SKPDB: a structural database of shikimate pathway enzymes

Helen A Arcuri 0 4 Geraldo FD Zafalon 3 Evandro A Marucci 3 Carlos E Bonalumi 3 Nelson JF da Silveira 2 Jos M Machado 3 Walter F de Azevedo Jr 1 5 Mrio S Palma 0 4 0 CEIS/Departamento de Biologia, Instituto de Biociencias , UNESP, Rio Claro, Sao Paulo , Brasil 1 Faculdade de Biociencias, PUCRS , Porto Alegre, Rio Grande do Sul , Brasil 2 Departamento de Ciencias Exatas, UNIFAL , Alfenas, Minas Gerais , Brasil 3 Departamento de Ciencia da Computacao e Estatistica, UNESP/IBILCE , Sao Jose do Rio Preto, Sao Paulo , Brasil 4 CEIS/Departamento de Biologia, Instituto de Biociencias , UNESP, Rio Claro, Sao Paulo , Brasil 5 Faculdade de Biociencias, PUCRS , Porto Alegre, Rio Grande do Sul , Brasil Background: The functional and structural characterisation of enzymes that belong to microbial metabolic pathways is very important for structure-based drug design. The main interest in studying shikimate pathway enzymes involves the fact that they are essential for bacteria but do not occur in humans, making them selective targets for design of drugs that do not directly impact humans. Description: The ShiKimate Pathway DataBase (SKPDB) is a relational database applied to the study of shikimate pathway enzymes in microorganisms and plants. The current database is updated regularly with the addition of new data; there are currently 8902 enzymes of the shikimate pathway from different sources. The database contains extensive information on each enzyme, including detailed descriptions about sequence, references, and structural and functional studies. All files (primary sequence, atomic coordinates and quality scores) are available for downloading. The modeled structures can be viewed using the Jmol program. Conclusions: The SKPDB provides a large number of structural models to be used in docking simulations, virtual screening initiatives and drug design. It is freely accessible at http://lsbzix.rc.unesp.br/skpdb/. - Background The functional and structural characterisation of enzymes belonging to microbial metabolic pathways is very important for structure-based drug design [1]. The main interest in the study of shikimate pathway enzymes (Figure 1) involves the fact that they are not present in humans, but are essential for algae, higher plants, bacteria, fungi, and apicomplexan parasites. This makes them attractive targets for development of new antimicrobial drugs and decreases the impact of drugs in humans [2,3]. This pathway links the metabolism of carbohydrates to the biosynthesis of aromatic compounds through seven metabolic steps, where phosphoenolpyruvate (PEP) and erythrose 4-phosphate are converted to chorismate, which in turn is the common precursor for synthesising a series of aromatic compounds, naphtoquinones, menaquinones, and mycobactins [3,4]. Inhibition of the shikimate pathway has been effective in controlling bacterial growth [5], and in mycobacteria, this pathway has been shown to be essential for the viability of Mycobacterium tuberculosis [6-8]. The functional and structural characterisation of a protein sequence is one of the most frequent problems in structural molecular biology. This task is usually facilitated by an accurate three-dimensional (3D) structure of the studied protein, which is best determined by experimental methods such as X-ray crystallography and NMR spectroscopy [9]. In the absence of an experimentally determined 3D structure, the modeling (comparative or by homology) can sometimes provide a useful 3D model for a target protein [10]. In the present work, we used comparative modeling at a large scale for predicting protein structures through the program MODELLER [11]. The automation of large-scale comparative modeling involves assembling a software pipeline, which consists of modules for fold assignment, template selection, target-template alignment, model generation, and model evaluation. Computer programs for these individual operations already exist, and it may seem trivial to combine them [11,12]. One example of large-scale Figure 1 The sequence of seven metabolic steps in the shikimate pathway, from phosphoenolpyruvate and erythrose 4-phosphate to chorismate, adapted from the site: http://www. chem.qmul.ac.uk/iubmb/enzyme/reaction/misc/shikim.html. comparative modeling for complete genomes has been described for sequences encoded in the Mycobacterium tuberculosis and Xylella fastidiosa genomes in the DBMODELING database [13,14]. The challenge in largescale comparative modeling is to build an automated, fast, robust, sensitive, and accurate pipeline applicable to whole genomes; such a pipeline should perform at least as well as a human expert on individual proteins. However, since the accuracy of structural models is highly dependent on sequence identity between template and target, it is necessary to make clear to the user that only models presenting high structural quality should be used in such efforts. Molecular modeling of these enzymes generated the SKPDB database, in which all structural models were built by using alignments presenting more than 30% sequence identity, generating models with medium and high accuracy [10,15]. SKPDB is a relational database of protein structure predicted by comparative modeling or solved by X-ray crystallography, applied to the study of shikimate pathway enzymes of microorganisms and plants. This database is freely accessible for all users on the Web, providing us with a large number of structural models for use in structure-based virtual screening and molecular docking analysis. Furthermore, SKPDB also provides a docking interface, which allows the user to carry out geometric docking simulations against the molecular models available in the database. Construction and Content Molecular modeling in large scale Homology modeling is usually the method of choice when there is a clear relationship of homology between the sequences of a target protein and at least one experimentally determined three-dimensional structure. This computational technique is based on the assumption that tertiary structures of two proteins will be similar if their sequences are related, and it is the approach most likely to give accurate results [16]. The number of protein sequences that can be modeled and the accuracy of the predictions are increasing steadily due to the growth in the number of experimentally determined protein structures and because of the improvements in the modeling software. It is currently possible to model with useful accuracy significant parts of approximately one half of all known protein sequences [17]. The molecular modeling in this work was performed by the MODELLER version 9v4 [10,18] program, which is a computer program for comparative protein structure modeling http://salilab.org/modeller. The program extracts atom-atom distance and dihedral angle restraints on the target from the template structure, and combines them with general rules of protein structure such as bond length and angl (...truncated)