ReviewJournal of computational chemistry2009
CHARMM: the biomolecular simulation program.
Review in Journal of computational chemistry, 2009. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3,940 papers.
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.
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.
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Who cites it
3,940 citing papers in PubMed.
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- Network analysis of correlated conformational dynamics across the evolution of influenza A virus NS1.bioRxiv : the preprint server for biology · 2026Article
- Design, synthesis, biological evaluation and computational studies of novel phthalimides as dual COX-2/5-LOX inhibitors.Molecular diversity · 2026Article
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- Mechanism of GPR84 allosteric modulation at a helix 8-proximate site.Science advances · 2026Article
- Predicting Oncogenic Mutants of Epidermal Growth Factor Receptor in Lung Cancer by Molecular Dynamics Simulation with Machine Learning.ACS omega · 2026Article
- Structure-based drug repurposing and in vitro evaluation of VAV2-associated candidates for suppression of macrophage foam-cell formation in atherosclerosis.Molecular diversity · 2026Article
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- Training a force field for proteins and small molecules from scratch.Chemical science · 2026Article
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- Which Metrics Best Capture Protein Structural Changes in Molecular Dynamics Simulations? Evaluating Score Combinations and Force-Field Effects.Journal of chemical information and modeling · 2026Article
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- Insights into the structural dynamics and free energy landscapes of Danio rerio RAB1A and RAB1B: a comparative molecular dynamics simulation approach.Journal of molecular modeling · 2026Article
- Predicting Supramolecular Self-Assembly of Peptide Structures with AlphaFold3.bioRxiv : the preprint server for biology · 2026Article
3,880 more citing papers are in PubMed but not listed here.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
35 authors.
Funding
Abstract
CHARMM (Chemistry at HARvard Molecular Mechanics) is a highly versatile and widely used molecular simulation program. It has been developed over the last three decades with a primary focus on molecules of biological interest, including proteins, peptides, lipids, nucleic acids, carbohydrates, and small molecule ligands, as they occur in solution, crystals, and membrane environments. For the study of such systems, the program provides a large suite of computational tools that include numerous conformational and path sampling methods, free energy estimators, molecular minimization, dynamics, and analysis techniques, and model-building capabilities. The CHARMM program is applicable to problems involving a much broader class of many-particle systems. Calculations with CHARMM can be performed using a number of different energy functions and models, from mixed quantum mechanical-molecular mechanical force fields, to all-atom classical potential energy functions with explicit solvent and various boundary conditions, to implicit solvent and membrane models. The program has been ported to numerous platforms in both serial and parallel architectures. This article provides an overview of the program as it exists today with an emphasis on developments since the publication of the original CHARMM article in 1983.
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Registered trials
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.