A Novel Geometry-Based Approach to Infer Protein Interface Similarity.

The protein interface is key to understand protein function, providing a vital insight on how proteins interact with each other and with other molecules. Over the years, many computational methods to compare protein structures were developed, yet evaluating interface similarity remains a very difficult task. Here, we present PatchBag - a geometry based method for efficient comparison of protein surfaces and interfaces. PatchBag is a Bag-Of-Words approach, which represents complex objects as vectors, enabling to search interface similarity in a highly efficient manner. Using a novel framework for evaluating interface similarity, we show that PatchBag performance is comparable to state-of-the-art alignment-based structural comparison methods. The great advantage of PatchBag is that it does not rely on sequence or fold information, thus enabling to detect similarities between interfaces in unrelated proteins. We propose that PatchBag can contribute to reveal novel evolutionary and functional relationships between protein interfaces.

RNA-dependent chromatin localization of KDM4D lysine demethylase promotes H3K9me3 demethylation.

The JmjC-containing lysine demethylase, KDM4D, demethylates di-and tri-methylation of histone H3 on lysine 9 (H3K9me3). How KDM4D is recruited to chromatin and recognizes its histone substrates remains unknown. Here, we show that KDM4D binds RNA independently of its demethylase activity. We mapped two non-canonical RNA binding domains: the first is within the N-terminal spanning amino acids 115 to 236, and the second is within the C-terminal spanning amino acids 348 to 523 of KDM4D. We also demonstrate that RNA interactions with KDM4D N-terminal region are critical for its association with chromatin and subsequently for demethylating H3K9me3 in cells. This study implicates, for the first time, RNA molecules in regulating the levels of H3K9 methylation by affecting KDM4D association with chromatin.

FragBag, an accurate representation of protein structure, retrieves structural neighbors from the entire PDB quickly and accurately.

Fast identification of protein structures that are similar to a specified query structure in the entire Protein Data Bank (PDB) is fundamental in structure and function prediction. We present FragBag: An ultrafast and accurate method for comparing protein structures. We describe a protein structure by the collection of its overlapping short contiguous backbone segments, and discretize this set using a library of fragments. Then, we succinctly represent the protein as a "bags-of-fragments"-a vector that counts the number of occurrences of each fragment-and measure the similarity between two structures by the similarity between their vectors. Our representation has two additional benefits: (i) it can be used to construct an inverted index, for implementing a fast structural search engine of the entire PDB, and (ii) one can specify a structure as a collection of substructures, without combining them into a single structure; this is valuable for structure prediction, when there are reliable predictions only of parts of the protein. We use receiver operating characteristic curve analysis to quantify the success of FragBag in identifying neighbor candidate sets in a dataset of over 2,900 structures. The gold standard is the set of neighbors found by six state of the art structural aligners. Our best FragBag library finds more accurate candidate sets than the three other filter methods: The SGM, PRIDE, and a method by Zotenko et al. More interestingly, FragBag performs on a par with the computationally expensive, yet highly trusted structural aligners STRUCTAL and CE.