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Related papers: Method for Computing Protein Binding Affinity

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We investigate the properties of a sequential Monte Carlo method where the particle weight that appears in the algorithm is estimated by a positive, unbiased estimator. We present broadly-applicable convergence results, including a central…

Methodology · Statistics 2022-08-26 Paul B. Rohrbach , Robert L. Jack

The transition metal-oxygen bond appears prominently throughout chemistry and solid-state physics. Many materials, from biomolecules to ferroelectrics to the components of supernova remnants contain this bond in some form. Many of these…

Strongly Correlated Electrons · Physics 2009-11-13 Lucas K. Wagner

Protein-ligand complex structures have been utilised to design benchmark machine learning methods that perform important tasks related to drug design such as receptor binding site detection, small molecule docking and binding affinity…

Biomolecules · Quantitative Biology 2021-08-26 Rishal Aggarwal , Akash Gupta , U Deva Priyakumar

Simple Monte Carlo is a versatile computational method with a convergence rate of $O(n^{-1/2})$. It can be used to estimate the means of random variables whose distributions are unknown. Bernoulli random variables, $Y$, are widely used to…

Numerical Analysis · Mathematics 2014-11-06 Lan Jiang , Fred J. Hickernell

Monte Carlo methods to evaluate and maximize the likelihood function enable the construction of confidence intervals and hypothesis tests, facilitating scientific investigation using models for which the likelihood function is intractable.…

Methodology · Statistics 2017-02-13 Edward L. Ionides , Carles Breto , Joonha Park , Richard A. Smith , Aaron A. King

Finite detector resolution and limited acceptance require to apply unfolding methods in high energy physics experiments. Information on the detector resolution is usually given by a set of Monte Carlo events. Based on the experience with a…

High Energy Physics - Experiment · Physics 2007-05-23 Volker Blobel

Understanding how protein mutations affect protein-nucleic acid binding is critical for unraveling disease mechanisms and advancing therapies. Current experimental approaches are laborious, and computational methods remain limited in…

Quantitative Methods · Quantitative Biology 2025-05-30 Xiang Liu , Junjie Wee , Guo-Wei Wei

We investigate aggregation mechanism of two proteins in a thermodynamically unambiguous manner by considering the finite size effect of free energy landscape of HP lattice protein model. Multi-Self-Overlap-Ensemble Monte Carlo method is…

Biomolecules · Quantitative Biology 2009-11-13 Kazuki Nakanishi , Macoto Kikuchi

Side chain flexibility is an important factor in ligand binding. In order to determine the extent to which side chain flexibility is involved in ligand binding, a knowledge-based approach was taken. A database composed of examples of…

Biomolecules · Quantitative Biology 2013-01-22 Rafael Najmanovich

Macromolecular complexation leading to coupling of two or more cellular membranes is a crucial step in a number of biological functions of the cell. While other mechanisms may also play a role, adhesion always involves the fluctuations of…

Soft Condensed Matter · Physics 2015-09-02 Timo Bihr , Udo Seifert , Ana-Suncana Smith

Quantum Monte Carlo methods have recently been employed to study properties of nuclei and infinite matter using local chiral effective field theory interactions. In this work, we present a detailed description of the auxiliary field…

Nuclear Theory · Physics 2018-05-02 D. Lonardoni , S. Gandolfi , J. E. Lynn , C. Petrie , J. Carlson , K. E. Schmidt , A. Schwenk

Computing systems interacting with real-world processes must safely and reliably process uncertain data. The Monte Carlo method is a popular approach for computing with such uncertain values. This article introduces a framework for…

Accurate prediction of protein-ligand binding affinities is crucial in drug discovery, particularly during hit-to-lead and lead optimization phases, however, limitations in ligand force fields continue to impact prediction accuracy. In this…

Chemical Physics · Physics 2025-04-04 Francesc Sabanés Zariquiey , Stephen E. Farr , Stefan Doerr , Gianni De Fabritiis

Free energy calculations are rapidly becoming indispensable in structure-enabled drug discovery programs. As new methods, force fields, and implementations are developed, assessing their expected accuracy on real-world systems…

We utilize a multiscale modeling framework to study the effect of shape, size and ligand composition on the efficacy of binding of a ligand-coated-particle to a substrate functionalized with the target receptors. First, we show how…

Soft Condensed Matter · Physics 2018-03-08 Matt McKenzie , Sung Min Ha , Aravind Rammohan , Ravi Radhakrishnan , N. Ramakrishnan

A novel statistical model for the cooperative binding of monomeric ligands to a linear lattice is developed to study the interaction of ionic surfactant molecules with flexible polyion chain in dilute solution. Electrostatic binding of a…

Soft Condensed Matter · Physics 2015-01-13 T. Nishio , T. Shimizu , Sh. Yoshida , A. Minakata

We present a temperature-independent Monte Carlo method for the determination of the density of states of lattice proteins that combines the fast ground-state search strategy of the nPERM chain growth and multicanonical reweighting for…

Statistical Mechanics · Physics 2009-11-10 Michael Bachmann , Wolfhard Janke

Although ligand-binding sites in many proteins contain a high number density of charged side chains that can polarize small organic molecules and influence binding, the magnitude of this effect has not been studied in many systems. Here, we…

Chemical Physics · Physics 2020-06-30 Soohaeng Yoo Willow , Bing Xie , Jason Lawrence , Robert S. Eisenberg , David D. L. Minh

Protein folding is the intricate process by which a linear sequence of amino acids self-assembles into a unique three-dimensional structure. Protein folding kinetics is the study of pathways and time-dependent mechanisms a protein undergoes…

Machine Learning · Computer Science 2023-09-19 Vijay Arvind. R , Haribharathi Sivakumar , Brindha. R

We propose an algorithmic strategy for improving the efficiency of Monte Carlo searches for the low-energy states of proteins. Our strategy is motivated by a model of how proteins alter their shapes. In our model when proteins fold under…

Soft Condensed Matter · Physics 2009-11-07 Michael Cahill , Sean Cahill , Kevin Cahill
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