Dedicated to Prof. Bernie Roth on the Occasion of his 70th Birthday

In the structural bioinformatics literature, a number of works address the geometry of how alpha-helices (one of the major components of proteins) pack against each other. Typically such studies involve isolating the axis of each helix, measuring the angle between helices that are judged to be in contact, and generating statistics of the inter-helical angle over many contacting pairs. Using techniques from theoretical kinematics, we show that previous efforts to normalize angle distribution data did not include important effects. Namely, helices can interact with each other in three distinct ways which we refer to as “line on line”, “end point to line ” and “endpoint to endpoint, ” and each of these interactions has its own geometric effects which must be included in the proper normalization of statistical data. This problem is one of many in the area of structural bioinformatics which can benefit from kinematics techniques