MODPROPEP: a program for knowledge-based modeling of protein–peptide complexes

MODPROPEP is a web server for knowledge-based modeling of protein–peptide complexes, specifically peptides in complex with major histocompatibility complex (MHC) proteins and kinases. The available crystal structures of protein–peptide complexes in PDB are used as templates for modeling peptides of desired sequence in the substrate-binding pocket of MHCs or protein kinases. The substrate peptides are modeled using the same backbone conformation as in the template and the side-chain conformations are obtained by the program SCWRL. MODPROPEP provides a number of user-friendly interfaces for visualizing the structure of the modeled protein–peptide complexes and analyzing the contacts made by the modeled peptide ligand in the substrate-binding pocket of the MHC or protein kinase. Analysis of these specific inter-molecular contacts is crucial for understanding structural basis of the substrate specificity of these two protein families. This software also provides appropriate interfaces for identifying, putative MHC-binding peptides in the sequence of an antigen or phosphorylation sites on the substrate protein of a kinase, by scoring these inter-molecular contacts using residue-based statistical pair potentials. MODPROPEP would complement various available sequence-based programs (SYFPEITHI, SCANSITE, etc.) for predicting substrates of MHCs and protein kinases. The program is available at http://www.nii.res.in/modpropep.htm

Genome scale prediction of substrate specificity for acyl adenylate superfamily of enzymes based on active site residue profiles

<p>Abstract</p> <p>Background</p> <p>Enzymes belonging to acyl:CoA synthetase (ACS) superfamily activate wide variety of substrates and play major role in increasing the structural and functional diversity of various secondary metabolites in microbes and plants. However, due to the large sequence divergence within the superfamily, it is difficult to predict their substrate preference by annotation transfer from the closest homolog. Therefore, a large number of ACS sequences present in public databases lack any functional annotation at the level of substrate specificity. Recently, several examples have been reported where the enzymes showing high sequence similarity to luciferases or coumarate:CoA ligases have been surprisingly found to activate fatty acyl substrates in experimental studies. In this work, we have investigated the relationship between the substrate specificity of ACS and their sequence/structural features, and developed a novel computational protocol for <it>in silico </it>assignment of substrate preference.</p> <p>Results</p> <p>We have used a knowledge-based approach which involves compilation of substrate specificity information for various experimentally characterized ACS and derivation of profile HMMs for each subfamily. These HMM profiles can accurately differentiate probable cognate substrates from non-cognate possibilities with high specificity (Sp) and sensitivity (Sn) (Sn = 0.91-1.0, Sp = 0.96-1.0) values. Using homologous crystal structures, we identified a limited number of contact residues crucial for substrate recognition i.e. specificity determining residues (SDRs). Patterns of SDRs from different subfamilies have been used to derive predictive rules for correlating them to substrate preference. The power of the SDR approach has been demonstrated by correct prediction of substrates for enzymes which show apparently anomalous substrate preference. Furthermore, molecular modeling of the substrates in the active site has been carried out to understand the structural basis of substrate selection. A web based prediction tool <url>http://www.nii.res.in/pred_acs_substr.html</url> has been developed for automated functional classification of ACS enzymes.</p> <p>Conclusions</p> <p>We have developed a novel computational protocol for predicting substrate preference for ACS superfamily of enzymes using a limited number of SDRs. Using this approach substrate preference can be assigned to a large number of ACS enzymes present in various genomes. It can potentially help in rational design of novel proteins with altered substrate specificities.</p

Towards Prediction of Metabolic Products of Polyketide Synthases: An In Silico Analysis

Sequence data arising from an increasing number of partial and complete genome projects is revealing the presence of the polyketide synthase (PKS) family of genes not only in microbes and fungi but also in plants and other eukaryotes. PKSs are huge multifunctional megasynthases that use a variety of biosynthetic paradigms to generate enormously diverse arrays of polyketide products that posses several pharmaceutically important properties. The remarkable conservation of these gene clusters across organisms offers abundant scope for obtaining novel insights into PKS biosynthetic code by computational analysis. We have carried out a comprehensive in silico analysis of modular and iterative gene clusters to test whether chemical structures of the secondary metabolites can be predicted from PKS protein sequences. Here, we report the success of our method and demonstrate the feasibility of deciphering the putative metabolic products of uncharacterized PKS clusters found in newly sequenced genomes. Profile Hidden Markov Model analysis has revealed distinct sequence features that can distinguish modular PKS proteins from their iterative counterparts. For iterative PKS proteins, structural models of iterative ketosynthase (KS) domains have revealed novel correlations between the size of the polyketide products and volume of the active site pocket. Furthermore, we have identified key residues in the substrate binding pocket that control the number of chain extensions in iterative PKSs. For modular PKS proteins, we describe for the first time an automated method based on crucial intermolecular contacts that can distinguish the correct biosynthetic order of substrate channeling from a large number of non-cognate combinatorial possibilities. Taken together, our in silico analysis provides valuable clues for formulating rules for predicting polyketide products of iterative as well as modular PKS clusters. These results have promising potential for discovery of novel natural products by genome mining and rational design of novel natural products

SEARCHGTr: a program for analysis of glycosyltransferases involved in glycosylation of secondary metabolites

SEARCHGTr is a web-based software for the analysis of glycosyltransferases (GTrs) involved in the biosynthesis of a variety of pharmaceutically important compounds like adriamycin, erythromycin, vancomycin etc. This software has been developed based on a comprehensive analysis of sequence/structural features of 102 GTrs of known specificity from 52 natural product biosynthetic gene clusters. SEARCHGTr is a powerful tool that correlates sequences of GTrs to the chemical structures of their corresponding substrates. This software indicates the donor/acceptor specificity and also identifies putative substrate binding residues. In addition, it provides interfaces to other public databases like GENBANK, SWISS-PROT, CAZY, PDB, PDBSum and PUBMED for extracting various information on GTrs homologous to the query sequence. SEARCHGTr would provide new dimension to our previously developed bioinformatics tool NRPS-PKS. Together, these tools facilitate comprehensive computational analysis of proteins involved in biosynthesis of aglycone core and its downstream glycosylations. Apart from presenting opportunities for rational design of novel natural products, these tools would assist in the identification of biosynthetic products of secondary metabolite gene clusters found in newly sequenced genomes. SEARCHGTr can be accessed at

PAR-3D: a server to predict protein active site residues

PAR-3D (http://sunserver.cdfd.org.in:8080/protease/PAR_3D/index.html) is a web-based tool that exploits the fact that relative juxtaposition of active site residues is a conserved feature in functionally related protein families. The server uses previously calculated and stored values of geometrical parameters of a set of known proteins (training set) for prediction of active site residues in a query protein structure. PAR-3D stores motifs for different classes of proteases, the ten glycolytic pathway enzymes and metal-binding sites. The server accepts the structures in the pdb format. The first step during the prediction is the extraction of probable active site residues from the query structure. Spatial arrangement of the probable active site residues is then determined in terms of geometrical parameters. These are compared with stored geometries of the different motifs. Its speed and efficiency make it a beneficial tool for structural genomics projects, especially when the biochemical function of the protein has not been characterized

In silico analysis of methyltransferase domains involved in biosynthesis of secondary metabolites

Background: Secondary metabolites biosynthesized by polyketide synthase (PKS) and nonribosomal peptide synthetase (NRPS) family of enzymes constitute several classes of therapeutically important natural products like erythromycin, rapamycin, cyclosporine etc. In view of their relevance for natural product based drug discovery, identification of novel secondary metabolite natural products by genome mining has been an area of active research. A number of different tailoring enzymes catalyze a variety of chemical modifications to the polyketide or nonribosomal peptide backbone of these secondary metabolites to enhance their structural diversity. Therefore, development of powerful bioinformatics methods for identification of these tailoring enzymes and assignment of their substrate specificity is crucial for deciphering novel secondary metabolites by genome mining. Results: In this work, we have carried out a comprehensive bioinformatics analysis of methyltransferase (MT) domains present in multi functional type I PKS and NRPS proteins encoded by PKS/NRPS gene clusters having known secondary metabolite products. Based on the results of this analysis, we have developed a novel knowledge based computational approach for detecting MT domains present in PKS and NRPS megasynthases, delineating their correct boundaries and classifying them as N-MT, C-MT and O-MT using profile HMMs. Analysis of proteins in nr database of NCBI using these class specific profiles has revealed several interesting examples, namely, C-MT domains in NRPS modules, N-MT domains with significant homology to C-MT proteins, and presence of NRPS/PKS MTs in association with other catalytic domains. Our analysis of the chemical structures of the secondary metabolites and their site of methylation suggested that a possible evolutionary basis for the presence of a novel class of N-MT domains with significant homology to C-MT proteins could be the close resemblance of the chemical structures of the acceptor substrates, as in the case of pyochelin and yersiniabactin. These two classes of MTs recognize similar acceptor substrates, but transfer methyl groups to N and C positions on these substrates. Conclusion: We have developed a novel knowledge based computational approach for identifying MT domains present in type I PKS and NRPS multifunctional enzymes and predicting their site of methylation. Analysis of nr database using this approach has revealed presence of several novel MT domains. Our analysis has also given interesting insight into the evolutionary basis of the novel substrate specificities of these MT proteins

A new family of type III polyketide synthases in Mycobacterium tuberculosis

The Mycobacterium tuberculosis genome has revealed a remarkable array of polyketide synthases (PKSs); however, no polyketide product has been isolated thus far. Most of the PKS genes have been implicated in the biosynthesis of complex lipids. We report here the characterization of two novel type III PKSs from M. tuberculosis that are involved in the biosynthesis of long-chain &#945;-pyrones. Measurement of steady-state kinetic parameters demonstrated that the catalytic efficiency of PKS18 protein was severalfold higher for long-chain acyl-coenzyme A substrates as compared with the small-chain precursors. The specificity of PKS18 and PKS11 proteins toward long-chain aliphatic acyl-coenzyme A (C12 to C20) substrates is unprecedented in the chalcone synthase (CHS) family of condensing enzymes. Based on comparative modeling studies, we propose that these proteins might have evolved by fusing the catalytic machinery of CHS and &#946;-ketoacyl synthases, the two evolutionarily related members with conserved thiolase fold. The mechanistic and structural importance of several active site residues, as predicted by our structural model, was investigated by performing site-directed mutagenesis. The functional identification of diverse catalytic activity in mycobacterial type III PKSs provide a fascinating example of metabolite divergence in CHS-like proteins

Two functionally distinctive phosphopantetheinyl transferases from amoeba Dictyostelium discoideum

The life cycle of Dictyostelium discoideum is proposed to be regulated by expression of small metabolites. Genome sequencing studies have revealed a remarkable array of genes homologous to polyketide synthases (PKSs) that are known to synthesize secondary metabolites in bacteria and fungi. A crucial step in functional activation of PKSs involves their post-translational modification catalyzed by phosphopantetheinyl transferases (PPTases). PPTases have been recently characterized from several bacteria; however, their relevance in complex life cycle of protozoa remains largely unexplored. Here we have identified and characterized two phosphopantetheinyl transferases from D. discoideum that exhibit distinct functional specificity. DiAcpS specifically modifies a stand-alone acyl carrier protein (ACP) that possesses a mitochondrial import signal. DiSfp in contrast is specific to Type I multifunctional PKS/fatty acid synthase proteins and cannot modify the stand-alone ACP. The mRNA of two PPTases can be detected during the vegetative as well as starvation-induced developmental pathway and the disruption of either of these genes results in non-viable amoebae. Our studies show that both PPTases play an important role in Dictyostelium biology and provide insight into the importance of PPTases in lower eukaryotes

Dissecting the functional role of polyketide synthases in Dictyostelium discoideum

Dictyostelium discoideum exhibits the largest repository of polyketide synthase (PKS) proteins of all known genomes. However, the functional relevance of these proteins in the biology of this organism remains largely obscure. On the basis of computational, biochemical, and gene expression studies, we propose that the multifunctional Dictyostelium PKS (DiPKS) protein DiPKS1 could be involved in the biosynthesis of the differentiation regulating factor 4-methyl-5-pentylbenzene-1,3-diol (MPBD). Our cell-free reconstitution studies of a novel acyl carrier protein Type III PKS didomain from DiPKS1 revealed a crucial role of protein-protein interactions in determining the final biosynthetic product. Whereas the Type III PKS domain by itself primarily produces acyl pyrones, the presence of the interacting acyl carrier protein domain modulates the catalytic activity to produce the alkyl resorcinol scaffold of MPBD. Furthermore, we have characterized an O-methyltransferase (OMT12) from Dictyostelium with the capability to modify this resorcinol ring to synthesize a variant of MPBD. We propose that such a modification in vivo could in fact provide subtle variations in biological function and specificity. In addition, we have performed systematic computational analysis of 45 multidomain PKSs, which revealed several unique features in DiPKS proteins. Our studies provide a new perspective in understanding mechanisms by which metabolic diversity could be generated by combining existing functional scaffolds

RECQL4 is essential for the transport of p53 to mitochondria in normal human cells in the absence of exogenous stress

Mutations in RECQL4 helicase are associated with Rothmund–Thomson syndrome (RTS). A subset of RTS patients is predisposed to cancer and is sensitive to DNA damaging agents. The enhanced sensitivity of cells from RTS patients correlates with the accumulation of transcriptionally active nuclear p53. We found that in untreated normal human cells these two nuclear proteins, p53 and RECQL4, instead colocalize in the mitochondrial nucleoids. RECQL4 accumulates in mitochondria in all phases of the cell cycle except S phase and physically interacts with p53 only in the absence of DNA damage. p53–RECQL4 binding leads to the masking of the nuclear localization signal of p53. The N-terminal 84 amino acids of RECQL4 contain a mitochondrial localization signal, which causes the localization of RECQL4–p53 complex to the mitochondria. RECQL4–p53 interaction is disrupted after stress, allowing p53 translocation to the nucleus. In untreated normal cells RECQL4 optimizes de novo replication of mtDNA, which is consequently decreased in fibroblasts from RTS patients. Wild-type RECQL4-complemented RTS cells show relocalization of both RECQL4 and p53 to the mitochondria, loss of p53 activation, restoration of de novo mtDNA replication and resistance to different types of DNA damage. In cells expressing Δ84 RECQL4, which cannot translocate to mitochondria, all the above functions are compromised. The recruitment of p53 to the sites of de novo mtDNA replication is also regulated by RECQL4. Thus these findings elucidate the mechanism by which p53 is regulated by RECQL4 in unstressed normal cells and also delineates the mitochondrial functions of the helicase