Evidence map›Paper›PMID 27196035›Full record

ArticleJournal of chemical information and modeling2016

TopoGromacs: Automated Topology Conversion from CHARMM to GROMACS within VMD.

Josh V Vermaas, David J Hardy, John E Stone, Emad Tajkhorshid, Axel Kohlmeyer

Abstract read
In one paragraph

Article in Journal of chemical information and modeling, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 34 papers.

0numbers the graph read from it
0cells of the map it votes in
34citing 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

34 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Monosaccharide-Derived Enantioselectivity in SWCNT Chemoresistive VOC Sensing.Chemistry (Weinheim an der Bergstrasse, Germany) · 2025
    Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. PACKMOL-GUI: An All-In-One VMD Interface for Efficient Molecular Packing.Journal of chemical information and modeling · 2025
    Article
  10. Atomic view of photosynthetic metabolite permeability pathways and confinement in synthetic carboxysome shells.Proceedings of the National Academy of Sciences of the United States of America · 2024
    Article
  11. Article
  12. Article
  13. Article
  14. Article
  15. Article
  16. Article
  17. Biomolecules · 2023
    Article
  18. Article
  19. Article
  20. Review
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

5 authors.

Josh V VermaasCenter for Biophysics and Quantitative Biology, University of Illinois at Urbana-Champaign , Urbana, Illinois 61801, United States.
David J HardyBeckman Insitute, University of Illinois at Urbana-Champaign , Urbana, Illinois 61801, United States.
John E StoneBeckman Insitute, University of Illinois at Urbana-Champaign , Urbana, Illinois 61801, United States.
Emad TajkhorshidCenter for Biophysics and Quantitative Biology, University of Illinois at Urbana-Champaign , Urbana, Illinois 61801, United States.
Axel KohlmeyerInsitute for Computational Molecular Science, Temple University , Philadelphia, Pennsylvania 19122, United States.

Funding

Synthetic Antigen Binder CoreU54GM087519 · NIGMS · UNIVERSITY OF CHICAGO · PI NAKAMOTO, ROBERT K. · 2010 to 2017
$31.9M
WHOLE CELL SIMULATIONP41GM104601 · NIGMS · UNIVERSITY OF ILLINOIS AT URBANA-CHAMPAIGN · PI TAJKHORSHID, EMAD · 2012 to 2021
$19.0M
NIGMS NIH HHS P41 GM104601NIGMS NIH HHS U54 GM087519
6 · The paper itself

Abstract

Molecular dynamics (MD) simulation engines use a variety of different approaches for modeling molecular systems with force fields that govern their dynamics and describe their topology. These different approaches introduce incompatibilities between engines, and previously published software bridges the gaps between many popular MD packages, such as between CHARMM and AMBER or GROMACS and LAMMPS. While there are many structure building tools available that generate topologies and structures in CHARMM format, only recently have mechanisms been developed to convert their results into GROMACS input. We present an approach to convert CHARMM-formatted topology and parameters into a format suitable for simulation with GROMACS by expanding the functionality of TopoTools, a plugin integrated within the widely used molecular visualization and analysis software VMD. The conversion process was diligently tested on a comprehensive set of biological molecules in vacuo. The resulting comparison between energy terms shows that the translation performed was lossless as the energies were unchanged for identical starting configurations. By applying the conversion process to conventional benchmark systems that mimic typical modestly sized MD systems, we explore the effect of the implementation choices made in CHARMM, NAMD, and GROMACS. The newly available automatic conversion capability breaks down barriers between simulation tools and user communities and allows users to easily compare simulation programs and leverage their unique features without the tedium of constructing a topology twice.

Indexed as

Molecular Dynamics SimulationAmino AcidsAutomationCarbohydratesDNAInformation Storage and RetrievalLipidsOligopeptidesRNASoftwareAmino AcidsCarbohydratesDNALipidsOligopeptidesRNA

Identifiers

PMID27196035
PMCPMC5543333

What OpenQuestion holds

Textmetadata
LicenceTDM
Read underepoch 390

Registered trials

None linked

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.