scholarly journals Bayesian inference of protein ensembles from SAXS data

2016 ◽  
Vol 18 (8) ◽  
pp. 5832-5838 ◽  
Author(s):  
L. D. Antonov ◽  
S. Olsson ◽  
W. Boomsma ◽  
T. Hamelryck
Keyword(s):  
Bayesian Inference ◽  
Force Field ◽  
Intrinsically Disordered Proteins ◽  
Probabilistic Method ◽  
Disordered Proteins ◽  
Saxs Data ◽  
Intrinsically Disordered ◽  
Protein Ensembles

A probabilistic method infers ensembles of intrinsically disordered proteins (IDPs) by combining SAXS data with a force field.

scholarly journals Refinement of α-synuclein ensembles against SAXS data: Comparison of force fields and methods

2021 ◽  
Author(s):  
Mustapha Carab Ahmed ◽  
Line K. Skaanning ◽  
Alexander Jussupow ◽  
Estella A. Newcombe ◽  
Birthe B. Kragelund ◽  
...  
Keyword(s):  
Experimental Data ◽  
Force Field ◽  
Intrinsically Disordered Proteins ◽  
Force Fields ◽  
The Other ◽  
Disordered Proteins ◽  
Saxs Data ◽  
Intrinsically Disordered ◽  
Other Hand ◽  
Dynamics Simulations

AbstractThe inherent flexibility of intrinsically disordered proteins (IDPs) makes it difficult to interpret experimental data using structural models. On the other hand, molecular dynamics simulations of IDPs often suffer from force-field inaccuracies, and long simulations times or enhanced sampling methods are needed to obtain converged ensembles. Here, we apply metainference and Bayesian/Maximum Entropy reweighting approaches to integrate prior knowledge of the system with experimental data, while also dealing with various sources of errors and the inherent conformational heterogeneity of IDPs. We have measured new SAXS data on the protein α-synuclein, and integrate this with simulations performed using different force fields. We find that if the force field gives rise to ensembles that are much more compact than what is implied by the SAXS data it is difficult to recover a reasonable ensemble. On the other hand, we show that when the simulated ensemble is reasonable, we can obtain an ensemble that is consistent with the SAXS data, but also with NMR diffusion and paramagnetic relaxation enhancement data.

scholarly journals Refinement of α-Synuclein Ensembles Against SAXS Data: Comparison of Force Fields and Methods

2021 ◽  
Vol 8 ◽  
Author(s):  
Mustapha Carab Ahmed ◽  
Line K. Skaanning ◽  
Alexander Jussupow ◽  
Estella A. Newcombe ◽  
Birthe B. Kragelund ◽  
...  
Keyword(s):  
Experimental Data ◽  
Force Field ◽  
Intrinsically Disordered Proteins ◽  
Force Fields ◽  
The Other ◽  
Disordered Proteins ◽  
Saxs Data ◽  
Intrinsically Disordered ◽  
Other Hand ◽  
Dynamics Simulations

The inherent flexibility of intrinsically disordered proteins (IDPs) makes it difficult to interpret experimental data using structural models. On the other hand, molecular dynamics simulations of IDPs often suffer from force-field inaccuracies, and long simulation times or enhanced sampling methods are needed to obtain converged ensembles. Here, we apply metainference and Bayesian/Maximum Entropy reweighting approaches to integrate prior knowledge of the system with experimental data, while also dealing with various sources of errors and the inherent conformational heterogeneity of IDPs. We have measured new SAXS data on the protein α-synuclein, and integrate this with simulations performed using different force fields. We find that if the force field gives rise to ensembles that are much more compact than what is implied by the SAXS data it is difficult to recover a reasonable ensemble. On the other hand, we show that when the simulated ensemble is reasonable, we can obtain an ensemble that is consistent with the SAXS data, but also with NMR diffusion and paramagnetic relaxation enhancement data.

scholarly journals Rescuing the Over-Collapse of Intrinsically Disordered Proteins using a Force Field Derived by a New Paradigm

2016 ◽  
Vol 110 (3) ◽  
pp. 556a
Author(s):  
Davide Mercadante ◽  
Sigrid Milles ◽  
Gustavo Fuertes ◽  
Dmitri Svergun ◽  
Edward A. Lemke ◽  
...  
Keyword(s):  
Force Field ◽  
Intrinsically Disordered Proteins ◽  
Disordered Proteins ◽  
New Paradigm ◽  
Intrinsically Disordered

scholarly journals CHARMM36: An Improved Force Field for Folded and Intrinsically Disordered Proteins

2017 ◽  
Vol 112 (3) ◽  
pp. 175a-176a ◽  
Author(s):  
Jing Huang ◽  
Sarah Rauscher ◽  
Grzegorz Nawrocki ◽  
Ting Ran ◽  
Michael Feig ◽  
...  
Keyword(s):  
Force Field ◽  
Intrinsically Disordered Proteins ◽  
Disordered Proteins ◽  
Intrinsically Disordered

scholarly journals Structural Ensembles of Intrinsically Disordered Proteins Depend Strongly on Force Field

2014 ◽  
Vol 106 (2) ◽  
pp. 271a ◽  
Author(s):  
Sarah Rauscher ◽  
Vytautas Gapsys ◽  
Andreas Volkhardt ◽  
Christian Blau ◽  
Bert L. de Groot ◽  
...  
Keyword(s):  
Force Field ◽  
Intrinsically Disordered Proteins ◽  
Disordered Proteins ◽  
Intrinsically Disordered ◽  
Structural Ensembles

scholarly journals Modelling the structure and interactions of intrinsically disordered peptides with multiple-replica, metadynamics-based sampling methods and force-field combinations

2021 ◽  
Author(s):  
Lunna Li ◽  
Tommaso Casalini ◽  
Paolo Arosio ◽  
Matteo Salvalaglio
Keyword(s):  
Force Field ◽  
Sampling Method ◽  
Intrinsically Disordered Proteins ◽  
Thermodynamic Characteristics ◽  
Building Blocks ◽  
Disordered Proteins ◽  
Intrinsically Disordered ◽  
Self Association ◽  
Disordered Peptides

Intrinsically disordered proteins (IDPs) play a key role in many biological processes, including the formation of biomolecular condensates within cells. A detailed characterization of their configurational ensemble and structure-function paradigm is crucial for understanding their biological activity and for exploiting them as building blocks in material sciences. In this work, we incorporate bias-exchange metadynamics and parallel-tempering well-tempered metadynamics with CHARMM36m and CHARMM22* to explore the structural and thermodynamic characteristics of a short archetypal disordered sequence derived from a DEAD-box protein. The conformational landscapes emerging from our simulations are largely congruent across methods and forcefields. Nevertheless, differences in fine details emerge from varying forcefield/sampling method combinations. For this protein, our analysis identifies features that help to explain the low propensity of this sequence to undergo self-association in vitro, which can be common to all force-field/sampling method combinations. Overall, our work demonstrates the importance of using multiple force-field/enhanced sampling method combinations for accurate structural and thermodynamic information in the study of general disordered proteins.

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 Molecular Dynamics Simulations of Phosphorylated Intrinsically Disordered Proteins: A Force Field Comparison

2021 ◽  
Vol 22 (18) ◽  
pp. 10174
Author(s):  
Ellen Rieloff ◽  
Marie Skepö
Keyword(s):  
Force Field ◽  
Intrinsically Disordered Proteins ◽  
Disordered Proteins ◽  
Conformational Ensemble ◽  
Salt Bridges ◽  
Post Translational Modification ◽  
Intrinsically Disordered ◽  
The Difference ◽  
Disordered Peptides ◽  
Dynamics Simulations

Phosphorylation is a common post-translational modification among intrinsically disordered proteins and regions, which helps regulate function by changing the protein conformations, dynamics, and interactions with binding partners. To fully comprehend the effects of phosphorylation, computer simulations are a helpful tool, although they are dependent on the accuracy of the force field used. Here, we compared the conformational ensembles produced by Amber ff99SB-ILDN+TIP4P-D and CHARMM36m, for four phosphorylated disordered peptides ranging in length from 14–43 residues. CHARMM36m consistently produced more compact conformations with a higher content of bends, mainly due to more stable salt bridges. Based on comparisons with experimental size estimates for the shortest and longest peptide, CHARMM36m appeared to overestimate the compactness. The difference between the force fields was largest for the peptide showing the greatest separation between positively charged and phosphorylated residues, in line with the importance of charge distribution. For this peptide, the conformational ensemble did not change significantly upon increasing the ionic strength from 0 mM to 150 mM, despite a reduction of the salt-bridging probability in the CHARMM36m simulations, implying that salt concentration has negligible effects in this study.

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