Docking domain-mediated subunit interactions in natural product megasynth(et)ases.
Ontology highlight
ABSTRACT:
SUBMITTER: Smith HG
PROVIDER: S-EPMC9113145 | biostudies-literature | 2021 Jun
REPOSITORIES: biostudies-literature
Publications
Docking domain-mediated subunit interactions in natural product megasynth(et)ases.
Smith Helen G HG Beech Matthew J MJ Lewandowski Józef R JR Challis Gregory L GL Jenner Matthew M
Journal of industrial microbiology & biotechnology 20210601 3-4
Polyketide synthase (PKS) and non-ribosomal peptide synthetase (NRPS) multienzymes produce numerous high value metabolites. The protein subunits which constitute these megasynth(et)ases must undergo ordered self-assembly to ensure correct organisation of catalytic domains for the biosynthesis of a given natural product. Short amino acid regions at the N- and C-termini of each subunit, termed docking domains (DDs), often occur in complementary pairs, which interact to facilitate substrate transfe ...[more]
Similar Datasets
Project description:BackgroundFungi are prolific producers of secondary metabolites (SMs), which are bioactive small molecules with important applications in medicine, agriculture and other industries. The backbones of a large proportion of fungal SMs are generated through the action of large, multi-domain megasynth(et)ases such as polyketide synthases (PKSs) and nonribosomal peptide synthetases (NRPSs). The structure of these backbones is determined by the domain architecture of the corresponding megasynth(et)ase, and thus accurate annotation and classification of these architectures is an important step in linking SMs to their biosynthetic origins in the genome.ResultsHere we report synthaser, a Python package leveraging the NCBI's conserved domain search tool for remote prediction and classification of fungal megasynth(et)ase domain architectures. Synthaser is capable of batch sequence analysis, and produces rich textual output and interactive visualisations which allow for quick assessment of the megasynth(et)ase diversity of a fungal genome. Synthaser uses a hierarchical rule-based classification system, which can be extensively customised by the user through a web application ( http://gamcil.github.io/synthaser ). We show that synthaser provides more accurate domain architecture predictions than comparable tools which rely on curated profile hidden Markov model (pHMM)-based approaches; the utilisation of the NCBI conserved domain database also allows for significantly greater flexibility compared to pHMM approaches. In addition, we demonstrate how synthaser can be applied to large scale genome mining pipelines through the construction of an Aspergillus PKS similarity network.ConclusionsSynthaser is an easy to use tool that represents a significant upgrade to previous domain architecture analysis tools. It is freely available under a MIT license from PyPI ( https://pypi.org/project/synthaser ) and GitHub ( https://github.com/gamcil/synthaser ).
| S-EPMC8582187 | biostudies-literature
Project description:Several peptides in clinical use are derived from non-ribosomal peptide synthetases (NRPS). In these systems multiple NRPS subunits interact with each other in a specific linear order mediated by specific docking domains (DDs), whose structures are not known yet, to synthesize well-defined peptide products. In contrast to classical NRPSs, single-module NRPS subunits responsible for the generation of rhabdopeptide/xenortide-like peptides (RXPs) can act in different order depending on subunit stoichiometry thereby producing peptide libraries. To define the basis for their unusual interaction patterns, we determine the structures of all N-terminal DDs (NDDs) as well as of an NDD-CDD complex and characterize all putative DD interactions thermodynamically for such a system. Key amino acid residues for DD interactions are identified that upon their exchange change the DD affinity and result in predictable changes in peptide production. Recognition rules for DD interactions are identified that also operate in other megasynthase complexes.
| S-EPMC6195595 | biostudies-literature
Project description:Modular type I polyketide synthases (PKSs) are versatile biosynthetic systems that initiate, successively elongate, and modify acyl chains. Intermediate transfer between modules is mediated via docking domains, which are attractive targets for PKS pathway engineering to produce natural product analogs. We identified a class 2 docking domain in cyanobacterial PKSs and determined crystal structures for two docking domain pairs, revealing a distinct class 2 docking strategy for promoting intermediate transfer. The selectivity of class 2 docking interactions, demonstrated in binding and biochemical assays, could be altered by mutagenesis. We determined the ideal fusion location for exchanging class 1 and class 2 docking domains and demonstrated effective polyketide chain transfer in heterologous modules. Thus, class 2 docking domains are tools for rational bioengineering of a broad range of PKSs containing either class 1 or 2 docking domains.
| S-EPMC3870462 | biostudies-literature
Project description:Ribosomally synthesized and post-translationally modified peptides (RiPPs) are a rapidly growing class of natural products. RiPP precursor peptides can undergo extensive enzymatic tailoring to yield structurally and functionally diverse products, and their biosynthetic logic makes them attractive bioengineering targets. Recent work suggests that unrelated RiPP-modifying enzymes contain structurally similar precursor peptide-binding domains. Using profile hidden Markov model comparisons, we discovered related and previously unrecognized peptide-binding domains in proteins spanning the majority of known prokaryotic RiPP classes, and we named this conserved domain the RiPP precursor peptide recognition element (RRE). Through binding studies we verified RRE's roles for three distinct RiPP classes: linear azole-containing peptides, thiopeptides and lasso peptides. Because numerous RiPP biosynthetic enzymes act on peptide substrates, our findings have powerful predictive value as to which protein(s) drive substrate binding, thereby laying a foundation for further characterization of RiPP biosynthetic pathways and the rational engineering of new peptide-binding activities.
| S-EPMC4509860 | biostudies-literature
Project description:BackgroundPharmacokinetic natural product-drug interactions (NPDIs) occur when botanical or other natural products are co-consumed with pharmaceutical drugs. With the growing use of natural products, the risk for potential NPDIs and consequent adverse events has increased. Understanding mechanisms of NPDIs is key to preventing or minimizing adverse events. Although biomedical knowledge graphs (KGs) have been widely used for drug-drug interaction applications, computational investigation of NPDIs is novel. We constructed NP-KG as a first step toward computational discovery of plausible mechanistic explanations for pharmacokinetic NPDIs that can be used to guide scientific research.MethodsWe developed a large-scale, heterogeneous KG with biomedical ontologies, linked data, and full texts of the scientific literature. To construct the KG, biomedical ontologies and drug databases were integrated with the Phenotype Knowledge Translator framework. The semantic relation extraction systems, SemRep and Integrated Network and Dynamic Reasoning Assembler, were used to extract semantic predications (subject-relation-object triples) from full texts of the scientific literature related to the exemplar natural products green tea and kratom. A literature-based graph constructed from the predications was integrated into the ontology-grounded KG to create NP-KG. NP-KG was evaluated with case studies of pharmacokinetic green tea- and kratom-drug interactions through KG path searches and meta-path discovery to determine congruent and contradictory information in NP-KG compared to ground truth data. We also conducted an error analysis to identify knowledge gaps and incorrect predications in the KG.ResultsThe fully integrated NP-KG consisted of 745,512 nodes and 7,249,576 edges. Evaluation of NP-KG resulted in congruent (38.98% for green tea, 50% for kratom), contradictory (15.25% for green tea, 21.43% for kratom), and both congruent and contradictory (15.25% for green tea, 21.43% for kratom) information compared to ground truth data. Potential pharmacokinetic mechanisms for several purported NPDIs, including the green tea-raloxifene, green tea-nadolol, kratom-midazolam, kratom-quetiapine, and kratom-venlafaxine interactions were congruent with the published literature.ConclusionNP-KG is the first KG to integrate biomedical ontologies with full texts of the scientific literature focused on natural products. We demonstrate the application of NP-KG to identify known pharmacokinetic interactions between natural products and pharmaceutical drugs mediated by drug metabolizing enzymes and transporters. Future work will incorporate context, contradiction analysis, and embedding-based methods to enrich NP-KG. NP-KG is publicly available at https://doi.org/10.5281/zenodo.6814507. The code for relation extraction, KG construction, and hypothesis generation is available at https://github.com/sanyabt/np-kg.
| S-EPMC10150409 | biostudies-literature
Project description:The biological processes related to protein homeostasis in Mycobacterium tuberculosis, the etiologic agent of tuberculosis, have recently been established as critical pathways for therapeutic intervention. Proteins of particular interest are ClpC1 and the ClpC1-ClpP1-ClpP2 proteasome complex. The structure of the potent antituberculosis macrocyclic depsipeptide ecumicin complexed with the N-terminal domain of ClpC1 (ClpC1-NTD) is presented here. Crystals of the ClpC1-NTD-ecumicin complex were monoclinic (unit-cell parameters a = 80.0, b = 130.0, c = 112.0 Å, β = 90.07°; space group P21; 12 complexes per asymmetric unit) and diffracted to 2.5 Å resolution. The structure was solved by molecular replacement using the self-rotation function to resolve space-group ambiguities. The new structure of the ecumicin complex showed a unique 1:2 (target:ligand) stoichiometry exploiting the intramolecular dyad in the α-helical fold of the target N-terminal domain. The structure of the ecumicin complex unveiled extensive interactions in the uniquely extended N-terminus, a critical binding site for the known cyclopeptide complexes. This structure, in comparison with the previously reported rufomycin I complex, revealed unique features that could be relevant for understanding the mechanism of action of these potential antituberculosis drug leads. Comparison of the ecumicin complex and the ClpC1-NTD-L92S/L96P double-mutant structure with the available structures of rufomycin I and cyclomarin A complexes revealed a range of conformational changes available to this small N-terminal helical domain and the minor helical alterations involved in the antibiotic-resistance mechanism. The different modes of binding and structural alterations could be related to distinct modes of action.
| S-EPMC7193532 | biostudies-literature
Project description:Background/Objectives: Pteridine reductase 1 (PTR1) has been one of the prime targets for discovering novel antileishmanial therapeutics in the fight against Leishmaniasis. This enzyme catalyzes the NADPH-dependent reduction of pterins to their tetrahydro forms. While chemotherapy remains the primary treatment, its effectiveness is constrained by drug resistance, unfavorable side effects, and substantial associated costs. Methods: This study addresses the urgent need for novel, cost-effective drugs by employing in silico techniques to identify potential lead compounds targeting the PTR1 enzyme. A library of 1463 natural compounds from AfroDb and NANPDB, prefiltered based on Lipinski's rules, was used to screen against the LmPTR1 target. The X-ray structure of LmPTR1 complexed with NADP and dihydrobiopterin (Protein Data Bank ID: 1E92) was identified to contain the critical residues Arg17, Leu18, Ser111, Phe113, Pro224, Gly225, Ser227, Leu229, and Val230 including the triad of residues Asp181-Tyr194-Lys198, which are critical for the catalytic process involving the reduction of dihydrofolate to tetrahydrofolate. Results: The docking yielded 155 compounds meeting the stringent criteria of -8.9 kcal/mol instead of the widely used -7.0 kcal/mol. These compounds demonstrated binding affinities comparable to the known inhibitors; methotrexate (-9.5 kcal/mol), jatrorrhizine (-9.0 kcal/mol), pyrimethamine (-7.3 kcal/mol), hardwickiic acid (-8.1 kcal/mol), and columbamine (-8.6 kcal/mol). Protein-ligand interactions and molecular dynamics (MD) simulation revealed favorable hydrophobic and hydrogen bonding with critical residues, such as Lys198, Arg17, Ser111, Tyr194, Asp181, and Gly225. Crucial to the drug development, the compounds were physiochemically and pharmacologically profiled, narrowing the selection to eight compounds, excluding those with potential toxicities. The five selected compounds ZINC000095486253, ZINC000095486221, ZINC000095486249, 8alpha-hydroxy-13-epi-pimar-16-en-6,18-olide, and pachycladin D were predicted to be antiprotozoal (Leishmania) with Pa values of 0.642, 0.297, 0.543, 0.431, and 0.350, respectively. Conclusions: This study identified five lead compounds that showed substantial binding affinity against LmPTR1 as well as critical residue interactions. A 100 ns MD combined with molecular mechanics Poisson-Boltzmann surface area (MM/PBSA) calculations confirmed the robust binding interactions and provided insights into the dynamics and stability of the protein-ligand complexes.
| S-EPMC11768234 | biostudies-literature
Project description:Triptolide (1) is a structurally unique diterpene triepoxide isolated from a traditional Chinese medicinal plant with anti-inflammatory, immunosuppressive, contraceptive and antitumor activities. Its molecular mechanism of action, however, has remained largely elusive to date. We report that triptolide covalently binds to human XPB (also known as ERCC3), a subunit of the transcription factor TFIIH, and inhibits its DNA-dependent ATPase activity, which leads to the inhibition of RNA polymerase II-mediated transcription and likely nucleotide excision repair. The identification of XPB as the target of triptolide accounts for the majority of the known biological activities of triptolide. These findings also suggest that triptolide can serve as a new molecular probe for studying transcription and, potentially, as a new type of anticancer agent through inhibition of the ATPase activity of XPB.
| S-EPMC3622543 | biostudies-literature
Project description:Ikarugamycin (IKA) is a previously discovered antibiotic, which has been shown to inhibit the uptake of oxidized low-density lipoproteins in macrophages. Furthermore, several groups have previously used IKA to inhibit clathrin-mediated endocytosis (CME) in plant cell lines. However, detailed characterization of IKA has yet to be performed. Consequently, we performed biochemistry and microscopy experiments to further characterize the effects of IKA on CME. We show that IKA has an IC50 of 2.7 μm in H1299 cells and acutely inhibits CME, but not other endocytic pathways, in a panel of cell lines. Although long-term incubation with IKA has cytotoxic effects, the short-term inhibitory effects on CME are reversible. Thus, IKA can be a useful tool for probing routes of endocytic trafficking.
| S-EPMC5260662 | biostudies-literature
Project description:The botanical natural product goldenseal can precipitate clinical drug interactions by inhibiting cytochrome P450 (CYP) 3A and CYP2D6. Besides P-glycoprotein, effects of goldenseal on other clinically relevant transporters remain unknown. Established transporter-expressing cell systems were used to determine the inhibitory effects of a goldenseal extract, standardized to the major alkaloid berberine, on transporter activity. Using recommended basic models, the extract was predicted to inhibit the efflux transporter BCRP and uptake transporters OATP1B1/3. Using a cocktail approach, effects of the goldenseal product on BCRP, OATP1B1/3, OATs, OCTs, MATEs, and CYP3A were next evaluated in 16 healthy volunteers. As expected, goldenseal increased the area under the plasma concentration-time curve (AUC0-inf ) of midazolam (CYP3A; positive control), with a geometric mean ratio (GMR) (90% confidence interval (CI)) of 1.43 (1.35-1.53). However, goldenseal had no effects on the pharmacokinetics of rosuvastatin (BCRP and OATP1B1/3) and furosemide (OAT1/3); decreased metformin (OCT1/2, MATE1/2-K) AUC0-inf (GMR, 0.77 (0.71-0.83)); and had no effect on metformin half-life and renal clearance. Results indicated that goldenseal altered intestinal permeability, transport, and/or other processes involved in metformin absorption, which may have unfavorable effects on glucose control. Inconsistencies between model predictions and pharmacokinetic outcomes prompt further refinement of current basic models to include differential transporter expression in relevant organs and intestinal degradation/metabolism of the precipitant(s). Such refinement should improve in vitro-in vivo prediction accuracy, contributing to a standard approach for studying transporter-mediated natural product-drug interactions.
| S-EPMC8058163 | biostudies-literature