Establish an automated flow injection ESI-MS method for the screening of fragment based libraries: Application to Hsp90

European Journal of Pharmaceutical Sciences 76 (2015) 83–94

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European Journal of Pharmaceutical Sciences journal homepage: www.elsevier.com/locate/ejps

Establish an automated flow injection ESI-MS method for the screening of fragment based libraries: Application to Hsp90 Federico Riccardi Sirtori a,b,⇑, Dannica Caronni a, Maristella Colombo a, Claudio Dalvit a,1, Mauro Paolucci a, Luca Regazzoni b, Carlo Visco a, Gianpaolo Fogliatto a a b

Oncology Business Unit, Nerviano Medical Sciences, Viale Pasteur 10, 20014 Nerviano (MI), Italy Dipartimento di Scienze Farmaceutiche ‘‘Pietro Pratesi’’, Università degli Studi di Milano, Via Mangiagalli 25, 20133 Milan, Italy

a r t i c l e

i n f o

Article history: Received 5 December 2014 Received in revised form 30 April 2015 Accepted 3 May 2015 Available online 4 May 2015 Keywords: Mass spectrometry Hsp90 Antitumor agents Medicinal chemistry Fragment based approach

a b s t r a c t ESI-MS is a well established technique for the study of biopolymers (nucleic acids, proteins) and their non covalent adducts, due to its capacity to detect ligand–target complexes in the gas phase and allows inference of ligand–target binding in solution. In this article we used this approach to investigate the interaction of ligands to the Heat Shock Protein 90 (Hsp90). This enzyme is a molecular chaperone involved in the folding and maturation of several proteins which has been subjected in the last years to intensive drug discovery efforts due to its key role in cancer. In particular, reference compounds, with a broad range of dissociation constants from 40 pM to 100 lM, were tested to assess the reliability of ESI-MS for the study of protein–ligand complexes. A good agreement was found between the values measured with a fluorescence polarization displacement assay and those determined by mass spectrometry. After this validation step we describe the setup of a medium throughput screening method, based on ESI-MS, suitable to explore interactions of therapeutic relevance biopolymers with chemical libraries. Our approach is based on an automated flow injection ESI-MS method (AFI-MS) and has been applied to screen the Nerviano Medical Sciences proprietary fragment library of about 2000 fragments against Hsp90. In order to discard false positive hits and to discriminate those of them interacting with the N-terminal ATP binding site, competition experiments were performed using a reference inhibitor. Gratifyingly, this group of hits matches with the ligands previously identified by NMR FAXS techniques and confirmed by X-ray co-crystallization experiments. These results support the use of AFI-MS for the screening of medium size libraries, including libraries of small molecules with low affinity typically used in fragment based drug discovery. AFI-MS is a valid alternative to other techniques with the additional opportunities to identify compounds interacting with unpredicted or allosteric sites, without the need of any binding probes. Ó 2015 Elsevier B.V. All rights reserved.

1. Introduction The use of electrospray ionization mass spectrometry (ESI-MS) for the study of non covalent target–ligand interactions in medicinal chemistry is widely described in the literature (Hofstadler and Sannes-Lowery, 2006; Schalley, 2001; Vivat Hannah et al., 2009). This method directly detects non covalently bound complexes into ⇑ Corresponding author at: Oncology Business Unit, Nerviano Medical Sciences, Viale Pasteur 10, 20014 Nerviano (MI), Italy. E-mail address: [email protected] (F. Riccardi Sirtori). 1 Present address: Faculty of Science, University of Neuchâtel, Avenue de Bellevaux 51, CH-2000 Neuchâtel, Switzerland. http://dx.doi.org/10.1016/j.ejps.2015.05.001 0928-0987/Ó 2015 Elsevier B.V. All rights reserved.

the gas phase allowing the determination of target–ligand binding parameters in solution. Although there is an increasing interest in the use of this approach, a debate about the reliability of ESI-MS for the study of non covalent complexes is still open. Several papers highlighted that it is possible to transfer intact biomolecules and their non-covalent complexes into gas phase (Heck and Van Den Heuvel, 2004; Liu et al., 2009; Van den Heuvel and Heck, 2004) and the binding affinities measured by ESI-MS showed agreement with values determined by classical solution phase methods (El-Hawiet et al., 2010; Jecklin et al., 2009a,c). On the other side it should be pointed out that the loss

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of hydrophobic interactions and strengthening of electrostatic effects into gas phase could influence the stability of the protein– ligand complex, causing a difference between gas and solution phase binding properties (Cunniff and Vouros, 1995; Robinson et al., 1996; Xu et al., 2008). In addition, as reported by Breuker and McLafferty (2008) there is the possibility that non-covalent complexes could change their structure during electrospray process in order to stabilize the ion conformation, and also that unspecific bindings could occur in ESI-MS experiments requiring additional investigations to distinguish specific from non-specific interactions (Schalley, 2001; Sun et al., 2006). On the other side the ESI-MS has some key advantages over other techniques. The MS methods are rapid and automatable, and the high sensitivity of the mass detector requires minimal amount of target proteins. Another key advantage of mass spectrometry is specificity; in fact, the identity of different complexes can be directly deduced by the mass of each molecule that acts as intrinsic label. Consequently, labeled targets or ligands are not required. ESI-MS is also able to identify, within a mixture, components that selectively bind the biopolymer and could be profitably exploited to screen libraries of known compounds. In the present work we want to thoroughly investigate the reliability of ESI-MS results by comparing the data obtained with those determined by ‘‘gold standard’’ solution phase methods. We studied the interactions of different ligands with Heat Shock Protein 90 (Hsp90), which is a molecular chaperone involved in folding, assembly, maturation, and stabilization of different client proteins and is essential for the stability and activity of many key oncogenic proteins influencing cancer progression (Biamonte et al., 2010; Csermely et al., 1998; Goetz et al., 2003). For these reasons Hsp90 emerged in the last decade as a major therapeutic target and a great deal of efforts have been dedicated to the discovery of inhibitors, some of them currently under clinical evaluation (Bauer et al., 2006; Jhaveri et al., 2011; Shimamura et al., 2008). The attractiveness of Hsp90 inhibitors for the management of oncological diseases, led to establishing a research project in Nerviano Medical Sciences (NMS) including a FAXS (Fluorine chemical shift Anisotropy and eXchange for Screening) NMR 19F based screening (Dalvit et al., 2003) performed to support a fragment-based program (Brasca et al., 2010; Casale et al., 2014). The use of ESI-MS to investigate this target was previously reported by Vallée and coworkers in the medicinal chemistry optimization of tricyclic imidazo[4,5-c]pyridines as a new class of Hsp90 inhibitors (Vallee et al., 2011). The intensive work performed in NMS with Hsp90 gave us the opportunity to compare binding data obtained by different techniques to further validate the ESI-MS approach. Considering the issues related to the stability of non-covalent complexes in the gas phase it is noteworthy that the setup of an ESI-MS method could be target dependent and, moreover, it is important to validate the procedure with known inhibitors that belong to different structural classes. For this reason, we tested a set of chemically divergent compounds and next we compared ESI-MS results to those previously obtained by standard condensed phase assays (Fluorescence polarization, Surface Plasmon Resonance). Once verified the reliability of our approach we setup and validated an automated flow injection ESI-MS method (AFI-MS) to be used for the screening of chemical libraries. In particular, we focused our attention to the development of a procedure suitable to identify low affinity Hsp90 ligands with the aim to use them in a fragment based program. Fragment-based drug discovery (FBDD) is now a medicinal chemistry approach that differs substantially from more traditional procedures based on chemical hits derived from high throughput screening (Carr et al., 2005; Erlanson et al., 2004). It

requires fewer compounds to be screened, and despite the lower initial potency of the hits offers more efficient and fruitful optimization. Screening methods with high sensitivity, such as surface plasmon resonance (Neumann et al., 2007), nuclear magnetic resonance spectroscopy (Lepre et al., 2004), and X-ray crystallography (Hartshorn et al., 2005; Lesuisse et al., 2002), are required for identifying low affinity ligands and support fragment-based programs. Different medium to high-throughput ESI-MS assays have been previously described in the literature (Benkestock et al., 2003; Gao et al., 1996; Greig and Robinson, 2000; Sannes-Lowery et al., 2000; Wigger et al., 2002). Some of the more recent methods make use of an automated nano-electrospray ion source, based on a chip platform for sample infusion analysis (Benkestock et al., 2005, 2003; Jecklin et al., 2009c; Vivat Hannah et al., 2009; Wortmann et al., 2008), that was also applied to fragment based screening (Maple et al., 2012; Vivat Hannah et al., 2009). Compared to these methods, AFI-MS makes use of a flow injection operation mode; samples are injected in a micro-flow by an autosampler and reach in few seconds the mass spectrometer ion source. With the aim to identify those hits that specifically interact with the N-terminal ATP binding pocket and to exclude the possibility of aspecific interactions, we also implemented a MS based competition assay as described in the literature (Jecklin et al., 2009b; Vivat Hannah et al., 2009) using known ATP competitive molecules. Finally the Nerviano Medical Sciences fragment library was tested against the N-terminal domain of Hsp90 using AFI-MS and the identified hits were compared to those previously found by NMR FAXS experiments. 2. Experimental section 2.1. Chemicals All solvents and reagents, unless otherwise stated, were commercially available (Aldrich, Fluka), of the best grade and were used without further purification. The different standard compounds, used to set up the flow injection method, were synthesized by NMS Medicinal Chemistry Department (Fig. 1). AUY-922 (2) was synthesized as described in the literature (Brough et al., 2008). Compound 3 and PU3 (4) were prepared as previously reported (Biamonte et al., 2005). SNX-2112 (1), 17-AAG (5) and novobiocin (6) were commercially available. Pyrazole derivatives 7, 8, 9, and 10 were synthesized according to Dymock et al. (2005). The DMSO stock solution concentrations (nominal 10 mM) of standard compounds were assessed by NMR as previously described (Pinciroli et al., 2001). 2.2. Protein preparation For ESI-MS experiments, the ATPase domain of Hsp90a (a.a. 9–236) was expressed with an N terminal tag of 6 histidines in E. coli, and purified by nickel affinity chromatography by standard procedures. Subsequently, the tag was cleaved by incubation with PreScission protease, and an additional purification step was performed by gel filtration on a SDX 200 column. 2.3. Fragment library Compounds that were included in the fragment library were chosen based upon the commonly accepted ‘‘Rule of three’’. These criteria were previously proposed by Astex researchers for selecting suitable fragments (Congreve et al., 2003) to include in their library.

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Fig. 1. Structures of reported Hsp90 inhibitors tested in this study.

The compounds, belonging to the Nerviano Medical Sciences Fragment Library, have a molecular weight spanning from 150 to 300 Da. In case of fragments that contain halogen atoms, the upper molecular weight limit is extended to 380 Da. In addition, in the fragment library were included compounds with a number of heavy atoms below or equal to 22 and a predicted log P (A log P) < 3. The maximum number of hydrogen bond donors is three, whereas six hydrogen bond acceptor groups and six rotatable bonds are allowed. The maximum surface polar area is set to 80 Å2. Chemical reactive fragments, such as Michael acceptors or alkylating agents as well, were not included in the library. All the fragments were tested for identity by using 1H NMR and electrospray MS spectrometry. The concentration of the 100 mM DMSO stock solutions was determined by using a CLND detector coupled to a HPLC system (Kromidas, 2006). Solubility, stability, purity and aggregation of compounds were also assessed by NMR (SPAM filter) (Dalvit et al., 2006). The library used for MS screening consists of 1914 compounds and was tested against Hsp90a (a.a. 9–236) N-terminal domain. 2.4. Fluorescence polarization assay Reduced FITC-Geldanamycin (RFG) was used as probe in a Fluorescence Polarization (FP) assay. A commercially available FITC-Geldanamycin (InvivoGen) was reduced as elsewhere described (Lundgren et al., 2009) and conserved in aliquots at 80 °C. FP measurements were carried out at room temperature (RT) using black 384-well microplates (Corning Incorporated, Corning, NY) on a Tecan Safire2 reader with the excitation and emission respectively of 470 nm and 525 nm. RFG, at a final concentration of 0.5 nM, was titrated with different concentrations of Hsp90 in a binding experiment employing 20 mM HEPES pH 7.5, 50 mM KCl, 5 mM MgCl2, 1 mM DTT, 1 mM EDTA, 0.01% Triton X-100 as buffer and the signal was monitored over time. Experimental data were fitted using the quadratic equation for the saturation isotherm which takes into account the probe depletion due to binding to the protein Hsp90 (Copeland, 2005). The equilibrium was reached after 3 h of incubation and the signal was stable for at least 24 h. For competition experiments, a protein concentration of 5 nM was mixed with 0.5 nM RFG (final concentrations) and incubated for 3 h, subsequently the compound solution in 100% DMSO was added to the mixture at a final volume

of 80 lL (2% DMSO). To construct the competition curves the final compounds concentration in the assay was selected considering the inhibitor potency and was generally ranging from 10 lM to low nM with an appropriate dilutions pattern. The plate was incubated for 18 h at room temperature (RT) and then the FP signal was measured. Low and high control, prepared without protein and without compound respectively, were present in the plate. Data were fitted, as reported by Kuzmic (1996), with the program Dynafit version 3.28.039 (BioKin Ltd., Watertown, MA) or SigmaPlot (SSI, San Jose, CA) using the exact mathematical equation for competitive binding of two ligands to the receptor (Wang, 1995). 2.5. Surface plasmon resonance assay SPR analyses were performed using a BIAcore T100 (Biacore AB, Uppsala, Sweden). His-tag HSP90 N-terminal catalytic domain was immobilized in HBS-P+ on a Sensor Chip CM5 (GE Healthcare, Uppsala, Sweden) after amine coupling immobilization of an anti-His antibody. To avoid protein leakage during analysis one step of cross-linking of N-terminal His-HSP90 to anti-His antibody was performed with EDC/NHS. The reference surface was generated using the same procedure with the exception of the ligand injection step. Binding experiments were performed with the approach of the kinetic titration as previously described (Karlsson et al., 2006) in 20 mM Tris–HCl, pH 7.6, 150 mM NaCl, 0.05% (v/v) P20 (Tween 20), 5 mM MgCl2, 1% (v/v) DMSO. After 3 start-up cycles of buffer injections a fivefold concentration series of analyte were sequentially injected over both the Hsp90 and the reference surface. The reference surface was used to correct for instrument noise and drift. The data were fitted using the 1:1 kinetic titration model of BIAevaluation software. 2.6. NMR FAXS screening method Fluorine NMR experiments were carried out at 564 MHz, using an Inova 600 instrument (Varian, Palo Alto, USA) equipped with a 19 F–1H probe and with an autosampler. Samples for NMR screening were prepared in 50 mM Hepes buffer, pH 7.2, containing 100 mM KCl, 5 mM MgCl2, 10 lM EDTA and 8% D2O. A library of 300 fluorine-containing molecules was initially tested in mixtures (5–10 fragments in each mixture) against Hsp90 for the

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identification of potential spy molecules. Mixtures were tested at 50 lM concentration using 19F one dimensional T2 filter experiments recorded in the absence and presence of 1.5 lM Hsp90 and, as a result, FBA-11-021 was identified as a suitable spy molecule. In addition, a molecule that does not interact with the receptor was selected from the library of 300 fluorine (CF and CF3) compounds and used as control molecule. Typical screening samples against Hsp90 contained 0.016 mg/mL (0.6 lM) Hsp90 alpha (25,600 Da), 6 lM of the spy molecule FBA-11-021 (KD 7.5 lM, value measured using a competition binding FP assay), 6 lM of control molecule, and 50 lM (0.2% DMSO-d6) of the tested fragments. FAXS experiments were performed using the Carr–Purcell–Meibom–Gill (CPMG) spin-echo scheme (Carr and Purcell, 1954; Meiboom and Gill, 1958) with length of 240 and 480 ms before the acquisition period. Spectra were collected at 293 K using 128 transients. Intensity reduction of the signal of the spy molecule in the presence of the protein due to shortening of its transverse relaxation is a marker of the interactions of the molecule with the protein. Intensity recovery of the signal in the presence of a competitive ligand that displaced the spy molecule is an indication of specific binding. 2.7. ESI-MS sample preparation Protein aliquots were desalted on Microcon centrifugal filter devices (Millipore, Milan, Italy) by rinsing with distilled water, and diluted with 20 mM ammonium acetate buffer (pH 7.0) to a final concentration of 100 lM (2.5 mg/mL). Tested compounds (5 lM) were assessed against protein target (Hsp90 2.5 lM) in ammonium acetate buffer 20 mM (pH 7.0). All samples were prepared in duplicate and two measurements were performed on each one. In the screening, compounds of the fragment library were tested at 10 lM in mixture of five components. Starting from 10 mM ligand DMSO stock solutions, 5-component mixtures were prepared in a 96-well working plate at 2 mM concentration in DMSO. Next, ligand solutions were further diluted at 500 lM in DMSO. 1 lL of this solution was added to 50 lL of a solution 2.5 lM of Hsp90 in 20 mM ammonium acetate buffer in a 384-well plate obtaining the final samples that were analyzed by the flow injection method. 2.8. Mass spectrometry infusion method ESI MS spectra were recorded on a Q-TOF Ultima mass spectrometer (Waters, Manchester, UK) with positive ion detection by continuous infusion at 5 lL/min (Ammonium acetate buffer 20 mM, pH 7.0). A Speedivalve (Edwards, Crawley, UK) was installed on the mass spectrometer to manually adjust ion source pressure that was usually maintained at 2.5 mbar. Typical collision cell pressure was 3.0  105 mbar. Ions were generated under the following conditions: ESI sprayer voltage 2.0 kV, desolvation temperature 100 °C, source block temperature 60 °C, cone voltage 35 V, RF lens 1 35 V, and collision energy 5 V. The acquired mass range was 100–4500 m/z with scan duration set to 2 s, interscan delay of 0.1 s. 55 scans were combined for each spectrum. All the settings of ion optics region were optimized in order to preserve the non-covalent adducts generated in the ion source. The time-of-flight analyzer operated in V-mode. 2.9. Mass spectrometry medium throughput screening method (AFI-MS) Flow-injection ESI-MS analyses were carried out on a Q-Tof Ultima mass spectrometer (Waters, Manchester, UK) directly connected to an Agilent 1100 l-HPLC (Agilent, Palo Alto, USA) system

equipped with a micro volume autosampler. The connection was set by using a 1/3200 OD  0.003500 ID Peek tube (Upchurch Scientific, Oak Harbor, US) in order to reduce the dead volume between autosampler and mass spectrometer. Samples were analyzed (8 lL injection) by AFI-MS at 40 lL/min in 20 mM ammonium acetate buffer. The time between two successive injections was 120 s; this value was optimized in order to reduce carry over. Compared to the infusion method, ion source parameters were changed because the flow rate increased from 5 lL/min to 40 lL/min; desolvation temperature was set to 150 °C, source temperature 80 °C and spray voltage 2.5 kV. All the other parameters remain unchanged. Data reprocessing was automatically performed by Openlynx Software. 1914 compounds were assayed by AFI-MS method using 5-members mixtures, hits were then tested as single-compound for reconfirmation purpose. 2.10. Reprocessing settings Openlynx software (Waters, Milford, USA) automatically reprocesses the data of flow injection analyses. Five consecutive spectra, in the chromatographic region after the apex of the flow injection peak (0.1 min), were combined. A background subtraction was performed (polynomial order 1, below curve 40%) and next the combined spectrum was smoothed by using a mean algorithm (10 channels). Finally it was centered by area (8 channels, 80% profile peak) obtaining a centroid mass spectrum. Openlynx searches in the mass spectrum for the signal of the expected protein–ligand complex. Threshold mode was set to ‘‘absolute’’ therefore the signal must be above the confirmation threshold that was set to 300 counts in centroid spectrum. The size of the window to search for the entered molecular weight in the combined spectrum was 1.2 m/z (Mass Window). If the expected mass signal was found and fulfilled criteria for confirmation, the correspondent well will be flagged as green otherwise the well will be red flagged as shown in Fig. S1 (Supplementary material) where a software screenshot is reported. Data analyses variables are contained in a ⁄.olp file; results from data reprocessing, shown in the Openlynx browser, are instead stored in a report file (⁄.rpt). From the browser an EXCEL-readable file (⁄.csv), containing intensities of free and bound protein, is finally obtained and used for binding parameters determination. 2.11. Data analysis The fraction of bound protein was considered to evaluate the binding affinities of the different compounds (Wang et al., 2008).

Percentage of Bound Protein ð%BPÞ ¼ 100  IðPLÞ =ðIðProtein freeÞ þ IðPLÞ Þ ð1Þ where I(protein free) and I(PL) stand for intensity (peak height) of free and bound protein respectively. Data analysis was performed on the most abundant charge state of the protein, no deconvolution of mass spectra was done. The apparent dissociation constants (KDs) were directly determined from the MS spectrum following a procedure developed by Rosu et al. (2002) and calculated using Eq. (2):

K D ¼ ð½Proteinfree ½Ligandfree Þ=½PL

ð2Þ

Assuming that the response factors are the same for free protein and complexes, the concentration of the free and bound proteins were determined by the peak heights shown in the spectrum.

½Proteinfree ¼ ½Protein0 IðProtein freeÞ =ðIðProtein freeÞ þ IðPLÞ Þ

ð3Þ

F. Riccardi Sirtori et al. / European Journal of Pharmaceutical Sciences 76 (2015) 83–94

½PL ¼ ½Protein0 IðPLÞ =ðIðProtein freeÞ þ IðPLÞ Þ

ð4Þ

[Protein]0 is the initial concentration of the target. The concentration of the unbound drug was calculated by the mass balance equation (5):

½Ligandfree ¼ ½Ligand0  ½Ligandbound

ð5Þ

½Ligandbound ¼ ½PL

ð6Þ

For which [Ligand]0 is the total concentration of the ligand. 2.12. Assay performance evaluation The amount of bound ligand determined by AFI-MS method for the interaction between Hsp90 (2.5 lM) and compound 10 (10 lM) was monitored daily to control the performance of the mass spectrometry system over the time. Assay performance was evaluated following the Signal-to-Background ratio (S/B), Dynamic Range (DR), and Z0 factor. The following equations were used:

S=B ¼ X std =X blank

ð7Þ

DR ¼ ðX std  X blank Þ=ð3SDstd þ 3SDblank Þ

ð8Þ

Z 0 ¼ ð1  1=DRÞ

ð9Þ

where Xstd is the average percentage of bound protein determined for 10 and Xblank the average %BP determined for blank samples where only DMSO was added to the protein solution. In this case I(PL) corresponds to the intensity of the baseline. SDstd and SDblank are the standard deviations for compound 10 samples and blanks. 3. Results and discussion 3.1. Method set up and mass spectrometry tuning One of the requirements for the investigation of non-covalent ligand–protein adducts by mass spectrometry is that the complexes should not be dissociated upon transfer from solution to gas phase. A fine tuning of the instrument was performed to set

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up soft conditions in the ion source to prevent the dissociation of the complexes. Most of the signal is usually lost during this operation so a balance between complexes dissociation and signal loss must be found. Following the results previously described by Zenobi and coworkers, who reported the optimization of a Q-TOF Ultima instrument for detection of non covalent protein–ligand complex (Jecklin et al., 2009c; Wortmann et al., 2008), instrumental parameters were optimized. Among the different parameters considered (position of the probe spray, ion source and analyzer voltages, and source temperatures) cone and RF Lens 1 voltages proved to be the most critical. We investigated the influence of mass spectrometer settings on the interaction between Hsp90a (N-terminal domain) and the pyrazole derivative compound 10 (Fig. 2), a close analogue of the well known Hsp90 inhibitor CCT018159 (Cheung et al., 2005; Smith et al., 2006). Compound 10 was found bound to the N-terminal ATP domain by X-ray crystallographic studies. When this ligand was tested at the concentration of 5 lM the measured percentage of bound protein was close to 50%. In our opinion this is the ideal value for an initial setup of the mass spectrometer as it allows to better appreciate the influence of instrumental settings on the relative intensity of bound and unbound protein signals. On the other side, the use of a ligand with lower affinity for mass spectrometer tuning, would result in a signal of bound protein which would be close to the limit of detection of the system and this fact could affect the proper setup of the instrument. The KD determined by an independent fluorescence polarization method for compound 10 was 0.591 lM. At the beginning the apparent dissociation constants obtained by MS method using parameters not yet optimized for non covalent adducts (Cone Voltage 100 V, RF Lens-1 50 V) were different to those determined by FP assay as shown in Fig. 2. Moreover, there was a strong dependence between apparent KDs and charge states. This dependence was lost by decreasing ion source voltages (Cone Voltage 35 V, RF Lens-1 35 V) and the apparent dissociation constants became close to the FP value. Moreover, the percentage of bound protein was determined for the two main charge states separately (7+ and 8+) for several compounds with a wide range of affinity toward Hsp90 (0.0085–

Fig. 2. Effect of instrumental parameters on the mass spectra of Hsp90 (2.5 lM) in 20 mM ammonium acetate buffer after addition of compound 10 (CMP10, 5 lM) used as reference ligand. ESI-MS spectra were obtained using different settings: (A) cone voltage 100 V, RF lens 1 50 V and (B) cone voltage 35 V, RF lens 1 35 V.

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37.2 lM). As reported in Supplementary Table 1 no significant differences in the calculated %BP were found between the two charge states. No significant changes were observed when the vacuum in the ion source was increased to 5  101 mbar by closing the Speedivalve. Argon was present in the collision cell as cooling gas and its pressure was maintained low (3.0  105 mbar). All the applied voltages in the time-of-flight mass analyzer region were optimized to increase the mass spectrometer response, although causing a decrease in the instrument resolution. Finally, under optimized experimental conditions, the apparent KD, inferred from MS spectrum, became close to the value obtained by FP. During method setup, we also monitored the interaction with a compound more likely to represent a fragment screening hit such as ATP, that is reported to have a very low affinity for Hsp90 with a KD of 98 lM (Scheibel et al., 1999) and, as depicted in Table 1, the percentage of binding protein (%BP) measured was 6.0%, confirming the ability of this method to detect ligands with low affinity, at least up to 98 lM. It must be pointed out that an extensive desalting of the protein is mandatory to reduce the number of sodium adducts. In this work we used microcon centrifugal filter devices to reduce sodium interferences. In addition the dimethyl sulfoxide (DMSO) influence on the charge states distribution was investigated as the ligand stock solutions were prepared in DMSO and 2% of this solvent was present in the samples. After DMSO addition the main signal shifts to lower charge states.

3.2. Infusion method validation Different known Hsp90 ligands, with equilibrium dissociation constants (KDs) ranging from 40 pM to 100 lM, were selected and assessed at the concentration of 5 lM against the N-terminal domain of Hsp90 (2.5 lM) for the validation of the ESI-MS method. In this set, the following Hsp90 inhibitors (Fig. 1) were tested to validate our ESI-MS assay: the 17-allylamino-17-demethoxy-Geld anamycin (17-AAG) compound 5 (Schulte and Neckers, 1998), the isoxazole derivative AUY922 2 (Brough et al., 2008), the tetrahydro indazole SNX-2112 1 (Chandarlapaty et al., 2008), along with purine PU-3 4 (Chiosis et al., 2001) and compound 3 (Chiosis et al., 2002), and selected pyrazole derivatives 7–10 (Cheung et al., 2005; Smith et al., 2006). Moreover, compounds FBA-11-021 11 and FBA-12-062 12, previously identified by NMR FAXS screening performed against Hsp90 and shown by X-ray crystallography to bind to the N-terminal ATP-binding site were tested (Fig. 3).

Fig. 3. Structures of ATP-binding pocket ligands found by ESI-MS assay and previously identified by NMR FAXS technique.

Dissociation constants of these inhibitors were obtained by a fluorescence polarization assay. Compounds with high affinity for Hsp90, such as SNX-2212 and AUY-922, were characterized by SPR; due to the more favorable lower end limit of resolvable inhibitor potency of this technique it is possible to accurately measure the KDs for potent ligands. As shown in Table 1 the results showed an acceptable correlation in the rank ordering of ligand affinity obtained between the percentages of bound protein and the dissociation constants determined by condensed phase assays. Moreover we calculated the theoretical percentage of bound protein on the basis of the dissociation constants determined by fluorescence polarization. As depicted in Fig. S2 (Supplementary material) theoretical %BPs were aligned to those determined in ESI-MS experiments. The three subnanomolar ligands SNX-2212, AUY-922, and the purine derivative compound 3 showed a %BP of 100% indicating that all the protein is bound to the inhibitor. For most compounds the binding parameters determined by ESI-MS were consistent with KDs determined in solution. We observed for three pyrazole compounds 7, 9 and 10 a percentage of bound protein lower than the theoretical value calculated on the basis of dissociation constants determined by FP (Table 1). This evidence suggests that, for these compounds, a partial dissociation of non-covalent complexes could occur in the ion source. Moreover the two NMR hits FBA-11-021 and FBA-12-062 were correctly identified by the MS method and the %BPs agreed with equilibrium constants obtained by FP.

Table 1 Comparison between equilibrium dissociation constants (KD) determined with FP, SPR, and percentage of bound protein (%BP) obtained by mass spectra for Hsp90 inhibitors. Results were obtained by ESI-MS using Hsp 90 (2.5 lM) and ligands (5 lM). Theoretical %BPs were calculated on the basis of the dissociation constants determined by FP. All the %BP determinations were performed in duplicate. Compound

KD FP (lM)

SNX-2112 (1) AUY-922 (2) (3) (7) (8) (9) 17-AAG (5) (10) PU3 (4) ADP FBA-11-021 (11)

0.00077 ± 0.0002 0.00089 ± 0.0003 0.0085 ± 0.001 0.012 ± 0.002 0.0179 ± 0.003 0.313 ± 0.025 0.591 ± 0.113 1.55 ± 0.23 5 ± 0.3 7.5 ± 4.0

FBA-12-062 (12) ATP Novobiocin (6)

37.2 ± 5.0 103 ± 6.0 Not tested

KD SPR (lM)

%BP theoretical

%BP found

0.00073 ± 0.00015 0.00004 ± 0.00001

100 100 100 100 100 99 90 83 68 44 35

100.0 ± 0.0 100.0 ± 0.0 100.0 ± 0.0 88.5 ± 3.8 95.6 ± 0.9 86.3 ± 2.6 87.4 ± 0.1 61.0 ± 6.0 71.9 ± 0.8 34.0 ± 1.8 30.4 ± 1.1 KD = 6.5 ± 0.4 lM 17.2 ± 3.7 6.0 ± 0.3 7.9 ± 4.1

0.055 ± 0.002

8.8 ± 0.9

184 ± 27

11 5

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All the results above reported were determined on single point concentration; to investigate the reliability of the method a dose– response experiment was performed. We determined the dissociation constant of FBA-11-021 by titration of the protein (2.5 lM) with ligand in the range from 1 to 100 lM and the obtained KD was 6.5 ± 0.4 lM (Fig. 4). The KD value determined by FP was 7.5 ± 4.0 lM, confirming a good agreement between the two procedures. Although the concentration of Hsp90 was accurately determined by titration with a tight binder (AUY-922), as described by Wortmann et al. (2008) the curve approaches an asymptotic value that is below the theoretical concentration of the protein (2.5 lM), behavior that was previously reported also by Vivat Hannah et al. (2009) and could be explained by a partial dissociation of the non-covalent protein–ligand complex in the gas phase during ionization process. Finally the sensitivity of this method, within the experimental condition used, was assessed to be in the high micromolar range, confirmed by the identification of ATP that has been reported to have an affinity of approximately 100 lM. 3.3. Setup and validation of automated flow injection method (AFI-MS) After verification of reliability of ESI-MS approach applied to Hsp90, we set up a medium-throughput method to investigate interactions of biopolymers with NMS proprietary fragment library that consists of about 2000 fragments. Compared to the previously described medium to high throughput methods, commonly based on infusion (Gao et al., 1996; Greig and Robinson, 2000; Maple et al., 2012; Vallee et al., 2011; Vivat Hannah et al., 2009; Wigger et al., 2002), our procedure is substantially different and makes use of a flow injection operation mode. The samples are injected directly in a microflow (40 lL/min) by an autosampler, and then they are readily transferred to the mass spectrometer for ESI-MS analysis. In addition, neither specific nor expensive devices are required as in case of the automated chip based nanoESI system. This method can be implemented using standard HPLC systems of last generation that are able to generate flowing carrier stream in this flow range. Different instrument conditions were tested in order to set up the AFI-MS screening method for this protein target. HPLC flows from 10 lL/min to 80 lL/min were tested in order to find the optimum flow rate that could readily transfer the sample to the ion source avoiding sample dilution in the HPLC stream. We found that 40 lL/min is a good compromise between analysis time and

Fig. 4. Titration curve obtained for ESI-MS using Hsp90 (2.5 lM) titrated with increasing concentrations of FBA-11-021 (11). The concentration of [PL] complex is plotted against ligand concentration. The dissociation constant determined is 6.46 lM and it is in agreement with the value of 7.5 lM determined by fluorescence polarization.

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sample dilution. As depicted in Fig. S1 (Supplementary material), in AFI-MS assay, 8 lL of sample were injected and the correspondent flow injection peak eluted at 0.4 min; the peak width at base was 0.3 min (12 lL), confirming that dilution of protein sample in the HPLC flow is minimum. Although the apex of the flow injection peak reached the detector in about 20–25 s, analysis time was set to 120 s in order to avoid carry over between samples. Compared to the infusion method, the mass spectrometer parameters were changed because the flow rate increased from 5 lL/min to 40 lL/min and for this reason the source and desolvation temperature were increased from 60 °C/100 °C in infusion to 80 °C/150 °C in flow injection analyses. A key feature of our method is the full automation of data processing; the software OpenLynx (Waters) was used to automatically analyze the raw data and to identify non-covalent adducts on the basis of ligand molecular weight. A particular attention was dedicated to Openlynx setup. As a matter of fact software reprocessing parameters (considered time range, smoothing channels, background subtraction, centroid settings, and confirmation threshold) greatly influenced the correct identification of the non-covalent complex. All the measurements were performed on the most intense charge state (7+) without using any deconvolution algorithms. The same set of compounds used to validate the infusion method was tested by AFI-MS and the observed percentages of bound protein were compared to those previously determined. Interestingly, in AFI-MS conditions it was observed an increasing of dissociation of non-covalent complexes, possibly due to the higher source temperatures and voltages used, problem that was solved by increasing ligand concentration to 10 lM, achieving in these conditions a better correlation of data (Fig. S3, Supplementary material). As depicted in Fig. S4, the %BP determined by AFI-MS showed a worse correlation with values observed by fluorescence polarization technique, indicating that this methodology does not reproduce binding data as well as infusion. However, it should be pointed out that AFI-MS is a qualitative method and the aim of this approach was to quickly identify hits. Found ligands will be reconfirmed by more accurate ESI-MS infusion experiments and solution phase methods such as FP or SPR. 3.4. Hsp90 screening The screening of NMS fragment library against Hsp90 was performed using AFI-MS. 1914 compounds were assayed, using 5-member mixtures, in 384-well microplate format (2.5 lM protein–10 lM compounds) and reprocessing was automatically done by Openlynx. Potential Hsp90 ligands were automatically identified by the software when a signal of sufficient intensity (300 counts in the centroid spectrum) was present at the expected molecular weight for the Hsp90–ligand complex. This threshold corresponds to about 5–10% of the free protein signal (about 4–6000 count/s). Fig. S1 (Supplementary data) depicts an example of a 5-members mixture assayed by AFI-MS; one component showed an affinity for Hsp90 and the correspondent adduct at 3719.4 m/z was correctly identified by software. The amount of bound protein determined by AFI-MS method for the interaction between Hsp90 (2.5 lM) and compound 10 (10 lM) was monitored to control the performance of the mass spectrometry assay over time. Pyrazole derivative 10 was chosen as reference compound due to its affinity for Hsp90 (%BP = 80%) that allows to better appreciate changes in instrument response. In fact higher affinity ligands are avoided because they strongly interact with protein giving a %BP of 100% with no free protein signal present in the spectrum. In this case, due to the high stability of these protein–ligand complexes, small changes in instrument

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performance do not affect the determined %BP. Fig. S5 (Supporting information) depicts the amount of bound protein determined over 60 days. The average determined percentage of bound protein was 76.8% and the standard deviation was 4.7%, confirming a good stability of the instrument response over the considered period of time. Comparing results obtained for set of standard samples (compound 10) with blank samples we were able to determine a Signal to Background ratio (S/B) of 21.9 and a Dynamic Range (DR) of 3.9. The calculated Z-factor (Z0 ), that gives an assessment of assay quality (Zhang et al., 1999), was 0.77, confirming the satisfactory performance of this method. 282 compounds were found as possible hits by the primary screening carried out on 5-members mixture. It is noteworthy that the signal intensity threshold for hit identification was maintained low in the primary screening to reduce the number of false negative in this step. On the other hand, working with ligand mixtures, a high number of false positives is expected because the baseline noise is higher. Furthermore, in 34 cases, instrument resolution and accuracy are not sufficient to univocally identify in the mixture the compound that interacts with Hsp90. In these cases more than one component in the mixture was selected to be further assayed. One of the possible issues, using multicomponent mixtures, is that high affinity ligands could prevents the binding of weak hits that interact with the same site. However, this problem is minimized as this methodology is applied to fragment based library whereas the expected percentage of bound protein is usually low. Whenever the obtained %BP, for a component of the mixture, was found above 20% all the components were tested as single compounds. The confirmation threshold was calculated as the mean %BP of the blanks incremented by the three-fold standard deviations of the blanks. Considering that the average %BP determined for blank samples was 2.7%, and the associated standard deviation 0.8%, a reconfirmation threshold of 5.1% was considered. All putative hits (282 compounds) were retested as single component and 146 of them were reconfirmed by AFI-MS method with a hit rate of 7.6% (Supporting information, Supplementary Table 2). Fig. S6 (Supplementary material) shows the distribution of binding results for confirmation step. Apparent KDs, estimated on the basis of ESI-MS data, were in the range from 20 to 179 lM. AFI-MS was successfully applied to the screening of the NMS fragment library against the N-terminal domain of Hsp90.

Five-component mixtures were tested in order to increase assay throughput, allowing the completion of the screening in 2 days. Plate reformatting and reconfirmation analyses required two additional days, proving that this technique allows a relatively high throughput and a limited sample consumption, since the total amount of protein was about 2 mg. 3.5. Competitive binding experiments Competitive binding experiments were performed to identify ligands that specifically interact with the ATP binding site of Hsp90. In fact the ESI-MS assay described in this paper is a direct binding method and every ligand that binds to the protein is identified as ‘‘hit’’. Hence, to understand the binding mode, a further characterization is necessary. The competition assay took advantage of the use of AUY-922 a well characterized Hsp90 inhibitor reported to bind at the ATP binding site, as shown by co-crystallization study (Brough et al., 2008), with a subnanomolar KD (Table 1). In our experiments 2.5 lM Hsp90 was mixed to 10 lM of tested ligand in presence or absence of AUY-922 at 5 lM concentration. Preliminary competition experiments were carried out by using a panel of known ATP competitors (pyrazole derivatives 9 and 10, 17-AAG, FBA-11-021) previously tested during validation of flow injection method. Whenever the potent inhibitor AUY-922 (KD = 0.77 nM determined by FP method) was added to a solution containing these inhibitors a complete displacement of the weaker ligand was observed. As depicted in Fig. 5, only the non-covalent complex [Hsp90–AUY-922] was present in the MS spectrum after the addition of AUY-922 to a solution containing 17-AAG (KD = 0.313 lM) confirming that the two ligands compete for the same site. Novobiocin was employed in this study as negative standard. As shown in Fig. 6, after the addition of AUY-922 a ternary complex [Hsp90–novobiocin–AUY-922] was detected with an intensity of about 10%, likely due to unspecific interactions. All the reconfirmed compounds were tested in this competition assay in presence of AUY-922. Hits with a %BP below the confirmation criterion (%BP < 5.1%) after the addition of AUY-922, were classified as ATP competitor (marked as ‘‘yes’’ in Supplementary Table 2) and prioritized respect to the others for further investigation by the FP based

Fig. 5. Competition experiments on Hsp90 performed by using 17-AAG (5) and the higher affinity ligand AUY-922 (2). Both compounds are known to bind to the ATP binding site of Hsp90. ESI-MS spectra of Hsp90 (2.5 lM) in presence of 17-AAG (5, 5 lM) before (A) and after the addition of AUY-922 (2, 5 lM) (B) are reported.

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Fig. 6. Competition experiments on Hsp90 performed by using novobiocin (6) and AUY-922 (2) that is described to bind to the ATP binding site of the N-terminal domain of Hsp90. Novobiocin was used as negative standard because it is known as a C-terminal Hsp90 ligand. ESI-MS spectra of Hsp90 (2.5 lM) in presence of novobiocin (6, 5 lM) before (A) and after the addition of AUY-922 (2, 5 lM) (B) are reported.

displacement assay. Five of these ligands were classified as ATP-competitors, although at this point we cannot unequivocally rule out the possibility that AUY922 could displace them by an allosteric mechanism. Nevertheless most of these hits, previously identified by NMR FAXS experiments and X-ray crystallography studies performed at NMS, confirmed the binding to the ATP pocket of Hsp90 (Casale et al., 2014). Moreover, as reported in Table 2, a fluorescence polarization method was used to determine equilibrium dissociation constants for these compounds and KD values were aligned to %BP obtained by AFI-MS determinations over a wide range of affinities (7.5–181 lM, see Table 2). The obtained hit rate (7.6%) was higher than other biophysical techniques used in FBDD and in addition only 5 of the initial 146 identified were identified as ATP competitors. This is likely due to the fact that ESI-MS is a direct binding method able to probe all protein surfaces, allowing in this way the discovery of ligands that interact, in addition to the investigated active site, also through other binding sites such as allosteric cavities. However, we cannot exclude that unspecific adducts could be formed in the ion source during ionization process leading to false-positive results, and the formation of non specific complexes was described in previous papers (Maple et al., 2012; Mathur et al., 2007; Peschke et al., 2004) and is a limitation of this approach. Considering these facts, among the hits identified, it is important to discriminate between the different possible mechanisms of inhibition (i.e. competitive, allosteric) and to highlight unspecific adducts. Using competitive binding experiments, it is possible to distinguish between ATP competitors and compounds with other mechanisms of action, including unspecific ligands.

Theoretically we could increase the detection limit to hits with lower affinity by increasing the initial ligand concentration, since the dynamic range of ESI-MS assay is a function of the initial ligand concentration as already described by Maple et al. (2012). We performed the screening on Hsp90 at 10 lM in order to reduce the formation of unspecific adducts in the ion source, phenomenon that is known to be concentration dependent (Smith et al., 1992; Sun et al., 2007, 2006). These results confirm the reliability of ESI-MS approach; in fact the Hsp90 ligands identified by AFI-MS were also found by solution phase techniques (NMR FAXS, X-ray, FP) with similar binding affinities. Among the identified hits, the novel Hsp90 ligand FBA-12-062 (KD = 37.2 lM determined by FP) paved the way to the design of a class of potent [1,2,4]triazolo[1,5-c]pyrimidine derivatives as Hsp90 modulators (Casale et al., 2014). 3.6. Comparison with NMR results In Nerviano Medical Science a NMR FAXS screening on Hsp90 was performed before the setup of ESI-MS approach. The FAXS methodology (Dalvit et al., 2003, 2002) initially requires the identification of a suitable fluorinated spy molecule that is then used for screening of a FBA library of approximately 1200 compounds. 12 out of the 14 hits identified by NMR were also detected by AFI-MS (Table 3), either during the screening or later on for those compounds not originally included in the ligand mixtures tested, confirming the possibility to use AFI-MS as screening methodology applied to fragment-based drug discovery. Two hits (FBA-11-036,

Table 2 ATP-binding pocket ligands found by AFI-MS assay (competition experiments) and previously identified by NMR FAXS technique. Ligand FBA-16-006 FBA-14-076 FBA-11-021 FBA-12-062 FBA-14-077

(15) (16) (11) (12) (17)

KD FP (lM)

SD (lM)

Percentage of observed bound protein

ATP competition

28.9 37.3 7.5 37.2 181.9

8.6 15.9 4.0 5.0 66.8

29.7 19.8 16.7 13.5 9.1

Yes Yes Yes Yes Yes

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Table 3 Comparison of the hits identified by NMR and ESI-MS methods. MIX 5 indicates hits obtained by testing five members mixture whereas MIX 1 corresponds to compounds assayed as single component. Some of the NMR Hits were individually tested by ESIMS as they were not initially included in ligand mixtures used in the screening. Ligand

NMR Hit

FBA Library FBA-19-048 FBA-19-026 FBA-14-077 FBA-14-076 FBA-19-083 FBA-11-036 FBA-16-003 FBA-12-062 FBA-21-042 FBA-21-039 FBA-21-037 FBA-21-038 FBA-21-035 FBA-21-036

Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes

ESI-MS Hit MIX 5

MIX 1

Yes Yes Yes Yes Yes No Yes Yes Not Not Not Not Not Not

Yes Yes Yes Yes Yes No Yes Yes No Yes Yes Yes Yes Yes

tested tested tested tested tested tested

FBA-21-042), previously found by NMR, were not identified by the mass spectrometry assay, possibly due to the low affinity of these ligands.

not available. It is noteworthy that it is possible to set up this procedure using standard HPLC equipments and top of the range mass spectrometers are not required. Moreover, the successful establishment of an ESI-MS based displacement assay paves the way to the possibility to develop a new screening assay based on this concept. Acknowledgements First and foremost, the authors would like to thank Sergio Mantegani (Nerviano Medical Sciences) for his strong support to this work and for thoroughly reviewing this paper providing valuable feedbacks. The authors thank to Gaia Sanga (Nerviano Medical Sciences) for initial cloning of Hsp90 constructs and Barbara Valsasina (Nerviano Medical Sciences) for protein characterization. Fabio Zuccotto is acknowledged for his contribution to the construction of fragment-based chemical library and Riccardo Corigli (Nerviano Medical Sciences) for collecting LC-MS, UV, and CLND data. The authors also thank Eduard Felder, Elena Casale (Nerviano Medical Sciences), and Giancarlo Aldini (Università degli Studi di Milano) for helpful discussions and support of the project. Appendix A. Supplementary material Supplementary data associated with this article can be found, in the online version, at http://dx.doi.org/10.1016/j.ejps.2015.05.001.

4. Conclusions References Non-covalent complexes have been investigated by ESI-MS over the past 20 years and encouraging results were reported on the capability of this technique to measure target–ligand binding properties. Nevertheless, there is still a skepticism that non covalent complexes detected in the gas phase by mass spectrometer are not indicative of complexes formed in solution, is still present. In this work the reliability of our approach was verified comparing affinity data obtained by ESI-MS with those determined by solution phase method (FP, SPR) on Hsp90 protein, confirming that once the method is properly set for a specific protein, it can be used to screen a library of molecules of different affinities and high molecular diversity. In conclusion, AFI-MS proved to be a fast and reliable method, suitable to be used to rapidly screen fragment libraries of different sizes. This method is able to identify fragments with KD in the high micromolar range whereas other techniques are able to discover hits in the millimolar range. However, weaker hits could be found by increasing ligand concentration considering the expected high solubility of fragments. On the other side AFI-MS showed several advantages; in most cases no ligand deconvolution is necessary because the molecular weight of the complexes acts as intrinsic label. This approach can be applied to any biomolecular target such as nucleic acids, proteins, oligosaccharides and glycopeptides, allowing a rapid identification of low molecular weight, low affinity hits, due to the high sample capacity associated with a limited consumption of target protein. The high number of found hits, mostly due to unspecific adducts formed during the electrospray process, could be considered a weakness of this approach. This issue can be overcome by performing displacement experiments with a known strong binder; in this way it is possible to identify compounds that specifically interact with the active site of the protein and discard ‘‘false’’ hits. These features suggest this method as a valuable alternative to other techniques frequently used to screen fragment libraries, especially when expensive technologies such as NMR and SPR are

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