Systematic Differences between Current Molecular Dynamics Force Fields To Represent Local Properties of Intrinsically Disordered Proteins

2021 ◽  
Vol 125 (3) ◽  
pp. 798-804
Author(s):  
Lei Yu ◽  
Da-Wei Li ◽  
Rafael Brüschweiler
Keyword(s):  
Molecular Dynamics ◽  
Intrinsically Disordered Proteins ◽  
Force Fields ◽  
Disordered Proteins ◽  
Intrinsically Disordered ◽  
Local Properties

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.

Do Molecular Dynamics Force Fields Accurately Model Ramachandran Distributions of Amino Acid Residues in Water?

2022 ◽  
Author(s):  
Brian Andrews ◽  
Jose Guerra ◽  
Reinhard Schweitzer-Stenner ◽  
Brigita Urbanc
Keyword(s):  
Molecular Dynamics ◽  
Amino Acid ◽  
Force Field ◽  
Intrinsically Disordered Proteins ◽  
Force Fields ◽  
Disordered Proteins ◽  
Amino Acid Residues ◽  
Intrinsically Disordered

Molecular dynamics (MD) is a powerful tool for studying intrinsically disordered proteins, however, its reliability depends on the accuracy of the force field. We here assess Amber ff14SB, Amber ff14SB,...

scholarly journals Full structural ensembles of intrinsically disordered proteins from unbiased molecular dynamics simulations

2020 ◽  
Author(s):  
Utsab R. Shrestha ◽  
Jeremy C. Smith ◽  
Loukas Petridis
Keyword(s):  
Molecular Dynamics ◽  
Md Simulation ◽  
Intrinsically Disordered Proteins ◽  
Force Fields ◽  
Disordered Proteins ◽  
Hamiltonian Replica Exchange ◽  
Intrinsically Disordered ◽  
Angle Scattering ◽  
Structural Ensembles ◽  
Dynamics Simulations

ABSTRACTMolecular dynamics (MD) simulation is widely used to complement ensemble-averaged experiments of intrinsically disordered proteins (IDPs). However, MD often suffers from limitations of inaccuracy in the force fields and inadequate sampling. Here, we show that enhancing the sampling using Hamiltonian replica-exchange MD led to unbiased ensembles of unprecedented accuracy, reproducing small-angle scattering and NMR chemical shift experiments, for three IDPs of variable sequence properties using two recently optimized force fields. Surprisingly, we reveal that despite differences in their sequence, the inter-chain statistics of all three IDPs are similar for short contour lengths (< 10 residues).

scholarly journals Generation of the configurational ensemble of an intrinsically disordered protein from unbiased molecular dynamics simulation

2019 ◽  
Vol 116 (41) ◽  
pp. 20446-20452 ◽  
Author(s):  
Utsab R. Shrestha ◽  
Puneet Juneja ◽  
Qiu Zhang ◽  
Viswanathan Gurumoorthy ◽  
Jose M. Borreguero ◽  
...  
Keyword(s):  
Molecular Dynamics ◽  
Intrinsically Disordered Proteins ◽  
Chemical Shifts ◽  
Intrinsically Disordered Protein ◽  
Physical Models ◽  
Dynamics Simulation ◽  
Disordered Proteins ◽  
Intrinsically Disordered ◽  
Eukaryotic Proteomes ◽  
Heterogeneous Ensemble

Intrinsically disordered proteins (IDPs) are abundant in eukaryotic proteomes, play a major role in cell signaling, and are associated with human diseases. To understand IDP function it is critical to determine their configurational ensemble, i.e., the collection of 3-dimensional structures they adopt, and this remains an immense challenge in structural biology. Attempts to determine this ensemble computationally have been hitherto hampered by the necessity of reweighting molecular dynamics (MD) results or biasing simulation in order to match ensemble-averaged experimental observables, operations that reduce the precision of the generated model because different structural ensembles may yield the same experimental observable. Here, by employing enhanced sampling MD we reproduce the experimental small-angle neutron and X-ray scattering profiles and the NMR chemical shifts of the disordered N terminal (SH4UD) of c-Src kinase without reweighting or constraining the simulations. The unbiased simulation results reveal a weakly funneled and rugged free energy landscape of SH4UD, which gives rise to a heterogeneous ensemble of structures that cannot be described by simple polymer theory. SH4UD adopts transient helices, which are found away from known phosphorylation sites and could play a key role in the stabilization of structural regions necessary for phosphorylation. Our findings indicate that adequately sampled molecular simulations can be performed to provide accurate physical models of flexible biosystems, thus rationalizing their biological function.

scholarly journals Optimization of Molecular Dynamics Simulations of c-MYC1-88—An Intrinsically Disordered System

Life ◽  
2020 ◽  
Vol 10 (7) ◽  
pp. 109 ◽  
Author(s):  
Sandra S. Sullivan ◽  
Robert O.J. Weinzierl
Keyword(s):  
Molecular Dynamics ◽  
Molecular Dynamics Simulations ◽  
Intrinsically Disordered Proteins ◽  
Disordered Proteins ◽  
Intrinsically Disordered ◽  
Intrinsically Disordered Regions ◽  
Proliferation And Apoptosis ◽  
Conventional Structure ◽  
Experimental Approaches ◽  
Dynamics Simulations

Many of the proteins involved in key cellular regulatory events contain extensive intrinsically disordered regions that are not readily amenable to conventional structure/function dissection. The oncoprotein c-MYC plays a key role in controlling cell proliferation and apoptosis and more than 70% of the primary sequence is disordered. Computational approaches that shed light on the range of secondary and tertiary structural conformations therefore provide the only realistic chance to study such proteins. Here, we describe the results of several tests of force fields and water models employed in molecular dynamics simulations for the N-terminal 88 amino acids of c-MYC. Comparisons of the simulation data with experimental secondary structure assignments obtained by NMR establish a particular implicit solvation approach as highly congruent. The results provide insights into the structural dynamics of c-MYC1-88, which will be useful for guiding future experimental approaches. The protocols for trajectory analysis described here will be applicable for the analysis of a variety of computational simulations of intrinsically disordered proteins.

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