Prediction of the substrate for nonribosomal peptide synthetase (NRPS) adenylation domains by virtual screening

Chemical structure metagenomics of microbial natural products: surveying nonribosomal peptides and beyond

Bioactivity-guided fractionation (BGF) has historically been a fruitful natural product discovery workflow. However, it is plagued by increasing rediscovery rates in recent years and new methods capable of exploring the natural product chemical space more broadly and more efficiently is in urgent need. Chemical structure metagenomics as one such method is the theme of this Perspective. It emphasizes a chemical-structure-centered viewpoint toward natural product research. Key to chemical structure metagenomics is the ability to predict the structure of a natural product based on its biosynthetic gene sequences, which facilitated the discovery of numerous new bioactive molecules and helped uncover oversampled/underexplored niches of decades of BGF based discovery. While microbial nonribosomal peptides have been the focus of chemical structure metagenomics efforts thus far, it is in principle applicable to other natural product families. The future outlook of this new approach will also be discussed.

Inhibitory selectivity to the AKR1B10 and aldose reductase (AR): insight from molecular dynamics simulations and free energy calculations

AKR1B10 is over-expressed in many cancer types and is related to chemotherapy resistance, which makes AKR1B10 a potential anti-cancer target. The high similarity of the protein structure between AKR1B10 and AR makes it difficult to develop highly selective inhibitors against AKR1B10. Understanding the interaction between AKR1B10 and inhibitors is very important for designing selective inhibitors of AKR1B10. In this study, Fidarestat, Zopolrestat, MK184 and MK204 bound to AKR1B10 and AR were used to investigate the selectivity mechanism. The results of MM/PBSA calculations show that van der Waals and electrostatic interaction provide the main contributions of the binding free energy. The hydrogen bonding between residues Y49 and H111 and inhibitors plays a pivotal role in contributing to the high inhibitory activity of AKR1B10 inhibitors. The π-π stacking interaction between residue W112 and inhibitor also plays a key role in the stability of inhibitors and AKR1B10, but W112 should keep its natural conformation to stabilize the inhibitor-AKR1B10 complex. Highly selective AKR1B10 inhibitors should have a bulky moiety like a phenyl group, which can change its binding with ABP in binding with AR and cannot change its binding with AKR1B10. The free energy decomposition shows that residues W21, V48, Y49, K78, W80, H111, R298 and V302 are beneficial to the stability of the inhibitor-AKR1B10. Our work will provide an important in silico basis for researchers to develop highly selective inhibitors of AKR1B10.

Advances in the adenylation domain: discovery of diverse non-ribosomal peptides

Non-ribosomal peptide synthetases are mega-enzyme assembly lines that synthesize many clinically useful compounds. As a gatekeeper, they have an adenylation (A)-domain that controls substrate specificity and plays an important role in product structural diversity. This review summarizes the natural distribution, catalytic mechanism, substrate prediction methods, and in vitro biochemical analysis of the A-domain. Taking genome mining of polyamino acid synthetases as an example, we introduce research on mining non-ribosomal peptides based on A-domains. We discuss how non-ribosomal peptide synthetases can be engineered based on the A-domain to obtain novel non-ribosomal peptides. This work provides guidance for screening non-ribosomal peptide-producing strains, offers a method to discover and identify A-domain functions, and will accelerate the engineering and genome mining of non-ribosomal peptide synthetases. KEY POINTS: • Introducing adenylation domain structure, substrate prediction, and biochemical analysis methods • Advances in mining homo polyamino acids based on adenylation domain analysis • Creating new non-ribosomal peptides by engineering adenylation domains.

Bioinformatic Analysis Reveals both Oversampled and Underexplored Biosynthetic Diversity in Nonribosomal Peptides

The traditional natural product discovery approach has accessed only a fraction of the chemical diversity in nature. The use of bioinformatic tools to interpret the instructions encoded in microbial biosynthetic genes has the potential to circumvent the existing methodological bottlenecks and greatly expand the scope of discovery. Structural prediction algorithms for nonribosomal peptides (NRPs), the largest family of microbial natural products, lie at the heart of this new approach. To understand the scope and limitation of the existing prediction algorithms, we evaluated their performances on NRP synthetase biosynthetic gene clusters. Our systematic analysis shows that the NRP biosynthetic landscape is uneven. Phenylglycine and its derivatives as a group of NRP building blocks (BBs), for example, have been oversampled, reflecting an extensive historical interest in the glycopeptide antibiotics family. In contrast, the benzoyl BB, including 2,3-dihydroxybenzoate (DHB), has been the most underexplored, hinting at the possibility of a reservoir of as yet unknown DHB containing NRPs with functional roles other than a siderophore. Our results also suggest that there is still vast unexplored biosynthetic diversity in nature, and the analysis presented herein shall help guide and strategize future natural product discovery campaigns. We also discuss possible ways bioinformaticians and biochemists could work together to improve the existing prediction algorithms.

In Silico/In Vitro Strategies Leading to the Discovery of New Nonribosomal Peptide and Polyketide Antibiotics Active against Human Pathogens

Antibiotics are majorly important molecules for human health. Following the golden age of antibiotic discovery, a period of decline ensued, characterised by the rediscovery of the same molecules. At the same time, new culture techniques and high-throughput sequencing enabled the discovery of new microorganisms that represent a potential source of interesting new antimicrobial substances to explore. The aim of this review is to present recently discovered nonribosomal peptide (NRP) and polyketide (PK) molecules with antimicrobial activity against human pathogens. We highlight the different in silico/in vitro strategies and approaches that led to their discovery. As a result of technological progress and a better understanding of the NRP and PK synthesis mechanisms, these new antibiotic compounds provide an additional option in human medical treatment and a potential way out of the impasse of antibiotic resistance.

Microbial Lipopeptide-Producing Strains and Their Metabolic Roles under Anaerobic Conditions

The lipopeptide produced by microorganisms is one of the representative biosurfactants and is characterized as a series of structural analogues of different families. Thirty-four families covering about 300 lipopeptide compounds have been reported in the last decades, and most of the reported lipopeptides produced by microorganisms were under aerobic conditions. The lipopeptide-producing strains under anaerobic conditions have attracted much attention from both the academic and industrial communities, due to the needs and the challenge of their applications in anaerobic environments, such as in oil reservoirs and in microbial enhanced oil recovery (MEOR). In this review, the fifty-eight reported bacterial strains, mostly isolated from oil reservoirs and dominated by the species Bacillus subtilis, producing lipopeptide biosurfactants, and the species Pseudomonas aeruginosa, producing glycolipid biosurfactants under anaerobic conditions were summarized. The metabolic pathway and the non-ribosomal peptide synthetases (NRPSs) of the strain Bacillus subtilis under anaerobic conditions were analyzed, which is expected to better understand the key mechanisms of the growth and production of lipopeptide biosurfactants of such kind of bacteria under anaerobic conditions, and to expand the industrial application of anaerobic biosurfactant-producing bacteria.

Structure of the adenylation domain Thr1 involved in the biosynthesis of 4-chlorothreonine in Streptomyces sp. OH-5093-protein flexibility and molecular bases of substrate specificity

We determined the crystal structure of Thr1, the self-standing adenylation domain involved in the nonribosomal-like biosynthesis of free 4-chlorothreonine in Streptomyces sp. OH-5093. Thr1 shows two monomers in the crystallographic asymmetric unit with different relative orientations of the C- and N-terminal subdomains both in the presence of substrates and in the unliganded form. Cocrystallization with substrates, adenosine 5'-triphosphate and l-threonine, yielded one monomer containing the two substrates and the other in complex with l-threonine adenylate, locked in a postadenylation state. Steady-state kinetics showed that Thr1 activates l-Thr and its stereoisomers, as well as d-Ala, l- and d-Ser, albeit with lower efficiency. Modeling of these substrates in the active site highlighted the molecular bases of substrate discrimination. This work provides the first crystal structure of a threonine-activating adenylation enzyme, a contribution to the studies on conformational rearrangement in adenylation domains and on substrate recognition in nonribosomal biosynthesis.

DATABASE

Structural data are available in the Protein Data Bank under the accession number 5N9W and 5N9X.

Revealing inhibition difference between PFI-2 enantiomers against SETD7 by molecular dynamics simulations, binding free energy calculations and unbinding pathway analysis

SETD7 is associated with multiple diseases related signaling pathways. (R)-PFI-2 is the first SETD7 inhibitor with nanomolar inhibitory potency. The activity of (R)-PFI-2 is about 500 times over that of (S)-PFI-2. Understanding the mechanism behind this difference will be helpful to discovery and design of more potent SETD7 inhibitors. A computational study combining molecular dynamics simulation, binding free energy calculations, and residue interaction network (RIN) was performed on the (S)-PFI-2/SETD7 and (R)-PFI-2/SETD7 complexes to explore the molecular mechanism behind the different inhibition activity. The results from Molecular Mechanics/Generalized Born Surface Area (MM/GBSA) calculation show (R)-PFI-2 has lower binding free energy. Residues H252, D256, L267, Y335, G336 and H339 are responsible for the binding of SETD7 to the (R)-PFI-2. RIN analysis indicates van der Waals interaction is critical for the binding of (R)-PFI-2. The results from adaptive basing force (ABF) simulation confirm that the free energy barrier of (R)-PFI-2 dissociating from the SETD7 is larger than that of (S)-PFI-2. (S)-PFI-2 and (R)-PFI-2 dissociate from the SETD7 binding site along different reaction coordinate and have potential mean of force (PMF) depth. Our simulations results will be useful to understand molecular mechanism of activity difference between PFI-2 enantiomers against SETD7.

Illustrating and homology modeling the proteins of the Zika virus

The Zika virus (ZIKV) is a flavivirus of the family Flaviviridae, which is similar to dengue virus, yellow fever and West Nile virus. Recent outbreaks in South America, Latin America, the Caribbean and in particular Brazil have led to concern for the spread of the disease and potential to cause Guillain-Barré syndrome and microcephaly. Although ZIKV has been known of for over 60 years there is very little in the way of knowledge of the virus with few publications and no crystal structures. No antivirals have been tested against it either in vitro or in vivo. ZIKV therefore epitomizes a neglected disease. Several suggested steps have been proposed which could be taken to initiate ZIKV antiviral drug discovery using both high throughput screens as well as structure-based design based on homology models for the key proteins. We now describe preliminary homology models created for NS5, FtsJ, NS4B, NS4A, HELICc, DEXDc, peptidase S7, NS2B, NS2A, NS1, E stem, glycoprotein M, propeptide, capsid and glycoprotein E using SWISS-MODEL. Eleven out of 15 models pass our model quality criteria for their further use. While a ZIKV glycoprotein E homology model was initially described in the immature conformation as a trimer, we now describe the mature dimer conformer which allowed the construction of an illustration of the complete virion. By comparing illustrations of ZIKV based on this new homology model and the dengue virus crystal structure we propose potential differences that could be exploited for antiviral and vaccine design. The prediction of sites for glycosylation on this protein may also be useful in this regard. While we await a cryo-EM structure of ZIKV and eventual crystal structures of the individual proteins, these homology models provide the community with a starting point for structure-based design of drugs and vaccines as well as a for computational virtual screening.

The Adenylate-Forming Enzymes AfeA and TmpB Are Involved in Aspergillus nidulans Self-Communication during Asexual Development

Aspergillus nidulans asexual sporulation (conidiation) is triggered by different environmental signals and involves the differentiation of specialized structures called conidiophores. The elimination of genes flbA-E, fluG, and tmpA results in a fluffy phenotype characterized by delayed conidiophore development and decreased expression of the conidiation essential gene brlA. While flbA-E encode regulatory proteins, fluG and tmpA encode enzymes involved in the biosynthesis of independent signals needed for normal conidiation. Here we identify afeA and tmpB as new genes encoding members the adenylate-forming enzyme superfamily, whose inactivation cause different fluffy phenotypes and decreased conidiation and brlA expression. AfeA is most similar to unknown function coumarate ligase-like (4CL-Lk) enzymes and consistent with this, a K544N active site modification eliminates AfeA function. TmpB, identified previously as a larger homolog of the oxidoreductase TmpA, contains a NRPS-type adenylation domain. A high degree of synteny in the afeA-tmpA and tmpB regions in the Aspergilli suggests that these genes are part of conserved gene clusters. afeA, tmpA, and tmpB double and triple mutant analysis as well as afeA overexpression experiments indicate that TmpA and AfeA act in the same conidiation pathway, with TmpB acting in a different pathway. Fluorescent protein tagging shows that functional versions of AfeA are localized in lipid bodies and the plasma membrane, while TmpA and TmpB are localized at the plasma membrane. We propose that AfeA participates in the biosynthesis of an acylated compound, either a p-cuomaryl type or a fatty acid compound, which might be oxidized by TmpA and/or TmpB, while TmpB adenylation domain would be involved in the activation of a hydrophobic amino acid, which in turn would be oxidized by the TmpB oxidoreductase domain. Both, AfeA-TmpA and TmpB signals are involved in self-communication and reproduction in A. nidulans.

Docking Screens for Novel Ligands Conferring New Biology

It is now plausible to dock libraries of 10 million molecules against targets over several days or weeks. When the molecules screened are commercially available, they may be rapidly tested to find new leads. Although docking retains important liabilities (it cannot calculate affinities accurately nor even reliably rank order high-scoring molecules), it can often can distinguish likely from unlikely ligands, often with hit rates above 10%. Here we summarize the improvements in libraries, target quality, and methods that have supported these advances, and the open access resources that make docking accessible. Recent docking screens for new ligands are sketched, as are the binding, crystallographic, and in vivo assays that support them. Like any technique, controls are crucial, and key experimental ones are reviewed. With such controls, docking campaigns can find ligands with new chemotypes, often revealing the new biology that may be docking's greatest impact over the next few years.

Illustrating and homology modeling the proteins of the Zika virus

The Zika virus (ZIKV) is a flavivirus of the family Flaviviridae, which is similar to dengue virus, yellow fever and West Nile virus. Recent outbreaks in South America, Latin America, the Caribbean and in particular Brazil have led to concern for the spread of the disease and potential to cause Guillain-Barré syndrome and microcephaly. Although ZIKV has been known of for over 60 years there is very little in the way of knowledge of the virus with few publications and no crystal structures. No antivirals have been tested against it either in vitro or in vivo. ZIKV therefore epitomizes a neglected disease. Several suggested steps have been proposed which could be taken to initiate ZIKV antiviral drug discovery using both high throughput screens as well as structure-based design based on homology models for the key proteins. We now describe preliminary homology models created for NS5, FtsJ, NS4B, NS4A, HELICc, DEXDc, peptidase S7, NS2B, NS2A, NS1, E stem, glycoprotein M, propeptide, capsid and glycoprotein E using SWISS-MODEL. Eleven out of 15 models pass our model quality criteria for their further use. While a ZIKV glycoprotein E homology model was initially described in the immature conformation as a trimer, we now describe the mature dimer conformer which allowed the construction of an illustration of the complete virion. By comparing illustrations of ZIKV based on this new homology model and the dengue virus crystal structure we propose potential differences that could be exploited for antiviral and vaccine design. The prediction of sites for glycosylation on this protein may also be useful in this regard. While we await a cryo-EM structure of ZIKV and eventual crystal structures of the individual proteins, these homology models provide the community with a starting point for structure-based design of drugs and vaccines as well as a for computational virtual screening.

The secondary metabolite bioinformatics portal: Computational tools to facilitate synthetic biology of secondary metabolite production

Natural products are among the most important sources of lead molecules for drug discovery. With the development of affordable whole-genome sequencing technologies and other ‘omics tools, the field of natural products research is currently undergoing a shift in paradigms. While, for decades, mainly analytical and chemical methods gave access to this group of compounds, nowadays genomics-based methods offer complementary approaches to find, identify and characterize such molecules. This paradigm shift also resulted in a high demand for computational tools to assist researchers in their daily work. In this context, this review gives a summary of tools and databases that currently are available to mine, identify and characterize natural product biosynthesis pathways and their producers based on ‘omics data. A web portal called Secondary Metabolite Bioinformatics Portal (SMBP at http://www.secondarymetabolites.org) is introduced to provide a one-stop catalog and links to these bioinformatics resources. In addition, an outlook is presented how the existing tools and those to be developed will influence synthetic biology approaches in the natural products field.