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The aim of the current study is to investigate the role of the CAD domain in the activation mechanism of calcium dependent protein kinase-1 of Plasmodium falciparum (PfCDPK1) and explore the possibility of allosteric inhibition of this kinase. PfCDPK1 belongs to CDPK family of apicomplexan kinases which have a C-terminal CAD domain. Microsecond scale MD simulations were performed on modeled structures of complete PfCDPK1 and its kinase domain alone. The simulations revealed that in absence of CAD the salt bridge between Glu116 in αC-helix and Lys85 in β3-sheet of kinase breaks after 200 ns resulting in inactive conformation of the kinase, but the salt bridge stays intact in the complete protein stabilizing it in active conformation. These results highlight the novel CAD mediated allosteric stabilization of the crucial salt bridge which is a hallmark of active conformation of kinase domains. The mechanistic details of the allosteric activation revealed by our study, opens up the possibility for design of allosteric inhibitors of PfCDPK1 kinase by disrupting the kinase:CAD interactions. Using a combination of machine learning and structure-based in silico screening, we have identified novel PPI modulators for allosteric inactivation of PfCDPK1 kinase. • PfCDPK1 kinase - an important drug target, undergoes Ca2+ dependent conformational transitions through its CAD domain. • The study showed that CAD activates the kinase domain of PfCDPK1 allosterically. • The CAD stabilizes the conserved salt bridge in the active state of the kinase domain. • The Kinase:CAD domain interface provides the opportunity to design novel allosteric inhibitors for PfCDPK1. [ABSTRACT FROM AUTHOR]

Small molecule modulators of protein–protein interactions (PPIs) are being pursued as novel anticancer, antiviral and antimicrobial drug candidates. We have utilized a large data set of experimentally validated PPI modulators and developed machine learning classifiers for prediction of new small molecule modulators of PPI. Our analysis reveals that using random forest (RF) classifier, general PPI Modulators independent of PPI family can be predicted with ROC-AUC higher than 0.9, when training and test sets are generated by random split. The performance of the classifier on data sets very different from those used in training has also been estimated by using different state of the art protocols for removing various types of bias in division of data into training and test sets. The family-specific PPIM predictors developed in this work for 11 clinically important PPI families also have prediction accuracies of above 90% in majority of the cases. All these ML-based predictors have been implemented in a freely available software named SMMPPI for prediction of small molecule modulators for clinically relevant PPIs like RBD:hACE2, Bromodomain_Histone, BCL2-Like_BAX/BAK, LEDGF_IN, LFA_ICAM, MDM2-Like_P53, RAS_SOS1, XIAP_Smac, WDR5_MLL1, KEAP1_NRF2 and CD4_gp120. We have identified novel chemical scaffolds as inhibitors for RBD_hACE PPI involved in host cell entry of SARS-CoV-2. Docking studies for some of the compounds reveal that they can inhibit RBD_hACE2 interaction by high affinity binding to interaction hotspots on RBD. Some of these new scaffolds have also been found in SARS-CoV-2 viral growth inhibitors reported recently; however, it is not known if these molecules inhibit the entry phase. [ABSTRACT FROM AUTHOR]

Motivation Even though genome mining tools have successfully identified large numbers of non-ribosomal peptide synthetase (NRPS) and polyketide synthase (PKS) biosynthetic gene clusters (BGCs) in bacterial genomes, currently no tool can predict the chemical structure of the secondary metabolites biosynthesized by these BGCs. Lack of algorithms for predicting complex macrocyclization patterns of linear PK/NRP biosynthetic intermediates has been the major bottleneck in deciphering the final bioactive chemical structures of PKs/NRPs by genome mining. Results Using a large dataset of known chemical structures of macrocyclized PKs/NRPs, we have developed a machine learning (ML) algorithm for distinguishing the correct macrocyclization pattern of PKs/NRPs from the library of all theoretically possible cyclization patterns. Benchmarking of this ML classifier on completely independent datasets has revealed ROC–AUC and PR–AUC values of 0.82 and 0.81, respectively. This cyclization prediction algorithm has been used to develop SBSPKSv3, a genome mining tool for completely automated prediction of macrocyclized structures of NRPs/PKs. SBSPKSv3 has been extensively benchmarked on a dataset of over 100 BGCs with known PKs/NRPs products. Availability and implementation The macrocyclization prediction pipeline and all the datasets used in this study are freely available at http://www.nii.ac.in/sbspks3.html. Supplementary information Supplementary data are available at Bioinformatics online. [ABSTRACT FROM AUTHOR]

Background: PDZ domains recognize short sequence stretches usually present in C-terminal of their interaction partners. Because of the involvement of PDZ domains in many important biological processes, several attempts have been made for developing bioinformatics tools for genome-wide identification of PDZ interaction networks. Currently available tools for prediction of interaction partners of PDZ domains utilize machine learning approach. Since, they have been trained using experimental substrate specificity data for specific PDZ families, their applicability is limited to PDZ families closely related to the training set. These tools also do not allow analysis of PDZ-peptide interaction interfaces. Results: We have used a structure based approach to develop modPDZpep, a program to predict the interaction partners of human PDZ domains and analyze structural details of PDZ interaction interfaces. modPDZpep predicts interaction partners by using structural models of PDZ-peptide complexes and evaluating binding energy scores using residue based statistical pair potentials. Since, it does not require training using experimental data on peptide binding affinity, it can predict substrates for diverse PDZ families. Because of the use of simple scoring function for binding energy, it is also fast enough for genome scale structure based analysis of PDZ interaction networks. Benchmarking using artificial as well as real negative datasets indicates good predictive power with ROC-AUC values in the range of 0.7 to 0.9 for a large number of human PDZ domains. Another novel feature of modPDZpep is its ability to map novel PDZ mediated interactions in human protein-protein interaction networks, either by utilizing available experimental phage display data or by structure based predictions. Conclusions: In summary, we have developed modPDZpep, a web-server for structure based analysis of human PDZ domains. It is freely available at http://www.nii.ac.in/modPDZpep.html or http://202.54.226.235/modPDZpep.html. [ABSTRACT FROM AUTHOR]

The Fic domain was recently shown to catalyze AMPylation--the transfer of AMP from ATP to hydroxyl side chains of diverse eukaryotic proteins, ranging from RhoGTPases to chaperon BiP. We have carried out a series of explicit solvent molecular dynamics (MD) simulations up to 1 μs duration on the apo, holo, and substrate/product bound IbpA Fic domain (IbpAFic2). Simulations on holo-IbpAFic2 revealed that binding of Mg2+ to α and β phosphates is crucial for preserving catalytically important contacts involving ATP. Comparative analysis of the MD trajectories demonstrated how binding of ATP allosterically induces conformational changes in the distal switch II binding region of Fic domains thereby aiding in substrate recognition. Our simulations have also identified crucial aromatic-aromatic interactions which stabilize the orientation of the catalytic histidine for inline nucleophilic attack during AMPylation, thus providing a structural basis for the evolutionary conservation of these aromatic residue pairs in Fic domains. On the basis of analysis of interacting interface residue pairs that persist over the microsecond trajectory, we identified a tetrapeptide stretch involved in substrate recognition. The structure-based genome-wide search revealed a distinct conservation pattern for this segment in different Fic subfamilies, further supporting its proposed role in substrate recognition. In addition, combined use of simulations and phylogenetic analysis has helped in the discovery of a new subfamily of Fic proteins that harbor a conserved Lys/Arg in place of the inhibitory Glu of the regulatory helix. We propose the novel possibility of auto-enhancement of AMPylation activity in this new subfamily via the movement of regulatory helix, in contrast to auto-inhibition seen in most Fic proteins. [ABSTRACT FROM AUTHOR]

Small open reading frames (smORFs) encoding proteins less than 100 amino acids (aa) are known to be important regulators of key cellular processes. However, their computational identification remains a challenge. Based on a comprehensive analysis of known prokaryotic small ORFs, we have developed the ProsmORF-pred resource which uses a machine learning (ML)-based method for prediction of smORFs in the prokaryotic genome sequences. ProsmORF-pred consists of two ML models, one for initiation site recognition in nucleic acid sequences upstream of putative start codons and the other uses translated amino acid sequences to decipher functional protein like sequences. The nucleotide sequence-based initiation site recognition model has been trained using longer ORFs (>100 aa) in the same genome while the ML model for identification of protein like sequences has been trained using annotated smORFs from Escherichia coli. Comprehensive benchmarking of ProsmORF-pred reveals that its performance is comparable to other state-of-the-art approaches on the annotated smORF set derived from 32 prokaryotic genomes. Its performance is distinctly superior to other tools like PRODIGAL and RANSEPS for prediction of newly identified smORFs which have a length range of 10–30 aa, where prediction of smORFs has been a major challenge. Apart from identification of smORFs in genomic sequences, ProsmORF-pred can also aid in functional annotation of the predicted smORFs based on sequence similarity and genomic neighbourhood similarity searches in ProsmORFDB, a well-curated database of known smORFs. ProsmORF-pred along with its backend database ProsmORFDB is available as a user-friendly web server (http://www.nii.ac.in/prosmorfpred.html). [ABSTRACT FROM AUTHOR]

With the recent discoveries of novel post-translational modifications (PTMs) which play important roles in signaling and biosynthetic pathways, identification of such PTM catalyzing enzymes by genome mining has been an area of major interest. Unlike well-known PTMs like phosphorylation, glycosylation, SUMOylation, no bioinformatics resources are available for enzymes associated with novel and unusual PTMs. Therefore, we have developed the novPTMenzy database which catalogs information on the sequence, structure, active site and genomic neighborhood of experimentally characterized enzymes involved in five novel PTMs, namely AMPylation, Eliminylation, Sulfation, Hydroxylation and Deamidation. Based on a comprehensive analysis of the sequence and structural features of these known PTM catalyzing enzymes, we have created Hidden Markov Model profiles for the identification of similar PTM catalyzing enzymatic domains in genomic sequences. We have also created predictive rules for grouping them into functional subfamilies and deciphering their mechanistic details by structure-based analysis of their active site pockets. These analytical modules have been made available as user friendly search interfaces of novPTMenzy database. It also has a specialized analysis interface for some PTMs like AMPylation and Eliminylation. The novPTMenzy database is a unique resource that can aid in discovery of unusual PTM catalyzing enzymes in newly sequenced genomes. Database URL: http://www.nii.ac.in/novptmenzy.html [ABSTRACT FROM AUTHOR]

Bacterial phosphothreonine lyases catalyze a novel posttranslational modification involving formation of dehydrobutyrine/dehyroalanine by β elimination of the phosphate group of phosphothreonine or phosphoserine residues in their substrate proteins. Though there is experimental evidence for presence of dehydro amino acids in human proteins, no eukaryotic homologs of these lyases have been identified as of today. A comprehensive genome-wide search for identifying phosphothreonine lyase homologs in eukaryotes was carried out. Our fold-based search revealed structural and catalytic site similarity between bacterial phosphothreonine lyases and BLES03 (basophilic leukemia-expressed protein 03), a human protein with unknown function. Ligand induced conformational changes similar to bacterial phosphothreonine lyases, and movement of crucial arginines in the loop region to the catalytic pocket upon binding of phosphothreonine-containing peptides was seen during docking and molecular dynamics studies. Genome-wide search for BLES03 homologs using sensitive profile-based methods revealed their presence not only in eukaryotic classes such as chordata and fungi but also in bacterial and archaebacterial classes. The synteny of these archaebacterial BLES03-like proteins was remarkably similar to that of type IV lantibiotic synthetases which harbor LanL-like phosphothreonine lyase domains. Hence, context-based analysis reinforced our earlier sequence/structure-based prediction of phosphothreonine lyase catalytic function for BLES03. Our in silico analysis has revealed that BLES03-like proteins with previously unknown function are novel eukaryotic phosphothreonine lyases involved in biosynthesis of dehydro amino acids, whereas their bacterial and archaebacterial counterparts might be involved in biosynthesis of natural products similar to lantibiotics. [ABSTRACT FROM AUTHOR]

Mycobacterial Ser/Thr kinase, PknB, is essential for the growth of the pathogen. Unphosphorylated PknB is catalytically inactive, and its activation requires autophosphorylation of Thr residues on the activation loop. Autophosphorylation can in principle take place via two distinct mechanisms. Intermolecular trans autophosphorylation involves dimerization and phosphorylation of the activation loop of one chain in the catalytic pocket of the other chain. On the other hand, intramolecular cis autophosphorylation involves phosphorylation of the activation loop of the kinases in its own catalytic pocket within a monomer. On the basis of the crystal structure of PknB in the front-to-front dimeric form, it is currently believed that activation of PknB involves trans autophosphorylation. However, because of the lack of coordinates of the activation loop in the crystal structures, atomic details of the conformational changes associated with activation are yet to be deciphered. Therefore, to understand the conformational transitions associated with activation via autophosphorylation, a series of explicit solvent molecular dynamics simulations with a duration of 1 µs have been performed on each of the phosphorylated and nonphosphorylated forms of the PknB catalytic domain in monomeric and dimeric states. Simulations on phosphorylated PknB revealed a differential network of crucial electrostatic and hydrophobic residues that stabilize the phosphorylated form in the active conformation. Interestingly, in our simulations on nonphosphorylated monomers, the activation loop was observed to fold into its own active site, thereby opening the novel possibility of activation through intramolecular cis autophosphorylation. Thus, our simulations suggest that autophosphorylation of PknB might also involve cis initiation followed by trans amplification as reported for other eukaryotic kinases based on recent reaction kinetics studies. [ABSTRACT FROM AUTHOR]

Motivation: In silico prediction of site-specific kinase–substrate relationships (ssKSRs) is crucial for deciphering phosphorylation networks by linking kinomes to phosphoproteomes. However, currently available predictors for ssKSRs give rise to a large number of false-positive results because they use only a short sequence stretch around phosphosite as determinants of kinase specificity and do not consider the biological context of kinase–substrate recognition.Results: Based on the analysis of domain-specific kinase–substrate relationships, we have constructed a domain-level phosphorylation network that implicitly incorporates various contextual factors. It reveals preferential phosphorylation of specific domains by certain kinases. These novel correlations have been implemented in PhosNetConstruct, an automated program for predicting target kinases for a substrate protein. PhosNetConstruct distinguishes cognate kinase–substrate pairs from a large number of non-cognate combinations. Benchmarking on independent datasets using various statistical measures demonstrates the superior performance of PhosNetConstruct over ssKSR-based predictors.Availability and implementation: PhosNetConstruct is freely available at http://www.nii.ac.in/phosnetconstruct.html.Contact: deb@nii.res.inSupplementary information: Supplementary data are available at Bioinformatics online. [ABSTRACT FROM PUBLISHER]

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]

Background: Modular polyketide synthases are multifunctional megasynthases which biosynthesize a variety of secondary metabolites using various combinations of dehydratase (DH), ketoreductase (KR) and enoyl-reductase (ER) domains. During the catalysis of various reductive steps these domains act on a substrate moiety which is covalently attached to the phosphopantetheine (P-pant) group of the holo-Acyl Carrier Protein (holo-ACP) domain, thus necessitating the formation of holo-ACP:DH and holo-ACP:KR complexes. Even though three dimensional structures are available for DH, KR and ACP domains, no structures are available for DH or KR domains in complex with ACP or substrate moieties. Since Ser of holo-ACP is covalently attached to a large phosphopantetheine group, obtaining complexes involving holo-ACP by standard protein-protein docking has been a difficult task. Results: We have modeled the holo-ACP:DH and holo-ACP:KR complexes for identifying specific residues on DH and KR domains which are involved in interaction with ACP, phosphopantetheine and substrate moiety. A novel combination of protein-protein and protein-ligand docking has been used to first model complexes involving apo-ACP and then dock the phosphopantetheine and substrate moieties using covalent connectivity between ACP, phosphopantetheine and substrate moiety as constraints. The holo-ACP:DH and holo-ACP:KR complexes obtained from docking have been further refined by restraint free explicit solvent MD simulations to incorporate effects of ligand and receptor flexibilities. The results from 50 ns MD simulations reveal that substrate enters into a deep tunnel in DH domain while in case of KR domain the substrate binds a shallow surface exposed cavity. Interestingly, in case of DH domain the predicted binding site overlapped with the binding site in the inhibitor bound crystal structure of FabZ, the DH domain from E.Coli FAS. In case of KR domain, the substrate binding site identified by our simulations was in proximity of the known stereo-specificity determining residues. Conclusions: We have modeled the holo-ACP:DH and holo-ACP:KR complexes and identified the specific residues on DH and KR domains which are involved in interaction with ACP, phosphopantetheine and substrate moiety. Analysis of the conservation profile of binding pocket residues in homologous sequences of DH and KR domains indicated that, these results can also be extrapolated to reductive domains of other modular PKS clusters. [ABSTRACT FROM AUTHOR]

Motivation:In silico methods are being widely used for identifying substrates for various kinases and deciphering cell signaling networks. However, most of the available phosphorylation site prediction methods use motifs or profiles derived from a known data set of kinase substrates and hence, their applicability is limited to only those kinase families for which experimental substrate data is available. This prompted us to develop a novel multi-scale structure-based approach which does not require training using experimental substrate data. [ABSTRACT FROM PUBLISHER]

Even though several in silico tools are available for prediction of the phosphorylation sites for mammalian, yeast or plant proteins, currently no software is available for predicting phosphosites for Plasmodium proteins. However, the availability of significant amount of phospho-proteomics data during the last decade and advances in machine learning (ML) algorithms have opened up the opportunities for deciphering phosphorylation patterns of plasmodial system and developing ML-based phosphosite prediction tools for Plasmodium. We have developed Pf-Phospho, an ML-based method for prediction of phosphosites by training Random Forest classifiers using a large data set of 12 096 phosphosites of Plasmodium falciparum and Plasmodium bergei. Of the 12 096 known phosphosites, 75% of sites have been used for training/validation of the classifier, while remaining 25% have been used as completely unseen test data for blind testing. It is encouraging to note that Pf-Phospho can predict the kinase-independent phosphosites with 84% sensitivity, 75% specificity and 78% precision. In addition, it can also predict kinase-specific phosphosites for five plasmodial kinases— Pf PKG, Plasmodium falciparum , Pf PKA, Pf PK7 and Pb CDPK4 with high accuracy. Pf-Phospho (http://www.nii.ac.in/pfphospho.html) outperforms other widely used phosphosite prediction tools, which have been trained using mammalian phosphoproteome data. It also has been integrated with other widely used resources such as PlasmoDB, MPMP, Pfam and recently available ML-based predicted structures by AlphaFold2. Currently, Pf-phospho is the only bioinformatics resource available for ML-based prediction of phospho-signaling networks of Plasmodium and is a user-friendly platform for integrative analysis of phospho-signaling along with metabolic and protein–protein interaction networks. [ABSTRACT FROM AUTHOR]

AMPylation is a novel post-translational modification (PTM) involving covalent attachment of an AMP moiety to threonine/tyrosine side chains of a protein. AMPylating enzymes belonging to three different families, namely Fic/Doc, GS-ATase and DrrA have been experimentally characterized. Involvement of these novel enzymes in a myriad of biological processes makes them interesting candidates for genome-wide search. We have used SVM and HMM to develop a computational protocol for identification of AMPylation domains and their classification into various functional subfamilies catalyzing AMPylation, deAMPylation, phosphorylation and phosphocholine transfer. Our analysis has not only identified novel PTM catalyzing enzymes among unannotated proteins, but has also revealed how this novel enzyme family has evolved to generate functional diversity by subtle changes in sequence/structures of the proteins. Phylogenetic analysis of Fic/Doc has revealed three new isofunctional subfamilies, thus adding to their functional divergence. Also, frequent occurrence of Fic/Doc proteins on highly mobile and unstable genomic islands indicated their evolution via extensive horizontal gene transfers. On the other hand phylogenetic analyses indicate lateral evolution of GS-ATase family and an early duplication event responsible for AMPylation and deAMPylation activity of GS-ATase. Our analysis also reveals molecular basis of substrate specificity of DrrA proteins. [ABSTRACT FROM AUTHOR]

Mycobacterium tuberculosis (Mtb) endures a combination of metal scarcity and toxicity throughout the human infection cycle, contributing to complex clinical manifestations. Pathogens counteract this paradoxical dysmetallostasis by producing specialized metal trafficking systems. Capture of extracellular metal by siderophores is a widely accepted mode of iron acquisition, and Mtb iron-chelating siderophores, mycobactin, have been known since 1965. Currently, it is not known whether Mtb produces zinc scavenging molecules. Here, we characterize low-molecular-weight zinc-binding com- pounds secreted and imported by Mtb for zinc acquisition. These molecules, termed kupyaphores, are produced by a 10.8 kbp bio- synthetic cluster and consists of a dipeptide core of ornithine and phenylalaninol, where amino groups are acylated with isonitrile- containing fatty acyl chains. Kupyaphores are stringently regulated and support Mtb survival under both nutritional deprivation and intoxication conditions. A kupyaphore-deficient Mtb strain is unable to mobilize sufficient zinc and shows reduced fitness upon infection. We observed early induction of kupyaphores in Mtb-infected mice lungs after infection, and these metabolites dis- appeared after 2 wk. Furthermore, we identify an Mtb-encoded isonitrile hydratase, which can possibly mediate intracellular zinc release through covalent modification of the isonitrile group of kupyaphores. Mtb clinical strains also produce kupyaphores during early passages. Our study thus uncovers a previously unknown zinc acquisition strategy of Mtb that could modulate host–pathogen interactions and disease outcome. [ABSTRACT FROM AUTHOR]

Background: 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 in silico assignment of substrate preference. Results: 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 http://www.nii.res.in/pred_acs_substr.html has been developed for automated functional classification of ACS enzymes. Conclusions: 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. [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]

Polyketide synthases (PKSs) form a large family of multifunctional proteins involved in the biosynthesis of diverse classes of natural products. Architecturally at least three different types of PKSs have been discovered in the microbial world and recent years have revealed tremendous versatility of PKSs, both in terms of their structural and functional organization and in their ability to produce compounds other than typical secondary metabolites. Mycobacterium tuberculosis exploits polyketide biosynthetic enzymes to synthesize complex lipids, many of which are essential for its survival. The functional significance of the large repertoire of PKSs in Dictyostelium discoideum, perhaps in producing developmental regulating factors, is emerging. Recently determined structures of fatty acid synthases (FASs) and PKSs now provide an opportunity to delineate the mechanistic and structural basis of polyketide biosynthetic machinery. [Copyright &y& Elsevier]

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 α-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 smallchain precursors. The specificity of PKS18 and PKS11 proteins toward long-chain aliphatic acyl-coenzyme A (C[sub 12] to C[sub 20]) 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 β-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 CHSlike proteins. [ABSTRACT FROM AUTHOR]

Modular polyketide synthases (PKSs) are large multi-enzymatic, multi-domain megasynthases, which are involved in the biosynthesis of a class of pharmaceutically important natural products, namely polyketides. These enzymes harbor a set of repetitive active sites termed modules and the domains present in each module dictate the chemical moiety that would add to a growing polyketide chain. This modular logic of biosynthesis has been exploited with reasonable success to produce several novel compounds by genetic manipulation. However, for harnessing their vast potential of combinatorial biosynthesis, it is essential to develop knowledge based in silico approaches for correlating the sequence and domain organization of PKSs to their polyketide products. In this work, we have carried out extensive sequence analysis of experimentally characterized PKS clusters to develop an automated computational protocol for unambiguous identification of various PKS domains in a polypeptide sequence. A structure based approach has been used to identify the putative active site residues of acyltransferase (AT) domains, which control the specificities for various starter and extender units during polyketide biosynthesis. On the basis of the analysis of the active site residues and molecular modelling of substrates in the active site of representative AT domains, we have identified a crucial residue that is likely to play a major role in discriminating between malonate and methylmalonate during selection of extender groups by this domain. Structural modelling has also explained the experimentally observed chiral preference of AT domain in substrate selection. This computational protocol has been used to predict the domain organization and substrate specificity for PKS clusters from various microbial genomes. The results of our analysis as well as the computational tools for prediction of domain organization and substrate specificity have been organized in the form of a searchable computerized database (PKSDB). PKSDB would serve as a valuable tool for identification of polyketide products biosynthesized by uncharacterized PKS clusters. This database can also provide guidelines for rational design of experiments to engineer novel polyketides††http://www.nii.res.in/pksdb.html. [Copyright &y& Elsevier]

Background: Antibody, the primary effector molecule of the immune system, evolves after initial encounter with the antigen from a precursor form to a mature one to effectively deal with the antigen. Antibodies of a lineage diverge through antigen-directed isolated pathways of maturation to exhibit distinct recognition potential. In the context of evolution in immune recognition, diversity of antigen cannot be ignored. While there are reports on antibody lineage, structural perspective with respect to diverse recognition potential in a lineage has never been studied. Hence, it is crucial to evaluate how maturation leads to topological tailoring within a lineage enabling them to interact with significantly distinct antigens. Results: A data-driven approach was undertaken for the study. Global experimental mouse and human antibody-antigen complex structures from PDB were compiled into a coherent database of germline-linked antibodies bound with distinct antigens. Structural analysis of all lineages showed variations in CDRs of both H and L chains. Observations of conformational adaptation made from analysis of static structures were further evaluated by characterizing dynamics of interaction in two lineages, mouse VH1–84 and human VH5–51. Sequence and structure analysis of the lineages explained that somatic mutations altered the geometries of individual antibodies with common structural constraints in some CDRs. Additionally, conformational landscape obtained from molecular dynamics simulations revealed that incoming pathogen led to further conformational divergence in the paratope (as observed across datasets) even while maintaining similar overall backbone topology. MM-GB/SA analysis showed binding energies to be in physiological range. Results of the study are coherent with experimental observations. Conclusions: The findings of this study highlight basic structural principles shaping the molecular evolution of a lineage for significantly diverse antigens. Antibodies of a lineage follow different developmental pathways while preserving the imprint of the germline. From the study, it can be generalized that structural diversification of the paratope is an outcome of natural selection of a conformation from an available ensemble, which is further optimized for antigen interaction. The study establishes that starting from a common lineage, antibodies can mature to recognize a wide range of antigens. This hypothesis can be further tested and validated experimentally. [ABSTRACT FROM AUTHOR]

Glycopeptidolipids (GPLs) are dominant cell surface molecules present in several non-tuberculous and opportunistic mycobacterial species. GPLs from Mycobacterium smegmatis are composed of a lipopeptide core unit consisting of a modified C26-C34 fatty acyl chain that is linked to a tetrapeptide (Phe- Thr-Ala-alaninol). The hydroxyl groups of threonine and terminal alaninol are further modified by glycosylations. Although chemical structures have been reported for 16 GPLs from diverse mycobacteria, there is still ambiguity in identifying the exact position of the hydroxyl group on the fatty acyl chain. Moreover, the enzymes involved in the biosynthesis of the fatty acyl component are unknown. In this study we show that a bimodular polyketide synthase in conjunction with a fatty acyl- AMP ligase dictates the synthesis of fatty acyl chain of GPL. Based on genetic, biochemical, and structural investigations, we determine that the hydroxyl group is present at the C-5 position of the fatty acyl component. Our retrobiosynthetic approach has provided a means to understand the biosynthesis of GPLs and also resolve the long-standing debate on the accurate structure of mycobacterial GPLs. [ABSTRACT FROM AUTHOR]

Calcium-dependent protein kinases (CDPKs) are major effectors of calcium signaling in apicomplexan parasites like Toxoplasma and Plasmodium and control important processes of the parasite life cycle. Despite recently reported crystal structures of Toxoplasma gondii (Tg)CDPKs, several important questions about their regulation remain unanswered. Plasmodiumfalciparum (Pf)CDPK1 has emerged as a key player in the life cycle of the malaria parasite, as it may be involved in the invasion of the host cells. Molecular modeling and site-directed mutagenesis studies on PfCDPK1 suggested that several residues in the regula- tory domain play a dual role, as they seem to contribute to the stabilization of both the active and inactive kinase. Mass spectrometry revealed that PfCDPK1 was autophosphorylated at several sites; some of these were placed at strategic locations and therefore were found to be critical for kinase activation. The N-terminal extension of PfCDPK1 was found to be important for Pfl:DPK1 activation. Unexpectedly, an ATP binding site in the NTE of PfCDPK1 was identified. Our studies highlight several novel features of Pfl2DPK1 regulation, which may be shared by other members of the CDPK family. These findings may also aid design of inhibitors against these important targets, which are absent from the host. [ABSTRACT FROM AUTHOR]

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 D84 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. [ABSTRACT FROM AUTHOR]

Polyketide synthases (PKSs) are multi-functional enzymes that exhibit a great deal of diversity in their biosynthetic mechanism. This versatility allows them to influence an organism's biology in varied ways. Although many polyketides have been identified till now, and their biosynthetic pathways characterized, many more are waiting to be uncovered. With genome sequences of many organisms available now, the repository of putative pks genes is growing and so is the complexity involved in determining their possible products and functional roles in nature. Needless to say, efforts at the identification of novel products and pathways require a systematic, multi-pronged approach. In this review we discuss the growth of the PKS field and how it has undergone a pronounced transformation. We examine the various ways by which nature introduces variations in the products formed by these enzymes in different organisms to suit their biology. We further examine the different tools employed to crack the 'PKS puzzle' and how the future looks for research in this field. [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]

The recent discovery of fatty acyl-AMP ligases (FAALs) in Mycobacterium tuberculosis (Mtb) provided a new perspective of fatty acid activation. These proteins convert fatty acids to the corresponding adenylates, which are intermediates of acyl-CoA–synthesizing fatty acyl-CoA ligases (FACLs). Presently, it is not evident how obligate pathogens such as Mtb have evolved such new themes of functional versatility and whether the activation of fatty acids to acyladenylates could indeed be a general mechanism. Here, based on elucidation of the first structure of an FAAL protein and by generating loss-of-function and gain-of-function mutants that interconvert FAAL and FACL activities, we demonstrate that an insertion motif dictates formation of acyladenylate. Because FAALs in Mtb are crucial nodes in the biosynthetic network of virulent lipids, inhibitors directed against these proteins provide a unique multipronged approach to simultaneously disrupting several pathways. [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]

Dictyostelium discoideum exhibits the largest repository of polyketide synthase (PKS) proteins of all known genomes. How- ever, 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 inter- acting acyl carrier protein domain modulates the catalytic activity to produce the alkyl resorcinol scaffold of MPBD. Further- more, 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 per- formed 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. [ABSTRACT FROM AUTHOR]

Mycobactins are a family of membrane-associated siderophores required for Mycobacterium tuberculosis to adapt to its intracellular habitat. These lipophilic siderophores have been recently shown to directly acquire intracellular iron through lipid trafficking. Despite tremendous progress in understanding the assembly- line enzymology of the siderophore biosynthesis, the genes as well as the mechanistic and biochemical principles involved in producing membrane-associated siderophores have not been investigated. Here, we report a biosynthetic locus that incorporates variety of aliphatic chains on the mycobactin skeleton. Cell-free reconstitution studies demonstrate that these acyl chains are directly transferred from a carrier protein on to the ϵ-amino group of lysine residue by an unidentified Rv1347c gene product. The unsaturation in the lipidic chain is produced by a novel acyl-acyl carrier protein dehydrogenase, which, in contrast to the conventional acyl-CoA dehydrogenases, is involved in the biosynthetic pathway. MbtG protein then performs the final N6-hydroxylation step. Genome-wide analysis revealed homologues of N-acyl transferase and MbtG in other pathogenic bacteria. Because iron plays a key role in the development of infectious diseases, the biosynthetic pathway described here represents an attractive target for developing new antibacterial agents. [ABSTRACT FROM AUTHOR]

Summary: Mycobacterium tuberculosis cell envelope is a treasure house of biologically active lipids of fascinating molecular architecture. Although genetic studies have alluded to an array of genes in biosynthesis of complex lipids, their mechanistic, structural, and biochemical principles have not been investigated. Here, we have dissected the molecular logic underlying the biosynthesis of a virulence lipid phthiocerol dimycocerosate (PDIM). Cell-free reconstitution studies demonstrate that polyketide synthases, which are usually involved in the biosynthesis of secondary metabolites, are responsible for generating complex lipids in mycobacteria. We show that PapA5 protein directly transfers the protein bound mycocerosic acid analogs on phthiocerol to catalyze the final esterification step. Based on precise identification of biological functions of proteins from Pps cluster, we have rationally produced a nonmethylated variant of mycocerosate esters. Apart from elucidating mechanisms that generate chemical heterogeneity with PDIMs, this study also presents an attractive approach to explore host-pathogen interactions by altering mycobacterial surface coat. [Copyright &y& Elsevier]

The metabolic repertoire in nature is augmented by generating hybrid metabolites from a limited set of gene products. In mycobacteria, several unique complex lipids are produced by the combined action of fatty acid synthases and polyketide synthases (PKSs), although it is not clear how the covalently sequestered biosynthetic intermediates are transferred from one enzymatic complex to another. Here we show that some of the 36 annotated fadD genes, located adjacent to the PKS genes in the Mycobacterium tuberculosis genome, constitute a new class of long-chain fatty acyl-AMP ligases (FAALs). These proteins activate long-chain fatty acids as acyl-adenylates, which are then transferred to the multifunctional PKSs for further chain extension. This mode of activation and transfer of fatty acids is contrary to the previously described universal mechanism involving the formation of acyl-coenzyme A thioesters. Similar mechanisms may operate in the biosynthesis of other lipid-containing metabolites and could have implications in engineering novel hybrid products. [ABSTRACT FROM AUTHOR]

[Display omitted] • Completely automated prediction of crosslinked chemical structure of RiPPs using genomic sequences of RiPP BGCs. • ML approach for identifying precursor from multiple small ORFs in a RiPP BGC & predicting cleavage and cross-links. • Identification of uncrosslinked modified residues in lanthipeptides and enhancement of prediction accuracy. RiPPMiner-Genome is a unique bioinformatics resource for identifying Biosynthetic Gene Clusters (BGC) for RiPPs (Ribosomally Synthesized and Post-translationally Modified Peptides) and automated prediction of crosslinked chemical structures of RiPPs starting from genomic sequences. It is a major update of the RiPPMiner webserver, which used only peptide sequence of RiPP precursors as input for predicting RiPP class and crosslinked chemical structures. Other major improvements are, machine learning (ML) based identification of correct RiPP precursor peptide from among multiple small ORFs (Open Reading Frames) in a BGC, prediction of the cleavage site and cross-links in thiopeptides and identification of non-crosslinked modified residues in lanthipeptides. It has been benchmarked on a dataset of 204 experimentally characterized RiPP BGCs. RiPPMiner-Genome also facilitates visualization of the RiPP BGCs and depiction of the chemical structure of crosslinked RiPP. It also has an interface for searching characterized RiPPs, similar to the predicted core peptide sequence or crosslinked chemical structure. [ABSTRACT FROM AUTHOR]

This article focuses on the precursors of polyketide biosynthesis. The study of bioactive natural products has undergone rapid advancement with the cloning and sequencing of large numbers of gene clusters. Polyketide synthases utilize acyl-coenzyme A (CoA) precursors and synthesize polyketides by repetitive decarboxylative condensations. The potential of these proteins to produce varied CoA precursors and their utilization in polyketide biosynthesis have not been investigated. Acyl-activating enzymes proteins provide an attractive route to expand the precursors available for polyketide biosynthesis.

Presents a correction to the article "Enzymatic activation and transfer of fatty acids and acyl-adenylates in mycobacteria," published in a 2004 issue of "Nature".

Presents a correction to the article "Enzymic Activation and Transfer of Fatty Acids as Acyl-Adenylates in Mycobacteria," that was previously published in the periodical "Nature."