Evidence map›Paper›PMID 33514116›Full record

ArticleThe Journal of chemical physics2021

A new one-site coarse-grained model for water: Bottom-up many-body projected water (BUMPer). I. General theory and model.

Jaehyeok Jin, Yining Han, Alexander J Pak, Gregory A Voth

Abstract read
In one paragraph

Article in The Journal of chemical physics, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing 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

12 citing papers in PubMed.

  1. Article
  2. Mapping Still Matters: Coarse-Graining with Machine Learning Potentials.Journal of chemical information and modeling · 2026
    Article
  3. Article
  4. Article
  5. Article
  6. OpenMSCG: A Software Tool for Bottom-Up Coarse-Graining.The journal of physical chemistry. B · 2023
    Article
  7. Article
  8. Bottom-up Coarse-Graining: Principles and Perspectives.Journal of chemical theory and computation · 2022
    Review
  9. Article
  10. Article
  11. "Dividing and Conquering" and "Caching" in Molecular Modeling.International journal of molecular sciences · 2021
    Review
  12. 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

4 authors.

Jaehyeok JinDepartment of Chemistry, Chicago Center for Theoretical Chemistry, Institute for Biophysical Dynamics, and James Franck Institute, The University of Chicago, Chicago, Illinois 60637, USA.ORCID 0000000338593545
Yining HanDepartment of Chemistry, Chicago Center for Theoretical Chemistry, Institute for Biophysical Dynamics, and James Franck Institute, The University of Chicago, Chicago, Illinois 60637, USA.ORCID 0000000265772015
Alexander J PakDepartment of Chemistry, Chicago Center for Theoretical Chemistry, Institute for Biophysical Dynamics, and James Franck Institute, The University of Chicago, Chicago, Illinois 60637, USA.ORCID 0000000328236480
Gregory A VothDepartment of Chemistry, Chicago Center for Theoretical Chemistry, Institute for Biophysical Dynamics, and James Franck Institute, The University of Chicago, Chicago, Illinois 60637, USA.ORCID 0000000232676748

Funding

New Method for Biomembrane SimulationsR01GM063796 · NIGMS · UNIVERSITY OF UTAH · PI VOTH, GREGORY A. · 2001 to 2025
$6.3M
Computational Insights into Assembly, Budding, and Maturation during HIV-1 ReplicationF32AI150477 · NIAID · UNIVERSITY OF CHICAGO · PI PAK, ALEXANDER · 2019 to 2019
$64k
NIAID NIH HHS F32 AI150477NIGMS NIH HHS R01 GM063796
6 · The paper itself

Abstract

Water is undoubtedly one of the most important molecules for a variety of chemical and physical systems, and constructing precise yet effective coarse-grained (CG) water models has been a high priority for computer simulations. To recapitulate important local correlations in the CG water model, explicit higher-order interactions are often included. However, the advantages of coarse-graining may then be offset by the larger computational cost in the model parameterization and simulation execution. To leverage both the computational efficiency of the CG simulation and the inclusion of higher-order interactions, we propose a new statistical mechanical theory that effectively projects many-body interactions onto pairwise basis sets. The many-body projection theory presented in this work shares similar physics from liquid state theory, providing an efficient approach to account for higher-order interactions within the reduced model. We apply this theory to project the widely used Stillinger-Weber three-body interaction onto a pairwise (two-body) interaction for water. Based on the projected interaction with the correct long-range behavior, we denote the new CG water model as the Bottom-Up Many-Body Projected Water (BUMPer) model, where the resultant CG interaction corresponds to a prior model, the iteratively force-matched model. Unlike other pairwise CG models, BUMPer provides high-fidelity recapitulation of pair correlation functions and three-body distributions, as well as N-body correlation functions. BUMPer extensively improves upon the existing bottom-up CG water models by extending the accuracy and applicability of such models while maintaining a reduced computational cost.

Identifiers

PMID33514116
PMCPMC7826168

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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.