amino acids using the Einstein diffusionequation (see Methods). Encouragingly, forthe 12 amino acids that were studied experimentally by Longsworth,97 we obtain excellent agreement between the simulatedand experimental values (r2 = 0.97, Figure 1A). Despite this good agreement, it is noticeablethat the MD values are uniformly lower than the corresponding experimentalvalues (the slope of the regression line is 0.66). This is likelydue to a combination of the following two factors: (a) the simulatedamino acids possess capping groups (which double the molecular massfor glycine for example); (b) simulated translational diffusion coefficientsare known to be subject to a system-size dependent slowdown when periodicboundary conditions are imposed.98 Thesetwo factors appear to outweigh the compensating effect of the TIP4P-Ewwater model’s viscosity being somewhat lower (0.742 mPa)99 than the experimental value (0.899 mPa)100 at 298 K. Having determined the translationdiffusion coefficient of each amino acid, we could determine whetherassociation of amino acid pairs is diffusion-limited by comparingthe computed effective association rate constants (see Methods) with the sums of the translational diffusion coefficientsof the two amino acids. Such a comparison is shown in Figure 1B; the linear regression gives r2 = 0.69 with p < 0.001, which suggeststhat such associations are in general effectively diffusion-limited.


COFFDROP: A Coarse-Grained Nonbonded Force Field for Proteins Derived from All-Atom Explicit-Solvent Molecular Dynamics Simulations of Amino Acids.

Andrews CT, Elcock AH - J Chem Theory Comput (2014)

Translationaldiffusion coefficients and association kinetics ofamino acids calculated from all-atom MD simulations. (A) Translationaldiffusion coefficients of 12 amino acids calculated from MD and comparedto experimental data from Longsworth.97 Each symbol is labeled using the one letter amino acid code. (B)Plot showing the correlation between the calculated effective associationrate constant (kon) and the sum of theindividual amino acid translational diffusion coefficients. Each symbolrepresents a different amino acid pair.
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4230375&req=5

fig1: Translationaldiffusion coefficients and association kinetics ofamino acids calculated from all-atom MD simulations. (A) Translationaldiffusion coefficients of 12 amino acids calculated from MD and comparedto experimental data from Longsworth.97 Each symbol is labeled using the one letter amino acid code. (B)Plot showing the correlation between the calculated effective associationrate constant (kon) and the sum of theindividual amino acid translational diffusion coefficients. Each symbolrepresents a different amino acid pair.
Mentions: We deal with kinetic aspects first. In previouswork we showed that the effective association rate constants of smallaliphatic hydrocarbons appear to be diffusion-limited.82 To determine if the same is true for the cappedamino acids studied here, we first computed the translational diffusioncoefficients of the isolated amino acids using the Einstein diffusionequation (see Methods). Encouragingly, forthe 12 amino acids that were studied experimentally by Longsworth,97 we obtain excellent agreement between the simulatedand experimental values (r2 = 0.97, Figure 1A). Despite this good agreement, it is noticeablethat the MD values are uniformly lower than the corresponding experimentalvalues (the slope of the regression line is 0.66). This is likelydue to a combination of the following two factors: (a) the simulatedamino acids possess capping groups (which double the molecular massfor glycine for example); (b) simulated translational diffusion coefficientsare known to be subject to a system-size dependent slowdown when periodicboundary conditions are imposed.98 Thesetwo factors appear to outweigh the compensating effect of the TIP4P-Ewwater model’s viscosity being somewhat lower (0.742 mPa)99 than the experimental value (0.899 mPa)100 at 298 K. Having determined the translationdiffusion coefficient of each amino acid, we could determine whetherassociation of amino acid pairs is diffusion-limited by comparingthe computed effective association rate constants (see Methods) with the sums of the translational diffusion coefficientsof the two amino acids. Such a comparison is shown in Figure 1B; the linear regression gives r2 = 0.69 with p < 0.001, which suggeststhat such associations are in general effectively diffusion-limited.

Bottom Line: In a first test of the force field, it was used to predict the clustering behavior of concentrated amino acid solutions; the predictions were directly compared with the results of corresponding all-atom explicit-solvent MD simulations and found to be in excellent agreement.The anomalously strong intermolecular interactions seen in the MD study were reproduced in the COFFDROP simulations; a simple scaling of COFFDROP's nonbonded parameters, however, produced results in better accordance with experiment.Overall, our results suggest that potential functions derived from simulations of pairwise amino acid interactions might be of quite broad applicability, with COFFDROP likely to be especially useful for modeling unfolded or intrinsically disordered proteins.

View Article: PubMed Central - PubMed

Affiliation: Department of Biochemistry, University of Iowa , Iowa City, Iowa 52242, United States.

ABSTRACT
We describe the derivation of a set of bonded and nonbonded coarse-grained (CG) potential functions for use in implicit-solvent Brownian dynamics (BD) simulations of proteins derived from all-atom explicit-solvent molecular dynamics (MD) simulations of amino acids. Bonded potential functions were derived from 1 μs MD simulations of each of the 20 canonical amino acids, with histidine modeled in both its protonated and neutral forms; nonbonded potential functions were derived from 1 μs MD simulations of every possible pairing of the amino acids (231 different systems). The angle and dihedral probability distributions and radial distribution functions sampled during MD were used to optimize a set of CG potential functions through use of the iterative Boltzmann inversion (IBI) method. The optimized set of potential functions-which we term COFFDROP (COarse-grained Force Field for Dynamic Representation Of Proteins)-quantitatively reproduced all of the "target" MD distributions. In a first test of the force field, it was used to predict the clustering behavior of concentrated amino acid solutions; the predictions were directly compared with the results of corresponding all-atom explicit-solvent MD simulations and found to be in excellent agreement. In a second test, BD simulations of the small protein villin headpiece were carried out at concentrations that have recently been studied in all-atom explicit-solvent MD simulations by Petrov and Zagrovic (PLoS Comput. Biol. 2014, 5, e1003638). The anomalously strong intermolecular interactions seen in the MD study were reproduced in the COFFDROP simulations; a simple scaling of COFFDROP's nonbonded parameters, however, produced results in better accordance with experiment. Overall, our results suggest that potential functions derived from simulations of pairwise amino acid interactions might be of quite broad applicability, with COFFDROP likely to be especially useful for modeling unfolded or intrinsically disordered proteins.

No MeSH data available.