g_mmpbsa—A GROMACS Tool for High-Throughput MM-PBSA Calculations
Article Properties
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LanguageEnglish
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DOI (url)
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Publication Date2014/06/19
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Indian UGC (journal)
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Refrences102
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Citations3,112
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Rashmi Kumari School of Computational and Integrative Sciences, Jawaharlal Nehru University, New Delhi 110067, India
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Rajendra Kumar School of Computational and Integrative Sciences, Jawaharlal Nehru University, New Delhi 110067, India
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Andrew Lynn School of Computational and Integrative Sciences, Jawaharlal Nehru University, New Delhi 110067, India
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Cite
Kumari, Rashmi, et al. “g_mmpbsa—A GROMACS Tool for High-Throughput MM-PBSA Calculations”. Journal of Chemical Information and Modeling, vol. 54, no. 7, 2014, pp. 1951-62, https://doi.org/10.1021/ci500020m.
Kumari, R., Kumar, R., & Lynn, A. (2014). g_mmpbsa—A GROMACS Tool for High-Throughput MM-PBSA Calculations. Journal of Chemical Information and Modeling, 54(7), 1951-1962. https://doi.org/10.1021/ci500020m
Kumari, Rashmi, Rajendra Kumar, and Andrew Lynn. “g_mmpbsa—A GROMACS Tool for High-Throughput MM-PBSA Calculations”. Journal of Chemical Information and Modeling 54, no. 7 (2014): 1951-62. https://doi.org/10.1021/ci500020m.
1.
Kumari R, Kumar R, Lynn A. g_mmpbsa—A GROMACS Tool for High-Throughput MM-PBSA Calculations. Journal of Chemical Information and Modeling. 2014;54(7):1951-62.
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Refrences
| Title | Journal | Journal Categories | Citations | Publication Date |
|---|---|---|---|---|
GROMACS 4.5: a high-throughput and highly parallel open source molecular simulation toolkit | Bioinformatics |
| 5,392 | 2013 |
| Influence of Grid Spacing in Poisson–Boltzmann Equation Binding Energy Estimation | Journal of Chemical Theory and Computation |
| 23 | 2013 |
| Oligomerization of Peptides LVEALYL and RGFFYT and Their Binding Affinity to Insulin | PLOS ONE |
| 21 | 2013 |
| Origin of Decrease in Potency of Darunavir and Two Related Antiviral Inhibitors against HIV-2 Compared to HIV-1 Protease | The Journal of Physical Chemistry B |
| 48 | 2012 |
| Molecular Dynamics Investigation on a Series of HIV Protease Inhibitors: Assessing the Performance of MM-PBSA and MM-GBSA Approaches | Journal of Chemical Information and Modeling |
| 90 | 2012 |
Refrences Analysis
The category
Science: Chemistry 52
is the most frequently represented among the references in this article. It primarily includes studies from Journal of Computational Chemistry and The Journal of Chemical Physics. The chart below illustrates the number of referenced publications per year.
Refrences used by this article by year
Citations
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| 2024 | |
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| 2024 | |
New enantioenriched β‐indolyl ketones as aromatase inhibitors: Unraveling heme–ligand interactions by MD simulation and MMPBSA analysis | Archiv der Pharmazie |
| 2024 | |
Synthesis, Antimicrobial Activities, and Molecular Modeling Studies of Agents for the Sortase A Enzyme | Chemistry & Biodiversity |
| 2024 | |
Spiro‐Acridine Compound as a Pteridine Reductase 1 Inhibitor: in silico Target Fishing and in vitro Studies | ChemMedChem |
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Citations Analysis
The category
Science: Biology (General) 1,687
is the most commonly referenced area in studies that cite this article. The first research to cite this article was titled ABS–Scan: In silico alanine scanning mutagenesis for binding site residues in protein–ligand complex and was published in 2014. The most recent citation comes from a 2024 study titled Decoding dynamic interactions between EGFR‐TKD and DAC through computational and experimental approaches: A novel breakthrough in lung melanoma treatment. This article reached its peak citation in 2023, with 645 citations. It has been cited in 580 different journals, 21% of which are open access. Among related journals, the Journal of Biomolecular Structure and Dynamics cited this research the most, with 633 citations. The chart below illustrates the annual citation trends for this article.