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Inhibitors of PDZ-peptide interactions have important implications in a variety of biological processes including treatment of cancer and Parkinson’s disease. Even though experimental studies have reported characterization of peptidomimetic inhibitors of PDZ-peptide interactions, the binding modes for most of them have not been characterized by structural studies. In this study we have attempted to understand the structural basis of the small molecule-PDZ interactions by in silico analysis of the binding modes and binding affinities of a set of 38 small molecules with known Ki or Kd values for PDZ2 and PDZ3 domains of PSD-95 protein. These two PDZ domains show differential selectivity for these compounds despite having a high degree of sequence similarity and almost identical peptide binding pockets. Optimum binding modes for these ligands for PDZ2 and PDZ3 domains were identified by using a novel combination of semi-flexible docking and explicit solvent molecular dynamics (MD) simulations. Analysis of the binding modes revealed most of the peptidomimectic ligands which had high Ki or Kd moved away from the peptide binding pocket, while ligands with high binding affinities remained in the peptide binding pocket. The differential specificities of the PDZ2 and PDZ3 domains primarily arise from differences in the conformation of the loop connecting βB and βC strands, because this loop interacts with the N-terminal chemical moieties of the ligands. We have also computed the MM/PBSA binding free energy values for these 38 compounds with both the PDZ domains from multiple 5 ns MD trajectories on each complex i.e. a total of 228 MD trajectories of 5 ns length each. Interestingly, computational binding free energies show good agreement with experimental binding free energies with a correlation coefficient of approximately 0.6. Thus our study demonstrates that combined use of docking and MD simulations can help in identification of potent inhibitors of PDZ-peptide complexes. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

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 posttranslational 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. [ABSTRACT FROM AUTHOR]

A novel iterative biosynthetic mechanism for multifunctional polyketide synthases reveals how the metabolic diversity of this enzyme family can arise by using existing scaffolds in novel combinations. [ABSTRACT FROM AUTHOR]