AlzDiscovery: A computational tool to identify Alzheimer's disease‐causing missense mutations using protein structure information DOI Creative Commons
Qisheng Pan,

Georgina Becerra Parra,

Yoochan Myung

et al.

Protein Science, Journal Year: 2024, Volume and Issue: 33(10)

Published: Sept. 14, 2024

Abstract Alzheimer's disease (AD) is one of the most common forms dementia and neurodegenerative diseases, characterized by formation neuritic plaques neurofibrillary tangles. Many different proteins participate in this complicated pathogenic mechanism, missense mutations can alter folding functions these proteins, significantly increasing risk AD. However, many methods to identify AD‐causing variants did not consider effect from perspective a protein three‐dimensional environment. Here, we present machine learning‐based analysis classify their benign counterparts 21 AD‐related leveraging both sequence‐ structure‐based features. Using computational tools estimate on stability, first observed bias with significant destabilizing effects family proteins. Combining insight, built generic predictive model, improved performance tuning sample weights training process. Our final model achieved area under receiver operating characteristic curve up 0.95 blind test 0.70 an independent clinical validation, outperforming all state‐of‐the‐art methods. Feature interpretation indicated that hydrophobic environment polar interaction contacts were crucial decision phenotypes mutations. Finally, presented user‐friendly web server, AlzDiscovery, for researchers browse predicted possible study will be valuable resource AD screening development personalized treatment.

Language: Английский

Misfolded protein oligomers: mechanisms of formation, cytotoxic effects, and pharmacological approaches against protein misfolding diseases DOI Creative Commons
Dillon J. Rinauro, Fabrizio Chiti, Michele Vendruscolo

et al.

Molecular Neurodegeneration, Journal Year: 2024, Volume and Issue: 19(1)

Published: Feb. 20, 2024

The conversion of native peptides and proteins into amyloid aggregates is a hallmark over 50 human disorders, including Alzheimer's Parkinson's diseases. Increasing evidence implicates misfolded protein oligomers produced during the formation process as primary cytotoxic agents in many these devastating conditions. In this review, we analyze processes by which are formed, their structures, physicochemical properties, population dynamics, mechanisms cytotoxicity. We then focus on drug discovery strategies that target ability to disrupt cell physiology trigger degenerative processes.

Language: Английский

Citations

47

Small molecules targeting the disordered transactivation domain of the androgen receptor induce the formation of collapsed helical states DOI Creative Commons
Jiaqi Zhu, Xavier Salvatella, Paul Robustelli

et al.

Nature Communications, Journal Year: 2022, Volume and Issue: 13(1)

Published: Oct. 27, 2022

Abstract Intrinsically disordered proteins, which do not adopt well-defined structures under physiological conditions, are implicated in many human diseases. Small molecules that target the transactivation domain of androgen receptor have entered trials for treatment castration-resistant prostate cancer (CRPC), but no structural or mechanistic rationale exists to explain their inhibition mechanisms relative potencies. Here, we utilize all-atom molecular dynamics computer simulations elucidate atomically detailed binding compounds EPI-002 and EPI-7170 receptor. Our reveal both bind at interface two transiently helical regions induce formation partially folded collapsed states. We find binds more tightly than identify a network intermolecular interactions drives higher affinity binding. results suggest strategies developing potent inhibitors general protein drug design.

Language: Английский

Citations

53

Picosecond Dynamics of a Small Molecule in Its Bound State with an Intrinsically Disordered Protein DOI Creative Commons
Gabriella T. Heller, Vaibhav Kumar Shukla, Angelo Miguel Figueiredo

et al.

Journal of the American Chemical Society, Journal Year: 2024, Volume and Issue: 146(4), P. 2319 - 2324

Published: Jan. 22, 2024

Intrinsically disordered proteins (IDPs) are highly dynamic biomolecules that rapidly interconvert among many structural conformations. These involved in cancers, neurodegeneration, cardiovascular illnesses, and viral infections. Despite their enormous therapeutic potential, IDPs have generally been considered undruggable because of lack classical long-lived binding pockets for small molecules. Currently, only a few instances known where molecules observed to interact with IDPs, this situation is further exacerbated by the limited sensitivity experimental techniques detect such events. Here, using nuclear magnetic resonance (NMR) spectroscopy

Language: Английский

Citations

16

Folding-upon-binding pathways of an intrinsically disordered protein from a deep Markov state model DOI Creative Commons
Thomas R. Sisk, Paul Robustelli

Proceedings of the National Academy of Sciences, Journal Year: 2024, Volume and Issue: 121(6)

Published: Jan. 31, 2024

A central challenge in the study of intrinsically disordered proteins is characterization mechanisms by which they bind their physiological interaction partners. Here, we utilize a deep learning–based Markov state modeling approach to characterize folding-upon-binding pathways observed long timescale molecular dynamics simulation region measles virus nucleoprotein N TAIL reversibly binding X domain phosphoprotein complex. We find that predominantly occurs via two distinct encounter complexes are differentiated orientation, helical content, and conformational heterogeneity . observe proceeds through multi-step induced fit mechanism with several intermediates do not evidence for existence canonical selection pathways. four kinetically separated native-like bound states interconvert on timescales eighty five hundred nanoseconds. These share core set native intermolecular contacts stable helices sequential formation non-native additional turns. Our analyses provide an atomic resolution structural description intermediate pathway elucidate nature kinetic barriers between metastable dynamic heterogenous, or “fuzzy”, protein

Language: Английский

Citations

10

Extracellular protein homeostasis in neurodegenerative diseases DOI
Mark R. Wilson, Sandeep Satapathy, Michele Vendruscolo

et al.

Nature Reviews Neurology, Journal Year: 2023, Volume and Issue: unknown

Published: Feb. 24, 2023

Language: Английский

Citations

23

Context-dependent, fuzzy protein interactions: Towards sequence-based insights DOI Creative Commons
Mónika Fuxreiter

Current Opinion in Structural Biology, Journal Year: 2024, Volume and Issue: 87, P. 102834 - 102834

Published: May 16, 2024

Predicting protein interactions in the cellular environment still remains a challenge AlphaFold era. Protein interactions, similarly to their structures, sample continuum from ordered disordered states, with specific partners many bound configurations. A multiplicity of binding modes (MBM) enables transition between these states under different conditions. This review focuses on how affects highlighting molecular mechanisms, biophysical origin, and sequence-based principles context-dependent, fuzzy interactions. It summarises experimental computational approaches address interaction heterogeneity its contribution wide range biological functions. These insights will help understanding complex processes, involving conversions assembly such as liquid-like droplet state amyloid state.

Language: Английский

Citations

7

Rational drug design targeting intrinsically disordered proteins DOI
H. Wang,

Ruoyao Xiong,

Luhua Lai

et al.

Wiley Interdisciplinary Reviews Computational Molecular Science, Journal Year: 2023, Volume and Issue: 13(6)

Published: Aug. 26, 2023

Abstract Intrinsically disordered proteins (IDPs) are that perform important biological functions without well‐defined structures under physiological conditions. IDPs can form fuzzy complexes with other molecules, participate in the formation of membraneless organelles, and function as hubs protein–protein interaction networks. The malfunction causes major human diseases. However, drug design targeting remains challenging due to their highly dynamic interactions. Turning into druggable targets provides a great opportunity extend target‐space for novel discovery. Integrative structural biology approaches combine information derived from computational simulations, artificial intelligence/data‐driven analysis experimental studies have been used uncover interactions IDPs. An increasing number ligands directly bind found either by target‐based screening or phenotypic screening. Along understanding IDP binding its partners, structure‐based strategies, especially conformational ensemble‐based ligand computer‐aided optimization algorithms, greatly accelerated development ligands. It is inspiring several IDP‐targeting small‐molecule peptide drugs advanced clinical trials. new methods need be further developed efficiently discovering optimizing specific potent vast interactions, expected become valuable treasure targets. This article categorized under: Structure Mechanism > Computational Biochemistry Biophysics

Language: Английский

Citations

15

CoVAMPnet: Comparative Markov State Analysis for Studying Effects of Drug Candidates on Disordered Biomolecules DOI Creative Commons
Sérgio M. Marques, Petr Kouba, Anthony Legrand

et al.

JACS Au, Journal Year: 2024, Volume and Issue: 4(6), P. 2228 - 2245

Published: May 28, 2024

Computational study of the effect drug candidates on intrinsically disordered biomolecules is challenging due to their vast and complex conformational space. Here, we developed a comparative Markov state analysis (CoVAMPnet) framework quantify changes in distribution dynamics biomolecule presence absence small organic candidate molecules. First, molecular trajectories are generated using enhanced sampling, molecule candidates, ensembles soft models (MSMs) learned for each system unsupervised machine learning. Second, these MSMs aligned across different systems based solution an optimal transport problem. Third, directional importance inter-residue distances assignment states assessed by discriminative aggregated neural network gradients. This final step provides interpretability biophysical context MSMs. We applied this novel computational assess effects ongoing phase 3 therapeutics tramiprosate (TMP) its metabolite 3-sulfopropanoic acid (SPA) Aβ42 peptide involved Alzheimer's disease. Based adaptive sampling CoVAMPnet analysis, observed that both TMP SPA preserved more structured conformations interacting nonspecifically with charged residues. impacted than TMP, protecting α-helices suppressing formation aggregation-prone β-strands. Experimental analyses showed only mild TMP/SPA activity enhancement endogenous metabolization into SPA. Our data suggest may also target other Aβ peptides. The method broadly applicable behavior biomolecules.

Language: Английский

Citations

4

An Integrated Machine Learning Approach Delineates Entropy-mediated Conformational Modulation of α-synuclein by Small Molecule DOI Open Access
Sneha Menon,

Subinoy Adhikari,

Jagannath Mondal

et al.

Published: June 3, 2024

The mis-folding and aggregation of intrinsically disordered proteins (IDPs) such as α -synuclein ( S) underlie the pathogenesis various neurodegenerative disorders. However, targeting S with small molecules faces challenges due to its lack defined ligand-binding pockets in structure. Here, we implement a deep artificial neural network based machine learning approach, which is able statistically distinguish fuzzy ensemble conformational substates neat water from those aqueous fasudil (small molecule interest) solution. In particular, presence milieu either modulates pre-existing states or gives rise new S, akin an ensemble-expansion mechanism. ensembles display strong conformation-dependence residue-wise interaction molecule. A thermodynamic analysis indicates that small-molecule structural repertoire via tuning protein backbone entropy, however keeping entropic ordering surrounding solvent unperturbed. Together, this study sheds light on intricate interplay between IDPs, offering insights into modulation expansion key biophysical mechanisms driving potential therapeutics.

Language: Английский

Citations

4

Atomistic molecular dynamics simulations of intrinsically disordered proteins DOI Creative Commons

Fidha Nazreen Kunnath Muhammedkutty,

Matthew MacAinsh,

Huan‐Xiang Zhou

et al.

Current Opinion in Structural Biology, Journal Year: 2025, Volume and Issue: 92, P. 103029 - 103029

Published: March 10, 2025

Language: Английский

Citations

0