Rottlerin is a pan phosphodiesterase inhibitor and can induce neurodifferentiation in IMR-32 human neuroblastoma cells

European Journal of Pharmacology 857 (2019) 172448

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Rottlerin is a pan phosphodiesterase inhibitor and can induce neurodifferentiation in IMR-32 human neuroblastoma cells

T

Mohd Ishaq Dara,1, Priya Mahajanb,1, Suraya Jana, Shreyans K. Jainc,2, Harshita Tiwarib, Jagjeet Sandeya, Sandip Bharatec, Amit Nargotrab,∗∗, Sajad Hussain Syeda,d,∗ a

Cancer Pharmacology Division, AcSIR, Canal Road, Jammu, 180001, India Discovery Informatics Division, AcSIR, Canal Road, Jammu, 180001, India c Medicinal Chemistry Division of CSIR-Indian Institute of Integrative Medicine, AcSIR, Canal Road, Jammu, 180001, India d CSIR-Indian Institute of Integrative Medicine, Sanat Nagar, Srinagar, 190005, Jammu and Kashmir, India b

A R T I C LE I N FO

A B S T R A C T

Keywords: Phosphodiesterases Rottlerin Differentiation IMR-32 AMPK CADD

Phosphodiesterases are promising targets for pharmacological intervention against various diseases. There are already inhibitors of PDE3, PDE4 and PDE5 as approved drugs. However there is an unmet need to discover new chemical scaffolds as PDE inhibitors. The main drawback of most of PDE inhibitors is their non specificity; owing to their structural resemblance to cAMP or cGMP. Natural product compounds offer high structural diversity hence may provide new PDE inhibitors. We decided to screen our institutional natural product compound library of nearly 900 molecules for PDE5 inhibition and explore the selectivity against PDE1-11 and cytotoxicity of the hit molecule/s. Rottlerin was identified as a PDE5 inhibitor. It was found to inhibit other PDEs with varying specificities. Structure activity relationship data and molecular dynamics studies showed that Tyr612, Asp764, Gln817 and Phe820 in the binding pocket of PDE5 play an important role in the activity of rottlerin. As a pan PDE inhibitor, rottlerin was also found to activate the AMPK pathway and induce neurodifferentiation in IMR32 cells, with the effect more efficient in samples co-treated with cAMP activator Forskolin. Rottlerin at higher concentrations was shown to induce autophagy, apoptosis and G2/S cell cycle arrest in IMR-32 cells.

1. Introduction Phosphodiesterases (PDEs) comprise a family of related proteins, which can be subdivided into 11 families (PDE1-PDE11) based on their amino acid sequences; sensitivity to different activators and inhibitors; and their ability to preferentially hydrolyze either cAMP, cGMP, or both cAMP and cGMP (Maurice et al., 2014). cAMP and cGMP-signalling regulate vast number of physiological processes. Cyclic nucleotides are known to activate cGMP-dependent protein kinase, cAMP-dependent protein kinase, cAMP-regulated guanine nucleotide exchange factors, cyclic nucleotide-gated ion channels and cyclic nucleotide-regulated PDEs. Many natural compounds like Theophylline, Methylxanthine, Papaverine have been traditionally used against PDE related complications like asthama, erectile dysfunction etc. and were later identified as PDE inhibitors (Abusnina and Lugnier, 2017). Rottlerin is a major constituent of Mallotus philippensis, which grows in Southeast Asia. It

is traditionally used against tapeworm, scabies and herpetic ringworm infections. Structurally, rottlerin is a polyphenolic ketone compound having poly-pharmacological activity and is reported to inhibit many enzymes including several kinases (Bain et al., 2007). It is also reported to block the oxidative phosphorylation during mitochondrial respiration, hence reducing cellular ATP levels (Soltoff, 2001). There are also some contradicting reports of rottlerin as a protein kinase C delta inhibitor. Rottlerin is reported to inhibit cell division, angiogenesis and reactive oxygen species formation in different cancer cell lines (Singh et al., 2012) with unclear underlying molecular mechanisms. The aim of the present study was to identify new natural product based chemical scaffolds from our institutional natural product compound library as PDE5 inhibitors, so that they can be utilised, if feasible, for further medicinal chemistry based approaches for drug discovery and development.

∗

Corresponding author. CSIR-Indian Institute of Integrative Medicine, Sanat Nagar, Srinagar, 190005, Jammu and Kashmir, India. Corresponding author. E-mail addresses: [email protected] (A. Nargotra), [email protected] (S.H. Syed). 1 Authors contributed equally as first authors to this work. 2 Present Address: Department of Pharmaceutical Engineering & Technology, IIT-BHU, Varanasi, 221005, India. ∗∗

https://doi.org/10.1016/j.ejphar.2019.172448 Received 3 March 2019; Received in revised form 8 June 2019; Accepted 12 June 2019 Available online 14 June 2019 0014-2999/ © 2019 Elsevier B.V. All rights reserved.

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Fig. 1. In silico screening strategies applied for identification of PDE5 inhibitors from institutional natural product library.

Fig. 2. Rottlerin inhibits all phosphodiesterases. Dose-response curve of (A) rottlerin and (B) sildenafil on PDE5 activity, as measured by the Scintillation Proximity assay. Rottlerin showed an IC50 value of 1.02 μM and sildenafil showed an IC50 value of 0.009 μM against PDE5. (C) activity inhibition profile of PDE enzymes by rottlerin as determined by fluorescence polarization assay.

2. Material and methods

2.2. In silico screening studies

2.1. Molecular modeling methods

Ensemble of in silico models viz. similarity search, e-Pharmacophore mapping, and pharmacophore modeling were developed and applied in parallel to screen the NP library for the identification of novel PDE5 inhibitors. For building in silico models a) similarity search of 53 diverse PDE5 inhibitors was performed using ChemAxon (www.chemaxon. com) software keeping the tanimoto co-efficient of 0.7. b) Pharmacophore based 3D-QSAR models were developed from the fourcongeneric series of PDE5 inhibitors using PHASE 4.1 version of Schrodinger software(Dixon et al., 2006). Each hypothesis conveys a particular 3D conformation of a set of ligands in which ligands bind to the receptor. For the validation of these 3D pharmacophore models, the dataset of inhibitors were divided into training and test sets in ratio of 4:1. The best common pharmacophore hypothesis was selected which showed good value of correlation coefficient of the training set close to 1 and the internal predictivity coefficient of the test set value more than 0.5 were considered for screening the NP library. C) 20 X-ray crystal structure of PDE5 co-crystallized with ligand were prepared for epharmacophore mapping which resulted in the identification of

To screen the NP library for the identification of novel PDE5 inhibitors ligand and structure based in silico models were developed. The dataset for building the in silico models comprised of a) 53 diverse PDE5 inhibitors collected from ChEMBL database for carrying out similarity search (Table S1) (Bento et al., 2014), b) 4 congenric series viz. Cyclic Guanin Series (49 compounds), Pyrazinone Series (110 compounds), Sildenafil analogues (32 derivatives) and 1-(2-Ethoxyethyl)-1H-pyrazolo[4,3d]pyrimidines (33 compounds) were considered to build pharmacophore models (Hughes et al., 2009, 2011; Owen et al., 2009; Pissarnitski et al., 2004; Tollefson et al., 2010; Yoo et al., 2007). c) 20 X-ray crystal structure of PDE5 bound with different inhibitors reported in PDB were considered for building e-Pharmacophore models (Table S2) (Berman et al., 2000).

2

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Fig. 3. Binding orientations of rottlerin with PDE5, key interaction of the ligand with the amino acid residue Gln817 of the enzyme. M-Pocket (Metal Binding Pocket) show in blue constitutes: His613, His617, His653, Asp654, His657, Asn662, Met681, Glu682, Asp724, Leu725, Asp764 residues. S-Pocket (Solvent-filled Pocket) shown in green constitutes: Gly659, Asn661, Glu785, Phe786, Gln789, Thr802, Met805 residues. Q-Pocket (Purine-selective glutamine and hydrophobic clamp) shown in red constitutes: Tyr612, Leu765, Ala767, Ile768, Gln775, Ile778, Ala779, Val782, Ala783, Leu804, Ile813, Met816, Gln817, Phe820 residues. The counter ions, Zn2+ and Mg2+ are shown with cyan and pink spheres at the metal binding side. (For interpretation of the references to color in this figure legend, the reader is referred to the Web version of this article.)

Canada: Cat No. P93-31G), expressed in sf9 insect cells and CGMP SPA enzyme assay kit (TRKQ7100; PerkinElmer) as per the manufacturer recommended protocol. The plates were read by MicroBeta counter (PerkinElmer). The assays were done in duplicates and the IC50 value was calculated by using the computer software, Graphpad Prism.

compounds which shares similar pharmacophoric features and interactions between the PDE5-inhibitors complexes (Berman et al., 2000; Mahajan et al., 2017; Salam et al., 2009). All these three filters were applied in parallel and the compounds identified from screening the NP library were docked against the X-ray crystal of PDE5 in complex with the sildenafil drug i.e. 1TBF (Zhang et al., 2004). The Top 50 compounds were selected from each filtering criteria and their interaction with the key residue Gln817 was evaluated and the identified compounds were validated by the PDE5 enzyme based assay.

2.5. PDE selectivity assays For Phosphodiesterase inhibition assays 5 μl of the compound (100%DMSO) diluted in 10x fold assay buffer was added to a 50 μl reaction so that the final concentration of DMSO is 1% in all of reactions. The enzymatic reactions were conducted at room temperature for 60 min in a 50 μl mixture containing PDE assay buffer, 100 nM FAMcAMP or 100 nM FAM-cGMP, a PDE enzyme and the test compound. After the enzymatic reaction, 100 μl of a binding solution (1:100 dilution of the binding agent with the binding agent diluent) was added to each reaction and the reaction was performed at room temperature for 60 min. Fluorescence intensity was measured at an excitation of 485 nm and an emission of 528 nm using a Tecan Infinite M1000 microplate reader. PDE activity assays were performed in duplicate at each concentration. Fluorescence intensity was converted to fluorescence polarization using the Tecan Magellan6 software. The fluorescence polarization data were analyzed using Graphpad Prism. The fluorescence polarization (FPt) in absence of the compound in each data set was defined as 100% activity. In the absence of PDE and the compound, the value of fluorescent polarization (FPb) in each data set was defined as 0% activity. The percent activity in the presence of the compound was calculated according to the following equation: % activity = (FP–FPb)/ (FPt–FPb) × 100%, where FP = the fluorescence polarization in the presence of the compound. The values of % activity versus a series of compound concentrations were then plotted using non-linear regression analysis of Sigmoidal dose-response curve generated with equation Y=B+(T-B)/1 + 10((LogEC50−X)×Hill Slope), where Y = percent activity, B = minimum percent activity, T = maximum percent activity, X = logarithm of compound and Hill Slope = slope factor or Hill coefficient. The IC50 value was determined by the concentration

2.3. Molecular dynamics studies The docked complex of rottlerin in complex with PDE5 was subjected to MD simulation studies to understand important interactions involved in providing stability of the protein-ligand complex. To perform MD simulations, SPC (simple point charge) solvent model with orthorhombic boundary conditions within a radius of 12 Å was used to define the core and the whole complex was neutralized by adding Na+ and Cl-counter ion to stabilize the complex to perform simulation studies. These complexes were further minimized using a hybrid method of the steepest descent (SD) and Broyden−Fletcher−Goldfarb−Shanno algorithms (LBFGS) with a convergence threshold of 1 kcal/mol/Å and 2000 iterations. MD simulation was carried out at NPT ensemble with 1 bar pressure and 300 K temperature using Nose-Hover chain thermostat and Martyna-Tobias-Klein barostat methods. Coulombic interactions were defined by a short-range cut off radius of 9.0 Å and by a long-range smooth particle mesh Ewald tolerance to 1e-09. The whole model system was relaxed before a simulation run of 10 ns with a recording interval of 1.2 ps (for energy) and 4.8 ps (for trajectory) using Maestro-Desmond interoperability tool (version 4.1, Schrodinger, LLC, 2015) (Shivakumar et al., 2010). 2.4. PDE5 enzyme inhibition assay The PDE5 inhibition activity of rottlerin was evaluated by using commercially available purified human PDE5A enzyme (Signalchem, 3

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Fig. 4. MD simulation studies on rottlerin in complex with PDE5. A) RMSD plot of protein backbone in the presence of rottlerin B) Interaction plot of contacts between protein and ligand during the simulation run of 10 ns C) A detailed protein-ligand interaction diagram after MD run with protein residues interacting more than 25% during the simulation with the rottlerin.

Invitrogen supplemented with 10% FBS (Gibco10270-106), 1% penicillin-streptomycin (Invitrogen, 15070-063) at 37 °C in an incubator with proper humidity and 5% CO2. IMR32 cells were sub-cultured after every 3 days using 0.25% trypsin-EDTA (Gibco 25200-114).

Table 1 Isoform selectivity profile of rottlerin against 11 PDE isoforms. Enzymes

IC50(μM)

Reference

PDE1A1 PDE2A1 PDE3A PDE4A1A PDE5A1 PDE6C PDE7A1 PDE8A1 PDE9A2 PDE10A1 PDE11A4

15.6 26.9 45.6 45.0 17.33 25.2 51.2 64.9 > 100, 28% at 100 μM 21.1 25.4

0.18 Bay 60-7550 0.00058 Bay 60-7550 0.026 Cilostamide 0.021 Apremilast 0.0054 Sildenafil Citrate 0.019 Sildenafil Citrate 1.6BR L-50481 7.6 Dipyridamole 0.26 Bay 73-6991 7.6 Dipyridamole 0.26 Bay 73-6991

2.7. Compound treatment to cells For AMPK activation, IMR-32 cells were seeded at a density of 5 × 105 cells per well in 6 well dishes and allowed to attach overnight. After overnight incubation, cells were treated with different concentrations of rottlerin as per the assay requirement for 12 h in 5% CO2 incubator at 37 °C temperatures. Forskolin (10 μM final) was added simultaneously to cells in experiments involving co-treatment with rottlerin. For autophagy experiments, IMR32 cells were seeded at a density of 2.5 × 105 cells per well in 6 well dishes and allowed to attach overnight. After overnight incubation cells were treated with increasing concentration of rottlerin (10–40 μM) for 48 h in 5% CO2 incubator at 37 °C. Cells were lysed in RIPA buffer (R0278 Sigma) and the final protein concentration was estimated by Bradford protein estimation assay. Equivalent amounts of protein extracted from untreated and rottlerin treated cells were subjected to SDS-PAGE and transferred to

causing a half-maximal percent activity. 2.6. Cell culture Human IMR32 cells were obtained from the Sigma Aldrich (86041809) and were cultured in DMEM (12100-061), Gibco/ 4

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Fig. 5. Rottlerin activates the AMPK-ACC signalling pathway in IMR-32 cells, with the effect more pronounced in presence of forskolin. (A) IMR32 cells were treated with different doses of rottlerin for 12 h in complete DMEM. The total cell extract was then probed by the pAMPK, AMPK, pACC, ACC and β-Actin (loading control). There was steady increase in the phosphorylation of AMPK and ACC by rottlerin. (B) Densitometric analysis of pAMPK/AMPK and (C) pACC/ACC from the same Western blot (D) Western blot analysis of cells treated with different doses of rottlerin in presence and absence of forskolin. (E) Densitometric analysis of the gel (D) shows that rottlerin in presence of forskolin is activating the AMPK pathway more efficiently than alone.

PVDF membrane. After blocking with 5% BSA (0582 Sigma) for 2 h, these membranes were probed with antibodies against: P-ACC antibody (Ser79 CST#3667), ACC antibody (CST#3662), P-AMPKα antibody (Thr172 CST#2531), AMPKα antibody (CST#5831), β-Actin antibody (CST #8457), LC3B antibody (L7543 Sigma), p62 antibody (P0067 Sigma), Beclin-1 Antibody (CST# 3738S) and anti-rabbit IgG-HRP (SC2004). Membranes were developed by using ECL substrate (Millipore) and X-ray film (Thermo scientific). 2.8. Cell cycle analysis IMR32 cell lines were treated with different doses (5–40 μM) of rottlerin for 48 h. After incubation, cells were trypsinized and fixed in 70% ethanol at −20 °C. After fixation, cells were centrifuged at 600 g for 5 min and the supernatant was discarded. The cells were resuspended in 1 ml of PBS, centrifuged at 2000g and the supernatant was discarded. The cell pellets was again resuspended in 100 μl PBS and 20 μL of RNase (100 μg/ml) was added to each sample. Cells were incubated at 37 °C for 90 min in water bath. 200 μL propidium iodide (537059 Calbiochem) dye was added to each sample to the final concentration of 50 μg/ml and cells were incubated in dark for 30 min at room temperature. The cells were finally analyzed by FACS (BD). Fig. 6. Rotlerin induced neurite formation in IMR32 cells in a concentration dependent manner. (A) Untreated control IMR-32 cells (B) Cells treated with 10 μM rottlerin (C) 20 μM rottlerin and (D) 40 μM rottlerin. Arrows indicate the neurite formation.

2.9. Immunofluorescence IMR-32 cells were seeded at a density of 1 × 105 cells per well in 6 well dishes and allowed to attach overnight. After overnight incubation, the cells were treated with increasing concentration of rottlerin (10–40 μM) in absence or presence of forskolin 10 μM for 48 h, as per 5

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Fig. 7. Rottlerin induces expression of neuronal marker βIII tubulin in IMR-32 cells and enhances neurite formation. (A) Undifferentiated IMR-32 cells express low levels of βIII tubulin and almost no presence of neurites. IMR-32 cells treated with (B) 10 μM, (C) 20 μM and (D) 40 μM rottlerin for 48 h showed increase in expression of βIII tubulin as well as appearance of neurite outgrowths. (E) Forskolin (10 μM), a known differentiating agent is also shown increasing the expression levels of βIII tubulin and inducing the neurite formation in IMR-32. However the expression levels of βIII tubulin as well as the neurite formation were more pronounced or synergistic in cells co-treated with forskolin (10 μM) and different doses of rottlerin (F) 10 μM, (G) 20 μM and (H) 40 μM.

employed to screen the Natural Product (NP) library of our institute (∼700 compounds) to identify PDE5 inhibitors. The screening resulted in the identification of 82, 112 and 246 NP compounds via similarity search, pharmacophore modeling and e-Pharmacophore mapping respectively. Top 50 compounds from each filter were selected and analyzed with respect to their interaction with the critical amino acid Gln817 (Zoraghi et al., 2007). This resulted in the identification of 37 compounds after removing duplicate compounds from each filter. The entire in silico screening methodology followed for the identification of PDE5 inhibitors from NP library is summarized in (Fig. 1). These 37 compounds were further evaluated for PDE5 enzyme inhibition assay by using Phosphodiesterase [3H] cGMP SPA enzyme assay from PerkinElmer. All the compounds were tested in triplicates at a single dose concentration of 10 μM. The concentration was chosen keeping in mind the sub-nanomolar IC50 of the already known PDE5 inhibitors (sildenafil, tadalafil, avanafil etc.) in the literature. The only compound which showed activity in the assay was rottlerin. Dose dependent studies confirmed that rottlerin indeed inhibited the PDE5 with an IC50 of 1.02 μM (Fig. 2). On analysing the binding pocket of PDE5 in complex with rottlerin (Fig. 3), it was found that the compound is fitting very well in the binding pocket (occupying fully the Q, S pocket). The aromatic ring of chromene moiety is involved in π-π interaction with

the experimental requirement, and the media was changed every 24 h in 5% CO2 incubator at 37 °C. After 48 h media was removed and the cells were rinsed with 1 ml PBS. Cells were fixed in 4% Para formaldehyde. Cells were washed three times with PBS (each wash of 5 min) and blocked for 2 h in blocking buffer (1X PBS/5% Normal Goat serum/0.3% Triton X-100). Blocking solution was aspirated and βIIITubulin (CST#5666) primary antibody (diluted at 1:250 in antibody dilution buffer) was added. Cells were incubated overnight at 4 °C. Next day the cells were rinsed three times in 1XPBS for 5 min each. Cells were incubated with fluorochrome conjugated secondary antibody (Dnk PAb Rb IgG ab98502-FITC) for 1–2 h at room temperature in the dark. Cells were rinsed three times in 1XPBS for 5 min each and counterstained with DapI (D1306 Life Technologies) 1 μg/ml in PBS. Images were taken by Floid cell imaging system from Invitrogen.

3. Results 3.1. Discovery of rottlerin as PDE5 inhibitor Structure and Ligand guided in silico models were developed by using the chemical information of known PDE inhibitors (Table S1) and the X-ray crystal structure of PDE5 (Table S2). These models were 6

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Fig. 8. Rotlerin induced autophagy in IMR-32 cells. (A) Western blot analysis of autophagy marker LC3B-II, Beclin and P62 in IMR32 cells after treatment with 10–40 μM of rotlerin for 24 h using β-Actin was used as internal loading control and Rapamycin 200 nM as a positive autophagy inducer. (B, C and D) Densiometric analysis for LC3B-II, Beclin and P62.

depicting the detailed protein-ligand interaction diagram after MD run it was observed that Tyr612 forms water linking interaction with the compound, Asp764 forms indirect and direct interaction with the compound via water and H-bonding respectively whereas Gln817 forms direct hydrogen bonding and Phe820 is involved in π-π interaction (Fig. 4C).

Phe820 and the substituted 8 position with carbonyl forms H-bonding with the critical residue Gln817 present in the Q-pocket. Further similarity search of rottlerin form the NP compound library lead to identification of four rottlerin derivative compounds from the library, but these compounds were found inactive in PDE5 enzyme activity assay. In order to understand this loss of activity by these rottlerin derivatives, molecular modeling studies were performed. Through molecular interaction studies and orientation analysis of these inactive rottlerin derivatives with rottlerin (Fig. S1), it was observed that none of its derivatives were attaining the similar conformations to that of rottlerin and moreover they were not showing key interaction with the critical key residue Gln817. This, we assume may be the reason for loss of activity by the rottlerin derivates for PDE5.

3.3. Rottlerin showed a non selective PDE inhibitory activity Selectivity is the primary concern for the PDEs in drug discovery programs as different isoforms are implicated in different clinical manifestations. This prompted us to check the activity of rottlerin against a representative member from eleven different families of the PDE using fluorescence polarization based enzyme inhibition assay (BPS Biosciences, USA). The results showed that rottlerin is actually a pan PDE inhibitor, inhibiting all the eleven families of PDEs (Fig. 2C and Table 1) with most active against PDE1A1 (IC50 = 15.6 μM) and least active against PDE9A2 (IC50 > 100 μM). The slight variation in IC50 values obtained for rottlerin against the PDE5 by using two different assay systems (1.02 μM by using SPA based assay from PerkinElmer, as described in section 3.1, and 17.33 μM by using fluorescence polarization assay from BPS Biosciences) is something known for PDE5 inhibitors (Bischoff, 2004).

3.2. Molecular dynamics studies In order to understand the detailed interaction of rottlerin within the binding pocket of PDE5, molecular dynamics studies of rottlerin with PDE5 was carried out. RMSD analysis of the protein backbone in complex with the rottlerin showed stable conformation after 4ns during the simulation run of 10ns with RMSD of 1 to 1.6 Å (Fig. 4A). The protein-ligand interactions and contacts depicted Asp764 and Gln817 are the important amino acid residue involved in H-bonding to provide stability to the complex during the whole simulation (Fig. 4B). On 7

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Fig. 9. Cell cycle analysis by flow cytometry showed an increase in G2/S phase and reduction in G1 phase after 48 h drug treatment. A concentration dependent increase in apoptosis was observed. Maximum apoptosis was observed at 40 μM of rotlerin. (A) Control, (B) 5 μM rottlerin, (C) 10 μM rottlerin (D) 20 μM rottlerin and (E) 40 μM rottlerin treated cells.

adenylyl cyclase (Hedin and Rosberg, 1983) and checked the rottlerin induced activation of AMPK pathway. As evident (Fig. 5D), the activation of AMPK was higher in samples treated with rottlerin and forskolin together compared to the forskolin alone or corresponding rottlerin doses alone treated samples. Densiometric analysis showed that rottlerin (40 μM) in presence of the forskolin (10 μM) increased AMPK phosphorylation by 4.89 folds compared to 2.99 folds by rottlerin (40 μM) alone treated sample (Fig. 5E). This data suggests that forskolin is raising the levels of cAMP through its synthesis by activating adenylyl cyclase and rottlerin is helping to maintain the higher levels by preventing their degradation by (inhibiting) PDEs.

3.4. Rottlerin activates AMP-activated protein kinase (AMPK) signalling pathway in IMR-32 cells Inhibition of PDE activity has been shown to activate the AMPK in normal and cancer cells through elevation of cyclic nucleotides (Bang et al., 1994; Park et al., 2012; Wang et al., 2005). Resveratrol, a non specific PDE inhibitor, is known to activate the AMPK in neuronal cell lines, primary neurons, and brain (Baur et al., 2006; Dasgupta and Milbrandt, 2007; Park et al., 2012; Um et al., 2010). AMPK is a trimer complex composed of catalytic (α-subunit) and regulatory (β and γ) subunits. It is the energy sensor and energy regulator of the cell which gets activated by elevated AMP/ATP (Carling et al., 1987) and ADP/ ATP (Xiao et al., 2011) levels. Neurons are metabolically very active cells and any decrease in the ATP levels (or increase in AMP levels) is known to activate AMPK signalling in these cells [9,24]. The activation of AMPK is known to protect the neurons under ischemic and pathological conditions [9]. Neuroblastoma cells being cancerous cells are routinely used as a model system for understanding the neuronal differentiation and cell signalling processes (Cernaianu et al., 2008; Kimura et al., 2005; Shen et al., 2011; Sherer et al., 2001; Singh and Kaur, 2007; Tremblay et al., 2010). As a pan PDE inhibitor rottlerin will be increasing the levels of cAMP and cGMP, which tempted us to check if the treatment of this compound can activate the AMPK pathway in IMR-32 cells. The cells were grown and treated with different concentrations (0, 5, 10, 20, 40 μM) of rottlerin. Western blotting analysis against phosphorylated AMPK (T172) showed that indeed rottlerin was activating this pathway by increasing the phosphorylation levels of AMPK in a dose dependent manner (Fig. 5A and Fig. 5B). Next we checked the phosphorylation of acetyl-CoA carboxylase (ACC) (S79), which is a direct target of AMPK. As shown (Fig. 5A and C) the ACC was also getting phosphorylated in the rottlerin treated samples in a dose dependent manner. Both these phosphorylation events are the markers of AMPK activity. Next we questioned if the effect of rottlerin on AMPK activation is through inhibiting PDEs, we increased the synthesis of cAMP in cells by adding forskolin, which is a known stimulator of

3.5. Rottlerin induces neurodifferentiation of IMR-32 cells cAMP analogues, such as di-butyryl-cAMP (dbcAMP), are known to induce differentiation (increasing the neurite outgrowth as well as upregulating the expression of neuronal markers) of neuroblastoma cell lines (SH-SY5Y and IMR32) and neuronal cell line PC12 (Birkeland E, 2009; Christensen et al., 2003). Forskolin is also known to induce differentiation in these cell lines by elevating the cAMP levels (Waschek et al., 1988). It is known that cAMP works at least through two pathways including Epac1/2 (exchange protein activated by cAMP)/Rap GTPase and the PKA pathways to induce the process of differentiation (Bos, 2006). As rottlerin is elevating the levels of cAMP and activating the AMPK pathway in IMR-32 cells, we became curious to check if it can also induce the differentiation of these cells. Additionally, in an unpublished work, we found sildenafil to induce differentiation of IMR32 cells. Therefore, the IMR-32 cells were treated with different doses of rottlerin and the cells were observed under microscope for the emergence of cellular outgrowths as a marker of differentiation. As seen (Fig. 6) the cells were indeed showing the formation of the cell outgrowths in the rottlerin treated cells. To confirm if these outgrowths are expressing the neuronal markers, the cells were immuno-stained with antibody against a neuronal marker protein β3 –tubulin and DAPI as a nuclear marker. As evident from the images (Fig. 7), these outgrowths 8

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were found expressing the β3–tubulin, confirming them as neurite outgrowths. Also, the overall intensity or expression levels of β3–tubulin in the main cellular body of samples treated with rottlerin were higher compared to the untreated cells (compare Fig. 7 row A with row B, C and D). Then we used rottlerin in combination with forskolin for evaluating the efficiency of differentiation. Forskolin at 10 μM concentration showed mild differentiation (Fig. 7, row E) where as in combination with different doses of rottlerin, the forskolin treated cells were showing very prominent differentiation and higher levels of β3–tubulin expression (Fig. 7, row F, G and H). Comparing row D of Fig. 7 (40 μM rottlerin) or row E (10 μM forskolin) with row H (40 μM rottlerin with 10 μM forskolin) clearly demonstrates the synergistic effect of forskolin on rottlerin induced neural differentiation in IMR32 cells.

different phases of cell cycle i.e G1, S, G2/M. Analysis of cell cycle showed an increase in population of cells at G2 and S phase and a decrease in G1 phase in the rottlerin treated cells. Accumulation of cells in G2/S phase increased as the concentration of rottlerin increased from 5 to 40 μM suggesting G2/S arrest. There was also a positive correlation between the dose of rottlerin and the percentage of apoptotic cell population (Fig. 9) indicating that rottlerin is inducing apoptosis of IMR32 cells at higher concentrations. 4. Discussion Natural compounds are structurally diverse, often interact with many biological targets and have been the backbone of most of the drugs discovered, either as intact compounds or their semi synthetic derivatives. In the present study, we were interested to discover new chemical scaffolds as PDE5 inhibitor from the natural compound library of our Institute. The compound library, consisting of ∼700 compounds, was screened by using different in silico methods, including similarity search, pharmacophore modeling, pharmacophore mapping, and molecular docking. The 37 hits obtained by the in silico screening were further evaluated by PDE5 enzyme inhibition assay at 10 μM concentration. The data showed that only rottlerin was able to inhibit the PDE5 enzyme, which was further confirmed by the dose depended enzyme based assay. Rottlerin was shown to inhibit the PDE5 with an IC50 value of 1.02 μM. From the MD studies it was observed that Tyr612, Asp764, Phe820 and Gln817 amino acid residues play an important role in providing stability to PDE5-rottlerin complex. The interaction is highly specific as small chemical modifications in the rottlerin backbone in the form of rottlerin derivatives IN00543, IN00544 and IN005425 (Jain et al., 2013) resulted in complete loss of the inhibitory activity. The modifications perturbed the key interaction with the Gln 817 of PDE5. Further site directed mutational analysis is required to confirm the role of the above amino acids in this interaction. We next screened the rottlerin against 11 different isoforms of PDE (PDE1- PDE11) to check its specificity and possible utility against a specific pathological condition related to a specific PDE. The results, however, showed that rottlerin is actually a pan PDE inhibitor with a slight difference in potency against different isoforms. This will mean that although rottlerin provides a new chemical scaffold as a PDE inhibitor, but will certainly need more medicinal chemistry approaches to design, synthesize and screen its derivatives against different PDE isoforms to obtain isoform selective new chemical entities. AMPK maintains Drosophila genome integrity during cell division of neuronal progenitor cells in Drosophila (Lee et al., 2007). Various research studies have shown AMPK activators induce differentiation in neuroblastoma cell lines (Caraci et al., 2003; Garcia-Gil et al., 2003; Van Ginkel et al., 2007). Our data shows that rottlerin is able to activate the AMPK pathway and also differentiate the human neuroblastoma IMR-32 cells. Rottlerin and forskolin were found to synergistically increase the phosphorylation of AMPK and induce differentiation of IMR32 cells. This type of activity is already known for another non specific PDE inhibitor, resveratrol, that is known to activate AMPK, through cAMP-Epac1-AMPK-Sirt1 pathway (Park et al., 2012), and induce differentiation in mouse neuroblastoma N2A cells (Dasgupta and Milbrandt, 2007). Genetic and pharmacological inhibition of AMPK has been shown to prevent the resveratrol induced differentiation of N2A cells, confirming that activation of AMPK is playing an essential role in mouse neuroblastoma differentiation (Dasgupta and Milbrandt, 2007). Several specific as well as non-specific PDE inhibitors including resveratrol, theophylline and caffeine are reported to inhibit cell proliferation and metastasis of different type of cancers (Lentini et al., 1998; Marko et al., 1998; Sarfati et al., 2003; Thompson et al., 2000). Rottlerin has been traditional used in Indian medicine against worm infections and exhibits good safety and toxicity profile, even after extensive exposure (Hong et al., 2015). In recent past, rottlerin has been studied for its role in anticancer activities in different cancer cell lines,

3.6. Rottlerin induces autophagy in IMR-32 cells AMPK signalling plays a protective role in cells under stress conditions by inducing autophagy (Sid et al., 2013). Autophagy is primarily a survival mechanism by cells in stressful conditions, which in some instances can also lead to cell death (Mizushima et al., 2008). It is reported that activation of AMPK by activator compound A769662 and over expression of a constitutively active form of AMPKα in mouse embryonic fibroblasts (MEFs) and STHdh cells induces the over expression of the autophagosomal markers LC3 and p62 (Walter et al., 2016). LC3 (microtubule-associated protein 1 light chain 3) is a main marker of autophagy, that exists as LC3-I in cytosol, which gets converted during the process of autophagy, to LC3-II by truncation and lipidation in autophagosomal membrane (Kabeya et al., 2000). p62 also called sequestosome 1 (SQSTM1), is an adaptor protein that serves as a link between LC3 and ubiquitinated substrates. p62 itself is also degraded during the process of autophagy and its declining levels at the onset of autophagy has been used as a marker for tracking the process of autophagy (Bjorkoy et al., 2009). Beclin-1, another commonly used marker protein for autophagy, is a key regulator of autophagy, that plays an important role in localization of proteins involved in the formation of pre-autophagosomal structure (Kang et al., 2011). Since we found rottlerin as an activator of AMPK, we became interested to check if it can also induce autophagy in IMR-32 cells. Cells were treated with increasing concentrations of rottlerin and the expression of the three autophagy markers including conversion of LC3-I to LC3-II, P62, and Beclin were evaluated. Rapamycin a known autophagy inducer (Noda and Ohsumi, 1998) was used as a positive control. Interestingly we observed that rottlerin was indeed increasing the conversion of LC3-I to LC3-II, decreasing the levels of p62 and also increasing the levels of autophagy regulator protein Beclin-1 in a dose dependent manner (Fig. 8A), indicating the formation of autophagosome. The western blotting data was quantified and present as Fig. 8B–D. 3.7. Rotlerin induces G2/S arrest and apoptosis in IMR32-cells Activation of AMPK is known to induce apoptosis in different cancer cell lines through pathways including inhibition of fattyacid synthesis and activation of JNK and caspase-3 (Cai et al., 2007; Concannon et al., 2010; Jung et al., 2004; Kefas et al., 2003; Li et al., 2003; Meisse et al., 2002; Saitoh et al., 2004; Xiang et al., 2004). AMPK activator 5-Aminoimidazole-4-carboxamide-1-β-4-ribofuranoside (AICAR) is reported to induce apoptosis in mouse Neuro 2a neuroblastoma cells by cell cycle arrest through activation of nuclear factor-κB (Jung et al., 2004). AICAR is also reported to inhibit the Akt phosphorylation, increase the expression of cell cycle inhibitors p21, p27, and p53 and arrest the cell cycle at S- phase of glioma cells (Rattan et al., 2005). As an activator of AMPK in IMR-32 cells, we checked if rottlerin can also cause apoptosis and cell cycle arrest in these cells. IMR-32 cells were treated with different doses of rottlerin for 48 h and the cell cycle analysis was done by FACS. Cell cycle analysis by using flow cytometry distinguishes cells in 9

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including prostrate, breast, colorectal and pancreatic cancers and has been found to play role in altering cell growth, autophagy, apoptosis and cell migration (Daveri et al., 2015). These anti-neoplastic activities of rottlerin have been assigned to its inhibitory role of multiple cell signalling pathways like mTOR, Wnt/β-catenin etc (Zhu et al., 2017). AMPK activation is known to inhibit the mTOR signalling, which in turn suppresses the induction of Bcl-2 and favour the onset of apoptosis (Sid et al., 2013). In our study we report that rottlerin is also able to induce autophagy, apoptosis and cell cycle arrest in human neuroblastoma IMR-32 cells. These effects could be the result of many pharmacological activities reported for the rottlerin including the AMPK activation caused as a result of PDE inhibition. There is a need to carry out additional studies to explore the cross talk between the activities reported for rottlerin to understand the role of individual pharmacological activity reported for this molecule.

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5. Conclusion In the current work we have discovered Rottlerin as a pan PDE inhibitor which inhibits all the 11 isoforms of the PDE. As a pan PDE inhibitor Rottlerin was found as an activator of AMPK signalling and an inducer of differentiation in IMR-32 neuroblastoma cells. Rottlerin was also found to induce autophagy and apoptosis in IMR-32 cells. This work may help to understand the poly-pharmacological activities of rottlerin, which could be due to its inhibition of different isoforms of PDE, who are known to play role in divergent cellular processes. In addition this work may help medicinal chemists to synthesize isoform selective analogues of rottlerin. Conflicts of interest The authors declare that there is no conflict of interest. Author contribution MID, SJ and JS performed the biological experiments; PM and HT performed the bioinformatics work; SKJ and SB provided the purified Rottlerin and its derivatives; AN and SHS analyzed the data and wrote the manuscript; SHS conceptualized and coordinated the work. Acknowledgements The work was supported by the funding from CSIR [BSC-0108, HCP0008] and SERB-DST [ECR/2016/000625]. The institutional publication number of this manuscript is IIIM/2201/2018. SJ thanks UGC and JS acknowledges INSPIRE for the fellowship. Appendix A. Supplementary data Supplementary data to this article can be found online at https:// doi.org/10.1016/j.ejphar.2019.172448. References Abusnina, A., Lugnier, C., 2017. Therapeutic potentials of natural compounds acting on cyclic nucleotide phosphodiesterase families. Cell. Signal. 39, 55–65. https://doi.org/ 10.1016/j.cellsig.2017.07.018. Bain, J., Plater, L., Elliott, M., Shpiro, N., Hastie, C.J., McLauchlan, H., Klevernic, I., Arthur, J.S., Alessi, D.R., Cohen, P., 2007. The selectivity of protein kinase inhibitors: a further update. Biochem. J. 408, 297–315. https://doi.org/10.1042/bj20070797. Bang, B.E., Ericsen, C., Aarbakke, J., 1994. Effects of cAMP and cGMP elevating agents on HL-60 cell differentiation. Pharmacol. Toxicol. 75, 108–112. Baur, J.A., Pearson, K.J., Price, N.L., Jamieson, H.A., Lerin, C., Kalra, A., Prabhu, V.V., Allard, J.S., Lopez-Lluch, G., Lewis, K., Pistell, P.J., Poosala, S., Becker, K.G., Boss, O., Gwinn, D., Wang, M., Ramaswamy, S., Fishbein, K.W., Spencer, R.G., Lakatta, E.G., Le Couteur, D., Shaw, R.J., Navas, P., Puigserver, P., Ingram, D.K., de Cabo, R., Sinclair, D.A., 2006. Resveratrol improves health and survival of mice on a high-calorie diet. Nature 444, 337–342. https://doi.org/10.1038/nature05354. Bento, A.P., Gaulton, A., Hersey, A., Bellis, L.J., Chambers, J., Davies, M., Kruger, F.A.,

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