NANOGOLD decorated by pHLIP peptide: comparative force field study

2015 ◽  
Vol 17 (19) ◽  
pp. 12648-12660 ◽  
Author(s):  
A. Kyrychenko
Keyword(s):  
Force Field ◽  
Field Study ◽  
Force Fields ◽  
Md Simulations ◽  
Computational Studies ◽  
Peptide Interactions

Structure of Au135 nanoparticle functionalized by pH low insertion peptide (pHLIP) compared by MD simulations based on six popular biomolecular force fields, suggesting OPLS-AA and CHARMM36 as a tool of choice for the computational studies of NANOGOLD–peptide interactions.

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.

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 Developing a molecular dynamics force field for both folded and disordered protein states

2018 ◽  
Vol 115 (21) ◽  
pp. E4758-E4766 ◽  
Author(s):  
Paul Robustelli ◽  
Stefano Piana ◽  
David E. Shaw
Keyword(s):  
Molecular Dynamics ◽  
Force Field ◽  
Md Simulation ◽  
State Of The Art ◽  
Force Fields ◽  
Md Simulations ◽  
Disordered Proteins ◽  
Disordered Protein ◽  
Data Points ◽  
Folded Proteins

Molecular dynamics (MD) simulation is a valuable tool for characterizing the structural dynamics of folded proteins and should be similarly applicable to disordered proteins and proteins with both folded and disordered regions. It has been unclear, however, whether any physical model (force field) used in MD simulations accurately describes both folded and disordered proteins. Here, we select a benchmark set of 21 systems, including folded and disordered proteins, simulate these systems with six state-of-the-art force fields, and compare the results to over 9,000 available experimental data points. We find that none of the tested force fields simultaneously provided accurate descriptions of folded proteins, of the dimensions of disordered proteins, and of the secondary structure propensities of disordered proteins. Guided by simulation results on a subset of our benchmark, however, we modified parameters of one force field, achieving excellent agreement with experiment for disordered proteins, while maintaining state-of-the-art accuracy for folded proteins. The resulting force field, a99SB-disp, should thus greatly expand the range of biological systems amenable to MD simulation. A similar approach could be taken to improve other force fields.

scholarly journals Force Field Development of β-lactam Class Antibiotics

2020 ◽  
Vol 5 (Spring 2020) ◽  
Author(s):  
Trevor Heinzmann
Keyword(s):  
Force Field ◽  
Force Fields ◽  
Molecular System ◽  
Equations Of Motion ◽  
Computational Cost ◽  
Potential Energy Function ◽  
Md Simulations ◽  
Field Development ◽  
Force Field Development ◽  
Low Computational Cost

Molecular dynamics (MD) simulation is a computational chemistry technique used to observe how a molecular system behaves as time passes. MD is based on solving Newton’s equations of motion. This requires the use of force fields to describe the potential energy function of each different molecule type in molecular system. In order to develop a force field, charges, bonds, angles, and dihedrals must be parameterized to fit quantum mechanics (QM) data. By basing the force field on QM data, MD simulations have higher accuracy while still using the low computational cost of molecular mechanics. This project focuses on developing well-fit force fields for β-lactam class antibiotics for future MD simulations. Full antibiotics are too large of a molecule to parameterize from scratch, so instead we broke them down into fragments. Smaller molecule fragments allow less terms to be optimized which greatly simplifies force field development. By the transferable nature of parameters in CHARMM force fields, the fragment parameters can be transferred to connecting molecules. Due to this, we can build up larger organic molecule force fields piece by piece.In this work, we developed CHARMM force fields for cephalothin, cefotaxime, ceftazidime, and aztreonam.

scholarly journals Effects of Force Fields on the Conformational and Dynamic Properties of Amyloid β(1-40) Dimer Explored by Replica Exchange Molecular Dynamics Simulations

2017 ◽  
Author(s):  
Charles R. Watts ◽  
Andrew Gregory ◽  
Cole Frisbie ◽  
Sándor Lovas
Keyword(s):  
Molecular Dynamics ◽  
Force Field ◽  
Force Fields ◽  
Dynamic Properties ◽  
Amyloid Β ◽  
Md Simulations ◽  
Conformational Space ◽  
Random Coil ◽  
Replica Exchange ◽  
Β Sheet

AbstractAlzheimer’s disease is histologically marked by fibrils of Amyloid beta (Aβ) peptide within the extracellular matrix. Fibrils themselves are benign compared to the cytotoxicity of the oligomers and pre-fibrillary aggregates. The conformational space and structural ensembles of Aβ peptides and their oligomers in solution are inherently disordered and proven to be challenging to study. Optimum force field selection for molecular dynamics (MD) simulations and the biophysical relevance of results are still unknown. We compared the conformational space of the Aβ(1–40) dimers by 300 ns replica exchange MD simulations at physiological temperature (310 K) using: the AMBER-ff99sb-ILDN, AMBER-ff99sb*-ILDN, AMBER-ff99sb-NMR, and CHARMM22* force fields. Statistical comparisons of simulation results to experimental data and previously published simulations utilizing the CHARMM22* and CHARMM36 force fields were performed. All force fields yield sampled ensembles of conformations with collision cross sectional areas for the dimer that are statistically significantly larger than experimental results. All force fields, with the exception of AMBER-ff99sb-ILDN (8.8±6.4%) and CHARMM36 (2.7±4.2%), tend to overestimate the α-helical content compared to experimental CD (5.3±5.2%). Using the AMBER-ff99sb-NMR force field resulted in the greatest degree of variance (41.3±12.9%). Except for the AMBER-ff99sb-NMR force field, the others tended to under estimate the expected amount of β-sheet and over estimate the amount of turn/bend/random coil conformations. All force fields, with the exception AMBER-ff99sb-NMR, reproduce a theoretically expected β-sheet-turn-β-sheet conformational motif, however, only the CHARMM22* and CHARMM36 force fields yield results compatible with collapse of the central and C-terminal hydrophobic cores from residues 17-21 and 30-36. Although analyses of essential subspace sampling showed only minor variations between force fields, secondary structures of lowest energy conformers are different.

CONFORMATIONAL DYNAMICS OF HIV-1 PROTEASE: A COMPARATIVE MOLECULAR DYNAMICS SIMULATION STUDY WITH MULTIPLE AMBER FORCE FIELDS

2012 ◽  
Vol 10 (06) ◽  
pp. 1250018 ◽  
Author(s):  
BISWA RANJAN MEHER ◽  
MATTAPARTHI VENKATA SATISH KUMAR ◽  
SMRITI SHARMA ◽  
PRADIPTA BANDYOPADHYAY
Keyword(s):  
Force Field ◽  
Active Site ◽  
Force Fields ◽  
Conformational Dynamics ◽  
Md Simulations ◽  
Order Parameters ◽  
Dynamics Simulation ◽  
Active Site Cavity ◽  
Amber Force Fields ◽  
Hiv 1

Flap dynamics of HIV-1 protease (HIV-pr) controls the entry of inhibitors and substrates to the active site. Dynamical models from previous simulations are not all consistent with each other and not all are supported by the NMR results. In the present work, the effect of force field on the dynamics of HIV-pr is investigated by MD simulations using three AMBER force fields ff99, ff99SB, and ff03. The generalized order parameters for amide backbone are calculated from the three force fields and compared with the NMR S2 values. We found that the ff99SB and ff03 force field calculated order parameters agree reasonably well with the NMR S2 values, whereas ff99 calculated values deviate most from the NMR order parameters. Stereochemical geometry of protein models from each force field also agrees well with the remarks from NMR S2 values. However, between ff99SB and ff03, there are several differences, most notably in the loop regions. It is found that these loops are, in general, more flexible in the ff03 force field. This results in a larger active site cavity in the simulation with the ff03 force field. The effect of this difference in computer-aided drug design against flexible receptors is discussed.

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.

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