SCOPPI, the structural classification of protein-protein interfaces, is a comprehensive database that classifies and annotates domain interactions derived from all known protein structures. SCOPPI applies SCOP domain definitions and a distance criterion to determine inter-domain interfaces. Using a novel method based on multiple sequence and structural alignments of SCOP families, SCOPPI presents a comprehensive geometrical classification of domain interfaces. Various interface characteristics such as number, type and position of interacting amino acids, conservation, interface size, and permanent or transient nature of the interaction are further provided. Proteins in SCOPPI are annotated with Gene Ontology terms, and the ontology can be used to quickly browse SCOPPI. Screenshots are available for every interface and its participating domains. Here, we describe contents and features of the web-based user interface as well as the underlying methods used to generate SCOPPI's data. In addition, we present a number of examples where SCOPPI becomes a useful tool to analyze viral mimicry of human interface binding sites, gene fusion events, conservation of interface residues and diversity of interface localizations. SCOPPI is available at http://www.scoppi.org.
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http://dx.doi.org/10.1093/nar/gkj099 | DOI Listing |
Int J Environ Res Public Health
November 2020
Department of Maternal, Infantile and Urological Sciences, Sapienza University of Rome, 00161 Rome, Italy.
From 9 March to 3 May 2020, lockdown was declared in Italy due to the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic. Our aim was to evaluate how the SARS-CoV-2 pandemic and related preventive strategies affected pediatric emergency rooms (ERs) during this period. We performed a retrospective cohort multicenter study, comparing the lockdown period to the corresponding period in 2019.
View Article and Find Full Text PDFItal J Pediatr
April 2018
Department of Woman and Child and General and Specialized Surgery, University of Campania Luigi Vanvitelli, Naples, Italy.
Background: Acute asthma attack is a frequent condition in children. It is one of the most common reasons for emergency department (ED) visit and hospitalization. Appropriate care is fundamental, considering both the high prevalence of asthma in children, and its life-threatening risks.
View Article and Find Full Text PDFJ Mol Biol
February 2011
Computer Science and Artificial Intelligence Laboratory, MIT, Cambridge, MA 02139, USA.
Current homology modeling methods for predicting protein-protein interactions (PPIs) have difficulty in the "twilight zone" (<40%) of sequence identities. Threading methods extend coverage further into the twilight zone by aligning primary sequences for a pair of proteins to a best-fit template complex to predict an entire three-dimensional structure. We introduce a threading approach, iWRAP, which focuses only on the protein interface.
View Article and Find Full Text PDFBioinformatics
October 2008
Computer Science and Artificial Intelligence Laboratory, MIT, MIT, Cambridge, USA.
The long-standing problem of constructing protein structure alignments is of central importance in computational biology. The main goal is to provide an alignment of residue correspondences, in order to identify homologous residues across chains. A critical next step of this is the alignment of protein complexes and their interfaces.
View Article and Find Full Text PDFGene
October 2008
Bioinformatics Group, Biotechnological Center, Technical University Dresden, Germany.
Predicting protein interaction interfaces and protein complexes are two important related problems. For interface prediction, there are a number of tools, such as PPI-Pred, PPISP, PINUP, Promate, and SPPIDER, which predict enzyme-inhibitor interfaces with success rates of 23% to 55% and other interfaces with 10% to 28% on a benchmark dataset of 62 complexes. Here, we develop, metaPPI, a meta server for interface prediction.
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