Letunic, I. et al. SMART 5: domains in the context of genomes and networks. Nucleic Acids Res. 34, D257-D260

EMBL, Meyerhofstrasse 1, 69012 Heidelberg, Germany.
Nucleic Acids Research (Impact Factor: 9.11). 02/2006; 34(Database issue):D257-60. DOI: 10.1093/nar/gkj079
Source: PubMed


The Simple Modular Architecture Research Tool (SMART) is an online resource ( used for protein domain identification and the analysis of protein domain architectures. Many new features were implemented
to make SMART more accessible to scientists from different fields. The new ‘Genomic’ mode in SMART makes it easy to analyze
domain architectures in completely sequenced genomes. Domain annotation has been updated with a detailed taxonomic breakdown
and a prediction of the catalytic activity for 50 SMART domains is now available, based on the presence of essential amino
acids. Furthermore, intrinsically disordered protein regions can be identified and displayed. The network context is now displayed
in the results page for more than 350 000 proteins, enabling easy analyses of domain interactions.

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Available from: Jörg Schultz, Aug 13, 2014
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    • ".de/) [31]. Alignment of multiple PLD-related domains was performed using the clustalW program ( clustalw/). "

    Full-text · Dataset · Aug 2015
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    • "The SMART, http://smart.embl-heidelbergde > / (Letunic et al., 2006; Schultz et al., 1998), PFAM, ? "
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    ABSTRACT: Pathogenic Leptospira is the etiological agent of leptospirosis, a life-threatening disease of human and veterinary concern. The search for novel antigens that could mediate host-pathogen interactions is been pursued. Due to their location, these antigens have the potential to elicit numerous activities, including immune response and adhesion. This study focuses on a hypothetical protein of Leptospira, encoded by the gene LIC11089 and of its three derived fragments: N-terminus, intermediate and C-terminus regions. The gene coding for the full-length protein and fragments were cloned and expressed in Escherichia coli BL21-SI strain by using the expression vector pAE. The recombinant protein and fragments tagged with hexahistidine at N-terminal were purified by metal-charged chromatography. The leptospiral full-length protein, named Lsa32 (Leptospiral surface adhesin, 32 kDa), adheres to laminin, being the C-terminus region responsible for this interaction. Lsa32 binds to plasminogen (PLG), in a dose-dependent fashion, generating plasmin (PLA) when activator is provided. Moreover, antibodies present in leptospirosis serum samples were able to recognize Lsa32. The Lsa32 is most likely a new surface protein of Leptospira as revealed by proteinase K susceptibility. All together, our data suggest that this multifaceted protein is expressed during infection and may play a role in host - L. interrogans interactions.
    Full-text · Article · Jan 2015 · Microbiology
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    • "Works done in this category are PROMALS [7], DDBASE [8] and Mateo [9]. Methods that used comparative model to identify other member of protein domain family such as Protein Family database (Pfam) [10], Conserved Domain Database (CDD) [11] and Simple Modular Architecture Research Tool (SMART) [12]. Methods that are based only on sequence information to provide an appealing alternative, especially for large-scale domain classification such as Domain Guess by Size (DGS) [13]. "
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    ABSTRACT: Protein domains are portion block of protein sequence that evolved independent function. Therefore, the classification of protein domain is becoming very importance in order to produce new sequence with new function. However the main issue in protein domain classification is to classify the domain correctly into their category since the sequence coincidently classify to both category. Therefore, to overcome this issue, this paper proposed a computational method to classify protein domain from protein subsequences and protein structure information using sigmoid kernel function. The proposed method consists of three phases: pre-processing, protein structure information generating and post-processing. The pre-processing phase selects potential protein. The protein structure information generating phase used several calculations to generate protein structure information in order to optimize the domain signal information. The classification phase involves Sigmoid SVM and performance evaluation. The performance of the proposed method is evaluated in terms of sensitivity and specificity on single-domain and multiple-domain using dataset SCOP 1.75. This method showed an improvement of prediction in term of sensitivity, specificity and accuracy. Keywords— protein domain; protein sequence; protein structure; support vector machine; protein subsequence.
    Full-text · Conference Paper · May 2014
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