Proteins are chemically simple molecules, being unbranched polymers of uncomplicated organic compounds. Nonetheless, they fold up into a dazzling variety of complex and beautiful configurations with a dizzying array of structural, regulatory, and catalytic functions. Despite great progress, we still have very limited ability to predict the folded conformation of an amino acid sequence, and limited understanding of its dynamics and motions. Thus, this work presents a quartet of interrelated studies that address some aspects of the detailed local conformations and motions of protein backbone. First, I used a density-dependent smoothing algorithm and a high-quality, B-filtered data set to construct highly accurate conformational distributions for protein backbone (Ramachandran plots) and sidechains (rotamers). These distributions are the most accurate and restrictive produced to date, with improved discrimination between rare-but-real conformations and artifactual ones. Second, I analyzed hundreds of alternate conformations in atomic resolution crystal structures, and discovered that dramatic conformational change in a protein sidechain is often coupled to a subtle but very common mode of conformational change in its backbone -- the backrub motion. Examination of other biophysical data further supports the ubiquity of this motion. Third, I applied a model of backrub motion to protein design calculations. Although experimental characterization of the designs showed them to be unstable and/or inactive, the computational results proved to be very sensitive to changes in the backbone. Finally, I describe how MolProbity uses my conformational distributions together with all-atom contacts and other tools to validate protein structures, and how those quality metrics can be combined visually or analytically to provide "multi-criterion" validation summaries. / dissertation