Energy landscapes of Aβ monomers are sculpted in accordance with Ostwald’s rule of stages

Chakraborty, Debayan; Straub, John E.; Thirumalai, D.

doi:10.1126/sciadv.add6921

Cited by 21 publications

(15 citation statements)

References 108 publications

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“…The inverse correlation is consistent with the Ostwald's rule of stages, which we recently showed holds in the formation of distinct polymorphic structures of Aβ 42 peptides. 44 Effect of phosphorylation -location matters: Murray et. al., 12 systematically examined the effects of phosphorylation by DNA-proteinase K on the stability of the ordered S-bend structure in FUS-LC.…”

Section: Resultsmentioning

confidence: 99%

Conformational Fluctuations and Phases in Fused in Sarcoma (FUS) Low-Complexity Domain

Thirumalai,

Kumar,

Chakraborty

et al. 2023

Preprint

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The well known phenomenon of phase separation in synthetic polymers and proteins has become a major topic in biophysics because it has been invoked as a mechanism of compartment formation in cells, without the need for membranes. Most of the coacervates (or condensates) are composed of Intrinsically Disordered Proteins (IDPs) or regions that are structureless, often in interaction with RNA and DNA. One of the more intriguing IDPs is the 526 residue RNA binding protein, Fused In Sarcoma (FUS), whose monomer conformations and condensates exhibit unusual behavior that are sensitive to solution conditions. By focussing principally on the N-terminus low complexity domain (FUS-LC comprising of residues 1-214) and other truncations, we rationalize the findings in solid state NMR experiments, which show that FUS-LC adopts a nonpolymorphic fibril (core-1) involving residues 39-95, flanked by fuzzy coats on both the N-and C-terminal ends. An alternate structure (core-2), whose free energy is comparable to core-1, emerges only in the truncated construct (residues 110-214). Both core-1 and core-2 fibrils are stabilized by a Tyrosine ladder as well as hydrophilic interactions.The morphologies (gels, fibrils, and glass-like behavior) adopted by FUS seem to vary greatly, depending on the experimental conditions. The effect of phosphorylation is site specific and affects the stability of the fibril depending on the sites that are phosphorylated. Many of the peculiarities associated with FUS may also be shared by other IDPs, such as TDP43 and hnRNPA2. We outline a number of problems for which there is no clear molecular understanding

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Section: Resultsmentioning

confidence: 99%

Conformational Fluctuations and Phases in Fused in Sarcoma (FUS) Low-Complexity Domain

Thirumalai,

Kumar,

Chakraborty

et al. 2023

Preprint

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“…While the current approach to understand the free energy landscape employs dimension reduction using autoencoder, this can also be achieved without projecting the data on a few CVs, as in case of transition disconnectivity graph (TRDG), which has been used previously for IDPs. − The TRDG method can be used as a control to evaluate the free energy surface obtained from the latent dimensions of autoencoder. However, the free energy profile for the unphosphorylated and phosphorylated Ash1 and Sic1 system indicated a lack of well-defined metastable states, a typical signature for IDPs, which we expect to get had we used TRDG in the first place, thereby justifying the robustness of autoencoder in learning the low dimensional subspace of IDPs.…”

Section: Discussionmentioning

confidence: 99%

Machine Learning Subtle Conformational Change due to Phosphorylation in Intrinsically Disordered Proteins

Adhikari,

Mondal

2023

J. Phys. Chem. B

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Phosphorylation of intrinsically disordered proteins/regions (IDPs/IDRs) has a profound effect in biological functions such as cell signaling, protein folding or unfolding, and long-range allosteric effects. However, here we focus on two IDPs, namely 83-residue IDR transcription factor Ash1 and 92-residue long N-terminal region of CDK inhibitor Sic1 protein, found in Saccharomyces cerevisiae, for which experimental measurements of average conformational properties, namely, radius of gyration and structure factor, indicate negligible changes upon phosphorylation. Here, we show that a judicious dissection of conformational ensemble via combination of unsupervised machine learning and extensive molecular dynamics (MD) trajectories can highlight key differences and similarities among the phosphorylated and wild-type IDP. In particular, we develop Markov state model (MSM) using the latent-space dimensions of an autoencoder, trained using multi-microsecond long MD simulation trajectories. Examination of structural changes among the states, prior to and upon phosphorylation, captured several similarities and differences in their backbone contact maps, secondary structure, and torsion angles. Hydrogen bonding analysis revealed that phosphorylation not only increases the number of hydrogen bonds but also switches the pattern of hydrogen bonding between the backbone and side chain atoms with the phosphorylated residues. We also observe that although phosphorylation introduces salt bridges, there is a loss of the cation–π interaction. Phosphorylation also improved the probability for long-range hydrophobic contacts and also enhanced interaction with water molecules and improved the local structure of water as evident from the geometric order parameters. The observations on these machine-learnt states gave important insights, as it would otherwise be difficult to determine experimentally which is important, if we were to understand the role of phosphorylation of IDPs in their biological functions.

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“…Energy function: In the spirit of an earlier study, 31 and subsequent reports , 30,[32][33][34] each amino acid is represented by two beads, one representing the C α atom. The other bead is located at the center of mass of the side-chain (SC) of the amino acid residues.…”

Section: Computational Detailsmentioning

confidence: 99%

Sizes, conformational fluctuations, and SAXS profiles for Intrinsically Disordered Proteins

Mugnai

Chakraborty

Kumar

et al. 2023

Preprint

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The preponderance of Intrinsically Disordered Proteins (IDPs) in the eukaryotic proteome, and their ability to interact with each other, proteins, RNA, and DNA for functional purposes have made it important to quantitatively characterize their biophysical properties. Towards this end, we developed the transferable Self-Organized Polymer (SOP-IDP) model in order to calculate the properties of a number of IDPs. The calculated and measured radius of gyration values (Rgs) are in excellent agreement, with a correlation coefficient of 0.96. For AP180 and Epsin, the predicted and values obtained using Fluorescence Correlation Spectroscopy for the hydrodynamic radii (Rhs) are also in quantitative agreement. Strikingly, the calculated SAXS profiles for thirty six IDPs also nearly match the experiments. The dependence ofRg, the mean end-to-end distance (Re), andRhobey the Flory scaling law,Rα≈ ααN0.59(α =g, e, andh), suggesting that globally IDPs behave as polymers in a good solvent. The values of αg, αe, and αhare 0.21 nm, 0.53 nm, and 0.16 nm, respectively. Surprisingly, finite size corrections to scaling, expected on theoretical grounds, for all the three quantities are negligible. Sequence dependencies, masked in ensemble properties, emerge through a fine structure analyses of the conformational ensembles using a hierarchical clustering method. Typically, the ensemble of conformations partition into three distinct clusters, with differing extent of population and structural properties. The subpopulations could dictate phase separation tendencies and association with ligands. Without any adjustments to the three parameters in the SOP-IDP model, we obtained excellent agreement with paramagnetic relaxation enhancement (PRE) measurements for α-synuclein. The transferable SOP-IDP model sets the stage for a number of promising applications, including the study of phase separation in IDPs and interactions with nucleic acids.

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Energy landscapes of Aβ monomers are sculpted in accordance with Ostwald’s rule of stages

Cited by 21 publications

References 108 publications

Conformational Fluctuations and Phases in Fused in Sarcoma (FUS) Low-Complexity Domain

Conformational Fluctuations and Phases in Fused in Sarcoma (FUS) Low-Complexity Domain

Machine Learning Subtle Conformational Change due to Phosphorylation in Intrinsically Disordered Proteins

Sizes, conformational fluctuations, and SAXS profiles for Intrinsically Disordered Proteins

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