How different are marine microbial natural products compared to their terrestrial counterparts
TL;DR: In this paper, a cluster analysis of chemical fingerprints and molecular scaffold analysis of 55 817 compounds reported from marine and terrestrial microorganisms, and marine macro-organisms showed that 76.7% of the compounds isolated from marine microorganisms are closely related to compounds extracted from terrestrial micro organisms.
About: This article is published in Natural Product Reports.The article was published on 2021-10-15. It has received 27 citations till now. The article focuses on the topics: Microorganism & Marine bacteriophage.
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TL;DR: A review of the literature published in 2020 for marine natural products (MNPs), with 757 citations (747 for the period January to December 2020) referring to compounds isolated from marine microorganisms and phytoplankton, green, brown and red algae, sponges, cnidarians, bryozoans, molluscs, tunicates, echinoderms, mangroves and other intertidal plants and microorganisms as discussed by the authors .
45 citations
TL;DR: It is shown that the genus Streptomyces is still the largest current producer of new and innovative secondary metabolites, with a significantly high number of novel StrePTomyces spp.
Abstract: There is a real consensus that new antibiotics are urgently needed and are the best chance for combating antibiotic resistance. The phylum Actinobacteria is one of the main producers of new antibiotics, with a recent paradigm shift whereby rare actinomycetes have been increasingly targeted as a source of new secondary metabolites for the discovery of new antibiotics. However, this review shows that the genus Streptomyces is still the largest current producer of new and innovative secondary metabolites. Between January 2015 and December 2020, a significantly high number of novel Streptomyces spp. have been isolated from different environments, including extreme environments, symbionts, terrestrial soils, sediments and also from marine environments, mainly from marine invertebrates and marine sediments. This review highlights 135 new species of Streptomyces during this 6-year period with 108 new species of Streptomyces from the terrestrial environment and 27 new species from marine sources. A brief summary of the different pre-treatment methods used for the successful isolation of some of the new species of Streptomyces is also discussed, as well as the biological activities of the isolated secondary metabolites. A total of 279 new secondary metabolites have been recorded from 121 species of Streptomyces which exhibit diverse biological activity. The greatest number of new secondary metabolites originated from the terrestrial-sourced Streptomyces spp.
26 citations
TL;DR: In this paper, the authors discuss how metabolic engineering now raises reasonable expectations for the implementation of microbial cell factories, which may provide a sustainable approach for MNP-based drug supply in the near future.
24 citations
TL;DR: The authors summarizes more than 200 cases of misassigned marine natural products reported between July 2010 and August 2021, sorting out errors according to the structural elements, emphasizing the role of total synthesis, crystallography, as well as chemical and biosynthetic logic to complement spectroscopic data.
22 citations
TL;DR: This review aims to summarize the recent knowledge on the isolation, diversity, distribution and discovery of natural compounds from marine actinomycetes associated with hard corals and examines a total of 13 new compounds reported from 2017 to 2022 with antibacterial, antifungal and cytotoxic activities.
Abstract: Microbial secondary metabolites are an important source of antibiotics currently available for combating drug-resistant pathogens. These important secondary metabolites are produced by various microorganisms, including Actinobacteria. Actinobacteria have a colossal genome with a wide array of genes that code for several bioactive metabolites and enzymes. Numerous studies have reported the isolation and screening of millions of strains of actinomycetes from various habitats for specialized metabolites worldwide. Looking at the extent of the importance of actinomycetes in various fields, corals are highlighted as a potential hotspot for untapped secondary metabolites and new bioactive metabolites. Unfortunately, knowledge about the diversity, distribution and biochemistry of marine actinomycetes compared to hard corals is limited. In this review, we aim to summarize the recent knowledge on the isolation, diversity, distribution and discovery of natural compounds from marine actinomycetes associated with hard corals. A total of 11 new species of actinomycetes, representing nine different families of actinomycetes, were recovered from hard corals during the period from 2007 to 2022. In addition, this study examined a total of 13 new compounds produced by five genera of actinomycetes reported from 2017 to 2022 with antibacterial, antifungal and cytotoxic activities. Coral-derived actinomycetes have different mechanisms of action against their competitors.
13 citations
References
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TL;DR: It is found that intraflagellar transport 20 mediates the ability of Ror2 signaling to induce the invasiveness of tumors that lack primary cilia, and IFT20 regulates the nucleation of Golgi-derived microtubules by affecting the GM130-AKAP450 complex.
Abstract: Signaling through the Ror2 receptor tyrosine kinase promotes invadopodia formation for tumor invasion. Here, we identify intraflagellar transport 20 (IFT20) as a new target of this signaling in tumors that lack primary cilia, and find that IFT20 mediates the ability of Ror2 signaling to induce the invasiveness of these tumors. We also find that IFT20 regulates the nucleation of Golgi-derived microtubules by affecting the GM130-AKAP450 complex, which promotes Golgi ribbon formation in achieving polarized secretion for cell migration and invasion. Furthermore, IFT20 promotes the efficiency of transport through the Golgi complex. These findings shed new insights into how Ror2 signaling promotes tumor invasiveness, and also advance the understanding of how Golgi structure and transport can be regulated.
13,354 citations
TL;DR: This work uses shape description methods to analyze a database of commercially available drugs and prepares a list of common drug shapes, finding that the diversity of shapes in the set of known drugs is extremely low.
Abstract: In order to better understand the common features present in drug molecules, we use shape description methods to analyze a database of commercially available drugs and prepare a list of common drug shapes. A useful way of organizing this structural data is to group the atoms of each drug molecule into ring, linker, framework, and side chain atoms. On the basis of the two-dimensional molecular structures (without regard to atom type, hybridization, and bond order), there are 1179 different frameworks among the 5120 compounds analyzed. However, the shapes of half of the drugs in the database are described by the 32 most frequently occurring frameworks. This suggests that the diversity of shapes in the set of known drugs is extremely low. In our second method of analysis, in which atom type, hybridization, and bond order are considered, more diversity is seen; there are 2506 different frameworks among the 5120 compounds in the database, and the most frequently occurring 42 frameworks account for only one-fou...
1,670 citations
TL;DR: An unsupervised, 2-dimensional scaling algorithm is presented, which employs vector-based or nonvector-based descriptors to visualize the chemical or pharmacophore space of even large data sets, and DataWarrior uses this method to interactively explore chemical space, activity landscapes, and activity cliffs.
Abstract: Drug discovery projects in the pharmaceutical industry accumulate thousands of chemical structures and ten-thousands of data points from a dozen or more biological and pharmacological assays. A sufficient interpretation of the data requires understanding, which molecular families are present, which structural motifs correlate with measured properties, and which tiny structural changes cause large property changes. Data visualization and analysis software with sufficient chemical intelligence to support chemists in this task is rare. In an attempt to contribute to filling the gap, we released our in-house developed chemistry aware data analysis program DataWarrior for free public use. This paper gives an overview of DataWarrior’s functionality and architecture. Exemplarily, a new unsupervised, 2-dimensional scaling algorithm is presented, which employs vector-based or nonvector-based descriptors to visualize the chemical or pharmacophore space of even large data sets. DataWarrior uses this method to intera...
919 citations
Book•
28 Mar 2005
TL;DR: This work has shown that knowing Inhibitor Modality is important for Structure-Based Lead Organization and Associating Cellular Effects with Target Enzyme Inhibition should Require a Certain Affinity for the target Enzyme.
Abstract: Foreword. Preface. Acknowledgments. 1. Why Enzymes as Drug Targets? 1.1 Enzymes Are Essentials for Life. 1.2 Enzyme Structure and Catalysis. 1.3 Permutations of Enzyme Structure During Catalysis. 1.4 Other Reasons for Studying Enzymes. 1.5 Summary. References. 2. Enzyme Reaction Mechanisms. 2.1 Initial Binding of Substrate. 2.2 Noncovalent Forces in Reversible Ligand Binding to Enzymes. 2.2.1 Electrostatic Forces. 2.2.2 Hydrogen Bonds. 2.2.3 Hydrophobic Forces. 2.2.4 van der Waals Forces. 2.3 Transformations of the Bond Substrate. 2.3.1 Strategies for Transition State Stabilization. 2.3.2 Enzyme Active Sites Are Most Complementary to the Transition State Structure. 2.4 Steady State Analysis of Enzyme Kinetics. 2.4.1 Factors Affecting the Steady State Kinetic Constants. 2.5 Graphical Determination of k cat and K M 2.6 Reactions Involving Multiple Substates. 2.6.1 Bisubstrate Reaction Mechanisms. 2.7 Summary. References. 3. Reversible Modes of Inhibitor Interactions with Enzymes. 3.1 Enzyme-Inhibitor Binding Equilibria. 3.2 Competitive Inhibition. 3.3 Noncompetitive Inhibition. 3.3.1 Mutual Exclusively Studies. 3.4 Uncompetitive Inhibition. 3.5 Inhibition Modality in Bisubstrate Reactions. 3.6 Value of Knowing Inhibitor Modality. 3.6.1 Quantitative Comparisons of Inhibitor Affinity. 3.6.2 Relating K i to Binding Energy. 3.6.3 Defining Target Selectivity by K i Values. 3.6.4 Potential Advantages and Disadvantages of Different Inhibition Modalities In Vivo. 3.6.5 Knowing Inhibition Modality Is Important for Structure-Based Lead Organization. 3.7 Summary. References. 4. Assay Considerations for Compound Library Screening. 4.1 Defining Inhibition Signal Robustness, and Hit Criteria. 4.2 Measuring Initial Velocity. 4.2.1 End-Point and Kinetic Readouts. 4.2.2 Effects of Enzyme Concentration. 4.3 Balanced Assay Conditions. 4.3.1 Balancing Conditions for Multisubstrate Reactions. 4.4 Order of Reagent Addition. 4.5 Use of Natural Substrates and Enzymes. 4.6 Coupled Enzyme Assays. 4.7 Hit Validation and Progression. 4.8 Summary. References. 5. Lead Optimization and Structure-Activity Relationships for Reversible Inhibitors. 5.1 Concentration-Response Plots and IC 50 Determination. 5.1.1 The Hill Coefficient. 5.1.2 Graphing and Reporting Concentration-Response Data. 5.2 Testing for Reversibility. 5.3 Determining Reversible Inhibition Modality and Dissociation Constant. 5.4 Comparing Relative Affinity. 5.4.1 Compound Selectivity. 5.5 Associating Cellular Effects with Target Enzyme Inhibition. 5.5.1 Cellular Phenotype Should Be Consistent with Genetic Knockout or Knockdown of the Target Enzyme. 5.5.2 Cellular Activity Should Require a Certain Affinity for the target Enzyme. 5.5.3 Buildup of Substrate and/or Diminution of Product for the Target Enzyme Should Be Observed in Cells. 5.5.4 Cellular Phenotype Should Be Reversed by Cell-Permeable Product or Downstream Metabolites of the Target Enzyme Activity. 5.5.5 Mutation of the Target Enzyme Should Lead to Resistance or Hypersensitivity to Inhibitors. 5.6 Summary. References. 6. Slow Binding Inhibitors. 6.1 Determining k obs : The Rate Constant for Onset of Inhibition. 6.2 Mechanisms of Slow Binding Inhibition. 6.3 Determination of Mechanism and Assessment of True Affinity. 6.3.1 Potential Clinical Advantages of Slow Off-rate Inhibitors. 6.4 Determining Inhibition Modality for Slow Binding Inhibitors. 6.5 SAR for Slow Binding Inhibitors. 6.6 Some Examples of Pharmacologically Interesting Slow Binding Inhibitors. 6.6.1 Examples of Scheme B: Inhibitors of Zinc Peptidases and Proteases. 6.6.2 Example of Scheme C: Inhibition of Dihydrofolate Reductase by Methotresate. 6.6.3 Example of Scheme C: Inhibition of Calcineurin by FKBP-Inhibitor Complexes. 6.6.4 Example of Scheme C When K i << K i : Aspartyl Protease Inhibitors. 6.6.5 Example of Scheme C When k 6 Is Very Small: Selective COX2 Inhibitors. 6.7 Summary. References. 7. Tight Binding Inhibitors. 7.1 Effects of Tight Binding Inhibition Concentration-Response Data. 7.2 The IC 50 Value Depends on K i app and [E] T . 7.3 Morrison's Quadratic Equation for Fiting Concentration-Response Data for Tight Binding Inhibitors. 7.3.1 Optimizing Conditions for K i app Determination Using Morrison's Equation. 7.3.2 Limits on K i app Determinations. 7.3.3 Use of a Cubic Equation When Both Substrate and Inhibitor Are Tight Binding. 7.4 Determining Modality for Tight Binding Enzyme Inhibitors. 7.5 Tight Binding Inhibitors Often Display Slow Binding Behavior. 7.6 Practical Approaches to Overcoming the Tight Binding Limit in Determine K i . 7.7 Enzyme-Reaction Intermediate Analogues as Example of Tight Binding Inhibitors. 7.7.1 Bisubstrate Analogues. 7.7.2 Testing for Transition State Mimicry. 7.8 Potential Clinical Advantages of Tight Binding Inhibitors. 7.9 Determination of [E] T Using Tight Binding Inhibitors. 7.10 Summary. References. 8. Irreversible Enzyme Inactivators. 8.1 Kinetic Evaluation of Irreversible Enzyme Inactivators. 8.2 Affinity Labels. 8.2.1 Quiescent Affinity Labels. 8.2.2 Potential Liabilities of Affinity Labels as Drugs. 8.3 Mechanism-Based Inactivators. 8.3.1 Distinguishing Features of Mechanism-Based Inactivation. 8.3.2 Determination of the Partition Ratio. 8.3.3 Potential Clinical Advantages of Mechanism-Based Inactivators. 8.3.4 Examples of Mechanism-Based Inactivators as Drugs. 8.4 Use of Affinity Labels as Mechanistic Tools. 8.5 Summary. References. Appendix 1. Kinetic of Biochemical Reactions. A1.1 The Law of Mass Action and Reaction Order. A1.2 First-Order Reaction Kinetics. A1.3 Second-Order Reaction Kinetics. A1.4 Pseudo-First-Order Reaction Conditions. A1.5 Approach to Equilibrium: An Example of the Kinetics of Reversible Reactions. References. Appendix 2. Derivation of the Enzyme-Ligand Binding Isotherm Equation. References. Appendix 3. Serial Dilution Schemes. Index.
913 citations
TL;DR: A simple scheme to realize ultracompact rejection ratio tunable notch microwave photonic filter (MPF) based on a silicon photonic crystal (PhC) nanocavity with fixed extinction ratio is proposed and experimentally demonstrated.
Abstract: Driven by the increasing demand on handing microwave signals with compact device, low power consumption, high efficiency and high reliability, it is highly desired to generate, distribute, and process microwave signals using photonic integrated circuits. Silicon photonics offers a promising platform facilitating ultracompact microwave photonic signal processing assisted by silicon nanophotonic devices. In this paper, we propose, theoretically analyze and experimentally demonstrate a simple scheme to realize ultracompact rejection ratio tunable notch microwave photonic filter (MPF) based on a silicon photonic crystal (PhC) nanocavity with fixed extinction ratio. Using a conventional modulation scheme with only a single phase modulator (PM), the rejection ratio of the presented MPF can be tuned from about 10 dB to beyond 60 dB. Moreover, the central frequency tunable operation in the high rejection ratio region is also demonstrated in the experiment.
845 citations