Detecting intermediate protein conformations using algebraic topology Understanding protein structure and dynamics is essential for understanding their function. This is a challenging task due to the high complexity of the conformational landscapes of proteins and their rugged energy levels. In particular, it is important to detect highly populated regions which could correspond to intermediate structures or local minima. We present a hierarchical clustering and algebraic topology based method that detects regions of interest in protein conformational space. The method is based on several techniques. We use coarse grained protein conformational search, efficient robust dimensionality reduction and topological analysis via persistent homology as the main tools. We use two dimensionality reduction methods as well, robust Principal Component Analysis (PCA) and Isomap, to generate a reduced representation of the data while preserving most of the variance in the data. Our hierarchical clustering method was able to produce compact, well separated clusters for all the tested examples.

Matching of EM Map Segments to StructurallyRelevant Biomolecular Regions Electron microscopy is a technique used to determine the structure of biomolecular machines via threedimensional images (called maps). The stateoftheart is able to determine structures at resolutions that allow us to identify up to secondary structural features, in some cases, but it is not widespread. Furthermore, because molecular interactions often require atomiclevel details to be understood, it is still necessary to complement current maps with techniques that provide finergrain structural details. We applied segmentation techniques to maps in the Electron Microscopy Data Bank (EMDB), the standard community repository for these data. We assessed the potential of these algorithms to match functionally relevant regions in their atomicresolution image counterparts by comparing against three protein systems, each with multiple atomicdetailed domains. We found that at least 80% of amino acid residues in 7 out of 12 domains were assigned to single segments, suggesting there is potential to match the lower resolution segmented regions to the atomic counterparts. We also qualitatively analyzed the potential on other EMDB structures, as well as generating the raw segmentation information for the complete EMDB, for interested researchers to use. Results can be accessed online and the library developed is provided as part of an opensource project.