Molecular dynamics simulations of protein aggregation: protocols for simulation setup and analysis with Markov state models and transition networks

Samantray, Suman; Schumann, Wibke; Illig, Alexander-Maurice; Paul, Arghadwip; Barz, Bogdan; Strodel, Birgit

doi:10.1101/2020.04.25.060269

Cited by 11 publications

(16 citation statements)

References 40 publications

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“…The peptide conformation with the lowest free energy value was selected for simulation of peptide aggregation. The method followed the previous study [ 57 ] for investigating the aggregation of six peptide molecules that were randomly inserted in a 10 nm cubic water box in combination with a Charmm36-mar2019 forcefield. The energy minimization was performed similarly with a maximum force tolerance of 500 kJ/mol/nm.…”

Section: Methodsmentioning

confidence: 99%

Aggregation and Its Influence on the Bioactivities of a Novel Antimicrobial Peptide, Temporin-PF, and Its Analogues

Zai

et al. 2021

IJMS

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Temporin is an antimicrobial peptide (AMP) family discovered in the skin secretion of ranid frog that has become a promising alternative for conventional antibiotic therapy. Herein, a novel temporin peptide, Temporin-PF (TPF), was successfully identified from Pelophylax fukienensis. It exhibited potent activity against Gram-positive bacteria, but no effect on Gram-negative bacteria. Additionally, TPF exhibited aggregation effects in different solutions. Three analogs were further designed to study the relationship between the aggregation patterns and bioactivities, and the MD simulation was performed for revealing the pattern of the peptide assembly. As the results showed, all peptides were able to aggregate in the standard culture media and salt solutions, especially CaCl2 and MgCl2 buffers, where the aggregation was affected by the concentration of the salts. MD simulation reported that all peptides were able to form oligomers. The parent peptide assembly depended on the hydrophobic interaction via the residues in the middle domain of the sequence. However, the substitution of Trp/D-Trp resulted in an enhanced inter-peptide interaction in the zipper-like domain and eliminated overall biological activities. Our study suggested that introducing aromaticity at the zipper-like domain for temporin may not improve the bioactivities, which might be related to the formation of aggregates via the inter-peptide contacts at the zipper-like motif domain, and it could reduce the binding affinity to the lipid membrane of microorganisms.

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Section: Methodsmentioning

confidence: 99%

Aggregation and Its Influence on the Bioactivities of a Novel Antimicrobial Peptide, Temporin-PF, and Its Analogues

Zai

et al. 2021

IJMS

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“…Transition networks and oligomer structures For the characterization of the intermediate oligomeric states and the transitions between them, we calculated transition networks (TNs). 34,58 As in our preceding study, 12 we chose to build the TNs in a two-dimensional space defined by β-strand content (x-axis) and oligomer size (y-axis) (Fig. 5).…”

Section: Characterization Of the Aggregation Processmentioning

confidence: 99%

Different Force Fields Give Rise to Different Amyloid Aggregation Pathways in Molecular Dynamics Simulations

Samantray

Yin

Kav

et al. 2020

J. Chem. Inf. Model.

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117

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The 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 Aβ 16−22 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. IntroductionIntrinsically disordered proteins (IDPs) are a class of proteins which are either completely unstructured or contain large disordered regions in their native state, which comes with a high tendency towards self-assembly leading to non-toxic or toxic aggregates and fibrils that may be related to diseases. 1 One of the IDPs is the amyloid-beta peptide (Aβ), forming 2

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“…The native WT 16-chain oligomers and the de-acetylated mimicking KR 16-chain oligomers demonstrated the least oligomerization with respect to time. Furthermore, to identify key residues during the spontaneous aggregation, inter-residue contact maps were constructed [ 25 ] and the results were shown in Figure 5 d. The contact map displays the probability of residues contact during oligomerization. For the ac-K174 16-chain oligomers system, the acetylated lysine ac-K174 depicts the highest number of inter-residue contacts.…”

Section: Resultsmentioning

confidence: 99%

“…DSSP analysis was used to assign a secondary structure profile to the peptides [ 24 ]. The oligomerization state and size were determined using python script previously reported [ 25 ].…”

Section: Methodsmentioning

confidence: 99%

Deciphering the Effect of Lysine Acetylation on the Misfolding and Aggregation of Human Tau Fragment 171IPAKTPPAPK180 Using Molecular Dynamic Simulation and the Markov State Model

Shah

Zhong

Zhang

et al. 2022

IJMS

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The formation of neurofibrillary tangles (NFT) with β-sheet-rich structure caused by abnormal aggregation of misfolded microtubule-associated protein Tau is a hallmark of tauopathies, including Alzheimer’s Disease. It has been reported that acetylation, especially K174 located in the proline-rich region, can largely promote Tau aggregation. So far, the mechanism of the abnormal acetylation of Tau that affects its misfolding and aggregation is still unclear. Therefore, revealing the effect of acetylation on Tau aggregation could help elucidate the pathogenic mechanism of tauopathies. In this study, molecular dynamics simulation combined with multiple computational analytical methods were performed to reveal the effect of K174 acetylation on the spontaneous aggregation of Tau peptide 171IPAKTPPAPK180, and the dimerization mechanism as an early stage of the spontaneous aggregation was further specifically analyzed by Markov state model (MSM) analysis. The results showed that both the actual acetylation and the mutation mimicking the acetylated state at K174 induced the aggregation of the studied Tau fragment; however, the effect of actual acetylation on the aggregation was more pronounced. In addition, acetylated K174 plays a major contributing role in forming and stabilizing the antiparallel β-sheet dimer by forming several hydrogen bonds and side chain van der Waals interactions with residues I171, P172, A173 and T175 of the corresponding chain. In brief, this study uncovered the underlying mechanism of Tau peptide aggregation in response to the lysine K174 acetylation, which can deepen our understanding on the pathogenesis of tauopathies.

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Molecular dynamics simulations of protein aggregation: protocols for simulation setup and analysis with Markov state models and transition networks

Cited by 11 publications

References 40 publications

Aggregation and Its Influence on the Bioactivities of a Novel Antimicrobial Peptide, Temporin-PF, and Its Analogues

Aggregation and Its Influence on the Bioactivities of a Novel Antimicrobial Peptide, Temporin-PF, and Its Analogues

Different Force Fields Give Rise to Different Amyloid Aggregation Pathways in Molecular Dynamics Simulations

Deciphering the Effect of Lysine Acetylation on the Misfolding and Aggregation of Human Tau Fragment 171IPAKTPPAPK180 Using Molecular Dynamic Simulation and the Markov State Model

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