Protein motions, ranging from molecular flexibility to large-scale conformational change, play an essential role in many biochemical processes. Despite the explosion in our knowledge of structural and functional data, our understanding of protein movement is very limited because it is difficult to measure experimentally and computationally expensive to simulate. In previous work, we have developed and validated a method based on motion planning for mapping protein folding pathways from unstructured conformations to the native state. In this paper, we propose a novel method based on rigidity theory to sample conformation space more effectively and we describe extensions of our framework to automate the mapping process and to map transitions between specified conformations. Our experimental results show that these additions both improve the accuracy of our maps and enable us to study a broader range of motions for larger proteins. For example, we show that rigidity-based sampling results in maps that capture subtle folding differences between protein G and its mutations, NuG1 and NuG2, and we illustrate how our technique can be used to study large-scale conformational changes in calmodulin, a 148 residue signaling
protein known to undergo conformational
changes when it binds to Ca2+.
Finally, we announce our web-based protein folding server which includes a publically available archive of protein motions: http://parasol.tamu.edu/foldingserver/