ABSINTH Implicit Solvation Model and Force Field Paradigm for Use in Simulations of Intrinsically Disordered Proteins

2014 ◽  
pp. 208-231
2016 ◽  
Vol 110 (3) ◽  
pp. 556a
Author(s):  
Davide Mercadante ◽  
Sigrid Milles ◽  
Gustavo Fuertes ◽  
Dmitri Svergun ◽  
Edward A. Lemke ◽  
...  

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

2014 ◽  
Vol 106 (2) ◽  
pp. 271a ◽  
Author(s):  
Sarah Rauscher ◽  
Vytautas Gapsys ◽  
Andreas Volkhardt ◽  
Christian Blau ◽  
Bert L. de Groot ◽  
...  

2016 ◽  
Vol 18 (8) ◽  
pp. 5832-5838 ◽  
Author(s):  
L. D. Antonov ◽  
S. Olsson ◽  
W. Boomsma ◽  
T. Hamelryck

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


2021 ◽  
Author(s):  
Lunna Li ◽  
Tommaso Casalini ◽  
Paolo Arosio ◽  
Matteo Salvalaglio

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.


2019 ◽  
Author(s):  
Joao Victor de Souza Cunha ◽  
Francesc Sabanes Zariquiey ◽  
Agnieszka K. Bronowska

Intrinsically disordered proteins (IDPs) are molecules without a fixed tertiary structure, exerting crucial roles in cellular signalling, growth and molecular recognition events. Due to their high plasticity, IDPs are very challenging in experimental and computational structural studies. To provide detailed atomic insight in IDPs dynamics governing its functional mechanisms, all-atom molecular dynamics (MD) simulations are widely employed. However, the current generalist force fields and solvent models are unable to generate satisfactory ensembles for IDPs when compared to existing experimental data. In this work, we present a new solvation model, denoted as Charge-Augmented 3 Point Water model for Intrinsically-disordered Proteins (CAIPi3P). CAIPi3P has been generated by performing a systematic scanning of atomic partial charges assigned to the widely popular molecular scaffold of the three-point TIP3P water model. We found that explicit solvent MD simulations employing CAIPi3P solvation considerably improved the SAXS scattering profiles for three different IDPs. Not surprisingly, this improvement was further enhanced by using CAIPi3P water in combination with the protein force field parametrized for IDPs. We have also demonstrated applicability of CAIPi3P to molecular systems containing structured as well as intrinsically disordered regions/domains. Our results highlight the crucial importance of solvent effects for generating molecular ensembles of IDPs which reproduce the experimental data available. Hence, we conclude that our newly developed CAIPi3P solvation model is a valuable tool assisting molecular simulations of intrinsically disordered proteins and assessing their molecular dynamics.


2020 ◽  
Author(s):  
Suman Samantray ◽  
Feng Yin ◽  
Batuhan Kav ◽  
Birgit Strodel

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.


2021 ◽  
Vol 22 (18) ◽  
pp. 10174
Author(s):  
Ellen Rieloff ◽  
Marie Skepö

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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