teaching and education
Jmol – a paradigm shift in crystallographic visualization
aDepartment of Chemistry, St Olaf College, 1520 St Olaf Avenue, Northfield, Minnesota 55057, USA
*Correspondence e-mail: hansonr@stolaf.edu
Recent advances in molecular and crystallographic visualization methods are allowing instructors unprecedented opportunities to enhance student learning using virtual models within a familiar web-browser context. In step with these advances, the latest versions of the Jmol molecular visualization applet offer capabilities that hold potential for revolutionizing the way students learn about symmetry, uncertainty and the overall enterprise of molecular structure determination.
Keywords: crystallographic education; symmetry; visualization software; Jmol.
1. Introduction – crystallographic visualization
It goes without saying that visualization is important in the area of crystallography. The introduction of ORTEP (Johnson, 1965) over 40 years ago made possible for the first time a ready two-dimensional projection of the three-dimensional atomic world of crystals and ushered in a revolution in molecular visualization. Since then, personal computing power has increased immensely, and a number of computer programs have been introduced that allow real-time interactive construction of crystals (CrystalMaker, 2009; Shape, 2009) and exploration of molecular structure and bonding in the context of databases [Mercury (Macrae et al., 2006) and Diamond (2010)]. While developed primarily for research purposes, these programs have found utility in the area of education as well, as noted in recent symposia at national American Chemical Society meetings (Kantardjieff, 2005; Battle et al., 2009). In addition, specialized software and web-based tutorials specifically targeting fundamental concepts of crystallography and molecular symmetry are now available (Cass & Rzepa, 2005; Harwood & Korkmaz, 2005; Johnston, 2005, 2008; Charistos et al., 2005; Kastner et al., 2000).
This paper focuses on a new paradigm of computer program that aims to revolutionize the area of visualization in chemical education again, particularly in the area of crystallography. These programs – web-based, open-source and platform-independent – combine features of rapid development, expert communities and widely accessible databases with the power of the web to communicate features of molecular and crystallographic structure in creative and artistic ways that could not have been imagined in 1965. The paradigm shift of the 21st century is away from monolithic programs that are designed to do a specific task on a specific platform in a specific subdiscipline of science and toward tools that are more modular, flexible and useful in a broad interdisciplinary context. The shift is away from licensed profit-driven software with periodic updates to openly available software with rapid community-based `immediate' development goals.
The Jmol molecular visualization applet (Jmol, 2010) is leading the way in this shift. We have just recently begun to learn how it can be used to enhance student understanding of the principles of crystallography and appreciation of the beauty of symmetry. The Jmol applet represents the third stage of an evolutionary process that started with the development of RasMol (Sayle & Milner-White, 1995) in 1989. This program, probably more than any other, brought the world of into the hands of educators. Focused as it was on biomolecular structures, RasMol represented a major advance in the area of biochemistry and molecular biology. One of the important features introduced in RasMol was the capability of scripting, thus allowing for a `guided tour' approach to exploration of crystal structures and opening entirely new possibilities for education.
With the development of the web during the 1990s came the second phase of this process, spearheaded by the release of the Chime Netscape plug-in in 1996. The Chime plug-in was essentially RasMol for the web with a broader focus that included calculated structures of small molecules. Educators with a bit of web-development experience could for the first time make available to a wider audience interactive molecular structure-annotated texts. Despite its limitations, Chime formed the basis of many tutorials and web-based educational software tools.
2. The Jmol molecular visualization project
The Jmol molecular visualization project, one of the early open-source projects of the 1990s, really came of age in 2002 when it became the de facto replacement for Chime, which had lost its commercial development support, was not released to the public domain and could not keep pace with the rapidly developing browser market. In contrast to Chime, Jmol presented the opportunity for a rapidly developing program within a dedicated community of users and developers,
Jmol has in the past several years grown from its initial focus as a web-based RasMol/Chime replacement into a powerful visualization and analysis tool that remains highly modular and customizable. Unlike the other programs of the previous century, Jmol is essentially a massive easily accessible toolbox that can be used at the lowest level by dedicated professional Java programmers wanting to integrate molecular visualization into larger projects, at a more common level by scientists and educators wishing to communicate information via the web, and, finally, by students with little or no web design experience in the context of class projects, tutorials and laboratory exercises.
In terms of crystallography and education, now as we start into the second decade of the 21st century, Jmol offers its community of developer/users a wealth of ever-expanding capabilities. Some of these capabilities are highlighted below, most deriving from suggestions made by the Jmol user community within just the past few years. Mostly it is hoped that this paper will spark interest in finding additional ways Jmol can be of service to the wider crystallographic community both in education and in research. Capabilities discussed include file reading, script-based atom selection and display, analytical capabilities including measurement and surface analysis, and output options.
It is important to understand that there are three ways that Jmol can be utilized. These include a stand-alone Java program, a library of Java `classes' and an applet for the web. Thus, Jmol can be used as a stand-alone program, much like the aforementioned programs. It can be used as a programming library that can be integrated with another program to provide molecular visualization. However, the real niche for Jmol is that it can be used as an applet in a web-based setting.
All of the features discussed below relate to all of these uses. However it is the integration of Jmol into a web page that offers the most for education, as that context provides an easy means of packaging a into a broader educational objective.
3. File-reading capabilities of Jmol
Probably more than any other broadly featured program in common use, Jmol includes an ever-expanding set of `readers' that can open just about any structure file of interest. In particular, Jmol can read standard SHELX (Sheldrick, 2008), PDB (Protein Data Bank; Berman et al., 2000), and mmCIF formats, including crystallographic unit-cell, symmetry operator and anisotropic displacement parameters. Additional file formats of interest within the crystallographic community that are supported include files generated by the programs FHI-aims (Blum et al., 2009; http://www.fhi-berlin.mpg.de/aims ), CASTEP (Segall et al., 2002; http://www.castep.org ), CRYSTAL (Dovesi et al., 1989), VASP (Jurgen, 2008; http://cms.mpi.univie.ac.at/vasp ) and WIEN (Blaha, 1990; http://www.wien2k.at ). Jmol recognizes space-group symmetry in terms of Jones–Faithful (x, −y, z + ) format, Hermann–Mauguin space-group names, Hall (1981) symbols and International Tables for Crystallography space-group numbers. Symmetry can be applied or not, and virtually any number of unit cells can be loaded at will using a simple script syntax (Figs. 1–7; interactive versions of all figures, and the data files used to generate these figures, are available as supplementary material1).
Fig. 6 illustrates one of the unique features of Jmol: that one can load a file and override the file-based crystallographic parameters associated with it. One can, for example, load a into Jmol and then only apply a single Jones–Faithful operator – or, for that matter, apply any operator of any kind just to see what it does. One can quickly experiment with different members of a space-group family to see incrementally how the symmetry operations combine to form the overall symmetry of the system.
A further application of this feature is seen in Fig. 8. In this case, a standard XYZ-format file with just the minimum of structural information was `loaded' into a and arbitrary symmetry was applied. This feature of Jmol holds great potential to form the basis of a tutorial in symmetry using simple molecules or molecular fragments, allowing a student to experiment with different space groups, unit-cell dimensions and symmetry operators in real time.
4. General Jmol capabilities relating to crystallography education
Jmol's scripting capability makes it perfectly suited to an educational environment. Any educator with a bit of interest, and, probably, with help from the Jmol user community, can easily construct web pages that focus on specific topics relating to Through the use of trivially implemented associated standard web `widgets' (buttons, links, selection boxes, text entry boxes etc.) a web page can be constructed in very short order that can allow quite a powerful educational experience. With some additional web savvy, an educator can produce a very professional piece of interactive technology focused on student learning.
What follows is a quick look at some of the features of Jmol applet scripting that are particularly suited to crystallography. This is by no means an exhaustive look at Jmol scripting. The interested reader is referred to the Jmol interactive documentation website (http://chemapps.stolaf.edu/jmol/docs ) for a full list of Jmol scripting capabilities.
4.1. Atom selection
Jmol has extensive capability to select, display, highlight, move and hide particular sets of atoms. Specifically in relation to when a structure is loaded, Jmol retains information about the symmetry origins of the atoms. So, for example, one can select only those atoms that arose by a specific using select SYMOP=3. One can query Jmol as to what that is using show SYMOP 3, and one can explore the entire set of symmetry operations of a molecule using show symmetry or show spacegroup. Atoms within a specific can be selected using, for example, select cell=555.
4.2. Fractional coordinates and crystallographic atomic properties
Jmol scripts can refer to standard Cartesian coordinates as {x y z} or to fractional coordinates using at least one slash character as part of that description: draw arrow {1/2 1/2 1/2} {1 1 1/1}. In addition, Jmol can be queried for atom properties, among which include fractional coordinates fx, fy, fz and fxyz, and normalized unit-cell coordinates ux, uy, uz and uxyz. The print command along with formatting is a powerful mechanism of querying Jmol for all sorts of information. For example, print {cell=555}.uxyz reports the average unit-cell position for the atoms in the primary and the command print {*}.label("%a%i\t%5.3fx\t%5.3fy\t%5.3fz") delivers a formatted list of atom names and numbers along with their fractional coordinates (Table 1).
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4.3. Additional properties
Additional crystallographic properties of atoms that can be queried are given in Table 2. Most of these properties can be tabulated, compared, and applied as colors to molecular surfaces or as sizes of atoms in order to highlight anomalies. The configuration property is interesting in that it allows the user to display specific disorder sets (display configuration=1) or a superposition of configurations (display configuration=0) (Figs. 9 and 10).
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4.4. Visualization of symmetry
One of the more recent and exciting areas of development of Jmol has been in the area of visualization of symmetry elements. Planes and axes are easy to produce in Jmol using, for example, isosurface plane x=3; draw axis {0 0 0} {0 0 1/1}. Given a specific one can draw the intersection of planes in a natural fashion (Fig. 11).
Most interesting by far, though, is the ability of Jmol to depict complex relationships between two atoms or between two molecules such as glide planes and screw axes in a relatively simple fashion. These elements of symmetry are by far the most difficult to visualize, but with Jmol they are trivial to produce based on symmetry operators present in the file or added by the user. So, for example, if symmetry operator 2 is (−x, y + , −z + ) (a twofold screw axis with translation along the b axis), then draw symop 2 {1/4 0 1/4} will depict that operation applied to an atom at position (, 0, ) (Fig. 12). Any arbitrary can be depicted this way. For example, opening a file with P21/c and then using draw symop "x,1/2-y,z+1/2" will depict that c-glide plane operation.
In fact, if we knew that two molecules `1' and `4' were related in some way but we did not know how, we could find that out simply by using show symop {molecule=1} {molecule=4}. If more than one relates the two molecules, then both will be listed. Even better, if we wish to depict the we just use draw instead of show (Fig. 13), and if we specify set picking symmetry, then the user can simply pick any two atoms, and Jmol will depict the symmetry relationship between them (Fig. 14).
Thus, Jmol can be used in a novel exploratory mode, where we are interested in checking out the sorts of relations between molecules or atoms in a A web page illustrating these capabilities accompanies the publication of this paper (Hanson, 2009).
4.5. Measuring interatomic distances
One of the most common interests in crystallography is to measure interatomic distances and angles. With Jmol's print command, again, this is almost trivial. To list all bond distances to C atoms, one uses print measure({_C}, {*}, "connected") (Table 3); to measure all close-contact non-hydrogen nonbonded distances we might issue print measure({!_H}, {!_H}, 0, 1.5, "notconnected").
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4.6. Mathematical scripting
One of the most powerful aspects of Jmol is its extensive mathematical scripting capability, which allows extensive analysis of structure. This is a relatively recent addition to Jmol and marks a major advance over the former minimal linear command-based scripting of RasMol and Chime. One can now use all of the popular command flow syntaxes common to modern programming languages, including if/else, for/next and while. Jmol allows for the creation of functions that augment the language in many ways. One can define variables of numerous types, including some more exotic types specifically useful in molecular structure analysis, for example planes, quaternions, axis-angles, atom and bond sets, and rotation matrices.
4.7. Callbacks to JavaScript
For a truly interactive experience one needs to build into a tutorial the possibility of feedback. Questions such as `Where did the user click?', `Has an atom been selected?' and `Was the file loaded successfully?' are answered best by the mechanism of callback functions. These are JavaScript functions designed into the applet-containing web page that receive notices when events involving user actions (such as atom picking) or page actions (such as resizing) arise. Jmol allows for a number of callback notifications, including file-opening status, animation status, mouse clicking, atom picking and hovering, distance, angle and torsion measurement, script status, message reporting, and several others.
4.8. Database exploration
We recently wanted to ask a question about environments of amino acids and Jmol script and running Jmol as a stand-alone application, we could compile data on all of the proteins and (or, actually, a certain subset of well characterized structures). While Jmol may not be the most efficient means of doing this sort of analysis, the power of Jmol's scripting language made the task quite simple. Just about any aspect of biomolecular structure can be investigated this way.
in the entire PDB. By writing a simpleIn our case, we were interested in a property we have recently discovered, quaternion-based straightness (Hanson et al., 2010). Fundamentally, this property measures relative orientation of groups within a model. In general, we expect straightness to be high within secondary structures such as helices and sheets and low in less structurally defined regions. One of the DNA–protein complexes investigated, however, was found to have very low straightness within its helix (Fig. 15). Upon closer inspection, it was found that one of the cytidine bases was flipped (Fig. 16). Upon communication with the author of the original study, it was found that a mistake in the model used for the crystallographic analysis was involved.
From an educational point of view, this example simply illustrates that the models we find in the PDB database should not be taken at face value and how programs like Jmol can be used to explore databases and to spot both expected and unexpected structural patterns.
4.9. Program output
Largely based on user requests, Jmol has an extensive suite of output options that complement its interactive use. With either the stand-alone version or the signed applet one can write files to disk or to the operating system clipboard and produce high-quality images or exported models. The most popular image-creation options – JPG and PNG – are fully supported. In addition, while Jmol's output quality is very high, even higher `point-of-view ray tracing' (POV-Ray, 2000) output is as simple as clicking a button on the tool bar of the application or selecting a menu option on the applet.
One of the interesting aspects of these two-dimensional image files is that they can be read back into Jmol to reproduce the exact three-dimensional scene depicted in the image. The almost magical quality of this dramatic result is always a hit with students in the classroom.
Finally, Jmol can also export models in a variety of formats readable by other three-dimensional visualization programs.
4.10. Surface generation and property mapping
An important aspect of crystallography involves the visualization of lattice planes specified with Jmol allows selection and display of atoms based on their proximity to Miller planes. So, for example, in NaCl, Fmm, one can first depict the (111) Miller plane using draw INTERSECTION unitcell hkl {1 1 1} and then display just the atoms on that plane using display within(0, hkl, {1 1 1}) (Fig. 17). The zero here indicates that we want atoms on the plane; a positive or negative number instead would select atoms within the specified distance on one side (positive) or the other (negative) of the plane. Since the Miller plane represents just one in an infinite family of planes, Jmol allows depiction of any member of this family by simply scaling the integers to the desired value: (), for example. An interesting effect is to create a surface that maps atom position onto a plane. This is done using isosurface hkl {2/3 2/3 2/3} map molecular. These maps roughly approximate the look of a slice of electron density (Fig. 18).
4.11. Novel depictions of electron density
One of the foremost challenges of instructors is giving students a sense of what a `structural model' actually is and how we arrive at that model from actual data. The textbook view – of balls and sticks and cartoonish helices and sheets – properly conveys neither the ambiguity of structure nor the mathematical origins of structural models. With the availability of online electron density servers such as the Uppsala Electron Density Server (EDS, 2010), Jmol can be used to help develop an appreciation for the underlying mathematical model from which these more common renderings derive. Jmol can depict standard mesh-type isosurfaces of electron density, but in addition, Jmol can represent electron-density maps using a grid-based `cloud' method. With this method, one can depict the three-dimensional grid of electron-density data in its raw form as a block of numbers, in which some hint of `structure' is present (Fig. 19). The simple act of progressively removing numbers from this block based on a cut-off value `reveals' the underlying structure as a sort of pointillist model in a novel and very striking manner that does not rely on the more abstract concept of an isosurface (Fig. 20). The experience of `discovering' the structure within the data is dramatic (DensitySlider, 2010).
4.12. Depicting uncertainty and dynamics
A major challenge in early crystallographic education is helping students to develop an understanding of the uncertainties inherent in models. Jmol can, of course, depict uncertainty in the standard form of displacement ellipsoids, but in addition to that, Jmol can depict isotropic B-value (`temperature') data found in PDB and mmCIF formats in numerous ways. For example, one can map isotropic temperature data onto a molecular surface (Fig. 21) or depict B factors as the radius of a sphere at a given atom position (Fig. 22). In addition, Jmol can read and animate the results of calculations, thus simulating the range of natural molecular motion at a given temperature.
5. Summary
Jmol is a versatile tool that can readily enhance many discussions relating to crystallography by aiding in the visualization of real crystallographic data in both traditional and nontraditional ways. With its extremely flexible file-loading and symmetry-handling capabilities, Jmol can be used to highlight the essential characteristics of unit cells, space groups and symmetry operators. Its rich mathematical scripting language and close connection to JavaScript allows detailed exploration and `guided tours' of systems of interest and has allowed database developers the unprecedented capability to produce highly customized visual front ends for their products. It behoves us as educators to introduce our students to these database resources and to emphasize a critical-thinking approach to their use: Is this model reasonable? What is its origin? What assumptions did the authors make? What are the uncertainties? These are the sorts of questions that students need to be thinking about, and while many of them are outside the scope of Jmol, many at least initially can be addressed using visualization.
Science education is all about communication – teachers communicating complex molecular interactions and symmetry relationships; students making presentations and learning from web-based tutorials and quizzes. As the technology of visualization has become more prevalent and expected, Jmol has proven to be a solid and dependable partner in project after project at all levels of the educational enterprise.
Communication, of course, is all about community, and this is where Jmol has made a unique and lasting contribution to education. The features discussed in this paper are not the isolated invention of a lone programmer or even that of a small developer team or research group. Rather, these features are the result of a whole new 21st-century way of doing business, incorporating peer-reviewed solutions based on ideas generated within an active user community of professional crystallographers, educators and students with turnaround times of hours to days rather than months to years.
In all, the focus in this paper has been on the features of Jmol that might be particularly useful in an educational setting. As with all such tools, it is really the creativity of the user, not the programmer, that defines the end result, and while many examples of Jmol's use in molecular structure education are available (JmolWiki, 2010), far more is possible than has been realized to date. By itself on a web page, Jmol is just a fantastically powerful black box. What makes it so useful is how easy it is to turn that black box into an interactive and educational window into the beauty of the molecular world.
Supporting information
Gallery of interactive figures. DOI: 10.1107/S0021889810030256/kk5066sup1.html
Interactive figure viewer. DOI: 10.1107/S0021889810030256/kk5066sup2.html
Jmol scripts and data for Fig. 1. DOI: 10.1107/S0021889810030256/kk5066sup3.zip
Jmol scripts and data for Fig. 2. DOI: 10.1107/S0021889810030256/kk5066sup4.zip
Jmol scripts and data for Fig. 3. DOI: 10.1107/S0021889810030256/kk5066sup5.zip
Jmol scripts and data for Fig. 4. DOI: 10.1107/S0021889810030256/kk5066sup6.zip
Jmol scripts and data for Fig. 5. DOI: 10.1107/S0021889810030256/kk5066sup7.zip
Jmol scripts and data for Fig. 6. DOI: 10.1107/S0021889810030256/kk5066sup8.zip
Jmol scripts and data for Fig. 7. DOI: 10.1107/S0021889810030256/kk5066sup9.zip
Jmol scripts and data for Fig. 8. DOI: 10.1107/S0021889810030256/kk5066sup10.zip
Jmol scripts and data for Fig. 9. DOI: 10.1107/S0021889810030256/kk5066sup11.zip
Jmol scripts and data for Fig. 10. DOI: 10.1107/S0021889810030256/kk5066sup12.zip
Jmol scripts and data for Fig. 11. DOI: 10.1107/S0021889810030256/kk5066sup13.zip
Jmol scripts and data for Fig. 12. DOI: 10.1107/S0021889810030256/kk5066sup14.zip
Jmol scripts and data for Fig. 13. DOI: 10.1107/S0021889810030256/kk5066sup15.zip
Jmol scripts and data for Fig. 14. DOI: 10.1107/S0021889810030256/kk5066sup16.zip
Jmol scripts and data for Fig. 15. DOI: 10.1107/S0021889810030256/kk5066sup17.zip
Jmol scripts and data for Fig. 16. DOI: 10.1107/S0021889810030256/kk5066sup18.zip
Jmol scripts and data for Fig. 17. DOI: 10.1107/S0021889810030256/kk5066sup19.zip
Jmol scripts and data for Fig. 18. DOI: 10.1107/S0021889810030256/kk5066sup20.zip
Jmol scripts and data for Fig.19. DOI: 10.1107/S0021889810030256/kk5066sup21.zip
Jmol scripts and data for Fig. 20. DOI: 10.1107/S0021889810030256/kk5066sup22.zip
Jmol scripts and data for Fig. 21. DOI: 10.1107/S0021889810030256/kk5066sup23.zip
Jmol scripts and data for Fig. 22. DOI: 10.1107/S0021889810030256/kk5066sup24.zip
Acknowledgements
It is not possible to thank all of the people who have made contributions to the Jmol project. Dan Gezelter was the original developer of Jmol, to whom we are all very much indebted. Several other programmers contributed over the years, most notably Egon Willighagen, Nico Vervelle, René Kanters and especially Michael (Miguel) Howard, who single-handedly made Jmol's rendering engine a marvel of Java programming. Many Jmol users have contributed ideas, designs and solutions to problems over the years. Special thanks go to Tim Driscoll, Frieda Reichsman, Angel Herráez, Brian McMahon, Peter Murray-Rust, Alan Hewat and Sydney Hall, among many, many others. An undergraduate in our research group, Dan Kohler, discovered the optimal definition of straightness and found the anomaly in PDB entry 1d66.
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