Impact of Phosphorylation on the Structural Ensemble of alpha-Synuclein in Aqueous Solution DOI Open Access
Emile De Bruyn, Anton Emil Dorn, Giulia Rossetti

et al.

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

Published: March 12, 2023

Abstract Serine 129 can be phosphorylated in pathological inclusions formed by the intrinsically disordered protein human α -synuclein (AS), a key player Parkinson’s disease and other synucleinopathies. Here, molecular simulations provide insight into structural ensemble of AS. The suggest that phosphorylation does not impact content physiological AS conformational aqueous solution, as phosphate group is mostly solvated. hydrophobic region contains β -hairpin structures, which may increase propensity to undergo amyloid formation, seen non-physiological (non-acetylated) form recent simulation study. Our findings are consistent with existing experimental data, caveat observed limitations force field for moiety. Figure

Language: Английский

The ribonucleoprotein hnRNPA1 mediates RNA and DNA telomeric G-quadruplexes through an RGG-rich region DOI Creative Commons
Sangeetha Balasubramanian,

Irawati Roy,

Rajeswari Appadurai

et al.

Journal of Biological Chemistry, Journal Year: 2025, Volume and Issue: unknown, P. 108491 - 108491

Published: April 1, 2025

hnRNPA1, a protein from the heterogeneous-nuclear ribonucleoprotein family, mediates cellular processes such as RNA metabolism and DNA telomere maintenance. Besides folded recognition motifs, hnRNPA1 has ∼135 amino-acids long low-complexity domain (LCD) consisting of an RGG-rich region prion-like (PrLD). Biochemical data suggest that modulates G-quadruplexes (GQs) in telomeric repeats. Here, we utilize in-house developed replica exchange technique (REHT) to generate heterogeneous conformational ensemble hnRNPA1-RGG explore its functional significance Single chain statistics abundance structural well consistency with experimentally reported faithful recapitulation local interactions. We also introduce protocol functionally significant IDP-nucleic acid complex structures corroborate experimental knowledge their binding. find RGG-box preferentially binds grooves loops GQs providing specificity towards certain GQ sequence secondary structures. Turn-like expose Phe promote stacking G-tetrads, while Tyr Asn residues form essential hydrogen bonds electrostatic Several these were identified important by earlier HSQC chemical shift data. Our binding simulation studies reveal minor population can perturb structure, which likely expedites unfolding activities hnRNPA1-UP1 at end.

Language: Английский

Citations

1
A Stochastic Landscape Approach for Protein Folding State Classification DOI Creative Commons
Michael Faran, Dhiman Ray,

Shubhadeep Nag

et al.

Journal of Chemical Theory and Computation, Journal Year: 2024, Volume and Issue: 20(13), P. 5428 - 5438

Published: June 26, 2024

Protein folding is a critical process that determines the functional state of proteins. Proper essential for proteins to acquire their three-dimensional structures and execute biological role, whereas misfolded can lead various diseases, including neurodegenerative disorders like Alzheimer's Parkinson's. Therefore, deeper understanding protein vital disease mechanisms developing therapeutic strategies. This study introduces Stochastic Landscape Classification (SLC), an innovative, automated, nonlearning algorithm quantitatively analyzes dynamics. Focusing on collective variables (CVs) – low-dimensional representations complex dynamical systems molecular dynamics (MD) macromolecules SLC approach segments CVs into distinct macrostates, revealing pathway explored by MD simulations. The segmentation achieved analyzing changes in CV trends clustering these using standard density-based spatial applications with noise (DBSCAN) scheme. Applied MD-based trajectories Chignolin Trp-Cage proteins, demonstrates apposite accuracy, validated comparing classification metrics against ground-truth data. These affirm efficacy capturing intricate offer method evaluate select most informative CVs. practical application this technique lies its ability provide detailed, quantitative description processes, significant implications manipulating behavior industrial pharmaceutical contexts.

Language: Английский

Citations

6
Machine-learning-based methods to generate conformational ensembles of disordered proteins DOI Creative Commons
Ishan Taneja, Keren Lasker

Biophysical Journal, Journal Year: 2023, Volume and Issue: 123(1), P. 101 - 113

Published: Dec. 5, 2023

Language: Английский

Citations

11
Boosting Electrochemical Sensing Performances Using Molecularly Imprinted Nanoparticles DOI Creative Commons
Francesco Gagliani, Tiziano Di Giulio, Muhammad Ibrar Asif

et al.

Biosensors, Journal Year: 2024, Volume and Issue: 14(7), P. 358 - 358

Published: July 22, 2024

Nanoparticles of molecularly imprinted polymers (nanoMIPs) combine the excellent recognition ability with specific properties related to nanosize, such as a high surface-to-volume ratio, resulting in highly performing elements surface-exposed binding sites that promote interaction target and, turn, kinetics. Different synthetic strategies are currently available produce nanoMIPs, possibility select conditions relation nature monomers/templates importantly, tune nanoparticle size. The sensing properties, combined size, tunability, and flexibility protocols applicable different targets, have enabled widespread use nanoMIPs several applications, including sensors, imaging, drug delivery. present review summarizes applications specifically focusing on electrochemical detection, for which been mostly applied. After general survey most widely adopted nanoMIP approaches, integration nanoparticles transducers will be discussed, representing key step enabling reliable stable sensor response. mechanisms signal generation also compared, followed by an illustration nanoMIP-based employment application fields. potentialities sensors presented, possible reasons still limit their commercialization issues resolved coupling increasingly daily-use technology discussed.

Language: Английский

Citations

4
Salts Influence IDP Properties by Modulating the Population of Conformational Clusters DOI
Lipika Baidya, Hiranmay Maity, Govardhan Reddy

et al.

The Journal of Physical Chemistry B, Journal Year: 2025, Volume and Issue: unknown

Published: Feb. 20, 2025

Salts readily alter the physical properties of intrinsically disordered proteins (IDPs) rich in charged residues. Using a coarse-grained IDP model and computer simulations, we investigated how salts affect heterogeneous conformational ensemble segment-level structures prothymosin-α, classified as polyelectrolyte. We show that clusters conformations with distinct structural features are present within prothymosin-α by projecting it onto two-dimensional latent space aid autoencoders. Although is inherently disordered, there preferred transitions between these conformations. Changing salt concentration led to formation new or/and disappearance existing clusters, contributing changes properties. Shuffling Skopelitian domain (C-terminal sequence) known for its anticancer activity, resulted different cluster, indicating specific related particular function. The multiple could be correlated functions, or inhibit functions modulating population clusters.

Language: Английский

Citations

0
New Approach for Targeting Small Molecule Candidates for Intrinsically Disordered Proteins DOI
Milan Senćanski

Published: April 23, 2025

Intrinsically disordered proteins (IDPs), like the Alzheimer’s associated tau protein, pose challenges for conventional drug discovery. This study applied Informational Spectrum Method Small Molecules (ISM-SM), a computational technique utilising electron-ion interaction potentials (EIIP), to identify potential modulators. Characteristic frequencies derived from known ligands and conserved mammalian sequences were used screen DrugBank COCONUT natural product database. The screening identified approved drugs previously reported indirectly influence pathology or disease pathways, alongside products Bryostatin-14, modulate kinases involved in phosphorylation. These findings suggest ISM-SM can serve as an silico tool candidate small molecules, including repurposed products, with relevance function pathology, complementing other IDP discovery strategies.

Language: Английский

Citations

0
Robustness in biomolecular simulations: Addressing challenges in data generation, analysis, and curation DOI Creative Commons
Anne M. Brown, Justin A. Lemkul

Cell Reports Physical Science, Journal Year: 2025, Volume and Issue: unknown, P. 102566 - 102566

Published: April 1, 2025

Language: Английский

Citations

0
Mapping conformational landscape in protein folding: Benchmarking dimensionality reduction and clustering techniques on the Trp-Cage mini-protein DOI
Sudha Bhattacharya, Suman Chakrabarty

Biophysical Chemistry, Journal Year: 2025, Volume and Issue: 319, P. 107389 - 107389

Published: Jan. 17, 2025

Language: Английский

Citations

0
Biological insights from integrative modeling of intrinsically disordered protein systems DOI
Zi Hao Liu, Maria Tsanai, Oufan Zhang

et al.

Current Opinion in Structural Biology, Journal Year: 2025, Volume and Issue: 93, P. 103063 - 103063

Published: May 10, 2025

Language: Английский

Citations

0
Manifold learning in atomistic simulations: a conceptual review DOI Creative Commons
Jakub Rydzewski, Ming Chen, Ómar Valsson

et al.

Machine Learning Science and Technology, Journal Year: 2023, Volume and Issue: 4(3), P. 031001 - 031001

Published: July 17, 2023

Abstract Analyzing large volumes of high-dimensional data requires dimensionality reduction: finding meaningful low-dimensional structures hidden in their observations. Such practice is needed atomistic simulations complex systems where even thousands degrees freedom are sampled. An abundance such makes gaining insight into a specific physical problem strenuous. Our primary aim this review to focus on unsupervised machine learning methods that can be used simulation find manifold providing collective and informative characterization the studied process. manifolds for sampling long-timescale processes free-energy estimation. We describe work datasets from standard enhanced simulations. Unlike recent reviews simulations, we consider only construct based Markov transition probabilities between samples. discuss these techniques conceptual point view, including underlying theoretical frameworks possible limitations.

Language: Английский

Citations

9