A brief history of amyloid aggregation simulations

Wiley Interdisciplinary Reviews Computational Molecular Science, Journal Year: 2024, Volume and Issue: 14(1)

Published: Jan. 1, 2024

Abstract Amyloid proteins are characterized by their tendency to aggregate into amyloid fibrils, which often associated with devastating diseases. Aggregation pathways typically involve unfolding or misfolding of monomeric and formation transient oligomers protofibrils before the final aggregation product is formed. The conformational dynamics polymorphic volatile nature these intermediates make characterization experimental techniques alone insufficient also require computational approaches. Over past 25 years, size simulated systems length simulations have increased significantly. These advances discussed here. review includes simulation approaches that model aggregating peptides at both all‐atom coarse‐grained levels, use molecular Monte Carlo sampling simulate changes, present results for various ranging from Lys‐Phe‐Phe‐Glu (KFFE) as smallest system an intermediate‐sized peptide α‐synuclein. presentation history concludes a discussion where future may lie. This article categorized under: Structure Mechanism > Computational Biochemistry Biophysics Molecular Statistical Mechanics Dynamics Monte‐Carlo Methods

Language: Английский

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The mechanism of amyloid fibril growth from Φ-value analysis

Nature Chemistry, Journal Year: 2025, Volume and Issue: 17(3), P. 403 - 411

Published: Jan. 16, 2025

Language: Английский

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Impacts of D-aspartate on the aggregation kinetics and structural polymorphism of amyloid β peptide 1-42

Journal of Molecular Biology, Journal Year: 2025, Volume and Issue: unknown, P. 169092 - 169092

Published: March 1, 2025

Language: Английский

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Massive experimental quantification allows interpretable deep learning of protein aggregation

Science Advances, Journal Year: 2025, Volume and Issue: 11(18)

Published: May 1, 2025

Protein aggregation is a pathological hallmark of more than 50 human diseases and major problem for biotechnology. Methods have been proposed to predict from sequence, but these trained evaluated on small biased experimental datasets. Here we directly address this data shortage by experimentally quantifying the >100,000 protein sequences. This unprecedented dataset reveals limited performance existing computational methods allows us train CANYA, convolution-attention hybrid neural network that accurately predicts sequence. We adapt genomic interpretability analyses reveal CANYA's decision-making process learned grammar. Our results illustrate power massive analysis random sequence-spaces provide an interpretable robust model aggregation.

Language: Английский

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Amyloid Aggregation and Liquid–Liquid Phase Separation from the Perspective of Phase Transitions

The Journal of Physical Chemistry B, Journal Year: 2023, Volume and Issue: 127(28), P. 6241 - 6250

Published: July 6, 2023

Amyloid aggregation describes the aberrant self-assembly of peptides into ordered fibrils characterized by cross-β spine cores and is associated with many neurodegenerative diseases Type 2 diabetes. Oligomers, populated during early stage aggregation, are found to be more cytotoxic than mature fibrils. Recently, amyloidogenic have been reported undergo liquid–liquid phase separation (LLPS)─a biological process important for compartmentalization biomolecules in living cells─prior fibril formation. Understanding relationship between LLPS amyloid especially formation oligomers, essential uncovering disease mechanisms mitigating toxicity. In this Perspective, available theories models first briefly reviewed. By drawing analogies gas, liquid, solid phases thermodynamics, a diagram protein monomer, droplet, states separated coexistence lines can inferred. Due high free energy barrier fibrillization kinetically delaying seeds out droplets, "hidden" monomer-droplet line extends phase. then described as equilibration from initial "out-of-equilibrium" state homogeneous solution monomers final equilibrium stable coexisting and/or droplets via metastable or intermediates. The oligomers also discussed. We suggest that droplet should considered future studies which may help better understand develop therapeutic strategies mitigate

Language: Английский

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

The Journal of Physical Chemistry B, Journal Year: 2023, Volume and Issue: 127(44), P. 9433 - 9449

Published: Oct. 31, 2023

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

Language: Английский

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

bioRxiv (Cold Spring Harbor Laboratory), Journal Year: 2023, Volume and Issue: unknown

Published: April 27, 2023

Abstract The preponderance of Intrinsically Disordered Proteins (IDPs) in the eukaryotic proteome, and their ability to interact with each other, folded proteins, RNA, DNA for functional purposes, have made it important quantitatively characterize biophysical properties. Toward this end, we developed transferable Self-Organized Polymer (SOP-IDP) model calculate properties several IDPs. values radius gyration ( R g ) obtained from SOP-IDP simulations are excellent agreement (correlation coefficient 0.96) those estimated SAXS experiments. For AP180 Epsin, predicted hydrodynamic radii h s) quantitative Fluorescence Correlation Spectroscopy (FCS) Strikingly, calculated spectra thirty-six IDPs also nearly superimposable on experimental profiles. dependence mean end-to-end distance ee chain length, N , follows Flory’s scaling law, α ≈ a 0.588 = e ), suggesting that globally behave as synthetic polymers good solvent. 0.20 nm 0.48 respectively. Surprisingly, finite size corrections scaling, expected theoretical grounds, negligible . In contrast, only by accounting sizes IDPs, experimentally measurable can be explained using ν 0.588. Although Flory law captures estimates accurately, spread simulated data around curve is suggestive sequence-specific features emerge through fine-grained analysis conformational ensembles hierarchical clustering. Typically, ensemble conformations partitiones into three distinct clusters, having different equilibrium populations structural Without any further readjustments parameters model, paramagnetic relaxation enhancement (PRE) measurements -synuclein. sets stage applications, including study phase separation interactions nucleic acids.

Language: Английский

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Hairpin trimer transition state of amyloid fibril

Nature Communications, Journal Year: 2024, Volume and Issue: 15(1)

Published: March 29, 2024

Abstract Protein fibril self-assembly is a universal transition implicated in neurodegenerative diseases. Although structure/growth are well characterized, nucleation poorly understood. Here, we use computational-experimental approach to resolve nucleation. We show that monomer hairpin content quantified from molecular dynamics simulations predictive of experimental formation kinetics across tau motif mutant library. Hairpin trimers predicted be states; one spontaneously converts into the cross-beta conformation, templating subsequent growth. designed disulfide-linked dimer mimicking state catalyzes formation, measured by ThT fluorescence and TEM, wild-type - which does not normally fibrillize. A compatible with extended conformations but transition-state fails nucleate at any concentration. Tau repeat domain how long-range interactions sequester this mutation-dependent manner. This work implies different morphologies could arise disease-dependent seeding loci.

Language: Английский

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Odd–even disparity in the population of slipped hairpins in RNA repeat sequences with implications for phase separation

Proceedings of the National Academy of Sciences, Journal Year: 2023, Volume and Issue: 120(24)

Published: June 5, 2023

Low-complexity nucleotide repeat sequences, which are implicated in several neurological disorders, undergo liquid-liquid phase separation (LLPS) provided the number of units, n, exceeds a critical value. Here, we establish link between folding landscapes monomers trinucleotide repeats and their propensity to self-associate. Simulations using coarse-grained Self-Organized Polymer (SOP) model for (CAG)n monovalent salt solutions reproduce experimentally measured melting temperatures, available only small n. By extending simulations large show that free-energy gap, ΔGS, ground state (GS) slipped hairpin (SH) states is predictor aggregation propensity. The GS even n perfect (PH), whereas it SH when odd. value ΔGS (zero odd n) larger than As result, rate dimer formation slower (CAG)30 relative (CAG)31, thus linking RNA-RNA association. yield decreases dramatically, compared wild type, mutant sequences population substantially. Association RNA chains preceded by transition if PH. finding excitation spectrum-which depends on exact sequence, ionic conditions-is self-association should also hold other RNAs (mRNA example) LLPS.

Language: Английский

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Sizes, conformational fluctuations, and SAXS profiles for intrinsically disordered proteins

Protein Science, Journal Year: 2025, Volume and Issue: 34(4)

Published: March 17, 2025

Abstract The preponderance of intrinsically disordered proteins (IDPs) in the eukaryotic proteome, and their ability to interact with each other, folded proteins, RNA, DNA for functional purposes, have made it important quantitatively characterize biophysical properties. Toward this end, we developed transferable self‐organized polymer (SOP‐IDP) model calculate properties several IDPs. values radius gyration () obtained from SOP‐IDP simulations are excellent agreement (correlation coefficient 0.96) those estimated SAXS experiments. For AP180 Epsin, predicted hydrodynamic radii nearly quantitative fluorescence correlation spectroscopy (FCS) Strikingly, calculated profiles 36 IDPs also superimposable on experimental profiles. dependence mean end‐to‐end distance chain length, , follows Flory's scaling law, ( ), suggesting that globally behave as synthetic polymers a good solvent. This finding depends solvent quality, which can be altered by changing variables such pH salt concentration. 0.20 0.48 nm, respectively. Surprisingly, finite size corrections scaling, expected theoretical grounds, negligible . In contrast, only accounting sizes IDPs, experimentally measurable explained using Although Flory law captures estimates accurately, spread simulated data around curve is suggestive sequence‐specific features emerge through fine‐grained analysis conformational ensembles hierarchical clustering. Typically, ensemble conformations partitions into three distinct clusters, having different equilibrium populations structural Without any further readjustments parameters model, paramagnetic relaxation enhancement (PRE) measurements α ‐synuclein. sets stage applications, including study phase separation interactions nucleic acids.

Language: Английский

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