Classification of the human THAP protein family identifies an evolutionarily conserved coiled coil region

Loss of the Ras Regulator RASAL1: Another Route to Ras Activation in Colorectal Cancer

The B30.2/SPRY domain is present in approximately 700 eukaryotic (approximately 150 human) proteins, including medically important proteins such as TRIM5alpha and Pyrin. Nonetheless, the functional role of this modular domain remained unclear. Here, we report the crystal structure of an SPRY-SOCS box family protein GUSTAVUS in complex with Elongins B and C, revealing a highly distorted two-layered beta-sandwich core structure of its B30.2/SPRY domain. Ensuing studies identified one end of the beta-sandwich as the surface interacting with an RNA helicase VASA with a 40 nM dissociation constant. The sequence variation in TRIM5alpha responsible for HIV-1 restriction and most of the mutations in Pyrin causing familial Mediterranean fever map on this surface, implicating the corresponding region in many B30.2/SPRY domains as the ligand-binding site. The amino acids lining the binding surface are highly variable among the B30.2/SPRY domains, suggesting that these domains are protein-interacting modules, which recognize a specific individual partner protein rather than a consensus sequence motif.

From the Similarity Analysis of Protein Cavities to the Functional Classification of Protein Families Using Cavbase

The Cytoplasmic Tail of the Mouse Brown Locus Product Determines Intracellular Stability and Export from the Endoplasmic Reticulum

The identities of signal transducer proteins that integrate histone hypoacetylation and transcriptional repression are largely unknown. Here we demonstrate that THAP7, an uncharacterized member of the recently identified THAP (Thanatos-associated protein) family of proteins, is ubiquitously expressed, associates with chromatin, and represses transcription. THAP7 binds preferentially to hypoacetylated (un-, mono-, and diacetylated) histone H4 tails in vitro via its C-terminal 77 amino acids. Deletion of this domain, or treatment of cells with the histone deacetylase inhibitor TSA, which leads to histone hyperacetylation, partially disrupts THAP7/chromatin association in living cells. THAP7 coimmunoprecipitates with histone deacetylase 3 (HDAC3) and the nuclear hormone receptor corepressor (NCoR) and represses transcription as a Gal4 fusion protein. Chromatin immunoprecipitation assays demonstrate that these corepressors are recruited to promoters in a THAP7 dependent manner and promote histone H3 hypoacetylation. The conserved THAP domain is a key determinant for full HDAC3 association in vitro, and both the THAP domain and the histone interaction domain are important for the repressive properties of THAP7. Full repression mediated by THAP7 is also dependent on NCoR expression. We hypothesize that THAP7 is a dual function repressor protein that actively targets deacetylation of histone H3 necessary to establish transcriptional repression and functions as a signal transducer of the repressive mark of hypoacetylated histone H4. This is the first demonstration of the transcriptional regulatory properties of a human THAP domain protein, and a critical identification of a potential transducer of the repressive signal of hypoacetylated histone H4 in higher eukaryotes.

Why don’t humans get scrapie from eating sheep? A possible explanation based on secondary structure predictions

The Cys loop family of ligand-gated ion channels mediate fast synaptic transmission for communication between neurons. They are allosteric proteins, in which binding of a neurotransmitter to its binding site in the extracellular amino-terminal domain triggers structural changes in distant transmembrane domains to open a channel for ion flow. Although the locations of binding site and channel gating machinery are well defined, the structural basis of the activation pathway coupling binding and channel opening remains to be determined. In this paper, by analyzing amino acid covariance in a multiple sequence alignment, we have identified an energetically interconnected network in the Cys loop family of ligand-gated ion channels. Statistical coupling and correlated mutational analyses along with clustering revealed a highly coupled cluster. Mapping the positions in the cluster onto a three-dimensional structural model demonstrated that these highly coupled positions form an interconnected network linking experimentally identified binding domains through the coupling region to the gating machinery. In addition, these highly coupled positions are also condensed in the transmembrane domains, which are a recent focus for the sites of action of many allosteric modulators. Thus, our results revealed a genetically interconnected network that potentially plays an important role in the allosteric activation and modulation of the Cys loop family of ligand-gated ion channels.

A significant fraction of the amino acids in proteins are alpha helical in conformation. Alpha helices in globular proteins are short, with an average length of about twelve residues, so that residues at the ends of helices make up an important fraction of all helical residues. In the middle of a helix, H-bonds connect the NH and CO groups of each residue to partners four residues along the chain. At the ends of a helix, the H-bond potential of the main chain remains unfulfilled, and helix capping interactions involving bonds from polar side chains to the NH or CO of the backbone have been proposed and detected. In a study of synthetic helical peptides, we have found that the sequence Ser-Glu-Asp-Glu stabilizes the alpha helix in a series of helical peptides with consensus sequences. Following the report by Harper and Rose, which identifies SerXaaXaaGlu as a member of a class of common motifs at the N termini of alpha helices in proteins that they refer to as "capping boxes," we have reexamined the side chain-main chain interactions in a variant sequence using 1H NMR, and find that the postulated reciprocal side chain-backbone bonding between the first Ser and last Glu side chains and their peptide NH partners can be resolved. Deletion of two residues N terminal to the Ser-Glu-Asp-Glu sequence in these peptides has no effect on the initiation of helical structure, as defined by two-dimensional (2D) NMR experiments on this variant.(ABSTRACT TRUNCATED AT 250 WORDS)

The DENN domain is a common, evolutionarily ancient, and conserved protein module, yet it has gone largely unstudied; until recently, little was known regarding its functional roles. New studies reveal that various DENN domains interact directly with members of the Rab family of small GTPases and that DENN domains function enzymatically as Rab-specific guanine nucleotide exchange factors. Thus, DENN domain proteins appear to be generalized regulators of Rab function. Study of these proteins will provide new insights into Rab-mediated membrane trafficking pathways.

Proteins mediate their biological function through interactions with other proteins. Therefore, the systematic identification and characterization of protein-protein interactions have become a powerful proteomic strategy to understand protein function and comprehensive cellular regulatory networks. For the screening of valosin-containing protein, carboxyl terminus of Hsp70-interacting protein (CHIP), and amphiphysin II interaction partners, we utilized a membrane-based array technology that allows the identification of human protein-protein interactions with crude bacterial cell extracts. Many novel interaction pairs such as valosin-containing protein/autocrine motility factor receptor, CHIP/caytaxin, or amphiphysin II/DLP4 were identified and subsequently confirmed by pull-down, two-hybrid and co-immunoprecipitation experiments. In addition, assays were performed to validate the interactions functionally. CHIP e.g. was found to efficiently polyubiquitinate caytaxin in vitro, suggesting that it might influence caytaxin degradation in vivo. Using peptide arrays, we also identified the binding motifs in the proteins DLP4, XRCC4, and fructose-1,6-bisphosphatase, which are crucial for the association with the Src homology 3 domain of amphiphysin II. Together these studies indicate that our human proteome array technology permits the identification of protein-protein interactions that are functionally involved in neurodegenerative disease processes, the degradation of protein substrates, and the transport of membrane vesicles.

With the current access to the whole genomes of various organisms and the completion of the first draft of the human genome, there is a strong need for a structure-function classification of protein families as an initial step in moving from DNA databases to a comprehensive understanding of human biology. As a result of the explosion in nucleic acid sequence information and the concurrent development of methods for high-throughput functional characterization of gene products, the genomic revolution also promises to provide a new paradigm for drug discovery, enabling the identification of molecular drug targets in a significant number of human diseases. This molecular view of diseases has contributed to the importance of combining primary sequence data with three-dimensional structure and has increased the awareness of computational homology modeling and its potential to elucidate protein function. In particular, when important proteins or novel therapeutic targets are identified—like the family of protein tyrosine phosphatases (PTPs) (reviewed in reference 53)—a structure-function classification of such protein families becomes an invaluable framework for further advances in biomedical science. Here, we present a comparative analysis of the structural relationships among vertebrate PTP domains and provide a comprehensive resource for sequence analysis of phosphotyrosine-specific PTPs.

Although genes carry information, proteins are the main role player in providing all the functionalities of a living organism. Massive amounts of different proteins involve in every function that occurs in a cell. These amino acid sequences can be hierarchically classified into a set of families and subfamilies depending on their evolutionary relatedness and similarities in their structure or function. Protein characterization to identify protein structure and function is done accurately using laboratory experiments. With the rapidly increasing huge amount of novel protein sequences, these experiments have become difficult to carry out since they are expensive, time-consuming, and laborious. Therefore, many computational classification methods are introduced to classify proteins and predict their functional properties. With the progress of the performance of the computational techniques, deep learning plays a key role in many areas. Novel deep learning models such as DeepFam, ProtCNN have been presented to classify proteins into their families recently. However, these deep learning models have been used to carry out the non-hierarchical classification of proteins. In this research, we propose a deep learning neural network model named DeepHiFam with high accuracy to classify proteins hierarchically into different levels simultaneously. The model achieved an accuracy of 98.38% for protein family classification and more than 80% accuracy for the classification of protein subfamilies and sub-subfamilies. Further, DeepHiFam performed well in the non-hierarchical classification of protein families and achieved an accuracy of 98.62% and 96.14% for the popular Pfam dataset and COG dataset respectively.

Using a SOM (self-organizing map) we can classify sequences within a protein family into subgroups that generally correspond to biological subcategories. These maps tend to show sequence similarity as proximity in the map. Combining maps generated at different levels of resolution, the structure of relations in protein families can be captured that could not otherwise be represented in a single map. The underlying representation of maps enables us to retrieve characteristic sequence patterns for individual subgroups of sequences. Such patterns tend to correspond to functionally important regions. We present a modified SOM algorithm that includes a convergence test that dynamically controls the learning parameters to adapt them to the learning set instead of being fixed and externally optimized by trial and error. Given the variability of protein family size and distribution, the addition of this features is necessary. The method is successfully tested with a number of families. The rab family of small GTPases is used to illustrate the performance of the method.

New insights into the evolution and nature of proteinsExploring several distinct approaches, this book describes the methods for comparing protein sequences and protein structures in order to identify homologous relationships and classify proteins and protein domains into evolutionary families. Readers will discover the common features as well as the key philosophical differences underlying the major protein classification systems, including Pfam, Panther, SCOP, and CATH. Moreover, they'll discover how these systems can be used to understand the evolution of protein families as well as understand and predict the degree to which structural and functional information are shared between relatives in a protein family.Edited and authored by leading international experts, Protein Families offers new insights into protein families that are important to medical research as well as protein families that help us understand biological systems and key biological processes such as cell signaling and the immune response. The book is divided into three sections: Section I: Concepts Underlying Protein Family Classification reviews the major strategies for identifying homologous proteins and classifying them into families. Section II: In-Depth Reviews of Protein Families focuses on some fascinating super protein families for which we have substantial amounts of sequence, structural and functional data, making it possible to trace the emergence of functionally diverse relatives. Section III: Review of Protein Families in Important Biological Systems examines protein families associated with a particular biological theme, such as the cytoskeleton.All chapters are extensively illustrated, including depictions of evolutionary relationships. References at the end of each chapter guide readers to original research papers and reviews in the field.Covering protein family classification systems alongside detailed descriptions of select protein families, this book offers biochemists, molecular biologists, protein scientists, structural biologists, and bioinformaticians new insight into the evolution and nature of proteins.

An Inducible Cartilage Oligomeric Matrix Protein Mouse Model Recapitulates Human Pseudoachondroplasia Phenotype