JSmol and the Next‐Generation Web‐Based Representation of 3D Molecular Structure as Applied to Proteopedia

Abstract

Although Java does not run on some handheld devices, e.g., iPads and iPhones, JavaScript does. The development of JSmol, a JavaScript‐only version of Jmol, is described, and its use in Proteopedia is demonstrated. A key aspect of JSmol is that it includes the full implementation of the entire set of Jmol functionalities, including file reading and writing, scripting, and rendering. The relative performances of Java‐based Jmol and JavaScript‐only JSmol are discussed. We can now confirm that the guiding principles of Java programming can be completely and relatively straightforwardly transformed directly into JavaScript, requiring no Java applet, and producing identical graphical results. JSmol is thus the first full‐featured molecular viewer, and the first ever viewer for proteins, which can be utilized with an internet browser on handheld devices lacking Java. Since the MediaWiki features of Proteopedia have been modified to optionally use JSmol, the wealth of crowd‐sourced content in Proteopedia is now directly available on such devices, without the need to download any additional applet.

ePlant: Visualizing and Exploring Multiple Levels of Data for Hypothesis Generation in Plant Biology

“…The PDB file is displayed with JSmol (Hanson et al, 2013). The protein sequence is drawn on the bottom of the screen along with pin markers that indicate the position and frequency of SNP locations.…”

Functional genomics in Campylobacter coli identified a novel streptomycin resistance gene located in a hypervariable genomic region

“…Model quality assessment, alignment confidence, catalytic site detection and conservation analysis using the aminoglycoside 6-nucleotidyltransferase from B. subtilis as reference structure were performed using Phyre2 investigator (Kelley et al, 2015). Models were visualized using JSmol (Hanson et al, 2013).…”

Recent developments in theCCP-EMsoftware suite

“…The number of SSEs generated by the clustering is tuneable via two spatial proximity parameters: the residue-contact distance, which represents the contact between any two residues (side-chain centroid-centroid distance) enforcing the minimum distance between the clustered SSEs, and the cluster cutoff, which clusters any two SSEs based on the percentage of residues in contact with them. The contact distance is set as an a priori input and the cluster cutoff can be tuned visually, postprocessing, using a JSmol (Hanson et al, 2013) plugin widget.…”