Macromolecular crystallography and electron microscopy (single-particle and in situ tomography) are merging into a single approach used by the two coalescing scientific communities. The merger is a consequence of technical developments that enabled determination of atomic structures of macromolecules by electron microscopy. Technological progress in experimental methods of macromolecular structure determination, computer hardware, and software changed and continues to change the nature of model building and visualization of molecular structures. However, the increase in automation and availability of structure validation are reducing interactive manual model building to fiddling with details. On the other hand, interactive modeling tools increasingly rely on search and complex energy calculation procedures, which make manually driven changes in geometry increasingly powerful and at the same time less demanding. Thus, the need for accurate manual positioning of a model is decreasing. The user’s push only needs to be sufficient to bring the model within the increasing convergence radius of the computing tools. It seems that we can now better than ever determine an average single structure. The tools work better, requirements for engagement of human brain are lowered, and the frontier of intellectual and scientific challenges has moved on. The quest for resolution of new challenges requires out-of-the-box thinking. A few issues such as model bias and correctness of structure, ongoing developments in parameters defining geometric restraints, limitations of the ideal average single structure, and limitations of Bragg spot data are discussed here, together with the challenges that lie ahead.
Turk, D. (2017). Boxes of model building and visualization. In Methods in Molecular Biology (Vol. 1607, pp. 491–548). Humana Press Inc. https://doi.org/10.1007/978-1-4939-7000-1_21