Evidence map›Paper›PMID 24320318›Full record

ArticleThe Journal of chemical physics2013

Multiscale multiphysics and multidomain models--flexibility and rigidity.

Kelin Xia, Kristopher Opron, Guo-Wei Wei

Abstract read
In one paragraph

Article in The Journal of chemical physics, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 41 papers.

0numbers the graph read from it
0cells of the map it votes in
41citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

41 citing papers in PubMed.

  1. Correlated clustering and projection for dimensionality reduction.Machine learning: science and technology · 2026
    Article
  2. Article
  3. Persistent Sheaf Laplacian Analysis of Protein Flexibility.The journal of physical chemistry. B · 2025
    Article
  4. Article
  5. Article
  6. Mayer-Homology Learning Prediction of Protein-Ligand Binding Affinities.Journal of computational biophysics and chemistry · 2025
    Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. Systematic review of digital twin technology and applications.Visual computing for industry, biomedicine, and art · 2023
    Review
  12. Review
  13. Review
  14. Geometric algebra generation of molecular surfaces.Journal of the Royal Society, Interface · 2022
    Article
  15. Article
  16. Review of COVID-19 Antibody Therapies.Annual review of biophysics · 2021
    Article
  17. Decoding Asymptomatic COVID-19 Infection and Transmission.The journal of physical chemistry letters · 2020
    Review
  18. Persistent spectral graph.International journal for numerical methods in biomedical engineering · 2020
    Article
  19. Article
  20. The de Rham-Hodge Analysis and Modeling of Biomolecules.Bulletin of mathematical biology · 2020
    Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Kelin XiaDepartment of Mathematics, Michigan State University, East Lansing, Michigan 48824, USA.
Kristopher Opron
Guo-Wei Wei

Funding

Collaborative research: Geometric flow approach to implicit solvation modelingR01GM090208 · NIGMS · MICHIGAN STATE UNIVERSITY · PI WEI, GUOWEI · 2009 to 2014
$1.3M
NIGMS NIH HHS R01 GM090208NIGMS NIH HHS R01GM-090208
6 · The paper itself

Abstract

The emerging complexity of large macromolecules has led to challenges in their full scale theoretical description and computer simulation. Multiscale multiphysics and multidomain models have been introduced to reduce the number of degrees of freedom while maintaining modeling accuracy and achieving computational efficiency. A total energy functional is constructed to put energies for polar and nonpolar solvation, chemical potential, fluid flow, molecular mechanics, and elastic dynamics on an equal footing. The variational principle is utilized to derive coupled governing equations for the above mentioned multiphysical descriptions. Among these governing equations is the Poisson-Boltzmann equation which describes continuum electrostatics with atomic charges. The present work introduces the theory of continuum elasticity with atomic rigidity (CEWAR). The essence of CEWAR is to formulate the shear modulus as a continuous function of atomic rigidity. As a result, the dynamics complexity of a macromolecular system is separated from its static complexity so that the more time-consuming dynamics is handled with continuum elasticity theory, while the less time-consuming static analysis is pursued with atomic approaches. We propose a simple method, flexibility-rigidity index (FRI), to analyze macromolecular flexibility and rigidity in atomic detail. The construction of FRI relies on the fundamental assumption that protein functions, such as flexibility, rigidity, and energy, are entirely determined by the structure of the protein and its environment, although the structure is in turn determined by all the interactions. As such, the FRI measures the topological connectivity of protein atoms or residues and characterizes the geometric compactness of the protein structure. As a consequence, the FRI does not resort to the interaction Hamiltonian and bypasses matrix diagonalization, which underpins most other flexibility analysis methods. FRI's computational complexity is of O(N(2)) at most, where N is the number of atoms or residues, in contrast to O(N(3)) for Hamiltonian based methods. We demonstrate that the proposed FRI gives rise to accurate prediction of protein B-Factor for a set of 263 proteins. We show that a parameter free FRI is able to achieve about 95% accuracy of the parameter optimized FRI. An interpolation algorithm is developed to construct continuous atomic flexibility functions for visualization and use with CEWAR.

Indexed as

Molecular Dynamics SimulationModels, MolecularProtein ConformationProteinsProteins

Identifiers

PMID24320318
PMCPMC3855066

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.