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相关论文: Method for Computing Protein Binding Affinity

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The molecular distributions obtained from canonical Monte Carlo simulations can be used to find an approximate interaction energy. This serves as the basis of a method for estimating the binding free energy for a ligand to a protein which…

化学物理 · 物理学 2007-05-23 Charles F. F. Karney , Jason E. Ferrara , Clay D. Spence

The major histocompatibility complex (MHC) molecules, which bind peptides for presentation on the cell surface, play an important role in cell-mediated immunity. In light of developing databases and technologies over the years, significant…

生物大分子 · 定量生物学 2023-01-26 Ayşenaz Ezgi Ergin , Deniz Turgay Altılar

A rigourous Monte Carlo method for protein folding simulation on lattice model is introduced. We show that a parameter which can be seen as the rigidity of the conformations has to be introduced in order to satisfy the detailed balance…

软凝聚态物质 · 物理学 2007-05-23 Olivier Collet

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

The principles behind the computation of protein-ligand binding free energies by Monte Carlo integration are described in detail. The simulation provides gas-phase binding free energies that can be converted to aqueous energies by solvation…

化学物理 · 物理学 2017-01-25 Matthew Clark , Jeffrey S. Wiseman

Protein-ligand binding is the process by which a small molecule (drug or inhibitor) attaches to a target protein. Binding affinity, which characterizes the strength of biomolecular interactions, is essential for tackling diverse challenges…

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

There is significant interest in rapid protein simulations because of the time-scale limitations of all-atom methods. Exploiting the low cost and great availability of computer memory, we report a Monte Carlo technique for incorporating…

生物物理 · 物理学 2008-12-04 Artem B. Mamonov , Divesh Bhatt , Derek J. Cashman , Daniel M. Zuckerman

Extensive Monte Carlo folding simulations for four proteins of various structural classes are carried out, using a single atomistic potential. In all cases, collapse occurs at a very early stage, and proteins fold into their native-like…

统计力学 · 物理学 2009-11-10 Seung-Yeon Kim , Julian Lee , Jooyoung Lee

Accurately determining a change in protein binding affinity upon mutations is important for the discovery and design of novel therapeutics and to assist mutagenesis studies. Determination of change in binding affinity upon mutations…

生物大分子 · 定量生物学 2021-09-01 Wajid Arshad Abbasi , Syed Ali Abbas , Saiqa Andleeb

This letter gives results on improving protein-ligand binding affinity predictions based on molecular dynamics simulations using machine learning potentials with a hybrid neural network potential and molecular mechanics methodology…

A Monte Carlo method for dynamics simulation of all-atom protein models is introduced, to reach long times not accessible to conventional molecular dynamics. The considered degrees of freedom are the dihedrals at C$_\alpha$-atoms. Two Monte…

chem-ph · 物理学 2009-10-28 Daniel Hoffmann , Ernst-Walter Knapp

Determination of binding affinity of proteins in the formation of protein complexes requires sophisticated, expensive and time-consuming experimentation which can be replaced with computational methods. Most computational prediction…

定量方法 · 定量生物学 2020-12-14 Wajid Arshad Abbasi , Fahad Ul Hassan , Adiba Yaseen , Fayyaz Ul Amir Afsar Minhas

Using Wang-Landau sampling with suitable Monte Carlo trial moves (pull moves and bond-rebridging moves combined) we have determined the density of states and thermodynamic properties for a short sequence of the HP protein model. For free…

软凝聚态物质 · 物理学 2015-03-18 Ying Wai Li , Thomas Wüst , David P. Landau

We compute absolute binding affinities for two ligands bound to the FKBP protein using non-equilibrium unbinding simulations. The methodology is straight-forward, requiring little or no modification to many modern molecular simulation…

生物物理 · 物理学 2008-11-24 F. Marty Ytreberg

Proteins must bind to specific other proteins in vivo in order to function. The proteins must bind only to one or a few other proteins of the of order a thousand proteins typically present in vivo. Using a simple model of a protein,…

生物大分子 · 定量生物学 2007-05-23 Richard P. Sear

Metadynamics is a powerful computational tool to obtain the free energy landscape of complex systems. The Monte Carlo algorithm has proven useful to calculate thermodynamic quantities associated with simplified models of proteins, and thus…

统计力学 · 物理学 2007-10-04 F. Marini , C. Camilloni , D. Provasi , R. A. Broglia , G. Tiana

Quantum Monte Carlo methods are used to calculate various ground state properties of charged bosons in two dimensions, throughout the whole density range where the fluid phase is stable. Wigner crystallization is predicted at $r_s\simeq…

凝聚态物理 · 物理学 2018-05-01 S. De Palo , S. Conti , S. Moroni

We offer simple solutions to three kinematic problems that occur in the folding of proteins. We show how to construct suitably local elementary Monte Carlo moves, how to close a loop, and how to fold a loop without breaking the bond that…

生物物理 · 物理学 2016-09-08 Sean Cahill , Michael Cahill , Kevin Cahill

We present a kinetic Monte Carlo method for simulating chemical transformations specified by reaction rules, which can be viewed as generators of chemical reactions, or equivalently, definitions of reaction classes. A rule identifies the…

定量方法 · 定量生物学 2010-07-09 Jin Yang , Michael I. Monine , James R. Faeder , William S. Hlavacek
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