Fast Hinge Detection Algorithms for Flexible Protein Structures
Analysis of conformational changes is one of the keys to the understanding of protein functions and interactions. For the analysis, we often compare two protein structures, taking flexible regions like hinge regions into consideration. The Root Mean Square Deviation (RMSD) is the most popular measure for comparing two protein structures, but it is only for rigid structures without hinge regions. In this paper, we propose a new measure called RMSD considering hinges (RMSDh) and its variant RMSDhd((k)) for comparing two flexible proteins with hinge regions. We also propose novel efficient algorithms for computing them, which can detect the hinge positions at the same time. The RMSDh is suitable for cases where there is one small hinge region in each of the two target structures. The new algorithm for computing the RMSDh runs in linear time, which is the same as the time complexity for computing the RMSD and is faster than any of previous algorithms for hinge detection. The RMSDhd((k)) is designed for comparing structures with more than one hinge region. The RMSDhd((k)) measure considers at most k small hinge region, i.e., the RMSDhd((k)) value should be small if the two structures are similar except for at most k hinge regions. To compute the value, we propose an O(kn(2))-time and O(n)-space algorithm based on a new dynamic programming technique. With the same computational time and space, we can enumerate the predicted hinge positions. We also test our algorithms against actual flexible protein structures, and show that the hinge positions can be correctly detected by our algorithms.
algorithm dynamic programming protein hinge detection protein 3d structure comparison