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相关论文: Using binding free energy to guide ligand design

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We present a method for the direct evaluation of the difference between the free energies of two crystalline structures, of different symmetry. The method rests on a Monte Carlo procedure which allows one to sample along a path, through…

统计力学 · 物理学 2009-10-30 A. D. Bruce , N. B. Wilding , G. J. Ackland

We present an efficient Monte-Carlo method for long-range interacting systems to calculate free energy as a function of an order parameter. In this method, a variant of the Wang-Landau method regarding the order parameter is combined with…

统计力学 · 物理学 2015-03-18 Kazuya Watanabe , Munetaka Sasaki

The effective free energy of globular protein chain is considered to be a functional defined on smooth curves in three dimensional Euclidean space. From the requirement of geometrical invariance, together with basic facts on conformation of…

凝聚态物理 · 物理学 2009-11-07 A. Feoli , V. V. Nesterenko , G. Scarpetta

Dynamic bonding is an essential feature of many soft materials. Molecular simulations have proven to be a powerful tool for modeling bonding kinetics and thermodynamics in these materials, providing insights into their properties that…

软凝聚态物质 · 物理学 2026-05-26 Tyla R. Holoman , B. P. Prajwal , Glen M. Hocky , Thomas M. Truskett

The free energy of globular protein chain is considered to be a functional defined on smooth curves in three dimensional Euclidean space. From the requirement of geometrical invariance, together with basic facts on conformation of helical…

统计力学 · 物理学 2007-05-23 V. V. Nesterenko , A. Feoli , G. Scarpetta

Here we present an approximate analytical theory for the relationship between a protein structure's contact matrix and the shape of its energy spectrum in amino acid sequence space. We demonstrate a dependence of the number of sequences of…

软凝聚态物质 · 物理学 2009-11-07 Jeremy L. England , Eugene I. Shakhnovich

We present a simple yet accurate numerical approach to compute the free energy of binding of multivalent objects on a receptor-coated surface. The method correctly accounts for the fact that one ligand can bind to at most one receptor. The…

软凝聚态物质 · 物理学 2016-05-05 Nicholas B. Tito , Stefano Angioletti-Uberti , Daan Frenkel

Recent progress in simulation methodologies and in computer power allow first principle simulations of condensed systems with Born-Oppenheimer electronic energies obtained by Quantum Monte Carlo methods. Computing free energies and…

统计力学 · 物理学 2015-05-30 Elisa Liberatore , Miguel A. Morales , David M. Ceperley , Carlo Pierleoni

While recent work towards the development of tight-binding and ab-initio algorithms has focused on molecular dynamics, Monte Carlo methods can often lead to better results with relatively little effort. We present here a multi-step Monte…

统计力学 · 物理学 2009-10-31 Parthapratim Biswas , G. T. Barkema , Normand Mousseau , W. F. van der Weg

We translate the problem of calculating the entropy of a set of binary configurations/signals into a sequence of supervised classification tasks. Subsequently, one can use virtually any machine learning classification algorithm for…

统计力学 · 物理学 2019-10-25 Romuald A. Janik

We carry out highly accurate \emph{ab initio} path integral Monte Carlo (PIMC) simulations to directly estimate the free energy of various warm dense matter systems including the uniform electron gas and hydrogen without any nodal…

量子气体 · 物理学 2024-07-02 Tobias Dornheim , Zhandos Moldabekov , Sebastian Schwalbe , Jan Vorberger

A simple technique is proposed for numerically determining equilibrium ion distribution functions belonging to free energies of the Poisson-Boltzmann type. The central idea is to perform a conventional Monte-Carlo simulation using the free…

软凝聚态物质 · 物理学 2009-10-31 Markus Deserno

In this paper we discuss how the information contained in atomistic simulations of homogeneous nucleation should be used when fitting the parameters in macroscopic nucleation models. We show how the number of solid and liquid atoms in such…

统计力学 · 物理学 2017-10-11 Bingqing Cheng , Gareth A. Tribello , Michele Ceriotti

Monte Carlo simulations are used to study the conformational properties of a folded semiflexible polymer confined to a long channel. We measure the variation in the conformational free energy with respect to the end-to-end distance of the…

软凝聚态物质 · 物理学 2018-09-05 James M. Polson

We provide accurate Monte Carlo results for the free energy of interfaces with periodic boundary conditions in the 3D Ising model. We study a large range of inverse temperatures, allowing to control corrections to scaling. In addition to…

高能物理 - 格点 · 物理学 2008-11-26 Michele Caselle , Martin Hasenbusch , Marco Panero

Free energies play a central role in characterising the behaviour of chemical systems and are among the most important quantities that can be calculated by molecular dynamics simulations. Solvation free energies in various organic solvents,…

化学物理 · 物理学 2026-02-11 J. Harry Moore , Daniel J. Cole , Gabor Csanyi

The system-level dynamics of multivalent biomolecular interactions can be simulated using a rule-based kinetic Monte Carlo method in which a rejection sampling strategy is used to generate reaction events. This method becomes inefficient…

定量方法 · 定量生物学 2010-03-04 Jin Yang , William S. Hlavacek

Free energy calculation is critical in predictive tasks such as protein folding, docking and design. However, rigorous calculation of free energy change is prohibitively expensive in these practical applications. The minimum potential…

生物大分子 · 定量生物学 2016-03-08 Kai Wang , Lanru Liu , Pu Tian

We present a methodology for accelerating the estimation of the free energy from path integral Monte Carlo simulations by considering an intermediate artificial reference system where interactions are inexpensive to evaluate numerically.…

Prediction of protein-ligand binding affinity is a major goal in drug discovery. Generally, free energy gap is calculated between two states (e.g., ligand binding and unbinding). The energy gap implicitly includes the effects of changes in…

生物大分子 · 定量生物学 2022-05-20 Ikki Yasuda , Katsuhiro Endo , Eiji Yamamoto , Yoshinori Hirano , Kenji Yasuoka