scholarly journals Predicting NMR Relaxation of Proteins from Molecular Dynamics Simulations with Accurate Methyl Rotation Barriers

2019 ◽  
Author(s):  
Falk Hoffmann ◽  
Frans Mulder ◽  
Lars V. Schäfer
Keyword(s):  
Molecular Dynamics ◽  
Force Field ◽  
Force Fields ◽  
Nmr Relaxation ◽  
Md Simulations ◽  
Quantitative Agreement ◽  
Relaxation Rates ◽  
Protein Force Fields ◽  
Dynamics Simulations ◽  
Methyl Rotation

The internal dynamics of proteins occurring on time scales from picoseconds to nanoseconds can be sensitively probed by nuclear magnetic resonance (NMR) spin relaxation experiments, as well as by molecular dynamics (MD) simulations. This complementarity offers unique opportunities, provided that the two methods are compared at a suitable level. Recently, several groups have used MD simulations to compute the spectral density of backbone and side-chain molecular motions, and to predict NMR relaxation rates from these. Unfortunately, in the case of methyl groups in protein side-chains, inaccurate energy barriers to methyl rotation were responsible for a systematic discrepancy in the computed relaxation rates, as demonstrated for the AMBER ff99SB*-ILDN force field (and related parameter sets), impairing quantitative agreement between simulations and experiments. However, correspondence could be regained by emending the MD force field with accurate coupled cluster quantum chemical calculations. Spurred by this positive result, we tested whether this approach could be generally applicable, in spite of the fact that different MD force fields employ different water models. Improved methyl group rotation barriers for the CHARMM36 and AMBER ff15ipq protein force fields were derived, such that the NMR relaxation data obtained from the MD simulations now also display very good agreement with experiment. Results herein showcase the performance of present-day MD force fields, and manifest their refined ability to accurately describe internal protein dynamics.

scholarly journals Predicting NMR Relaxation of Proteins from Molecular Dynamics Simulations with Accurate Methyl Rotation Barriers

2020 ◽  
Author(s):  
Falk Hoffmann ◽  
Frans Mulder ◽  
Lars V. Schäfer
Keyword(s):  
Molecular Dynamics ◽  
Force Field ◽  
Force Fields ◽  
Nmr Relaxation ◽  
Md Simulations ◽  
Quantitative Agreement ◽  
Relaxation Rates ◽  
Protein Force Fields ◽  
Dynamics Simulations ◽  
Methyl Rotation

The internal dynamics of proteins occurring on time scales from picoseconds to nanoseconds can be sensitively probed by nuclear magnetic resonance (NMR) spin relaxation experiments, as well as by molecular dynamics (MD) simulations. This complementarity offers unique opportunities, provided that the two methods are compared at a suitable level. Recently, several groups have used MD simulations to compute the spectral density of backbone and side-chain molecular motions, and to predict NMR relaxation rates from these. Unfortunately, in the case of methyl groups in protein side-chains, inaccurate energy barriers to methyl rotation were responsible for a systematic discrepancy in the computed relaxation rates, as demonstrated for the AMBER ff99SB*-ILDN force field (and related parameter sets), impairing quantitative agreement between simulations and experiments. However, correspondence could be regained by emending the MD force field with accurate coupled cluster quantum chemical calculations. Spurred by this positive result, we tested whether this approach could be generally applicable, in spite of the fact that different MD force fields employ different water models. Improved methyl group rotation barriers for the CHARMM36 and AMBER ff15ipq protein force fields were derived, such that the NMR relaxation data obtained from the MD simulations now also display very good agreement with experiment. Results herein showcase the performance of present-day MD force fields, and manifest their refined ability to accurately describe internal protein dynamics.

scholarly journals Predicting NMR Relaxation of Proteins from Molecular Dynamics Simulations with Accurate Methyl Rotation Barriers

2019 ◽  
Author(s):  
Falk Hoffmann ◽  
Frans Mulder ◽  
Lars V. Schäfer
Keyword(s):  
Molecular Dynamics ◽  
Force Field ◽  
Force Fields ◽  
Nmr Relaxation ◽  
Md Simulations ◽  
Quantitative Agreement ◽  
Relaxation Rates ◽  
Protein Force Fields ◽  
Dynamics Simulations ◽  
Methyl Rotation

The internal dynamics of proteins occurring on time scales from picoseconds to nanoseconds can be sensitively probed by nuclear magnetic resonance (NMR) spin relaxation experiments, as well as by molecular dynamics (MD) simulations. This complementarity offers unique opportunities, provided that the two methods are compared at a suitable level. Recently, several groups have used MD simulations to compute the spectral density of backbone and side-chain molecular motions, and to predict NMR relaxation rates from these. Unfortunately, in the case of methyl groups in protein side-chains, inaccurate energy barriers to methyl rotation were responsible for a systematic discrepancy in the computed relaxation rates, as demonstrated for the AMBER ff99SB*-ILDN force field (and related parameter sets), impairing quantitative agreement between simulations and experiments. However, correspondence could be regained by emending the MD force field with accurate coupled cluster quantum chemical calculations. Spurred by this positive result, we tested whether this approach could be generally applicable, in spite of the fact that different MD force fields employ different water models. Improved methyl group rotation barriers for the CHARMM36 and AMBER ff15ipq protein force fields were derived, such that the NMR relaxation data obtained from the MD simulations now also display very good agreement with experiment. Results herein showcase the performance of present-day MD force fields, and manifest their refined ability to accurately describe internal protein dynamics.

scholarly journals Predicting NMR Relaxation of Proteins from Molecular Dynamics Simulations with Accurate Methyl Rotation Barriers

2019 ◽  
Author(s):  
Falk Hoffmann ◽  
Frans Mulder ◽  
Lars V. Schäfer
Keyword(s):  
Molecular Dynamics ◽  
Force Field ◽  
Force Fields ◽  
Nmr Relaxation ◽  
Md Simulations ◽  
Quantitative Agreement ◽  
Relaxation Rates ◽  
Protein Force Fields ◽  
Dynamics Simulations ◽  
Methyl Rotation

The internal dynamics of proteins occurring on time scales from picoseconds to nanoseconds can be sensitively probed by nuclear magnetic resonance (NMR) spin relaxation experiments, as well as by molecular dynamics (MD) simulations. This complementarity offers unique opportunities, provided that the two methods are compared at a suitable level. Recently, several groups have used MD simulations to compute the spectral density of backbone and side-chain molecular motions, and to predict NMR relaxation rates from these. Unfortunately, in the case of methyl groups in protein side-chains, inaccurate energy barriers to methyl rotation were responsible for a systematic discrepancy in the computed relaxation rates, as demonstrated for the AMBER ff99SB*-ILDN force field (and related parameter sets), impairing quantitative agreement between simulations and experiments. However, correspondence could be regained by emending the MD force field with accurate coupled cluster quantum chemical calculations. Spurred by this positive result, we tested whether this approach could be generally applicable, in spite of the fact that different MD force fields employ different water models. Improved methyl group rotation barriers for the CHARMM36 and AMBER ff15ipq protein force fields were derived, such that the NMR relaxation data obtained from the MD simulations now also display very good agreement with experiment. Results herein showcase the performance of present-day MD force fields, and manifest their refined ability to accurately describe internal protein dynamics.

scholarly journals Predicting NMR Relaxation of Proteins from Molecular Dynamics Simulations with Accurate Methyl Rotation Barriers

2020 ◽  
Author(s):  
Falk Hoffmann ◽  
Frans Mulder ◽  
Lars V. Schäfer
Keyword(s):  
Molecular Dynamics ◽  
Force Field ◽  
Force Fields ◽  
Nmr Relaxation ◽  
Md Simulations ◽  
Quantitative Agreement ◽  
Relaxation Rates ◽  
Protein Force Fields ◽  
Dynamics Simulations ◽  
Methyl Rotation

The internal dynamics of proteins occurring on time scales from picoseconds to nanoseconds can be sensitively probed by nuclear magnetic resonance (NMR) spin relaxation experiments, as well as by molecular dynamics (MD) simulations. This complementarity offers unique opportunities, provided that the two methods are compared at a suitable level. Recently, several groups have used MD simulations to compute the spectral density of backbone and side-chain molecular motions, and to predict NMR relaxation rates from these. Unfortunately, in the case of methyl groups in protein side-chains, inaccurate energy barriers to methyl rotation were responsible for a systematic discrepancy in the computed relaxation rates, as demonstrated for the AMBER ff99SB*-ILDN force field (and related parameter sets), impairing quantitative agreement between simulations and experiments. However, correspondence could be regained by emending the MD force field with accurate coupled cluster quantum chemical calculations. Spurred by this positive result, we tested whether this approach could be generally applicable, in spite of the fact that different MD force fields employ different water models. Improved methyl group rotation barriers for the CHARMM36 and AMBER ff15ipq protein force fields were derived, such that the NMR relaxation data obtained from the MD simulations now also display very good agreement with experiment. Results herein showcase the performance of present-day MD force fields, and manifest their refined ability to accurately describe internal protein dynamics.

Predicting NMR Relaxation of Proteins from Molecular Dynamics Simulations with Accurate Methyl Rotation Barriers

2020 ◽  
Author(s):  
Falk Hoffmann ◽  
Frans Mulder ◽  
Lars V. Schäfer
Keyword(s):  
Molecular Dynamics ◽  
Force Field ◽  
Force Fields ◽  
Nmr Relaxation ◽  
Md Simulations ◽  
Quantitative Agreement ◽  
Relaxation Rates ◽  
Protein Force Fields ◽  
Dynamics Simulations ◽  
Methyl Rotation

The internal dynamics of proteins occurring on time scales from picoseconds to nanoseconds can be sensitively probed by nuclear magnetic resonance (NMR) spin relaxation experiments, as well as by molecular dynamics (MD) simulations. This complementarity offers unique opportunities, provided that the two methods are compared at a suitable level. Recently, several groups have used MD simulations to compute the spectral density of backbone and side-chain molecular motions, and to predict NMR relaxation rates from these. Unfortunately, in the case of methyl groups in protein side-chains, inaccurate energy barriers to methyl rotation were responsible for a systematic discrepancy in the computed relaxation rates, as demonstrated for the AMBER ff99SB*-ILDN force field (and related parameter sets), impairing quantitative agreement between simulations and experiments. However, correspondence could be regained by emending the MD force field with accurate coupled cluster quantum chemical calculations. Spurred by this positive result, we tested whether this approach could be generally applicable, in spite of the fact that different MD force fields employ different water models. Improved methyl group rotation barriers for the CHARMM36 and AMBER ff15ipq protein force fields were derived, such that the NMR relaxation data obtained from the MD simulations now also display very good agreement with experiment. Results herein showcase the performance of present-day MD force fields, and manifest their refined ability to accurately describe internal protein dynamics.

Structure and Dynamics of Spherical and Rodlike Alkyl Ethoxylate Surfactant Micelles Investigated Using NMR Relaxation and Atomistic Molecular Dynamics Simulations

2019 ◽  
Author(s):  
Allison Edwards ◽  
Abdolreza Javidialesaadi ◽  
Katie Weigandt ◽  
George Stan ◽  
Charles Eads
Keyword(s):  
Molecular Dynamics ◽  
Molecular Dynamics Simulations ◽  
Nmr Relaxation ◽  
Cross Relaxation ◽  
Relaxation Rates ◽  
Surfactant Micelles ◽  
Cylindrical Micelles ◽  
Spherical Micelles ◽  
Dynamics Simulations ◽  
Relative Motions

We study molecular arrangements and dynamics in alkyl ethoxylate nonionic surfactant micelles by combining high field (600 and 700 MHz) NMR relaxation measurements with large-scale atomistic molecular dynamics simulations. For spherical micelles, but not for cylindrical micelles, cross relaxation rates are positive only for surfactant alkyl tail atoms connected to the hydrophilic head group. All cross relaxation rates are negative for cylindrical micelles. This effect is reproducible either by changing composition (ratios of the nonionic surfactants) or changing temperature of a single surfactant in order to change the micelle shape. We validate the micelle shape by SANS and use the results as a guide for our simulations. We calculate parameters that determine relaxation rates directly from simulated trajectories, without introducing specific functional forms. Results indicate that relative motions of nearby atoms are liquid-like, in agreement with 13C T1 measurements, though constrained by micelle morphology. Relative motions of distant atoms have slower components because the relative changes in distances and angles are smaller when the moving atoms are further apart. The slow, long-range motions appear to be responsible for the predominantly negative cross relaxation rates observed in NOESY spectra. The densities of atoms from positions 1 and 2 in the boundary region are lower in spherical micelles compared to cylindrical micelles. Correspondingly, motions in this region are less constrained by micelle morphology in the spherical compared to the cylindrical cases. The two effects of morphology lead to the unusual occurrence of positive cross relaxation involving positions 1 and 2 for spheres.

scholarly journals Different force fields give rise to different amyloid aggregation pathways in molecular dynamics simulations

2020 ◽  
Author(s):  
Suman Samantray ◽  
Feng Yin ◽  
Batuhan Kav ◽  
Birgit Strodel
Keyword(s):  
Molecular Dynamics ◽  
Force Field ◽  
Intrinsically Disordered Proteins ◽  
Force Fields ◽  
Md Simulations ◽  
Peptide Sequence ◽  
Disordered Proteins ◽  
Test Case ◽  
Peptide Aggregation ◽  
Intrinsically Disordered

AbstractThe progress towards understanding the molecular basis of Alzheimers’s disease is strongly connected to elucidating the early aggregation events of the amyloid-β (Aβ) peptide. Molecular dynamics (MD) simulations provide a viable technique to study the aggregation of Aβ into oligomers with high spatial and temporal resolution. However, the results of an MD simulation can only be as good as the underlying force field. A recent study by our group showed that none of the force fields tested can distinguish between aggregation-prone and non-aggregating peptide sequences, producing the same and in most cases too fast aggregation kinetics for all peptides. Since then, new force fields specially designed for intrinsically disordered proteins such as Aβ were developed. Here, we assess the applicability of these new force fields to studying peptide aggregation using the Aβ16−22 peptide and mutations of it as test case. We investigate their performance in modeling the monomeric state, the aggregation into oligomers, and the stability of the aggregation end product, i.e., the fibrillar state. A main finding is that changing the force field has a stronger effect on the simulated aggregation pathway than changing the peptide sequence. Also the new force fields are not able to reproduce the experimental aggregation propensity order of the peptides. Dissecting the various energy contributions shows that AMBER99SB-disp overestimates the interactions between the peptides and water, thereby inhibiting peptide aggregation. More promising results are obtained with CHARMM36m and especially its version with increased protein–water interactions. It is thus recommended to use this force field for peptide aggregation simulations and base future reparameterizations on it.

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