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相关论文: Guiding Peptide Kinetics via Collective-Variable T…

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Engineering the free-energy surfaces (FES) of proteins and peptides is central to controlling conformational ensembles and their responses to perturbations. However, predicting how chemical modifications such as point mutations reshape the…

生物物理 · 物理学 2026-03-10 Muralika Medaparambath , Alexander Zhilkin , Dan Mendels

We introduce a method for elucidating and modifying the functionality of systems dominated by rare events that relies on the automated tuning of their underlying free energy surface. The proposed approach seeks to construct collective…

计算物理 · 物理学 2021-08-31 Dan Mendels , Juan J. de Pablo

Mini-proteins and peptides manifest dynamic conformational fluctuation and involve mutual interconversion among metastable states. A robust mapping of the conformational landscape underlying mini-proteins and peptides often requires…

化学物理 · 物理学 2021-09-29 Satyabrata Bandyopadhyay , Jagannath Mondal

Enhanced sampling methods such as metadynamics and umbrella sampling have become essential tools for exploring the configuration space of molecules and materials. At the same time, they have long faced a number of issues such as the…

化学物理 · 物理学 2021-12-28 Dongdong Wang , Yanze Wang , Junhan Chang , Linfeng Zhang , Han Wang , Weinan E

A variety of enhanced sampling methods predict multidimensional free energy landscapes associated with biological and other molecular processes as a function of a few selected collective variables (CVs). The accuracy of these methods is…

计算物理 · 物理学 2024-04-09 Lukas Müllender , Andrea Rizzi , Michele Parrinello , Paolo Carloni , Davide Mandelli

Many processes of scientific importance are characterized by time scales that extend far beyond the reach of standard simulation techniques. To circumvent this impediment a plethora of enhanced sampling methods has been developed. One…

Free energy biasing methods have proven to be powerful tools to accelerate the simulation of important conformational changes of molecules by modifying the sampling measure. However, most of these methods rely on the prior knowledge of…

生物物理 · 物理学 2021-10-20 Zineb Belkacemi , Paraskevi Gkeka , Tony Lelièvre , Gabriel Stoltz

The heat shock protein 90 (Hsp90) is a molecular chaperone that controls the folding and activation of client proteins using the free energy of ATP hydrolysis. The Hsp90 active site is in its N-terminal domain (NTD). Our goal is to…

In molecular dynamics simulations, rare events, such as protein folding, are typically studied using enhanced sampling techniques, most of which are based on the definition of a collective variable (CV) along which acceleration occurs.…

化学物理 · 物理学 2024-07-22 Soojung Yang , Juno Nam , Johannes C. B. Dietschreit , Rafael Gómez-Bombarelli

Protein function does not solely depend on structure but often relies on dynamical transitions between distinct conformations. Despite this fact, our ability to characterize or predict protein dynamics is substantially less developed…

统计力学 · 物理学 2026-05-08 Michael A. Sauer , Souvik Mondal , Brandon Neff , Sthitadhi Maiti , Matthias Heyden

Well-Tempered Metadynamics (WTmetaD) is an efficient method to enhance the reconstruction of the free-energy surface of proteins. WTmetaD guarantees a faster convergence in the long time limit in comparison with the standard metadynamics.…

生物物理 · 物理学 2015-06-12 Francois Sicard , Patrick Senet

This work examines the conformational ensemble involved in $\beta$-hairpin folding by means of advanced molecular dynamics simulations and dimensionality reduction. A fully atomistic description of the protein and the surrounding solvent…

化学物理 · 物理学 2023-06-16 Albert Ardevol , Gareth A. Tribello , Michele Ceriotti , Michele Parrinello

Understanding protein conformational dynamics is essential for elucidating biological function but remains challenging due to the wide range of timescales and the complexity of collective motions. Enhanced sampling methods overcome…

统计力学 · 物理学 2026-05-11 Souvik Mondal , Michael A. Sauer , Matthias Heyden

A central goal of protein-folding theory is to predict the stochastic dynamics of transition paths --- the rare trajectories that transit between the folded and unfolded ensembles --- using only thermodynamic information, such as a…

生物大分子 · 定量生物学 2018-08-09 William M. Jacobs , Eugene I. Shakhnovich

Enhanced sampling techniques such as umbrella sampling and metadynamics are now routinely used to provide information on how the thermodynamic potential, or free energy, depends on a small number of collective variables. The free energy…

计算物理 · 物理学 2018-08-31 Ilaria Gimondi , Gareth A. Tribello , Matteo Salvalaglio

A microscopic theory of the free energy barriers and folding routes for minimally frustrated proteins is presented, greatly expanding on the presentation of the variational approach outlined previously [J. J. Portman, S. Takada, P. G.…

软凝聚态物质 · 物理学 2009-10-31 John J. Portman , Shoji Takada , Peter G. Wolynes

Generating a data set that is representative of the accessible configuration space of a molecular system is crucial for the robustness of machine learned interatomic potentials (MLIP). However, the complexity of molecular systems,…

机器学习 · 计算机科学 2025-01-28 Aik Rui Tan , Johannes C. B. Dietschreit , Rafael Gomez-Bombarelli

Protein folding is one of the age-old biological problems that refers to the mechanism of understanding and predicting how a protein's linear sequence of amino acids folds into its specific three dimensional structure.This structure is…

A protein's function depends critically on its conformational ensemble, a collection of energy weighted structures whose balance depends on temperature and environment. Though recent deep learning (DL) methods have substantially advanced…

生物大分子 · 定量生物学 2026-01-09 Myeongsang Lee , Lauren L. Porter

We present a method for determining the free energy dependence on a selected number of collective variables using an adaptive bias. The formalism provides a unified description which has metadynamics and canonical sampling as limiting…

统计力学 · 物理学 2008-03-31 Alessandro Barducci , Giovanni Bussi , Michele Parrinello
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