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Discovery of Fungal Denitrification Inhibitors by Targeting Copper Nitrite Reductase from Fusarium Oxysporum Masaki Matsuoka, Ashutosh Kumar, Muhammad Muddassar, Akihisa Matsuyama, Minoru Yoshida, and Kam Y.J. Zhang J. Chem. Inf. Model., Just Accepted Manuscript • DOI: 10.1021/acs.jcim.6b00649 • Publication Date (Web): 24 Jan 2017 Downloaded from http://pubs.acs.org on January 25, 2017

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Journal of Chemical Information and Modeling

Discovery of Fungal Denitrification Inhibitors by Targeting Copper Nitrite Reductase from Fusarium Oxysporum Masaki Matsuoka,†,⊥ Ashutosh Kumar,‡,⊥ Muhammad Muddassar,‡,♯ Akihisa Matsuyama,†, § Minoru Yoshida,*,†, §, ∥ and Kam Y. J. Zhang*,‡

†

Chemical Genomics Research Group, Center for Sustainable Resource Science, RIKEN, 2-1

Hirosawa, Wako, Saitama 351-0198, Japan ‡

Structural Bioinformatics Team, Center for Life Science Technologies, RIKEN, 1-7-22 Suehiro,

Tsurumi, Yokohama, Kanagawa 230-0045, Japan §

Chemical Genetics Laboratory, RIKEN, 2-1 Hirosawa, Wako, Saitama 351-0198, Japan

∥Japan

Science and Technology Corporation, CREST Research Project, 4-1-8 Honcho,

Kawaguchi, Saitama 332-0012, Japan

ACS Paragon Plus Environment

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ABSTRACT

The efficient application of nitrogenous fertilizers is urgently required as their excessive and inefficient use is causing substantial economic loss and environmental pollution. A significant amount of applied nitrogen in agricultural soils is lost as nitrous oxide (N2O) in the environment due to microbial denitrification process. The widely distributed fungus Fusarium oxysporum is a major denitrifier in agricultural soils and its denitrification activity could be targeted to reduce nitrogen loss in the form of N2O from agricultural soils. Here, we report the discovery of first small molecule inhibitors of copper nitrite reductase (NirK) from F. oxysporum, which is a key enzyme in the fungal denitrification process. The inhibitors were discovered by a hierarchical in silico screening approach consisting of pharmacophore modeling and molecular docking. In vitro evaluation of F. oxysporum NirK activity revealed several pyrimidone and triazinone based compounds with potency in the low micromolar range. Some of these compounds suppressed the fungal denitrification in vivo as well. The compounds reported here could be used as starting points for the development of nitrogenous fertilizer supplements and coatings as a means to prevent nitrogen loss by targeting fungal denitrification.


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INTRODUCTION Nitrogen (N) is an essential macronutrient, affecting plant growth, crop production and photosynthesis.1 N makes 78 % of air, but this N is unavailable for use by plants and needs to be fixed either through a fertilizer manufacturing process or by N fixing bacteria.2,

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Soil also

contains a significant amount of N but 98 % of this N is organic and cannot be used by plants.4 As soils do not contain enough N to achieve maximum productivity, N fertilization is one of the widespread practices to improve agricultural productivity. Fertilizers such as urea and ammonium nitrate are the main sources of N. Due to the ease of applicability and storage, global consumption of N fertilizers has increased by 20 % in the past 20 years. It accounts for the increase in global value of N fertilizers from US$32B to over US$80B annually, and is estimated to increase to US$150B by 2030.5 Although there was considerable increase in fertilizer consumption, the crop productivity has increased only marginally and no improvement in N usage efficiency was observed.6 As excessive application of N fertilizers is causing significant economic and environmental problems by polluting water bodies and causing atmospheric pollution,7, 8 efficient application of N fertilizers is urgently required. Efficiency of N fertilization can be improved by preventing N loss from agricultural soils. Leaching and denitrification are two main causes of N loss from agricultural soils.9 Leaching loss of N occurs when water-soluble nitrate (NO3-) moves along with water. Denitrification is a microbial process in which NO3- or nitrite (NO2-) is reduced to gaseous N forms such as nitrogen (N2) and nitrous oxide (N2O) under anaerobiosis.10 Denitrification is an important stage of nitrogen cycle and responsible for the release of N2 back into the atmosphere. Denitrification is also responsible for the release of greenhouse gas N2O in the atmosphere. Activity of microorganisms is the dominant source of N2O in agricultural and natural soils that accounts for


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56-70 % of all global N2O sources.11 N loss due to leaching can be controlled through fertilizer management practices, but gaseous N loss in the form of N2O as a result of microbial denitrification is difficult to control. Taking into account of significant N loss due to denitrification, control of denitrification is very important for reducing N loss and N2O emissions. The denitrification process is catalyzed by four reducing enzymes in a stepwise manner: dissimilatory nitrate reductase (dNar; NO3-→NO2-), dissimilatory nitrite reductase (dNir; NO2→NO), nitric oxide reductase (Nor; NO→N2O), and nitrous oxide reductase (N2Or; N2O→N2). Denitrification has been considered as a prokaryotic process for a long time.10 Recently, denitrification activities were also observed among the eukaryotes such as fungi.12-15 The fungal denitrification system physiologically functions as anaerobic respiration to produce ATP by electron transfer along the electron transport chain in a similar way to that of the bacterial system, whereas unlike bacteria, denitrifying fungi generally cannot reduce N2O to N2 due to lack of nitrous oxide reductase.15-17 Therefore, it has been assumed among ecologists that fungal denitrification might be a dominant contributor to N2O production in terrestrial ecosystems. Actually, some recent reports have clearly shown that N2O emissions from fungi were greater than those from bacteria in diverse soils such as agricultural soil, grassland soil, semiarid soil and so on.18-21 Although important roles played by fungi in organic matter decomposition as well as interactions with plants via symbiotic or pathogenic relationships are well documented, knowledge about N2O production and fungal denitrification is limited. In general, essential components of the fungal denitrification system are a copper-containing dNir (NirK) and cytochrome P450-type Nor (P450nor), which were first purified and characterized from Fusarium oxysporum.22-24 An assessment of N2O producing ability of 207 fungal strains resulted


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in the identification of F. oxysporum as a major N2O producer.25 Although F. oxysporum strains are both pathogenic and non-pathogenic and some of them are known for disease suppression in plants26, 27, their major role in N2O emission warrants the control of their denitrification activity. NirK proteins are generally known to form a trimeric structure as a biological assembly.28-31 Each NirK monomer possesses a type-1 Cu (T1Cu) that is coordinated to a cysteine, a methionine and two histidines. The active site is formed by a type-2 Cu (T2Cu) adjacent to the interface between two monomers. The T2Cu is coordinated to two histidines from one monomer and one histidine from another monomer. In addition, the T2Cu is also coordinated to a water molecule, which is displaced by the substrate NO2-. Initially, NO2- binds to T2Cu during catalysis by displacing the coordinated water molecule. A partner redox protein transfers the electrons produced during respiration to T1Cu that are subsequently transferred to T2Cu via a Cys-His bridge and a network of water molecules to reduce NO2- to NO.28-35 Fungal NirK is highly homologous to its bacterial counterpart22, 36 and also associated with the mitochondrial electron transport chain to synthesize ATP. In contrast, P450nor is a unique characteristic of fungal system and a distinct type from the bacterial cytochrome cb-type Nor.23, 37, 38 The unique feature of P450nor is that it could receive electrons directly from NADH without the need of an electron transport system (redox partner).38 This fact suggested that the function of P450nor is not ATP synthesis but NO detoxification. Fungal dNar has been partially purified from the mitochondrial membrane fraction, indicating that fungal dNar possibly resembles the bacterial counterpart, NarGHI.16, 38, 39 However, the gene involved in fungal dNar reaction has not been identified yet. We have taken upon the challenge to develop fungal denitrification inhibitors as a mitigation technology for N loss in the form of N2O from agricultural soils. The application of fungal


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denitrification inhibitors together with N fertilizers will improve the efficiency of N uptake by plants. In this paper, we report several compounds as inhibitors of F. oxysporum NirK using structure based virtual screening combined with in vitro and in vivo biological assays. This result will probably provide the first step for further development of fungal denitrification inhibitors, which will bring considerable benefits to environmental protection and conservation.

MATERIAL AND METHODS

Preparation of F. oxysporum NirK homology model. An investigation of protein structures in Protein Data Bank (PDB)40 with sufficient sequence identity was performed using the Blast program.41 Sequence alignment for homology modeling was performed using the ClustalW program.42 Modeler, a comparative modeling program43 was employed to prepare homology model of F. oxysporum NirK. Ten models were prepared and ranked according to the Discrete Optimized Protein Energy (DOPE) score44 and the model with the lowest DOPE score was selected for further analysis.

Computational fragment mapping calculations. Computational fragment mapping was used to identify small molecule binding hotspots in F. oxysporum NirK. Computational fragment mapping calculations were performed using FTMap server (http://ftmap.bu.edu).45-47 Homology model of F. oxysporum NirK was utilized for FTMap calculations. The program maps protein surface using sixteen small organic molecules (ethanol, isopropanol, isobutanol, acetone, acetaldehyde, dimethyl

ether, cyclohexane, ethane, acetonitrile, urea, methylamine, phenol,


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benzaldehyde, benzene, acetamide and N, N-dimethylformamide) to find out energetically favorable binding regions.

Pharmacophore

modeling.

Namiki-Shoji

(http://www.namiki-s.co.jp/)

collection

of

commercially available small molecules was used to perform pharmacophoric screenings. Pharmacophore query was prepared using a selected consensus site from FTMap calculation results. The pharmacophore modeling utility in MOE48 was employed to perform virtual screening.

Molecular docking. The receptor for molecular docking was prepared by adding hydrogens, assigning bond orders and identifying the correct protonation state of charged residues. The Maestro protein preparation utility49 was employed for receptor preparations. The ligand threedimensional (3D) structures were prepared using LigPrep program.50 To further prepare ligand structures, hydrogens were added to ligands followed by the generation of ionization states and tautomers. Atomic charges were assigned using OPLS-2005 forcefield.51 Grids for molecular docking calculations were generated using FTMap consensus site. Molecular docking was performed using Glide program52-55 using high-throughput virtual screening (HTVS) and standard precision (SP) mode. Glide ‘gscore’ was used to rank-order ligands for selection. The graphics in the manuscript were prepared using MOE, PyMOL56 and GnuPlot5.0 program.57

Shape similarity search. Shape matching calculations were employed to identify compounds that are structurally similar in terms of their shape properties. ROCS program58, 59 were used to perform 3D alignment and calculation of shape overlap. Compounds were ranked based on


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“TanimotoCombo” score, which is a combined Tanimoto coefficient60 for shape and chemical feature overlap.

In vitro NirK activity assay. NirK derived from F. oxysporum JCM11502 was used for in vitro NirK activity assay. Expression of fungal NirK in E. coli and purification of the recombinant protein were performed as described.61 NirK plasmid was kindly provided by Laboratory of Enzymology in the University of Tokyo.22 Fungal NirK activity was measured by monitoring the increasing amounts of NirK product NO using the NO-fluorescent indicator 4,5diaminofluorescein-2 (DAF-2) (Goryo chemical, Japan). The PMS-NADH system was used as an electron donor for NirK. A 95 µl mixture of enzyme solution (50 mM sodium phosphate buffer (pH 7.0), 16 mg/l NirK solution, 2 mM sodium nitrite, 0.5 mM NADH, 50 mM glucose, 8 U/ml glucose oxidase, 240 U/ml catalase, 10 µM DAF-2), was prepared in a 96-well microplate and covered with 100 µl of liquid paraffin. NirK activity assay needs to be performed under anaerobic conditions. The mixture of glucose oxidase and catalase removes oxygen in the enzyme solution, and liquid paraffin blocks oxygen from outside. After the incubation at 30 ºC, 5 µl of 0.5 mM 1-methoxy PMS was added to the enzyme solution. The fluorescence intensity was measured at 30 ºC with excitation wavelength at 495 nm and emission wavelength at 515 nm using a SpectraMax M2 microplate reader (Molecular Device). The final concentration of DMSO was set to 1 % in the in vitro NirK activity assay.

In vivo denitrification activity assay. The following media were used: preculture medium (3 % glycerol, 0.2 % peptone, inorganic salts; pH 7.2) and denitrification medium (preculture medium containing 10 mM NH4Cl and 100 µM NaNO2). F. oxysporum JCM11502 was precultured with


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a rotary shaker (120 rpm) at 30 ºC, and 2 µl of the preculture was inoculated to 98 µl of denitrification medium in a 96-well microplate. The culture was covered with 100 µl of liquid paraffin and incubated at 30 ºC for 60 hr. Denitrification activity was measured by monitoring the consumption of denitrification substrate NO2- using nitrite-detecting Griess reagent. At culture times of 24 hr and 60 hr, 50 µl of each of Griess reagents A (25 % HCl, 1 % sulfanilic acid) and B (0.02 % N-1-naphthylethylenediamine dihydrochloride) were added to 100 µl of the culture, and the absorbance at 540 nm was spectrophotometrically measured. The difference of the absorbance between samples prepared at culture times 24 hr and 60 hr was calculated as denitrification activity. The final concentration of DMSO used in the in vivo assay was not more than 0.5 %.

Compounds. Compounds selected after in silico screening were purchased from commercial vendors. The vendors have verified more than 90 % purity for each of the compounds. All compounds were maintained as DMSO stock solution.

RESULTS AND DISCUSSION

Homology modeling. It was challenging to design an in silico screening strategy to identify compounds with a potential to inhibit the enzymatic activity of F. oxysporum NirK. Ligand based virtual screening approaches could not be used owing to the lack of small molecule inhibitors for any NirK whereas structure based approach suffers from the absence of crystal structure for F. oxysporum NirK. Homology models are frequently used when crystallographic or NMR protein structure is unavailable and they have achieved reasonable success in identifying


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initial hits in several inhibitor discovery studies.62-67 A search of Protein Data Bank (PDB) structures has revealed a copper nitrite reductase from Ralstonia pickettii (PDB code 3ZIY) with 48 % sequence identity with F. oxysporum NirK (Figure 1A). This level of sequence identity is generally considered sufficient for protein structure prediction by homology modeling.68 Hence to perform structure based virtual screening, a homology model of F. oxysporum NirK was generated using Modeler program while the best model was selected based on “DOPE score”. Since all known copper nitrite reductases form a trimeric structure, F. oxysporum NirK was modeled using multiple chains modeling protocol of Modeler (Figure 1B). A quality assessment of F. oxysporum NirK revealed no obvious flaws (Figure 1C) in the model and it was found suitable for in silico screenings and selection of compounds for inhibition of F. oxysporum NirK enzymatic activities. As each NirK monomer possesses T1Cu and T2Cu at the interface between two monomers, Cu ions were placed in F. oxysporum NirK homology model based on their positions in the template.29

Computational fragment mapping. We utilized computational fragment mapping to identify small molecule binding sites on the surface of F. oxysporum NirK model. FTMap program uses molecular docking, energy minimization and clustering to predict clusters of probe molecules called consensus sites (CSs) as small molecule binding hotspots. Generally, the most populated CS is considered as main hotspot, but here in this study we were interested in CS in the region relevant to the catalysis. Computational fragment mapping calculation revealed several CSs on the surface of F. oxysporum NirK homology model. Interestingly, a hotspot consisting of 10 unique probe molecules (ethanol, isopropanol, isobutanol, acetone, dimethyl ether, cyclohexane, ethane, acetonitrile, phenol and benzene) was observed in a small pocket near T2Cu (Figure 2A).


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This hotspot occupies a region consisting of Tyr217, Asp256, His258, Val291, His293, Val299, Pro300, Tyr165, Phe353, Tyr355, Leu359, Pro398, Asn399 and Cys435 amino acid residues. A superposition of R. pickettii NirK (PDB code 3ZIY) and nitrite bound crystal structure of Alcaligenes faecalis copper nitrite reductase (PDB code 1SJM) onto F. oxysporum NirK homology model revealed that this hotspot overlaps with two key water molecules (Figure 2B). These water molecules are part of a network involving two T2Cu liganded water molecules, which are displaced by nitrite during catalysis.29 Although the FTMap calculations were performed in the absence of copper ions, they placed copper coordinating group probe acetonitrile in a copper ion coordinating position. Computational fragment mapping calculation suggests that this region near T2Cu has high probability of small molecule binding, which may displace crucial water molecules and hence affect the catalysis. Furthermore, the predicted hotspot lies at the interface between two monomers (Supporting information Figure S1) and compounds targeting this region may interfere with the trimerization of F. oxysporum NirK.

Pharmacophore modeling. Pharmacophore based screening is one of the commonly used virtual screening methodology to identify compounds matching a pharmacophore query.69, 70 A pharmacophore is “an ensemble of steric and electronic features that is necessary to ensure the optimal supra-molecular interactions with a specific biological target structure and to trigger (or to block) its biological response”.71 The advantage with pharmacophore modeling is that it allows the generation of and screening for chemical features that are yet to be proven to trigger or block biological response. A pharmacophore query was prepared based on FTMap CS near T2Cu. MOE program48 was used to prepare query and perform screenings. Based on acetonitrile probe, a metal ligator feature was placed, which mimics metal ion interaction with T2Cu. An


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aromatic feature representing rings was also included in the query. As the computational fragment mapping predicted hotspot is comprised of several amino acids with hydrophobic sidechain, an aromatic hydrophobic feature was also included in the pharmacophore query. The final query consists of one aromatic, one hydrophobic and one metal-ligator feature (Figure 3). Excluded volumes were used in the query. As our pharmacophore query was based on chemical intuition and computational fragment mapping instead of known inhibitors, a compound needs to match at least two features to qualify as a hit to ensure the identification of a sufficient number of hits for docking-based prioritization. The query was used to screen the Namiki-Shoji collection of about 4 million commercially available compounds that resulted in the identification of 189,616 unique compounds matching at least two pharmacophore features.

Molecular docking and selection of hits for biological assay. The resulting 189,616 hits were further prioritized by docking them to the F. oxysporum NirK homology model. Docking was performed at the small molecule binding hotspot near T2Cu consisting of Tyr217, Asp256, His258, Val291, His293, Val299, Pro300, Tyr165, Phe353, Tyr355, Leu359, Pro398, Asn399 and Cys435 amino acid residues. This region in the homology model is predicted to have well defined secondary structure (similar to R. pickettii NirK crystal structure) and is more than 20 Å away from the loops on the opposite end of trimerization interface (Figure 1B). Glide virtual screening workflow was employed to dock pharmacophore-screening hits in two stages. Initially all 189,616 hits were docked using Glide in high throughput virtual screening (Glide-HTVS) mode. Top 20 % compounds were further docked using Glide in standard precision (Glide-SP) mode. All compounds were ranked using GlideScore that ranged from -7.1 to 2.6 kcal/mol. About 460 compounds (~1 % of hits docked using Glide-SP) with GlideScore better than -5.0


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kcal/mol were visually inspected. Selection of compounds for biological assay through visual inspection was based on three criteria: (a) the docking predicted binding pose of a compound should match the pharmacophore query, (b) the compound should interfere with trimerization, and (c) interactions with metal ion. Finally, a set of 21 compounds was selected out of which 19 compounds could be purchased from different chemical vendors via a local distributor.

Evaluation of F. oxysporum NirK enzymatic activity in vitro. Nineteen compounds selected from a hierarchical virtual screening protocol were evaluated for F. oxysporum NirK inhibitory activities using a fluorescence-based in vitro assay as described in material and methods section. The enzymatic reaction mixture without any inhibitor was used as a negative control for the experiment. The blank was measured without any inhibitor and the electron donor, 1-methoxy PMS. Diethyldithiocarbamate (DDC), a metal ion chelator and a general inhibitor of copper nitrite reductases, was used as a positive control.22 The compounds were tested at a concentration of 100 µM. The relative activities with respect to the negative control are presented in Figure 4 while the chemical structures and F. oxysporum NirK inhibitory activities are also given as supporting information Table S1. As can be seen in Figure 4, two compounds (compounds 2 and 11) inhibited more than 50 % of F. oxysporum NirK enzymatic activities. No significant activity was observed for the rest of compounds.

Identification and evaluation of structurally similar compounds. Although compounds 2 and 11 represent two interesting chemical classes (pyrimidone and benzimidazolone), they are not potent enough for their utility either as chemical probes or for improving the efficiency of nitrogen utilization by reducing N loss. Therefore, we decided to further improve the potency of


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these compounds by identifying structural analogs. Ligand 3D shape similarity is one of the commonly used virtual screening approaches to identify initial hits,72-74 to identify structural analogs for potency improvement,72 to hop from one chemical scaffold to another,75-77 and to derive structure activity relationships for inhibitor optimization.78, 79 Compounds 2 and 11 were then used as queries to screen out compounds with significant 3D shape similarities from Namiki-Shoji compound collection. ROCS program was used for the evaluation of ligand 3D shape similarity and compounds were rank-ordered based on their TanimotoCombo score. Many compounds from the screening library displayed significant 3D shape overlap with the queries. In case of compound 2, the TanimotoCombo ranged from 1.707 to 1.381 for the top 100 compounds. Similarly, high 3D shape overlaps were also observed for compound 11 with TanimotoCombo range of 1.999 to 1.457 for top 100 compounds. Molecular docking using Glide in extra-precision mode was then used to further prioritize these 100 compounds similar to either compound 2 or 11. Glide–XP scoring function was used to rank these compounds and each compound was inspected visually for the binding geometry and its interactions with F. oxysporum NirK homology model. The FTMap hotspot near T2Cu was used as targeted area for molecular docking. Docking predicted binding modes of compound 2 and 11 were used as a reference structure for selection of compounds for evaluation of F. oxysporum NirK inhibitory activities. Especially, these compounds interacting with metal ion were considered since both compounds 2 and 11 interact with T2Cu. Finally 41 and 35 analogs of compounds 2 and 11 (supporting information Table S2 and S3) could be acquired from commercial vendors and tested again for their inhibition of F. oxysporum NirK enzymatic activity. The compounds were tested following the similar protocol at concentrations of 100 and 30 µM. The relative activities are plotted as a histogram in Figure 5.


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As can be seen in Figure 5A, out of 41 compound 2 analogs 16 compounds (compounds 21, 23, 25, 28-33, 35, 37-39, 42, 43 and 51) displayed better activities than compound 2, i.e. with more than 60 % inhibition of F. oxysporum NirK enzymatic activities. Among these 16 compounds, compound 30 and 37 almost completely inhibited the F. oxysporum NirK activity at a concentration of 100 µM (Figure 5A). Moreover, their activities were found to be better than DDC, a metal ion chelator (Figure 5A and supporting information Table S2). All compound 2 analogs were further tested at a lower concentration of 30 µM and 11 compounds (compound 25, 29-33, 37-39, 42 and 51) were still found to exhibit more than 60 % inhibition of F. oxysporum NirK enzymatic activities. Compound 11 analogs displayed lower inhibition of F. oxysporum NirK enzymatic activities compared with compound 2 analogs, and only 8 out of 35 compounds (compounds 61, 62, 64, 66, 83, 87-89) could display more than 60 % inhibition at a concentration of 100 µM (Figure 5B). None of the compounds displayed more than 60 % inhibition on F. oxysporum NirK at 30 µM (Figure 5B). The F. oxysporum NirK inhibitory activities of compounds 25, 29-33, 37-39, 42 and 51 were confirmed by testing them in a concentration dependent assay. The compounds were tested in various concentrations ranging from 0.1 to 300 µM. The IC50 values were determined from three replicates and the average values along with their standard deviations are presented in Table 1. As none of the compound 11 analogs displayed significant inhibition so they were not tested for dose dependency. As shown in Table 1, several compounds displayed IC50 in a low micromolar range. Activities of four compounds (25, 29, 30 and 37) were found to be better than the reference compound DDC, while three other compounds (31, 32 and 39) had comparable activities. Compounds 25, 29 and 37 were found to be the three most potent compounds with IC50 values of 3.8, 4.1 and 3.1 µM respectively.


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Evaluation of denitrification activity in vivo. Evaluation of in vitro enzymatic activities resulted in the identification of compound 2 analogs as the first small molecule inhibitors of F. oxysporum NirK. As we intended to identify F. oxysporum NirK inhibitors as chemicals that could improve the nitrogen usage efficiency of plants by improving the nitrogen availability in soil, we designed an experiment that evaluates the inhibitory effect of these compounds in vivo. Some description of in vivo assay is in material and methods section. Ten compounds (compound 25, 29-33, 37-39 and 51) were tested in vivo at 300 µM. DDC was used as a positive control.22 Five compounds (compounds 25, 30, 33, 38 and 39) displayed either better or similar inhibition as DDC (supporting information Figure S2). The in vivo activities of compounds 25, 30, 33, 38 and 39 were further confirmed by testing them at 1, 3, 10, 30, 100 and 300 µM (Figure 6). As seen in Figure 6, compound 39 could inhibit F. oxysporum NirK in a concentration dependent manner in vivo. However, the overall inhibition was low when compared with its in vitro activity. This drop in the in vitro activity of compound 39 may be due to the long culture condition (over 24 hours) in the in vivo experiment. A similar drop in the in vivo activity was also observed in case of DDC (supporting information Figure S2).

Molecular docking predicted binding mode of compound 39. The NirK active site consists of a T2Cu coordinated to three histidines and a water molecule in the resting stage. The binding of nitrite displaces the water molecule.80 Nitrite is bidentately coordinated to Cu (II) via its two oxygen atoms. This event is subsequently followed by the formation of a hydrogen bond between a nearby aspartate and one of the oxygen atoms of nitrite. An electron from T1Cu then reduces the Cu (II) to Cu (I). The formation of a second hydrogen bond with a nearby histidine or a water molecule leads to the cleavage of the N-O bond. Finally,


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NO is released while Cu (I) is oxidized to Cu (II).81 There may be two possible mechanisms for the inhibition of catalytic activity by our reported compounds: (1) Since these compounds are predicted to bind at the interface of two subunits, they may interfere with trimerization, which is necessary for catalysis. (2) Since electrons are transferred from T1Cu to T2Cu via a Cys-His bridge and a network of water molecules, these compounds may displace some of these key water molecules and thereby interfering with electron transport. In order to understand the mechanism of inhibition of our reported compounds on the F. oxysporum NirK enzymatic activity, the docking predicted binding mode of compound 39 was analyzed. As shown in Figure 7A, the pyrimidone ring in compound 39 occupies a subpocket near T2Cu. This ring was also found to overlap with FTMap predicted small molecule binding hotspot (Figure 2). The binding of compound 39 was stabilized by the coordination between T2Cu and nitrogen at 5-position of the pyrimidone ring. Hydrophobic contacts with Val129, Pro130 and Ile133 and polar contacts with His88, Thr91, His123 and Asn229 further sustain the binding (Figure 7B). Docking of reported compounds was performed utilizing only one monomer of F. oxysporum NirK homology model. An overlay of modeled trimeric structure onto the docked protein complex of compound 39 revealed clashes with the other monomer (Figure 7C) suggesting interference with the trimerization. In fact, the pyrimidone ring of compound 39 was placed in such a position that it mimics the His286 side-chain from the other NirK monomer (Figure 7D). Moreover, the nitrogen at 5-position of the pyrimidone ring interacts with T2Cu in the same manner as His286. Therefore, it is expected that binding of this compound might interfere with trimerization. It is also possible that the binding of this compound might displace critical water molecules (2509 and/or 2510 in Figure 2) and thereby affecting the water network necessary for catalysis.


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CONCLUSION In this study, in silico screening followed by subsequent in vitro and in vivo biological validation were used to identify inhibitors of fungal denitrification. A hierarchical in silico screening protocol consisting of pharmacophore based screening and molecular docking was used. A pharmacophore query was prepared from small molecule binding hotspots that were predicted on the surface of a fungal copper nitrite reductase homology model. Evaluation of F. oxysporum NirK inhibitory activities of nineteen compounds resulted in the identification of two compounds with the moderate activities. Shape based similarity search was then used to identify another 76 compounds. In vitro assessment of these compounds resulted in the identification of several compounds with potency in a low micromolar range. Further, in vivo examination confirmed the denitrification inhibitory activities of some of these compounds. Our study provided the first small molecule inhibitors of F. oxysporum NirK that could be utilized either as chemical probes to study NirK biology or as starting points for the development of fertilizer coatings or supplements to prevent nitrogen loss in the form of N2O.


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FIGURES

Figure 1. Homology modeling of F. oxysporum NirK. (A) Pairwise sequence alignment between F. oxysporum NirK (FoNirK) and Ralstonia pickettii (RpNirK) copper nitrite reductase. (B) A model of F. oxysporum NirK homotrimer. Copper ions (brown spheres) were placed based on their position in R. pickettii copper nitrite reductase. (C) Ramachandran plot displaying stereochemical quality of generated model.


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Figure 2. Computational fragment mapping to identify small molecule binding hotspots on the surface of F. oxysporum NirK. (A) A cluster of probe molecules (white sticks) near T2Cu (shown as brown sphere). (B) Superposition of copper nitrite reductase from R. pickettii (PDB code 3ZIY) and A. faecalis (PDB code 1SJM). Amino acid (cyan sticks) and water (red spheres) numbers correspond to PDB code 3ZIY.


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Figure 3. Pharmacophore query prepared using a FTMap hotspot. A cluster of probe molecules is shown as white sticks. Metal ligator pharmacophore feature is represented by cyan sphere while green and yellow spheres represent a hydrophobic and aromatic feature respectively.


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Figure 4. Inhibition of the F. oxysporum NirK enzymatic activities by compounds selected from a hierarchical virtual screening protocol. The compounds were tested at a concentration of 100 µM. Orange line shows 50 % of relative activity.


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Figure 5. Inhibition of the F. oxysporum NirK enzymatic activities by (A) compound 2 analogs and (B) compound 11 analogs at 100 µM (pale blue) and 30 µM (pink).


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Figure 6. Concentration dependent inhibition of F. oxysporum NirK enzymatic activities in vivo by compound 2 analogs.


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Figure 7. A surface (A) and active site view (B) of docking predicted binding mode of compound 39 (shown as white sticks). (C) Overlay of trimeric structure of F. oxysporum NirK homology model with docked complex of compound 39 (shown as white spheres). (D) A close up view showing the coordination between T2Cu and compound 39.


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TABLES. Table 1. Chemical structures of compound 2 analogs and their IC50 values on F. oxysporum NirK. compound #

structure

IC50 ± SD (µM)

DDC

5.5 ± 0.6

25

3.8 ± 0.9

29

4.1 ± 0.2

30

4.2 ± 1.2

31

6.5 ± 1.6

32

14.7 ± 2.0

33

7.7 ± 1.5

37

3.1 ± 0.5


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38

10.6 ± 2.4

39

6.6 ± 2.6

42

22.1 ± 2.0

51

12.2 ± 2.1

ASSOCIATED CONTENT Supporting Information. The Supporting Information is available free of charge on the ACS Publications website. A comparative model of F. oxysporum NirK homotrimer shown with FTMap predicted hotspot (Figure S1); inhibition of F. oxysporum NirK enzymatic activities in vivo by compound 2 analogs (Figure S2); chemical structures and F. oxysporum NirK inhibitory activities of 19 compounds identified by virtual screening (Table S1); chemical structures and F. oxysporum NirK inhibitory activities of compound 2 analogs (Table S2); and chemical structures and F. oxysporum NirK inhibitory activities of compound 11 analogs (Table S3).


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AUTHOR INFORMATION Corresponding Authors *E-mail: [email protected] (M.Y.). *E-mail: [email protected] (K.Y.J.Z.). Present Addresses ♯

Department of Biosciences, COMSATS Institute of Information Technology, Park Road,

Islamabad, Pakistan Author Contributions ⊥M.M.

and A.K. contributed equally to this work.

Notes The authors declare no competing financial interests. ACKNOWLEDGMENT We acknowledge the Hokusai GreatWave supercomputer at RIKEN for the supercomputing resources used in this study. We acknowledge RIKEN Pioneering Project in Dynamic Structural Biology for funding. We thank Dr. Shinya Fushinobu for providing a plasmid containing the F. oxysporum NirK gene.


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Discovery of Fungal Denitrification Inhibitors by Targeting Copper Nitrite Reductase from Fusarium Oxysporum Masaki Matsuoka, Ashutosh Kumar, Muhammad Muddassar, Akihisa Matsuyama, Minoru Yoshida, and Kam Y. J. Zhang


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Discovery of Fungal Denitrification Inhibitors by ... - ACS Publications

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