The Energy Landscape Perspective: Encoding Structure and Function for Biomolecules

Frontiers in Molecular Biosciences, Journal Year: 2022, Volume and Issue: 9

Published: Jan. 27, 2022

The energy landscape perspective is outlined with particular reference to biomolecules that perform multiple functions. We associate these multifunctional molecules multifunnel landscapes, illustrated by some selected examples, where understanding the organisation of has provided new insight into function. Conformational selection and induced fit may provide alternative routes realisation multifunctionality, exploiting possibility environmental control distinct binding modes.

Language: Английский

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Mutations in Tau Protein Promote Aggregation by Favoring Extended Conformations

JACS Au, Journal Year: 2023, Volume and Issue: 4(1), P. 92 - 100

Published: Dec. 19, 2023

Amyloid aggregation of the intrinsically disordered protein (IDP) tau is involved in several diseases, called tauopathies. Some tauopathies can be inherited due to mutations gene encoding tau, which might favor formation amyloid fibrils. This work aims at deciphering mechanisms through disease-associated single-point promote formation. We combined biochemical and biophysical characterization, notably, small-angle X-ray scattering (SAXS), study six different FTDP-17 derived mutations. found that degrees modulate conformational ensembles, intermolecular interactions, liquid-liquid phase separation propensity. In particular, we a good correlation between lag time mutants their radii gyration. show disfavor intramolecular turn extended conformations aggregation. proposes new connection structural features monomers propensity aggregate, providing novel assay evaluate IDPs.

Language: Английский

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Advanced computational approaches to understand protein aggregation

Biophysics Reviews, Journal Year: 2024, Volume and Issue: 5(2)

Published: April 24, 2024

Protein aggregation is a widespread phenomenon implicated in debilitating diseases like Alzheimer's, Parkinson's, and cataracts, presenting complex hurdles for the field of molecular biology. In this review, we explore evolving realm computational methods bioinformatics tools that have revolutionized our comprehension protein aggregation. Beginning with discussion multifaceted challenges associated understanding process emphasizing critical need precise predictive tools, highlight how techniques become indispensable We focus on simulations, notably dynamics (MD) spanning from atomistic to coarse-grained levels, which emerged as pivotal unraveling governing such Parkinson's. MD simulations provide microscopic insights into interactions subtleties pathways, advanced replica exchange dynamics, Metadynamics (MetaD), umbrella sampling enhancing by probing intricate energy landscapes transition states. delve specific applications elucidating chaperone mechanism underlying cataract formation using Markov state modeling pathways driving toxic aggregate Alzheimer's Parkinson's disease. Transitioning techniques, including bioinformatics, sequence analysis, structural data, machine learning algorithms, artificial intelligence predicting propensity locating aggregation-prone regions within sequences. Throughout exploration, underscore symbiotic relationship between approaches empirical has paved way potential therapeutic strategies against aggregation-related diseases. conclusion, review offers comprehensive overview methodologies catalyzed breakthroughs basis aggregation, significant implications clinical interventions, standing at intersection biology experimental research.

Language: Английский

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Modeling the Structure and Interactions of Intrinsically Disordered Peptides with Multiple Replica, Metadynamics-Based Sampling Methods and Force-Field Combinations

Journal of Chemical Theory and Computation, Journal Year: 2022, Volume and Issue: 18(3), P. 1915 - 1928

Published: Feb. 17, 2022

Intrinsically disordered proteins play a key role in many biological processes, including the formation of biomolecular condensates within cells. A detailed characterization their configurational ensemble and structure-function paradigm is crucial for understanding activity exploiting them as building blocks material sciences. In this work, we incorporate bias-exchange metadynamics parallel-tempering well-tempered with CHARMM36m CHARMM22* to explore structural thermodynamic characteristics short archetypal sequence derived from DEAD-box protein. The conformational landscapes emerging our simulations are largely congruent across methods force fields. Nevertheless, differences fine details emerge varying combinations force-fields sampling methods. For protein, analysis identifies features that help explain low propensity undergo self-association vitro, which common all force-field/sampling method combinations. Overall, work demonstrates importance using multiple force-field accurate information study proteins.

Language: Английский

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AlphaFold2 models indicate that protein sequence determines both structure and dynamics

Research Square (Research Square), Journal Year: 2022, Volume and Issue: unknown

Published: May 18, 2022

Abstract AlphaFold 2 (AF2) has placed Molecular Biology in a new era where we can visualize, analyze and interpret the structures functions of all proteins solely from their primary sequences. We performed AF2 structure predictions for various protein systems, including globular proteins, multi-domain protein, an intrinsically disordered (IDP), randomized two larger (> 1000 AA), heterodimer homodimer complex. Our results show that along with three dimensional (3D) structures, also decodes sequences into residue flexibilities via both predicted local distance difference test (pLDDT) scores models, aligned error (PAE) maps. PAE maps are correlated variation (DV) matrices molecular dynamics (MD) simulations, which reveals predict dynamical nature residues. Here, introduce AF2-scores, simply derived pLDDT range [0, 1]. found good multisequence alignment (MSA) depths, large complexes, AF2-scores highly root mean square fluctuations (RMSF) calculated MD simulations. For little or no MSA hits (the IDP protein), do not correlate RMSF MD, especially (IDPs). indicate by convey information flexibility, i.e., dynamics.

Language: Английский

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