UniHI 4: new tools for query, analysis and visualization of the human protein–protein interactome

Human protein interaction maps have become important tools of biomedical research for the elucidation of molecular mechanisms and the identification of new modulators of disease processes. The Unified Human Interactome database (UniHI, http://www.unihi.org) provides researchers with a comprehensive platform to query and access human protein–protein interaction (PPI) data. Since its first release, UniHI has considerably increased in size. The latest update of UniHI includes over 250 000 interactions between ∼22 300 unique proteins collected from 14 major PPI sources. However, this wealth of data also poses new challenges for researchers due to the complexity of interaction networks retrieved from the database. We therefore developed several new tools to query, analyze and visualize human PPI networks. Most importantly, UniHI allows now the construction of tissue-specific interaction networks and focused querying of canonical pathways. This will enable researchers to target their analysis and to prioritize candidate proteins for follow-up studies

UniHI: an entry gate to the human protein interactome

Systematic mapping of protein–protein interactions has become a central task of functional genomics. To map the human interactome, several strategies have recently been pursued. The generated interaction datasets are valuable resources for scientists in biology and medicine. However, comparison reveals limited overlap between different interaction networks. This divergence obstructs usability, as researchers have to interrogate numerous heterogeneous datasets to identify potential interaction partners for proteins of interest. To facilitate direct access through a single entry gate, we have started to integrate currently available human protein interaction data in an easily accessible online database. It is called UniHI (Unified Human Interactome) and is available at . At present, it is based on 10 major interaction maps derived by computational and experimental methods. It includes more than 150 000 distinct interactions between more than 17 000 unique human proteins. UniHI provides researchers with a flexible integrated tool for finding and using comprehensive information about the human interactome

Flexible web-based integration of distributed large-scale human protein interaction maps

Protein-protein interactions constitute the backbone of many molecular processes. This has motivated the recent construction of several large-scale human protein-protein interaction maps [1-10]. Although these maps clearly offer a wealth of information, their use is challenging: complexity, rapid growth, and fragmentation of interaction data hamper their usability. To overcome these hurdles, we have developed a publicly accessible database termed UniHI (Unified Human Interactome) for integration of human protein-protein interaction data. This database is designed to provide biomedical researchers a common platform for exploring previously disconnected human interaction maps. UniHI offers researchers flexible integrated tools for accessing comprehensive information about the human interactome. Several features included in the UniHI allow users to perform various types of network-oriented and functional analysis. At present, UniHI contains over 160,000 distinct interactions between 17,000 unique proteins from ten major interaction maps derived by both computational and experimental approaches [1-10]. Here we describe the details of the implementation and maintenance of UniHI and discuss the challenges that have to be addressed for a successful integration of interaction data

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web-based integration of distributed large-scal

Self-assembly of Mutant Huntingtin Exon-1 Fragments into Large Complex Fibrillar Structures Involves Nucleated Branching

Huntingtin (HTT) fragments with extended polyglutamine tracts self-assemble into amyloid-like fibrillar aggregates. Elucidating the fibril formation mechanism is critical for understanding Huntington's disease pathology and for developing novel therapeutic strategies. Here, we performed systematic experimental and theoretical studies to examine the self-assembly of an aggregation-prone N-terminal HTT exon-1 fragment with 49 glutamines (Ex1Q49). Using high-resolution imaging techniques such as electron microscopy and atomic force microscopy, we show that Ex1Q49 fragments in cell-free assays spontaneously convert into large, highly complex bundles of amyloid fibrils with multiple ends and fibril branching points. Furthermore, we present experimental evidence that two nucleation mechanisms control spontaneous Ex1Q49 fibrillogenesis: (1) a relatively slow primary fibril-independent nucleation process, which involves the spontaneous formation of aggregation-competent fibrillary structures, and (2) a fast secondary fibril-dependent nucleation process, which involves nucleated branching and promotes the rapid assembly of highly complex fibril bundles with multiple ends. The proposed aggregation mechanism is supported by studies with the small molecule O4, which perturbs early events in the aggregation cascade and delays Ex1Q49 fibril assembly, comprehensive mathematical and computational modeling studies, and seeding experiments with small, preformed fibrillar Ex1Q49 aggregates that promote the assembly of amyloid fibrils. Together, our results suggest that nucleated branching in vitro plays a critical role in the formation of complex fibrillar HTT exon-1 aggregates with multiple ends