Tables for
Volume F
Crystallography of biological macromolecules
Edited by M. G. Rossmann and E. Arnold

International Tables for Crystallography (2006). Vol. F, ch. 17.2, pp. 365-366   | 1 | 2 |

Section 17.2.5. Looking ahead

A. J. Olsona*

aThe Scripps Research Institute, La Jolla, CA 92037, USA
Correspondence e-mail:

17.2.5. Looking ahead

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Moore's law has already delivered on the promise of three-dimensional graphics capability for the desktop and laptop. The internet and World Wide Web have made molecular structure data and display software available to the masses. Have molecular graphics reached a stage of maturity beyond which only small incremental changes will be made?

The Human Genome Initiative and high-throughput structure determination are beginning to change the scope of the questions asked of molecular modelling. Prediction of function, interactions, and large-scale assembly and mechanism will become the dominant domain of molecular graphics and modelling. These tasks will challenge the capabilities of the hardware, software and, particularly, the user interface. New modes of interacting with data and models are coming from the computer-graphics community. Molecular docking and protein manipulation using force-feedback devices have been demonstrated at the University of North Carolina (Brooks et al., 1990[link]). The same team has developed a `nanomanipulator' which couples a scanning atomic force microscope with stereoscopic display and force-feedback manipulation to control and sense the positioning and interactions of the probe within the molecular landscape (Taylor et al., 1993[link]). The challenge of bridging across the scales of size and complexity of the molecular world may lead us into the realm of virtual reality. Data from X-ray crystallography are being combined with data from large molecular complexes, characterized by electron microscopy. These data, in turn, can be integrated with those from optical confocal microscopy and other imaging techniques. With structures of molecules, assemblies and distributions, as well as data on molecular inventories, we can start to piece together integrated pictures of cellular environments, but with full atomic modelling at the base (Fig.[link]). Thus, while climbing around inside a protein molecule might not add much in the way of perceptual advantage, navigating through the molecular environment of a cell may prove to be instructive as well as inspirational.


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This image represents a volume of blood plasma 750 Å on a side. Within the three-dimensional model, antibodies (Y- and T-shaped molecules in light blue and pink) are binding to a virus (the large green spherical assembly on the right), labelling it for destruction. It shows all macromolecules present in the blood plasma at a magnification of about 10 000 000 times. This model is composed of over 450 individual protein domains, ranging in size from the 60 protomers making up the poliovirus to a single tiny insulin molecule (in magenta). The model was constructed using atomic level descriptions for each molecule, for a total of roughly 1.5 million atoms. Detailed surfaces were computed for each type of protein using MSMS by Michel Sanner and then smoothed to a lower resolution using the HARMONY spherical-harmonic surfaces developed by Bruce Duncan. The model geometry contains over 1.5 million triangles.


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