Part 1: Molecular Visualisation
The change in binding mode of oseltamivir in the R292K mutant of H7N9 neuraminidase that you have just quantified has been shown to reduce the binding affinity of the drug. Calculating binding affinities required more complex simulations, and we only committed to running these simulations because of the conformational changes that we observed in the molecular dynamics trajectories using VMD. Figures 2-6 from this paper were all produced using VMD, and the distances plotted in figures 4 and 5 were calculated based on initial observations and graphs produced using VMD. In addition, most of the figures and distances, angles and RMSDs in the supplementary information for that paper were produced using VMD, including the torsion angles shown in figure S6.
Hopefully, you have now seen that VMD can be a powerful tool to help you visualise biomolecular systems, analyse the output of molecular dynamics simulations and to produce figures ready for publication. If you want to learn more, there is a more detailed VMD tutorial available here.
It should also be noted that there are many different molecular viewer packages that are also freely available and that have similar capabilities to VMD. Two of the most popular are pymol and Chimera. Each package has its own strengths and weaknesses, and, as it says on this comparison page, everyone, at one point in their career, will tend to choose one of these viewers and will specialise in it to the point that their choice of viewer will become like a form of self-expression. While most viewers can do most things, VMD is particularly good for viewing very large biomolecular systems and the output of molecular dynamics trajectories, Chimera is tightly integrated with many molecular analysis and modelling tools (e.g including those for homology modelling and building missing loops in proteins), and pymol is built on top of python and is highly scriptable.