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Inference of the structural and functional consequences of amino acid-altering missense variants is challenging and not yet scalable. Clinical and research applications of the colossal number of identified missense variants is thus limited. Here we describe the aggregation and analysis of large-scale genomic variation and structural biology data for 1,330 disease-associated genes. Comparing the burden of 40 structural, physicochemical, and functional protein features of altered amino acids with 3-dimensional coordinates, we found 18 and 14 features that are associated with pathogenic and population missense variants, respectively. Separate analyses of variants from 24 protein functional classes revealed novel function-dependent vulnerable features. We then devised a quantitative spectrum, identifying variants with higher pathogenic variant-associated features. Finally, we developed a web resource (MISCAST; http://miscast.broadinstitute.org/) for interactive analysis of variants on linear and tertiary protein structures. The biological impact of missense variants available through the webtool will assist researchers in hypothesizing variant pathogenicity and disease trajectories.