Reformulation of Ensemble Averages via Coordinate Mapping.

J Chem Theory Comput

Department of Chemical and Biological Engineering, University at Buffalo, The State University of New York, Buffalo, New York 14260-4200, United States.

Published: April 2016

A general framework is established for reformulation of the ensemble averages commonly encountered in statistical mechanics. This "mapped-averaging" scheme allows approximate theoretical results that have been derived from statistical mechanics to be reintroduced into the underlying formalism, yielding new ensemble averages that represent exactly the error in the theory. The result represents a distinct alternative to perturbation theory for methodically employing tractable systems as a starting point for describing complex systems. Molecular simulation is shown to provide one appealing route to exploit this advance. Calculation of the reformulated averages by molecular simulation can proceed without contamination by noise produced by behavior that has already been captured by the approximate theory. Consequently, accurate and precise values of properties can be obtained while using less computational effort, in favorable cases, many orders of magnitude less. The treatment is demonstrated using three examples: (1) calculation of the heat capacity of an embedded-atom model of iron, (2) calculation of the dielectric constant of the Stockmayer model of dipolar molecules, and (3) calculation of the pressure of a Lennard-Jones fluid. It is observed that improvement in computational efficiency is related to the appropriateness of the underlying theory for the condition being simulated; the accuracy of the result is however not impacted by this. The framework opens many avenues for further development, both as a means to improve simulation methodology and as a new basis to develop theories for thermophysical properties.

Download full-text PDF

Source
http://dx.doi.org/10.1021/acs.jctc.6b00018DOI Listing

Publication Analysis

Top Keywords

ensemble averages
12
reformulation ensemble
8
statistical mechanics
8
molecular simulation
8
averages
4
averages coordinate
4
coordinate mapping
4
mapping general
4
general framework
4
framework established
4

Similar Publications

Robust RNA secondary structure prediction with a mixture of deep learning and physics-based experts.

Biol Methods Protoc

January 2025

Department of Physics, George Washington University, Washington, DC 20052, United States.

A mixture-of-experts (MoE) approach has been developed to mitigate the poor out-of-distribution (OOD) generalization of deep learning (DL) models for single-sequence-based prediction of RNA secondary structure. The main idea behind this approach is to use DL models for in-distribution (ID) test sequences to leverage their superior ID performances, while relying on physics-based models for OOD sequences to ensure robust predictions. One key ingredient of the pipeline, named MoEFold2D, is automated ID/OOD detection via consensus analysis of an ensemble of DL model predictions without requiring access to training data during inference.

View Article and Find Full Text PDF

Charge detection mass spectrometry (CDMS) allows direct mass measurement of heterogeneous samples by simultaneously determining the charge state and the mass-to-charge ratio (/) of individual ions, unlike conventional MS methods that use large ensembles of ions. CDMS typically requires long acquisition times and the collection of thousands of spectra, each containing tens to hundreds of ions, to generate sufficient ion statistics, making it difficult to interface with the time scales of online separation techniques such as ion mobility. Here, we demonstrate the application of Fourier transform multiplexing and drift tube ion mobility joined with Orbitrap-based CDMS for the analysis of multimeric protein complexes.

View Article and Find Full Text PDF

Single-molecule fluorescence resonance energy transfer (smFRET) is a powerful technique for studying the structural dynamics of protein molecules or detecting interactions between protein molecules in real time. Due to the high sensitivity in spatial and temporal resolution, smFRET can decipher sub-populations within heterogeneous native state conformations, which are generally lost in traditional measurements due to ensemble averaging. In addition, the single-molecule reconstitution allows protein molecules to be observed for an extensive period of time and can recapitulate the geometry of the cellular environment to retain biological function.

View Article and Find Full Text PDF

Genetically encoded tension sensors (GETSs) allow for quantifying forces experienced by intracellular proteins involved in mechanotransduction. The vast majority of GETSs are comprised of a FRET pair flanking an elastic "spring-like" domain that gradually extends in response to force. Because of ensemble averaging, the FRET signal generated by such analog sensors conceals forces that deviate from the average, and hence it is unknown if a subset of proteins experience greater magnitudes of force.

View Article and Find Full Text PDF

Middle-Aged and Elderly people today face a variety of health problems as a result of their modern lifestyle, which includes increased work stress, less physical activity, and altered food habits. Because of Complications arising, diabetes has become one of the most frequent, severe, and fatal illnesses around the world. Therefore, inaccurate measurements of blood glucose levels can seriously damage vital organs.

View Article and Find Full Text PDF

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!