PubMed HealthSearch

PubMed · 8744570

VMD: visual molecular dynamics.

Abstract

VMD is a molecular graphics program designed for the display and analysis of molecular assemblies, in particular biopolymers such as proteins and nucleic acids. VMD can simultaneously display any number of structures using a wide variety of rendering styles and coloring methods. Molecules are displayed as one or more "representations," in which each representation embodies a particular rendering method and coloring scheme for a selected subset of atoms. The atoms displayed in each representation are chosen using an extensive atom selection syntax, which includes Boolean operators and regular expressions. VMD provides a complete graphical user interface for program control, as well as a text interface using the Tcl embeddable parser to allow for complex scripts with variable substitution, control loops, and function calls. Full session logging is supported, which produces a VMD command script for later playback. High-resolution raster images of displayed molecules may be produced by generating input scripts for use by a number of photorealistic image-rendering applications. VMD has also been expressly designed with the ability to animate molecular dynamics (MD) simulation trajectories, imported either from files or from a direct connection to a running MD simulation. VMD is the visualization component of MDScope, a set of tools for interactive problem solving in structural biology, which also includes the parallel MD program NAMD, and the MDCOMM software used to connect the visualization and simulation programs. VMD is written in C++, using an object-oriented design; the program, including source code and extensive documentation, is freely available via anonymous ftp and through the World Wide Web.

Explore related subjects

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

W Humphrey, A Dalke, K Schulten. 1996. VMD: visual molecular dynamics.. https://doi.org/10.1016/0263-7855(96)00018-5

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related citations

XNBC: a simulation tool. Application to the study of neural coding using hybrid networks.

XNBC is a software package for simulating biological neural networks. Two neuron models are available, a leaky integrator model and an ion-conductance model. Inputs to the simulated neurons can be provided by experimental data stored in files, allowing the creation of 'hybrid' networks. Graphic tools are used to describe the modeled neurons as well as the network. Neuron and network parameters can be modified during the simulation, to mimic electrical stimulations and drugs action. The temporal evolution of the network and of selected neurons can be visualized. A point process, frequency or dynamic analysis of the simulator output can be performed. The successive stages of the creation of a hybrid network are explained.

Computer Graphics

Speaking graphically: an introduction to some newer graphing techniques.

The vast majority of graphs appearing in the psychiatric literature consist of the traditional line graphs, histograms, and bar charts. Over the past decade, new graphing techniques have appeared which make the data easier to read and which present much more information than simply group means and confidence intervals. These methods include horizontal bar charts, dot charts, stem-and-leaf plots, box plots, and notched box plots. This paper describes these new techniques, as well as older ones, such as smoothing, and warns against using some of the options found in graphics programs: 3-dimensional (3-D) graphs, stacked graphs, and pie charts.

Computer Graphics

Visual localization within single geometric planes of a space habitat.

BACKGROUND: The present study investigated how human subjects capture and restore visual information within a line representation drawing the three-dimensional configuration of a space module. METHODS: Nine subjects were asked to perform a visual localization task within this geometric model. The task consisted of localizing a light point appearing during 3 s in 40 different spatial positions and for 8 tilt angles of the model in the following random order: 0 degree, 45 degrees, 180 degrees, 225 degrees, 90 degrees, 315 degrees, 135 degrees, and 270 degrees. RESULTS: Results showed symmetric variations of the point-localizing errors about 180 degrees of tilt angle (vertical orientation) and a decrease of the errors when the points occurred in the distal, then in the median and in the proximal planes (virtual depth). The performance also varied according to the virtual ceiling, floor, right, left and back planes. The results have been discussed using a three-dimensional space representation based on a conservative mode of spatial information up to 90 degrees of tilt (horizontal orientation), and on a transformation mode beyond 90 degrees of tilt. CONCLUSION: We conclude that the visual localization in single geometric planes is orientation-dependent.

Computer Graphics