This un-edited manuscript has been accepted for publication in Biophysical Journal and is freely available on BioFAST at www.biophysj.org. The final copyedited version of the paper may be found at www.biophysj.org.

this paper is on new tools for structural and sequence analysis and visualization. AlignPlot, written in C and Python, provides a graphical representation of the RMSD values for each alignment in the set, allowing the user to quickly identify the regions of two structures that are most similar. Particularly important, it provides a user-friendly way to display specific alignments on the screen and navigate among them. MSFviewer, written in Python, provides an integrated link to sequence space, displaying multiple alignments of related sequences on the screen and providing for interactive highlighting of a selected structural align- ment and the associated multiple sequence alignment

Abstract—Availability of an effective tool for protein multiple structural alignment (MSTA) is essential for discovery and analysis of biologically significant structural motifs that can help solve functional annotation and drug design problems. Existing MSTA methods collect residue correspondences mostly through pairwise comparison of consecutive fragments, which can lead to suboptimal alignments, especially when the similarity among the proteins is low. We introduce a novel strategy based on: building a contact-window based motif library from the protein structural data, discovery and extension of common alignment seeds from this library, and optimal superimposition of multiple structures according to these alignment seeds by an enhanced partial order curve comparison method. The ability of our strategy to detect multiple correspondences simultaneously, to catch alignments globally, and to support flexible alignments, endorse a sensitive and robust automated algorithm that can expose similarities among protein structures even under low similarity conditions. Our method yields better alignment results compared to other popular MSTA methods, on several protein structure datasets that span various structural folds and represent different protein similarity levels. A web-based alignment tool, a downloadable executable, and detailed alignment results for the datasets used here are available at