Skip to main content

In silico structural, phylogenetic and drug target analysis of putrescine monooxygenase from Shewanella putrefaciens-95



The enormous and irresponsible use of antibiotics has led to the emergence of resistant strains of bacteria globally. A new approach to combat this crisis has been nutritional immunity limiting the availability of nutrients to pathogens. Targeting the siderophore biosynthetic pathway that helps in iron acquisition, an essential microelement in the bacterial system has been the topic of interest in recent days that backs the concept of nutritional immunity. Supporting this view, we have chosen to study a key enzyme in the biosynthetic pathway of putrebactin called putrescine monooxygenase (SpPMO) from Shewanella putrefaciens. In our previous study, we co-expressed putrescine monooxygenase recombinantly in Escherichia coli BL21 Star (DE3). The bioinformatic analysis and screening of inhibitors will broaden the scope of SpPMO as a drug target.


In the present study, we have analysed the physicochemical properties of the target enzyme and other N-hydroxylating monooxygenases (NMOs) using ExPASy server. The target enzyme SpPMO and most of the selected NMOs have a slightly acidic isoelectric point and are medially thermostable and generally insoluble. The multiple sequence alignment identified the GXGXX(N/A), DXXXFATGYXXXXP motives and conserved amino acids involved in FAD binding, NADP binding, secondary structure formation and substrate binding. The phylogenetic analysis indicated the distribution of the monooxygenases into different clades according to their substrate specificity. Further, a 3D model of SpPMO was predicted using I-TASSER online tool with DfoA from Erwinia amylovora as a template. The model was validated using the SAVES server and deposited to the Protein Model Database with the accession number PM0082222. The molecular docking analysis with different substrates revealed the presence of a putrescine binding pocket made of conserved amino acids and another binding pocket present on the surface of the protein wherein all other ligands interact with high binding affinity. The molecular docking of naturally occurring inhibitor molecules with SpPMO 3D model identified curcumin and niazirin with 1.83 and 2.81 μM inhibition constants as two promising inhibitors. Further studies on kinetic parameters of curcumin and niazirin inhibitors in vitro determined the Ki to be 2.6±0.0036 μM and 18.38±0.008 μM respectively.


This analysis will help us understand the structural, phylogenetic and drug target aspects of putrescine monooxygenase from Shewanella putrefaciens-95 in detail. It sheds light on the precautionary measures that can be developed to inhibit the enzyme and thereby the secondary infections caused by them.

Graphical abstract


  • The physicochemical properties of putrescine monooxygenase from Shewanella putrefaciens-95 were compared with other known N-hydroxylating monooxygenases.

  • The phylogenetic analysis of SpPMO and other selected class B monooxygenases clearly classified NMOs according to their substrate affinity.

  • The molecular docking analysis of various substrates to SpPMO enzyme showed the presence of two binding pockets.

  • Curcumin and niazirin were identified as two potential natural inhibitors to SpPMO enzyme with 2.6±0.0036 μM and 18.38±0.008 μM inhibition constants respectively.


Bioavailability of iron is a major challenge faced by saprophytic microorganisms. In order to tackle this, they produce iron-chelating molecules called siderophores. N-Hydroxylating monooxygenases (NMOs) are one of the principal enzymes involved in the production of hydroxamate siderophores. NMOs are classified under the category of flavin-dependent monooxygenases (FMO) and belong to class B type of FMOs [1]. NMOs are majorly present in siderophore producing prokaryotes and lower eukaryotes. Previous literature suggest that the inhibition of N-hydroxylating monooxygenases can reduce the virulence of the saprophytic pathogens [2, 3]. Therefore, NMOs can be used as drug targets.

Many studies are focussed on the heterologous expression and functional and structural characterization of NMOs from Escherichia coli, Pseudomonas aeroginosa, Mycobacterium spp, Aspergillus spp. etc. [4, 5]. The researchers have also identified methimazole, celastrol as the inhibitors to the SidA, the NMO from Aspergillus spp. [6, 7]. In our previous study, we have also co-expressed NMO from Shewanella putrefaciens (putresine monooxygenase—SpPMO) along with GroES/EL chaperone in E. coli BL21 star (DE3) [8]. Shewanella putrefaciens is gram-negative bacteria usually present in shallow water bodies. It is a major cause of fish spoilage, poultry and high pH meat destruction [9]. S. putrefaciens along with other Shewanella species can be responsible for secondary infections and bacteraemia in humans [10]. Therefore, prohibition of this bacterium holds potential applications in both food industry and health sector.

Since putrescine monooxygenase plays a key role in the process of siderophore production and thereby iron uptake, the inhibition of SpPMO will be a good approach for the control of Shewanella putrefaciens. As the heterologous expression of the NMOs in the soluble form is a major hindrance for the study of these enzymes [11], the drug target study using molecular docking tools can provide us with valuable insights. In this investigation, we intend to explore and compare the physicochemical properties, phylogenetic relationships and secondary structure analysis of SpPMO with other known NMOs. We also analysed the substrate specificity of selected diamines to SpPMO in silico. Further, we also screened a set of naturally occurring inhibitor molecules by molecular docking approach and studied the kinetic parameters of the two best inhibitors.


Sequence retrieval

The amino acid sequence of putrescine monooxygenase from Shewanella putrefaciens-95 was retrieved from the previous work [8]. The other NMO sequences from Shewanella baltica, Shewanella putrefaciens 200, Shewanella putrefaciens CN32, Gordonia ruberipertincta, Streptomyces, Bordetella pertussis, Erwinia amylovora, Escherichia coli, Mycobacterium tuberculosis, Nocardia facinica, Pseudomonas aeruginosa, Kutzneria spp., Aspergillus fumigates, Amycolatopsis alba along with the representative sequences of Baeyer-Villiger monooxygenases (BVMO) from Xanthobacter flavus and flavin containing monooxygenases (FMO) from Homo sapiens and Methylophaga aminisulfidivorans were retrieved from the National Centre for Biotechnology Information (NCBI) website [11] (Supplementary data).

Primary sequence analysis

The amino acid sequence of SpPMO and other NMOs were analysed by Expasy ProtParam tool [12]. The amino acid composition, the isoelectric point (pI), the molecular weight (MW), extinction coefficient (EC—quantitative study of protein-protein and protein-ligand interactions), instability index, aliphatic index (AI), and grand average of hydropathicities (GRAVY) were noted. Protein solubility index is calculated by Protein-sol [13].

Multiple sequence alignment and construction of phylogenetic tree

To construct the phylogenetic tree, the retrieved amino acid sequences of various NMOs were aligned using ClustalW [14] with default parameters. The aligned file was visualized and the conserved sequences were highlighted using GeneDoc software (version 2.7.000) [15]. The same file used as input for MEGA-X (version 10.1.7) [16] software and the evolutionary tree was constructed applying the maximum likelihood method with a confidence level of 1000 bootstrap replicates.

3D model prediction for SpPMO

Three-dimensional structures of SpPMO were constructed using Iterative Threading ASSEmbly Refinement (I-TASSER) server [17,18,19]. The predicted structure was verified using SAVES server [20]. The model in the specified format (.pdb) was submitted to Protein Model Database [21].

Substrate affinity analysis using molecular docking

The chemical structures (3D structures in .sdf format) of the selected substrates were obtained from the PubChem compound database and converted to. pdbqt format. SpPMO 3D model was viewed in the Autodock 4.2.6 software and the Gasteiger charges were added to the entire protein. The grid parameter file was prepared by setting the grid box to 60 Å × 60 Å × 60 Å with a spacing of 0.408 Å. The XYZ co-ordinates on the central grid point showed 64.460, 55.020 and 62.510 points. The Lamarckian genetic algorithm was employed for docking; 50 GA runs were performed for individual substrates with a population size of 300. Maximum number of evaluations was set to 2,500,000 and maximum number of generations to 27,000. All other parameters were set to default and docking was carried out using Autodock tools version 1.5.6 [22].

Molecular docking with selected naturally occurring antimicrobial compounds

The naturally occurring inhibitors mainly consisting of aliphatic and aromatic amines (about 30) with their previously known antimicrobial properties were selected from MolPort database [23]. The chemical structures of each inhibitor (.sdf format) were downloaded from PubChem compound database. Each of the inhibitors was computed with Gasteiger charges and saved in .pdbqt format. SpPMO protein was pre-processed with the addition of Gasteiger charges and saved as .pdbqt file. Later each of the inhibitor molecules were docked against SpPMO protein using the same grid and docking parameters as that of substrate docking protocol.

In vitro inhibitor studies

The quantity of N-hydroxyl putrescine formation in the presence and absence of inhibitors was assayed by a modified Csaky iodine oxidation protocol as done in our previous study [8]. The enzyme SpPMO (1 μM) in 100 mM sodium phosphate buffer was incubated with putrescine (0–25 mM) and the inhibitors curcumin or niazirin (0–0.01 mM) for 10 min at 25°C and 1000 rpm shaking. The cofactor NADPH concentration was maintained constant at 2.5 mM. The reaction was aborted by the addition of 0.05 mL of 2N perchloric acid and 50 μL of this mixture was moved to a neatly labelled 96 well plate. The mixture was neutralized by the addition of 10% sodium acetate solution. The individual wells were filled with 50 μL 1% sulfanilic acid in 25% acetic acid and 20 μL of 0.5% iodide in glacial acetic acid. The plate was incubated for 10 min with shaking at 25°C. The addition of 0.1 N sodium thiosulfate eliminated excess iodine, and the colour developed on the addition of 20 μL of 0.6% α-naphthalamine after an incubation period of 45–50 min. The absorbance at 565 nm was measured using a Biorad microplate reader. The amount of product formation was calculated with the help of hydroxylamine hydrochloride standard curve. The kinetics data were fit to Michaelis Menten curve and subsequently Lineweaver Burk plots were used to obtain Km, Vmax, and Ki.


The initial critical step of siderophore biosynthesis in microorganisms is catalyzed by N-hydroxylating monooxygenases (NMO) belonging to class B FAD-containing monooxygenases [24]. These NMO need either NAD or NADPH for catalysis [5]. In our previous study, chaperone-mediated expression of SpPMO was carried out along with kinetic studies using putrescine and lysine substrates [8]. Even so, SpPMO is not explored exhaustively. In the present study, physicochemical properties, evolutionary relationships, functional and structural properties and evaluation of substrate binding affinity of NMO from Shewanella putrefaciens (SpPMO) (MH899123) have been addressed in detail using various bioinformatics tools. Further, we have also attempted to screen a few naturally occurring inhibitors against SpPMO enzyme.

Sequence retrieval and primary sequence analysis

The amino acid sequence of SpPMO protein, along with seventeen known sequences of class B monooxygenases, was compared and analyzed for their physicochemical properties. This seventeen class B monooxygenases included thirteen NMOs from bacteria, fungi and actinomycetes. Two sequences represented FMOs from Homo sapiens and Methylophaga aminisulfidivorans bacteria and one representative sequence of BVMO from Xanthomonas flavus bacteria. The NMO sequence was chosen such that each protein had different substrate specificity and other class B monooxygenases were aptly chosen to get the right outgroups during phylogenetic analysis (Fig. 2). The results of physicochemical properties are consolidated in Table 1.

Table 1 Physicochemical properties of SpPMO and other class B monooxygenases used in the study

The number of amino acids in all the chosen class B monooxygenases ranged from 400 to 600, indicating that many substitutions, additions and deletions would have taken place in the due course of evolution. Ornithine monooxygenase of Aspergillus fumigatus is the longest NMO in the group with 595 amino acids and a molecular weight of 67.77 kDa. NMO from Shewanella species including SpPMO are generally 505 amino acids in length with a molecular weight ranging from 56.76 to 57.24 kDa. The isoelectric points (pIs) of the chosen NMOs fall in the range of 5.0–8.8; most of them are having slightly acidic pIs from 5.5 to 6.5. NMOs from Shewanella species also fall in the slightly acidic range (6.2–6.4). These data suggest that the proteins may be present in moderately halophytic environments [25, 26]. This also correlates well with the fact that Shewanella genus includes marine bacteria, most of which are found in extreme aquatic habitats [27].

Instability index (II) model was developed to calculate the in vivo protein stability based on the dipeptide composition of the primary sequence. Even though the application of this method for the calculation of protein stability under in vivo conditions is questionable using this method, it is still used routinely for prediction [28]. According to this method, proteins with instability index values greater than 40 are considered unstable. Among the protein groups chosen in our study, the instability indices of all the NMOs are close to 40 and above. In particular, the instability index of putrescine monooxygenase group has been observed to be between 37 and 48. The unstable nature of these proteins can be noted during heterologous expression studies of these proteins [4, 8, 29], wherein they have to be tagged with a soluble protein like MBP or co-expressed with a chaperone for soluble expression. Although the instability index of lysine monooxygenases falls within 40, the researchers have faced difficulties in soluble expression of these enzymes in E. coli [5].

The aliphatic index (AI) is directly proportional to the number and relative volume (percentage) of the aliphatic amino acids such as alanine, valine, isoleucine and leucine in the given protein. Higher value of aliphatic index indicates that the protein is highly thermostable. The AI of the chosen class B monooxygenases is in the range of 65.26 to 97.09. The FMO from Methylophaga aminisulfidivorans possess the lowest AI of 65.26 and the NMO from E. coli possess the highest AI of 97.09 indicating high thermostability among the shown NMOs. AI of Shewanella species is around 78 and falls in the medium range. Higher percentage of leucine, alanine, valine and isoleucine observed in the NMOs (Table S1) upholds the fact that NMOs possess high aliphatic index and are thermostable in nature. The grand average of hydropathy (GRAVY) values of all the class B monooxygenases is negative. This suggests that class B monooxygenases are polar and hydrophilic in nature [30]. The presence of both hydrophobic and hydrophilic amino acids implies that the proteins are amphipathic and may function as transmembrane proteins.

Multiple sequence alignment and construction of the phylogenetic tree

The multiple amino acid sequence (Fig S1) alignment clearly shows the presence of important conserved motifs in Sp95_NMO and other selected N-hydroxylating monooxygenases (Fig. 1). Instead of glycine in the sixth position of FAD binding motif [31], aspargine/alanine GXGXX(N/A) is present in N-hydroxylating monooxygenases. In the NADP binding sequence also glycine at the sixth position (GXGXXG) is replaced by alanine (GXGXXA) in the majority of the NMOs (Fig. 1). Further, the characteristic FATGY motif with the sequence DXXXFATGYXXXXP is present in all the selected NMOs (Table 1), though aspartic acid (D1) and proline (P14) are not conserved. D1 is replaced by either glutamic acid (E1) or glycine (G1). In the highly conserved FATGY sequence also, phenylalanine (F) is replaced by leucine (L) and alanine is substituted by glycine in Shewanella and Bordotella species. Only ‘TGY’ sequence is highly conserved across the selected NMO sequence with an exception of lysine monooxygenases from Mycobacterium tuberculosis and Nocardia farcinica (Fig. 1). Along with the coloured conserved motifs, other conserved sequences visualized in the GeneDoc software are marked in grey. Tryptophan at the positions 50 and 113 in SpPMO are found to be conserved across the NMOs and tryptophan (W50) is predicted to be involved in FAD binding using the COFACTOR server (Fig S8). Other amino acids like Glycine 162, Glycine 164, Leucine 399 and Valine 127 are conserved among NMOs and are involved in FAD binding. Arginine 104 and Proline 170 are involved in NADP binding (Fig S9) and conserved across all the selected NMO sequences except for lysine monooxygenases from Mycobacterium and Nocardia species. These two enzymes accept NADH as their co-factor but not NADPH and this might be the reason for not having the conserved NADP binding amino acids in their sequence [5]. Other conserved sequences like Proline 75, Proline 250, Glycine 53 and Glycine 393 are involved in secondary structure formation; nonpolar amino acids like alanine 28, Phenylalanine 65, Proline 75, Alanine 209, Leucine 215, Glycine 393 and Proline 250 are highly conserved; and these amino acids may help in the formation of pockets for ligand binding.

Fig. 1
figure 1

Multiple sequence alignment of the selected NMOs, FMOs and BVMO. The selected sequences (Table 1) were aligned using CLUSTAL W and the conserved sequences are highlighted using Gene Doc (Version 2.7)

The phylogenetic tree is reconstructed using the maximum likelihood method and shows the evolutionary relationships among class B monooxygenases supported by high bootstrap values (Fig. 2). The FMOs and the BVMO naturally stands as outgroup and all the selected NMOs are localized together in a clade with a frequency of 80%. Within the NMOs, the lysine monooxygenases from Mycobacterium tuberculosis and Nocardia farcinica forms a clade with 99% bootstrap frequency and all other NMOs from a clade with 87% bootstrap frequency (Fig S2). The ornithine monooxygenases from Aspergillus fumigates, Pseudomonas aeruginosa, Kutzneria species and Amycolatopsis alba are placed in one clade with 78% bootstrap support. The other sequences encoding putrescine monooxygenases, cadeverine monooxygenase and lysine monooxygenase from E. coli form another clade with 91% bootstrap support. The putrescine monooxygenases from Shewanella species are grouped together with 100% bootstrap support. The sequences from Shewanella putrefaciens 95 and S. putrefaciens 200 with 99% identity are placed together with 76% bootstrap support. From the phylogenetic tree (Fig. 2), it is clear that the evolutionary changes have taken place in the amino acid sequences of the class B Flavin containing monooxygenases based on their substrate specificity. Therefore, the amino acid substitutions are more likely to be present in the substrate binding sequences of the NMOs.

Fig. 2
figure 2

Evolutionary analysis of SpPMO and other class B monooxygenases by maximum likelihood method performed using MEGA-X software (Version 10.1.7)

Analysis of substrate affinity using Autodock 4.2.6

Firstly, the secondary structure of SpPMO was predicted using Chou-Fasman algorithm (Fig S3) and subsequently predicted the 3D-structure of SpPMO that was validated using ZLab server (Fig S4), ProSA (Fig S5) and SAVES server (Fig S10) which was deposited to Protein Model Database (PMDB) after checking the overall quality factor of SpPMO protein assessed using ERRAT software in SAVES sever and was found to be 84.306 (Fig S6), with a unique Accession no. PM0082222. NMOs catalyze the N-hydroxylation of the nucleophilic terminal amine groups of the primary aliphatic diamines. The best poses of interaction between selected aliphatic diamine substrates and SpPMO predicted using Autodock 4.2.6 are depicted in Fig. 3.

Fig. 3
figure 3

Pictorial representation of the SpPMO and substrate interactions as predicted using Autodock 4.2. A Putrescine. B Lysine. C Ornithine. D Cadaverine. E Arginine. F Aspargine. G Glutamine. H Spermidine. I 1,6-Hexanediamine. J Heptanediamine. K Dimethyl octanediamine. L 1,3-Diaminopropane

The docking of substrate molecules with SpPMO protein showed the presence of two probable binding sites. Putrescine (1,4-Diaminobutane) and 1,3-Diaminopropane share common binding sites involving interactions with Pro22, Phe23, Gly26, Leu399, Gly402 and Asn406 (Fig. 3A, I). In the case of other substrates, Met72, Ala73, Glu422, His420, Ser407 and Tyr407 are commonly involved (Fig. 3B–H, J–L). Though cadaverine is also an aliphatic diamine sharing similar chemical structure to that of putrescine with one additional carbon atom, the binding sites are not the same. The visual observation of the docked poses of the selected substrates suggests that a four-carbon chain aliphatic compound is the maximum length of the substrate that can fit into the substrate binding pocket. The other selected substrates interact with the outer surface amino acids with Vander Waals forces, electrostatic interactions and hydrogen bonding but cannot move into the binding pocket situated deep inside, so that it comes to the vicinity of FAD and NADP binding regions and participate in the oxidative and reductive cycles of N-hydroxylation activity of the SpPMO enzyme. The free energy of binding and dissociation constant as estimated by the software is lower for arginine with −4.79 kcal/mol and 309.71 μM respectively. It is followed by Dimethyloctanediamine > heptanediamine > ornithine > spermidine > glutamine > lysine > 1, 6-hexanediamine > putrescine > cadaverine > 1,3-diaminopropane (Table 2). Despite the high binding affinity of the other substrates, they might be involved only in the oxygenase activity of the enzyme and do not get N-hydroxylated, as they cannot fit in the binding pocket.

Table 2 Free energy of binding and dissociation constants of the selected substrates with SpPMO

Predominantly the N-hydroxylation catalyzing enzymes are substrate specific while others are more relaxed [32]. Likewise, SpPMO also cannot be categorized as an enzyme with broad specificity.

Molecular docking with selected naturally occurring antimicrobial compounds

The binding of the aliphatic diamines like arginine, ornithine, spermidine, etc., with high affinity at a site other than that of putrescine binding pocket inspired us to look for the binding of other naturally occurring inhibitory molecules. A set of 30 naturally occurring inhibitor molecules mainly consisting of aliphatic and aromatic amines along with certain other bioactive phytochemicals were chosen from the MolPort natural compound database. All the molecules were individually docked against SpPMO protein with the same parameters used for substrate docking.

In the selected molecules, curcumin has the highest binding affinity to the SpPMO with an estimated free energy of binding of −7.83 kcal and inhibition constant of 1.83 μM. β-Alanine has the lowest affinity with the estimated free energy of binding of −3.36 kCal and 3.46 mM inhibition constant (Table 3). The visualization of the docked poses and the interaction of the inhibitors with the protein suggest that niazirin, caffeine, piperidine and betaine bind at or near the putrescine binding pocket, while the other inhibitors have a different binding site (Fig S10). Therefore, compared to curcumin, niazirin would be regarded as a best inhibitor molecule with binding free energy of −7.57 kCal and inhibition constant of 2.81 μM. Niazirin, caffeine and piperidine being aromatic amines fit in the putrescine binding pocket and therefore may behave as good competitive inhibitors of the enzyme in vivo condition.

Table 3 Free energy of binding and dissociation constants of the selected inhibitors with SpPMO

In vitro inhibitor studies

The molecular docking experiments resulted in recognizing two good inhibitors namely niazirin and curcumin. Niazirin is a bioactive compound extracted from Moringa oleifera while the bright yellow compound and a principal curcuminoid called curcumin is extracted from Curcuma longa. These naturally occurring antimicrobials were tested in vitro for their inhibitory actions against SpPMO, the key enzyme for putrebactin synthesis. The initial velocities obtained with and without the inhibitors were fit to the double reciprocal plot (Fig. 4) and the kinetic constants Vmax and Km were determined (Table 4). The constant Vmax and decreased Km observed with and without niazirin suggested that it could act as a competitive inhibitor with Ki 18.38±0.008 μM. The curcumin showed decrease in Vmax suggesting that it inhibits SpPMO non-competitively. The Ki was determined to be 2.6±0.0036 μM. The values obtained by molecular docking correlated well with the in vitro determined values.

Fig. 4
figure 4

Double reciprocal plots for the inhibitors a niazirin and b curcumin

Table 4 Kinetic parameters of SpPMO with and without inhibitors

Putrescine monooxygenase from Shewanella putrefaciens (SpPMO) is a principal enzyme in the pathway of putrebactin synthesis. The role of genes coding enzymes involved in the putrebactin synthesis pathway is noted [24]. With this background, we co-expressed SpPMO along with pGroES/EL chaperone in E. coli BL21 Star (DE3) [8]. SpPMO, a putrescine hydroxylating monooxygenase, is the key enzyme of putrebactin synthesis. Thus, inhibition of the SpPMO enzyme leads to the decrease of S. putrefaciens growth. Disruption of N-hydroxylating monooxygenase of the siderophore pathway leads to the decreased persistence and colonization of pathogens [2, 3]. In this study, we have chosen a set of 28 naturally occurring small molecules mainly consisting of aliphatic and aromatic amines along with certain other bioactive phytochemicals from the MolPort database to check its inhibitory activity against SpPMO. We initially screened these molecules for better inhibition using docking tool Autodock version 1.5.6. In this screening, niazirin and curcumin came out as the best inhibitors based on the estimated free energy of binding and estimated inhibition constants (Table 3).

To further understand the inhibition by curcumin and niazirin, a kinetic study using product formation assay and double reciprocal plots was carried out. The observed Km and Vmax with and without inhibitors suggest that the curcumin inhibits SpPMO non-competitively and niazirin inhibits SpPMO by competitive mode of inhibition (Table 4 and Fig. 4). The data from docking studies also comply with the obtained results. The docked poses of SpPMO with curcumin and niazirin (Fig S9) suggest that niazirin binds to SpPMO at the vicinity of the putrescine binding pocket and therefore competes with the substrate and inhibit SpPMO activity. Similarly to niazirin, curcumin does not bind to the putrescine binding pocket and curcumin competes with the substrate. It inhibits SpPMO activity by non-competitive mode of inhibition (Fig. 5). In our previous study, after overexpression SpPMO protein was confirmed by gene sequencing and Western blotting [8]. As curcumin and niazirin are small organic molecules, they cannot be identified by the Western blot membrane. Curcumin and niazirin inhibit SpPMO protein by non-competitive and competitive modes only. In vitro, kinetic and biochemical studies show that regulatory genes are not involved in the inhibition mechanism.

Fig. 5
figure 5

Pictorial representation of the docked poses of ligands with SpPMO. a Putrescine. b Niazirin. c Curcumin


In this study, we have explored functional and structural properties of putrescine monooxygenase from S. putrefaciens using distinct bioinformatic tools such as Expasy, MEGA-X, I-TASSER and Autodock. We have also explored and compared the primary structure of SpPMO with other known NMOs. With the help of these tools, we were able to categorize the NMOs according to their substrate specificity (Table 1) as putrescine monooxygenases, cadaverine monooxygenases, lysine monooxygenases and ornithine monooxygenases. SpPMO aptly falls within the category of putrescine monooxygenases along with SbNMO, Sp200NMO, SpCN32NMO, GrNMO, StrNMO and BpNMO. Among these NMOs, only SpPMO and GrNMO have been expressed recombinantly in E. coli. Crystallographic structure of putrescine monooxygenases has not yet been elucidated. SpPMO was found to be moderately unstable, fairly thermostable and has a negative GRAVY value which suggests the possibility of protein being attached to the membrane. Our previous study of expressing SpPMO recombinantly supports this data [8]. The not-so-stable nature and the difficulties faced during the recombinant expression of SpPMO inspired us to develop a 3D protein model using the online ab initio modelling tool such as I-TASSER. The 3D model was derived comparing cadaverine monooxygenase from Erwinia amylovora as the template.

The phylogenetic tree analysis using MEGA-X software clearly demarcates all the putrescine and cadaverine monooxygenases to one clade, while ornithine and lysine monooxygenases fall into another (Fig. 2). The multiple sequence alignment using GeneDoc software (Fig. 1) identifies many conserved motifs like FAD binding, NADP binding and FATGY motifs. It also revealed the presence of other conserved amino acids like Pro22, Phe23, Asp68 and Leu399. With this information and the predicted 3D model, we further investigated the interactions of various diamine substrates with SpPMO protein. The molecular docking experiment deduced two binding pockets in SpPMO. One of them binds putrescine and 1,3-diamino propane and exists closer to the FAD binding region. The other pocket binds all other selected diamine substrates such as lysine, ornithine, cadaverine, spermidine and others (Table 2). Putrescine and 1,3-diamino propane interact with SpPMO at the conserved amino acid regions like Pro22, Phe23, Asp68, Leu399, Gly402 and Asn406. The other substrates form bonds with Met72, Ala73, Tyr404, Ser407, His420, Ile421 and Glu422 which are at the surface of the protein. These interactions indicate that SpPMO may be specific to putrescine and 1,3-diaminopropane. The other substrates such as arginine and lysine in spite of high binding energy and the lower dissociation constants (Table 2) might not get hydroxylated and increase the oxidase activity of the enzyme [5].

The putrescine monooxygenase being the first enzyme in the putrebactin biosynthetic pathway can become a potential drug target candidate. Hence, we further examined the binding interactions for a set of naturally occurring inhibitor molecules screened from MolPort natural compound database. Binding energy calculations obtained from the Autodock 4.2.6 software identified curcumin, an antimicrobial compound to bind SpPMO with lowest binding energy and dissociation constant. However, the analysis of molecular interactions suggests that niazirin, a bioactive nitrile glycoside from Moringa oleifera [33], interacts with SpPMO at the putrescine binding pocket with a binding energy of −7.57 kCal. In order to investigate further on the kinetic parameters of the two best inhibitors screened by molecular docking, we used the product formation assay and double reciprocal plots. It was evidently observed that curcumin inhibits SpPMO non-competitively and niazirin inhibits SpPMO competitively by the double reciprocal plots. This concept correlated well with the molecular interactions that were witnessed using Autodock. The curcumin binds to SpPMO at a site other than the substrate binding and cause inhibition non-competitively, while niazirin binds at the putrescine binding pocket and inhibits the SpPMO enzyme by the competitive method (Fig. S10).


The present study explores the physicochemical and functional properties of putrescine monooxygenase from S. putrefaciens using Bioinformatic approach. The study of kinetic parameters of the inhibitor’s curcumin and niazirin has provided us with a prototype for the use of natural chemicals against severe bacterial infections. This investigation can accelerate the process of developing therapeutic and inhibitory agents against Shewanella species and thus avoid secondary infection and food spoilage.

Availability of data and materials

All data generated or analysed during this study are included in this published article [and its supplementary information files].



Putrescine monooxygenase from Shewanella putrefaciens


N-Hydroxylating monooxygenases


Flavin-dependent monooxygenases


Baeyer-Villiger monooxygenases


National Centre for Biotechnology Information


Isoelectric point


Molecular weight


Extinction coefficient


Aliphatic index


Grand average of hydropathicities


Iterative Threading ASSEmbly Refinement server


  1. Huijbers MME, Montersino S, Westphal AH, Tischler D, van Berkel WJH (2014) Flavin dependent monooxygenases. Arch Biochem Biophysics 544:2–17.

    Article  Google Scholar 

  2. Schrettl M, Bignell E, Kragl C et al (2004) Siderophore biosynthesis but not reductive iron assimilation is essential for Aspergillus fumigatus virulence. J Exp Med 200(9):1213–1219.

    Article  Google Scholar 

  3. Visser MB, Majumdar S, Hani E, Sokol PA (2004) Importance of the ornibactin and pyochelin siderophore transport systems in Burkholderia cenocepacia lung infections. Infect Immun 72(5):2850–2857.

    Article  Google Scholar 

  4. Chocklett SW, Sobrado P (2010) Aspergillus fumigatus SidA is a highly specific ornithine hydroxylase with bound flavin cofactor. Biochemistry 49(31):6777–6783.

    Article  Google Scholar 

  5. Robinson R, Sobrado P (2011) Substrate binding modulates the activity of Mycobacterium smegmatis G, a flavin-dependent monooxygenase involved in the biosynthesis of hydroxamate-containing siderophores. Biochemistry 50(39):8489–8496.

    Article  Google Scholar 

  6. Kedderis GL, Rickert DE (1983) Inhibition of the microsomal N-hydroxylation of 2-amino-6-nitrotoluene by a metabolite of methimazole. Biochem Biophys Res Commun 113(2):433–438.

    Article  Google Scholar 

  7. Martín Del Campo JS, Vogelaar N, Tolani K, Kizjakina K, Harich K, Sobrado P (2016) Inhibition of the flavin-dependent monooxygenase siderophore A (SidA) blocks siderophore biosynthesis and Aspergillus fumigatus growth. ACS Chem Biol 11(11):3035–3042.

    Article  Google Scholar 

  8. Saroja NR, Mohan AHS, Srividya D, Supreetha K (2019) Chaperone-assisted expression and purification of putrescine monooxygenase from Shewanella putrefaciens-95. Protein Expr Purif 157:9–16.

    Article  Google Scholar 

  9. Gram L and Vogel BF. (1999). SHEWANELLA. Encyclopedia of Food Microbiology, 2008–2015. doi:

  10. Olucha J, Lamb AL (2011) Mechanistic and structural studies of the N-hydroxylating flavoprotein monooxygenases. Bioorg Chem 39(5–6):171–177.

    Article  Google Scholar 

  11. Home - Protein - NCBI. Accessed 7 Jun 2021.

  12. ExPASy - ProtParam tool. Accessed 7 Jun 2021.

  13. Hebditch M, Carballo-Amador MA, Charonis S, Curtis R, Warwicker J (2017) Protein–Sol: a web tool for predicting protein solubility from sequence. Bioinformatics 33(19):3098–3100.

    Article  Google Scholar 

  14. Multiple Sequence Alignment - CLUSTALW. Accessed 7 Jun 2021.

  15. Nicholas K, Nicholas H. GeneDoc: A tool for editing and annotating multiple sequence alignments. undefined. Published online 1997. Accessed 7 Jun 2021. /paper/GeneDoc%3A-a-tool-for-editing-and-annotating-multiple-Nicholas-Nicholas/bb5b2fa84ff9f38fc03e257671d984409d355640

  16. Kumar S, Stecher G, Li M, Knyaz C, Tamura K (2018) MEGA X: Molecular evolutionary genetics analysis across computing platforms. Mol Biol Evol 35(6):1547–1549.

    Article  Google Scholar 

  17. Roy A, Kucukural A, Zhang Y (2010) I-TASSER: a unified platform for automated protein structure and function prediction. Nat Protoc 5(4):725–738.

    Article  Google Scholar 

  18. Yang J, Yan R, Roy A, Xu D, Poisson J, Zhang Y (2015) The I-TASSER Suite: protein structure and function prediction. Nat Methods. 12(1):7–8.

    Article  Google Scholar 

  19. Zhang Y (2008) I-TASSER server for protein 3D structure prediction. BMC Bioinformatics 9(1):40.

    Article  Google Scholar 

  20. SAVESv6.0 - Structure Validation Server. Accessed 7 Jun 2021.

  21. Castrignanò T, De Meo PD, Cozzetto D, Talamo IG, Tramontano A (2006) The PMDB Protein Model Database. Nucleic Acids Res 34(Database issue):D306–D309.

    Article  Google Scholar 

  22. Morris GM, Huey R, Lindstrom W et al (2009) AutoDock4 and AutoDockTools4: automated docking with selective receptor flexibility. J Comput Chem 30(16):2785–2791.

    Article  Google Scholar 

  23. O’Hagan S, Kell DB (2018) Analysing and navigating natural products space for generating small, diverse, but representative chemical libraries. Biotechnol J 13(1):1700503.

    Article  Google Scholar 

  24. Kadi N, Arbache S, Song L, Oves-Costales D, Challis GL (2008) Identification of a gene cluster that directs putrebactin biosynthesis in Shewanella species: PubC Catalyzes Cyclodimerization of N-Hydroxy-N-succinylputrescine. J Am Chem Soc 130(32):10458–10459.

    Article  Google Scholar 

  25. Kiraga J, Mackiewicz P, Mackiewicz D et al (2007) The relationships between the isoelectric point and: length of proteins, taxonomy and ecology of organisms. BMC Genomics 8(1):163.

    Article  Google Scholar 

  26. Knight CG, Kassen R, Hebestreit H, Rainey PB (2004) Global analysis of predicted proteomes: Functional adaptation of physical properties. Proc Natl Acad Sci U S A 101(22):8390–8395.

    Article  Google Scholar 

  27. Gram L, Melchiorsen J (1996) Interaction between fish spoilage bacteria Pseudomonas sp. and Shewanella putrefaciens in fish extracts and on fish tissue. J Appl Bacteriol 80(6):589–595.

    Article  Google Scholar 

  28. Gamage DG, Gunaratne A, Periyannan GR, Russell TG (2019) Applicability of instability index for in vitro protein stability prediction. Protein Pept Lett 26(5):339–347.

    Article  Google Scholar 

  29. Meneely KM, Lamb AL (2007) Biochemical characterization of an FAD-dependent monooxygenase, the ornithine hydroxylase from Pseudomonas aeruginosa, suggests a novel reaction mechanism. Biochemistry 46(42):11930–11937.

    Article  Google Scholar 

  30. Chang KY, Yang J-R (2013) Analysis and prediction of highly effective antiviral peptides based on random forests. PLoS One 8(8):e70166.

    Article  Google Scholar 

  31. Stehr M, Smau L, Singh M et al (1999) Studies with lysine N6-hydroxylase. Effect of a mutation in the assumed FAD binding site on coenzyme affinities and on lysine hydroxylating activity. Biol Chem 380(1):47–54.

    Article  Google Scholar 

  32. Mügge C, Heine T, Baraibar AG, van Berkel WJH, Paul CE, Tischler D (2020) Flavin-dependent N-hydroxylating enzymes: distribution and application. Appl Microbiol Biotechnol 104(15):6481–6499.

    Article  Google Scholar 

  33. Wang F, Zhong H-H, Chen W-K et al (2017) Potential hypoglycaemic activity phenolic glycosides from Moringa oleifera seeds. Nat Prod Res 31(16):1869–1874.

    Article  Google Scholar 

Download references


We are thankful to Dr Kumar, Dayananda Sagar College of Engineering, Bengaluru and DSS Takara bio India, for providing valuable lab facility, and Dr. Hemalatha V, Genei Laboratories Pvt. Ltd, Bengaluru, for helpful suggestions.


This work was funded by the Department of Biotechnology, Ministry of Science and Technology, Government of India (BIOCARE project No: BT/BIOCARE/01/842/2011-12).

Author information

Authors and Affiliations



AHS, SD and SNR contributed to this work equally and performed the experiments. SNR analysed the data and wrote draft manuscript. RN reviewed and corrected the manuscript. SNR reviewed and approved the manuscript. The authors read and approved the final manuscript.

Corresponding author

Correspondence to Saroja Narsing Rao.

Ethics declarations

Ethics approval and consent to participate

Not applicable

Consent for publication

Not applicable

Competing interests

The authors declare that they have no competing interests.

Additional information

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Supplementary Information

Additional file 1: Fig. S1

. Amino acid sequences of all the proteins used for comparative study in FASTA format. Fig. S2. Graphical representation of percentage of helices, sheets and turns of N-hydroxylating monooxygenases from the selected microorganisms. Fig. S3. Pictorial representation of secondary structure predicted using Chou Fasman algorithm. Fig. S4. Validation of 3D model using Ramachandran plot by ZLab server. Fig. S5: Overall model quality assessment by ProSA-web. Fig. S6. Overall quality factor of SpPMO95 protein assessed using ERRAT software in SAVES server and was found to be 84.306. Fig. S7. The overall quality of SpPMO95 assessed by Verify-3D in SAVES server showing 83.96% of the residues have averaged 3D-1D score >= 0.2. Fig. S8. Predicted FAD binding site of SpPMO, coloured in blue. FAD binding sites are given in the box. Fig. S9. Predicted NAD binding site of SpPMO, colored in blue. NAD binding sites are given in the box. Fig. S10. Pictures showing the interaction of SpPMO and the respective inhibitors. Table S1. Percentage of amino acids present in the class B monooxygenases selected for the study.

Rights and permissions

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Shyam Mohan, A.H., Rao, S.N., D., S. et al. In silico structural, phylogenetic and drug target analysis of putrescine monooxygenase from Shewanella putrefaciens-95. J Genet Eng Biotechnol 20, 57 (2022).

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI:


  • N-Hydroxylating monooxygenases
  • Shewanella putrefaciens
  • Physicochemical characteristics
  • Phylogenetic relationship
  • Molecular docking
  • Naturally occurring inhibitors