Macromolecular crystal structures are among the best of scientific data, providing detailed insight into these complex and biologically important molecules with a relatively low level of error and subjectivity. However, there are two notable problems with getting the most information from them. The first is that the models are not perfect: there is still opportunity for improving them, and users need to evaluate whether the local reliability in a structure is up to answering their question of interest. The second is that protein and nucleic acid molecules are highly complex and individual, inherently handed and three-dimensional, and the cooperative and subtle interactions that govern their detailed structure and function are not intuitively evident. Thus there is a real need for graphical representations and descriptive classifications that enable molecular 3D literacy. We have spent our career working to understand these elegant molecules ourselves, and building tools to help us and others determine and understand them better. The Protein Data Bank (PDB) has of course been vital and central to this undertaking. Here we combine some history of our involvement as depositors, illustrators, evaluators, and end-users of PDB structures with commentary on how best to study and draw scientific inferences from them.
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