scholarly journals Simulation of lipid bilayer self-assembly using all-atom lipid force fields

2016 ◽  
Vol 18 (15) ◽  
pp. 10573-10584 ◽  
Author(s):  
Åge A. Skjevik ◽  
Benjamin D. Madej ◽  
Callum J. Dickson ◽  
Charles Lin ◽  
Knut Teigen ◽  
...  
Keyword(s):  
Molecular Dynamics ◽  
Lipid Bilayer ◽  
Self Assembly ◽  
Force Fields ◽  
Md Simulations ◽  
Anionic Phospholipids

Spontaneous bilayer self-assembly of zwitterionic and anionic phospholipids probed by unbiased all-atom molecular dynamics (MD) simulations with three major lipid force fields.

scholarly journals All-atom lipid bilayer self-assembly with the AMBER and CHARMM lipid force fields

2015 ◽  
Vol 51 (21) ◽  
pp. 4402-4405 ◽  
Author(s):  
Åge A. Skjevik ◽  
Benjamin D. Madej ◽  
Callum J. Dickson ◽  
Knut Teigen ◽  
Ross C. Walker ◽  
...  
Keyword(s):  
Molecular Dynamics ◽  
Lipid Bilayer ◽  
Self Assembly ◽  
Force Fields ◽  
Md Simulations ◽  
Bilayer Formation

In this work we report the first example of spontaneous lipid bilayer formation in unbiased all-atom molecular dynamics (MD) simulations.

scholarly journals High-resolution mining of the SARS-CoV-2 main protease conformational space: supercomputer-driven unsupervised adaptive sampling

2021 ◽  
Author(s):  
Théo Jaffrelot Inizan ◽  
Frédéric Célerse ◽  
Olivier Adjoua ◽  
Dina El Ahdab ◽  
Luc-Henri Jolly ◽  
...  
Keyword(s):  
Molecular Dynamics ◽  
High Resolution ◽  
Adaptive Sampling ◽  
Force Fields ◽  
Sampling Strategy ◽  
Md Simulations ◽  
Conformational Space ◽  
Many Body ◽  
Polarizable Force Fields ◽  
Main Protease

We provide an unsupervised adaptive sampling strategy capable of producing μs-timescale molecular dynamics (MD) simulations of large biosystems using many-body polarizable force fields (PFFs).

Cellular Injection Using Carbon Nanotube: A Molecular Dynamics Study

NANO ◽  
2015 ◽  
Vol 10 (02) ◽  
pp. 1550025 ◽  
Author(s):  
Seyed Hanif Mahboobi ◽  
Alireza Taheri ◽  
Hossein Nejat Pishkenari ◽  
Ali Meghdari ◽  
Mahya Hemmat
Keyword(s):  
Molecular Dynamics ◽  
Carbon Nanotube ◽  
Cell Membrane ◽  
Minimally Invasive ◽  
Lipid Bilayer ◽  
Membrane Structure ◽  
Md Simulations ◽  
Injection Process ◽  
Drug And Gene Delivery

Determination of an injection condition which is minimally invasive to the cell membrane is of great importance in drug and gene delivery. For this purpose, a series of molecular dynamics (MD) simulations are conducted to study the penetration of a carbon nanotube (CNT) into a pure POPC cell membrane under various injection velocities, CNT tilt angles and chirality parameters. The simulations are nonequilibrium and all-atom. The force and stress exerted on the nanotube, deformation of the lipid bilayer, and strain of the CNT atoms are inspected during the simulations. We found that a lower nanotube velocity results in successfully entering the membrane with minimum disruption in the CNT and the lipid bilayer, and CNT's chirality distinctly affects the results. Moreover, it is shown that the tilt angle of the CNT influences the nanotube's buckling and may result in destroying the membrane structure during the injection process.

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 Structure and Dynamics of Curcumin Encapsulated Lecithin Micelles: A Molecular Dynamics Simulation Study

2021 ◽  
Vol 6 (3) ◽  
pp. 113-120
Author(s):  
Lukman Hakim ◽  
Diah Mardiana ◽  
Urnik Rokhiyah ◽  
Maria Lucia Ardhani Dwi Lestari ◽  
Zubaidah Ningsih
Keyword(s):  
Molecular Dynamics ◽  
Self Assembly ◽  
Local Density ◽  
Center Of Mass ◽  
Md Simulations ◽  
Dynamics Simulation ◽  
Spherical Micelle ◽  
Natural Surfactant ◽  
Dynamics Response ◽  
Nano Emulsion

Curcumin is a natural product with potential pharmaceutical applications that can be augmented by drug delivery technology such as nano emulsion. Our study focuses on microscopic structural and dynamics response of curcumin encapsulation in micellar system with lecithin as a natural surfactant under variations of composition and temperature using molecular dynamics (MD) simulations. The results highlight the self-assembly of lecithin micelle, with curcumin encapsulated inside, from initial random configurations in the absence of external field. The variation of composition shows that lecithin can aggregate into spherical and rod-like micelle with the second critical micelle concentration lies between 0.17-0.22 mol dm−3. The radial local density centering at the micelle center of mass shows that the effective radius of micelle is indeed defined by the hydrophilic groups of lecithin molecule and theencapsulated curcumin molecules are positioned closer to these hydrophilic groups than the innermost part of the micelle. The spherical micelle is shown to be thermally stable within the temperature range of 277-310 K without a perceivable change in the spherical eccentricity. The dynamics of micelle are enhanced by the temperature, but it is shown to be insensitive to the variation of lecithin-curcumin composition within the studied range. Simulation results are in agreement with the pattern obtained from experimental results based on particle size, polydispersity index, and encapsulation efficiency.

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.

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