ArticleMethods in molecular biology (Clifton, N.J.)2026
Molecular Dynamics Simulations with NAMD and Trajectory Analysis.
Article in Methods in molecular biology (Clifton, N.J.), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Molecular simulations offer a window into proteins' movements, which other methods fail to measure. The fractional, slight modifications of structure seen, for example, in molecular breathing, or movements which are so fast as to evade wet lab detection, are made accessible through the use of high-powered computing to drive simulations. While simulations are theoretical, they rely largely on real-world data, utilizing solved crystal, cryo-EM, or SAXS structures as starting points. These can be used either for the simulation directly or for homology modeling to aid in the solving of novel structures and proteins. Simulations are run in parallel with increased power and altered conditions, allowing even unusual or rare event structures to be seen and studied, which may be missed by wet lab techniques. The data generated can then be corroborated in the wet laboratory through biophysical techniques, measuring the larger movements. The ability to discern discrete structures and complex movements becomes most useful for structurally promiscuous, multi-domain proteins. This description suits well the ADAMTS family of proteins, which have been shown to have multiple structures, cryptic epitopes, and high levels of glycosylation. Therefore, we present a method by which one can explore the structures generated by ADAMTS13 using MD.
Indexed as
Identifiers
41917367What OpenQuestion holds
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.