While bioinformatics efforts generally involve the classification, archiving, and model building from empirical data sources, computational biophysics is focused on the development of predictive models and simulation techniques based on first principles. Meaning, computational biophysics attempts to develop theoretical models that capture the essential physics, chemistry, and/or biology. In many instances, these models are used to design new biological systems that exhibit a specific function and/or phenotype. As a consequence, computational biophysics represents a truly interdisciplinary effort that brings together experts from biology, physics, chemistry, math, engineering, and (of course) computer science. Historically, computational biophysics and bioinformatics have been considered separate disciplines; however, the line between empirical and first principles efforts is increasingly being blurred. At the Bioinformatics Research Center at UNC Charlotte, investigators are working on several of these problems, including: (i.) macromolecular electrostatics, (ii.) quantified stability/flexibility relationships (QSFR) within biomolecules, (iii.) molecular dynamics simulations, and (iv.) coarse-grained modeling techniques.