Detection of Drug Binding to a Target Protein Using EVV 2DIR Spectroscopy

Hugh Sowley†, ZhiQiang Liu‡, Julia Davies†‖, Robert Peach§, Rui Guo†‼, Sophie Sim†, FengQin Long‡, Geoffrey Holdgate¶, Keith Willison†, Wei Zhuang‡, David R Klug†*

†Department of Chemistry, Imperial College London, SW7 2AZ, UK. § Department of Mathematics, Imperial College London, SW7 2AZ, UK. ¶Hit Discovery, Discovery Sciences, IMED Biotech Unit, AstraZeneca, Macclesfield, UK. ‡State Key Lab of Structural Chemistry, Fujian Institute of Research on Structure of Matters, CAS. ‖Current address, Department of Chemistry, University of Leicester, University Road, Leicester, LE1 7RH, UK. ‼Current address, Department of Chemistry, University College London, Gower Street, London, WC1E 6BT, *Corresponding Author d.klug@imperial.ac.uk

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Abstract

We demonstrate that Electron-Vibration-Vibration Two Dimensional Infrared Spectroscopy (EVV 2DIR) can be used to detect the binding of a drug to a target protein active site. The EVV 2DIR spectrum of the FGFR1 Kinase target protein is found to have ~200 detectable crosspeaks in the spectral region 1250 - 1750cm-1/2600 - 3400cm-1, with an additional 63 caused by the addition of a drug, SU5402. Of these 63 new peaks, it is shown that only 6 are due to protein-drug interactions, with the other 57 being due to vibrational coupling within the drug itself. Quantum mechanical calculations employing density functional theory are used to support assignment of the 6 binding-dependent peaks, with one being assigned to a known interaction between the drug and a backbone carbonyl group which forms part of the binding site. None of the 57 intramolecular coupling peaks associated with the drug molecule change substantially in either intensity or frequency when the drug binds to the target protein. This strongly suggests that the structure of the drug in the target binding site is essentially identical to that when it is not bound.

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Introduction

One of the fundamental requirements in the drug discovery process is the ability to detect the presence of a drug in a protein target binding site. Beyond this there is a need to verify the location of the drug, determine the contacts made between drug and protein and to calculate the geometry of the drug-protein complex. A wide range of techniques are used for these purposes, usually focussed either on the detection of binding, verification of the site or determination of the structure of the complex1-3. A typical drug development campaign can involve the synthesis of 10,000 molecules. Ideally, structural information would be obtained for many of the synthesised molecules and, in the case of fragment-based drug discovery where the fragments for each potential drug series needs to be elaborated, the chemical elaboration achieved through synthetic chemistry is ideally designed on the basis of structural information. Despite the power and utility of the suite of methods currently used for these analyses, there are many cases where practical limitations mean that the desired structural information cannot be retrieved in sufficient quantity (not enough structures for each step of drug development), with sufficient precision (ambiguity in the structural data), or even at all using existing techniques. This includes for example, cases where the protein cannot be crystallised, where the crystal structure has regions of disorder which cannot be resolved, where the precision of the structure at ligand contact is insufficient for driving the drug discovery process, where the protein is hard to produce in sufficient quantities or where the region of interest in the protein is relatively unstructured in its native condition. More quantitatively, there are over 100,000 macromolecular structures in the Protein Data Bank. Of these, 69% have strings of 3 or more missing amino acid residues4. The limitations of existing structural approaches are also true when it comes to probe molecule discovery and validation, as well as non-human ligand-protein interactions such as in pesticides or weedkillers. As a consequence, there continues to be a need for new and complimentary approaches to the detection and analysis of ligand-protein interactions.

Spectroscopic methods are, in principle, attractive approaches for developing general assay methods which are sufficiently competent in binding detection, quantification of binding, site verification and structural analysis. In particular, variants of two-dimensional nuclear magnetic resonance (2DNMR) spectroscopy are used successfully for structural analysis5 and a range of optical spectroscopies are used for binding detection, often in a fluorescence assay format. 2DNMR methods are used successfully in drug discovery6, but in general do not have the sensitivity or throughput to be used as a screening method for analysing drug binding7, whilst optical spectroscopies do not, in general, have sufficient structural competence to be used for structural analysis. Despite the relatively limited use of optical methods in analysing protein structure, the development of two-dimensional infrared (2DIR) spectroscopies over the past decade8-12 raises the question as to whether this family of vibrational spectroscopies could have both sufficient discrimination power and sensitivity to be used both for the detection of drug binding and, ultimately, determination of the binding geometry.

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Amongst the variants of 2DIR spectroscopy that have been explored, one variant is known either as Electron-Vibration-Vibration 2DIR (EVV 2DIR) spectroscopy (due to its measurement of the coupling of electrons to the vibrational coupling), or Doubly Vibrationally Enhanced (DOVE) Four Wave mixing spectroscopy(4-21). The first experimental embodiment of EVV 2DIR was described by Zhao and Wright in 1999 and has more recently been shown to be capable of determining the geometry between interacting chemical groups to a high level of precision and accuracy in model systems(18,

20, 21). Whilst these findings are promising, an outstanding question is whether data of useful quality can be obtained from more complex systems, such as the ligand-protein interactions caused by the binding of drugs to drug targets. In particular the question is whether it is possible to firstly detect the presence of a drug bound to a protein binding site, secondly identify ligand-protein contacts and finally determine the geometry of interaction. It is this first question that we address in this paper. We also illustrate the first steps towards answering the question as to whether contacts can be identified too.

One of the potential advantages of 2DIR spectroscopies in the context of ligand binding, is that the spectroscopic features analysed are essentially that of chemical groups and vibrationally coupled chemical groups. Most drug and drug-like molecules contain chemical groups that are not found naturally in proteins and hence they have the potential to stand-out from protein features when sought in a relatively decongested two-dimensional spectroscopic space such as that created by 2DIR spectroscopies in general, and by EVV 2DIR spectroscopy in particular. Thus there is the potential of being able to detect and analyse small molecule drug binding to proteins without having to go through the process of isotope labelling or crystallisation.

To evaluate the ability of EVV 2DIR spectroscopy to detect drug binding, we explore the situation in a real drug target: the protein kinase known as FGFR1 and one of its known ligands, SU5402. Kinases are a family of regulatory proteins which modify the behaviour and function of other proteins by phosphorylating specific amino acids. These kinases are an important class of drug target, with over 500 kinases organised into a range of sub-families and over 20 small molecule kinase drugs currently approved for use. One of the major limitations in developing new drugs affecting kinase function, is the difficulty in achieving specificity; drugging the ATP binding site found in all kinases yet, still allowing the targeting of individual kinases or smaller subgroups. Many of the small molecule inhibitors of kinase activity, including those drugs already in use, are not selective for a particular kinase but hit multiple family members and this selectivity challenge frequently prevents known kinase targets from being exploited23. There is thus a great deal of interest in being able to rapidly determine modes of binding and the structure of potential drugs in the ATP binding site.

In the work presented here, we show that even in the most congested part of EVV 2DIR spectral space, in the vicinity of the overtone coupling region, it is possible to identify spectral features that are only present when SU5402 is specifically bound to its target protein. We also demonstrate two independent methods for verifying the specificity of binding and show that the stoichiometry of binding is broadly as expected and use a counter example of Bovine Serum Albumin, which does

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not have a binding site for SU5402. Finally, we use quantum mechanical calculations of the vibrational couplings in the binding site, in the presence of the bound drug, to identify the binding-dependent features. From this we are able to assign at least one contact, demonstrating the potential for calculation to be used as an assignment tool even in a chemical system as complex as a drug bound to a protein.

Methods

Protein sample preparation

100µM FGFR1 kinase domain construct was buffer exchanged and concentrated using centrifugal concentrators (Corning Spin-X UF 30k MWCO) from a storage buffer of 40mM HEPES, pH7.5, 200mM NaCl, 1mM TCEP to a final solution of 1mM, 5 mM phosphate buffer, pH8.0, 5 mM NaCl. Lyophilized powder of BSA (heat shock fraction, Sigma Adrich) was dissolved in 5 mM phosphate buffer, pH8.0, 5 mM NaCl, to achieve a 1mM concentration. 2%/vol additions of SU-5402 solutions in DMSO (or pure DMSO) were made to samples of the 1mM protein solutions to yield final FGFR1 solutions contain 0 mM, 0.5 mM, 0.75 mM, 1 mM, 1.5 mM and 2 mM SU-5402 and BSA solutions containing 0mM and 1mM SU-5402. For EVV 2DIR experiments, 1 μL droplets for each protein solution were deposited onto a 1” Ø circular coverslip along with 8 2 μL droplets of saturated NaCl solution. By mounting the 1” Ø circular coverslip in a 1” Ø lens mount followed by a ¼” thick 1” Ø rubber O-ring and a 2 mm thick 1” Ø CaF2 window, a sealed volume could be created between the coverslip and the CaF2 window with a controlled humidity of 75.5% RH, mediated by the saturated NaCl solution spots. The protein droplets dried slowly under these humidity controlled conditions to form flat, hydrated gel-phase structures, similar to the coffee-ring structures previously reported to be formed by a similar approach(22). The height of each gel spot was measured to be approximately 10µm using a digital micrometre.

EVV 2DIR Spectroscopy

As EVV 2DIR spectroscopy is relatively unfamiliar, we provide a brief description of its workings here. The technique measures the coupling of a one quantum (fundamental vibration) transition to a 2 quantum (combination band or overtone) transition. If the combination band which is excited contains the one quantum transition which is also excited, then Raman scattering between the two levels is an allowed transition. The visible beam therefore effectively probes the coupling between the two excited vibrations, one of which is a vibrational fundamental frequency and one of which is a combination band or overtone. The spectra produced have columns of features corresponding to fundamental transitions which couple to many other vibrations. It also has diagonal features which are in effect lines where the second one quantum transition which is contained within the combination band is constant. The frequency of the second vibration within the combination band is easily estimated by subtracting the frequency of the one excitation beam, , from that of the

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second excitation beam, β. This assumes that the frequency shift in the combination band due to the coupling itself is small or negligible, which is not always the case.

A more detailed explanation of the underlying physical principles behind EVV 2DIR, including the relevant four wave mixing diagrams can be found in the references7, as well as an illustration of

some of the less well-known properties of the technique17.

EVV 2DIR Spectrometer

The experimental setup of EVV 2DIR spectroscopy, as performed here, has been described in detail elsewhere12. In brief, an ultrafast Ti:sapphire laser system (Newport Spectra-Physics) is used to generate a near-IR laser beam at 790 nm with a pulse duration of 1 ps and a repetition rate of 1 kHz. The generated beam is split into three arms, two of which drive optical parametric amplifiers (Newport Spectra-Physics) to produce tunable mid-IR 1ps outputs calibrated using a 38 μm thick polystyrene calibration film traceable to NIST 1921b frequencies. All three beams are linearly polarized parallel to the plane of propagation (PPP), spatially overlapped, and focused at the sample. The pulse energy of the 790nm beam is set to 300 nJ at the sample, and the mid-IR beams display near-symmetric energy profiles across an ωα/2πc range from 1250 to 1750 cm−1 (Emax = 800 nJ at 1500 cm−1) and an ωβ/2πc range from 2600 to 3400 cm−1 (Emax = 2.0 μJ at 3000 cm−1). These pulse energies are measured through a 100 μm diameter pinhole as it closely matches the 1/e2 diameter of the near-IR beam, which defines the sample area from which the FWM signal is generated. Delay stages are used to achieve temporal control of the laser pulses. The temporal order of the pulses used was ωα→ωβ → ωγ, leading to the coherence pathway described in Figure 1. The emitted FWM signal is detected using a photo- multiplier detector (Hamamatsu H7422-50), with the input beams being filtered out. The experiment in enclosed and purged with N2 to achieve a relative humidity below 3%. The EVV 2DIR spectra reported here were all obtained using pulse time delays of ταβ = 1.75 ps and τβγ = 1 ps. These time delays were chosen so as to provide maximum contrast for the most important features of the spectrum, whilst still keeping the non-resonant background low enough to be able to see the smaller, less intense features clearly.

Spectra were collected with a mid-IR frequency step size of 5 cm−1, and an acquisition rate of 100 laser shots per data point. The spectra had any mid-IR independent background subtracted, were smoothed with a nearest neighbour average smoothing filter and the spectral intensities normalised by the intensity of the methylene peak. All spectra shown here are plotted on a logarithmic intensity scale. When producing difference spectra, the spectra were first square rooted, then subtracted, as the signal intensity is proportional to the square of the sample concentration.

2D fitting of the Spectrum

Fitting was performed in MATLAB using a non-linear least squares routine to fit the data with a sum of 2D Gaussians, restricted to having equal x and y variances. The fitting requires an initial input of

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the Gaussian parameters. Initial locations for the peaks were chosen manually. Initial signal intensities were taken to be the spectral intensity at the initial locations, and the initial widths taken to be the spectral width of the mid IR laser pulses (25cm-1).

DFT Calculations and EVV 2DIR Simulations.

DFT calculations were performed using the 6-31G (d, p) basis set using GAUSSIAN 09. The calculations of the EVV 2DIR peaks from the vibrations of the model were made in accordance with the method reported by Kwak et al16 and applied in our previous work on model systems(12, 17, 18)7. A frequency factor of 0.96 was used to produce the frequencies seen in the calculated EVV 2DIR spectra. The calculated peaks were dressed with a width of 25cm-1 FWHM to correspond with the typical widths seen experimentally.

The spectrum was calculated for the FGFR1/SU5402 system using a model based on the co-crystal structure reported by Mohammadi, M. et al.33 and contained only the protein residues within 5Å of the SU5402 molecule. Methyl groups were added to terminate unsaturated parts of the model, and a water molecule was included which was within the 5Å range.

Results and discussion.

The objective of this paper is to demonstrate the development of a set of protocols that allow us to identify one or more EVV 2DIR peaks that are definitively correlated with binding of a drug to a protein active site. This requires identification of features that are not present when the protein or drug are measured independently or when the drug is mixed with a protein for which no specific binding site exists. As it proved impossible to generate a spectrum of SU-5402 in pure water due to aggregation of the drug, a background of a non-binding control protein is used at a 1:1 stoichiometric ratio as with the target protein. This allows the spectrum of unbound SU5402 to be deduced.

In this work we use the protein Bovine Serum Albumin (BSA) as the control protein and create difference spectra by subtracting the protein-only spectrum from that of the drug mixed with the target protein. This allows us to identify peaks that are only present in the case of specific binding, as a means of identifying binding-specific peaks. An alternative would have been to have compared the spectrum when it the presence of organic solvent, however we were unable to obtain good spectra for SU5402 from these. Whilst there are drugs that can bind specifically to BSA, most do not, but instead attach themselves to multiple locations on the surface with low binding affinity. Heuristically, our finding here is that SU5402 falls into the category of non-specific binding. An additional and independent method for assigning binding-specific peaks is to titrate the drug into the FGFR1 protein binding site and demonstrate the expected difference in titration curves between binding-dependent peaks and peaks that are independent of binding. This provides two

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independent methods for assigning peaks to the interaction between the drug and the target protein. It is noteworthy that both independent methods identify the same six peaks as being due to specific binding of SU5402 to FGFR, whilst the other 57 peaks dues to the presence of the drug are presumably dominated by intramolecular couplings.

Finally, we provide an interpretation of the binding-specific features, by using quantum mechanical calculations of the vibrational couplings in the binding site and showing how these correlate with the binding-dependent observations.

EVV 2DIR spectra were measured both for pure FGFR1 and containing 1mM SU540232. These can be seen in Figure 1A and B respectively, along with their difference spectra which were produced by subtracting the square root of the protein only spectrum from the square root of the protein with inhibitor spectrum. Roots have to be taken to make the spectra linear in concentration, as the signals are homodyne and are proportional to the square of the molecule number. The EVV 2DIR data shown here typically has a dynamic range of ~450.

A combination of inspection and fitting reveals that the FGFR1 protein spectrum (Figure 1A) contains ~ 200 peaks which have a maximum amplitude at least 3σ above the noise floor, where σ is the standard deviation of the feature-free regions of the spectrum. The BSA protein spectrum contains a similar number of identifiable peaks. It is worth noting that this specification of statistical validity is reasonably stringent. Signal averaging within the area of a peak provides greater signal averaging than the peak maximum alone, therefore, it is likely that all of the peaks identified are real.

The protein spectra contain some features which have already been assigned in previous work(15,

16)25. For example, the two largest spectral features seen at ωα = 1470 cm-1 / ωβ = 2945 cm-1 and ωα = 1640 cm-1 / ωβ = 3300 cm-1 correspond to methyl/methylene and amide I bands respectively. Features arising from phenylalanine side chains can be seen at ωα = 1470 cm-1 / ωβ = 3050 cm-1 and ωα = 1480 cm-1/ ωβ = 3070 cm-1 along with a tyrosine peak can at ωα = 1530 cm-1 / ωβ = 3130 cm-1. The most relevant features for the purposes of this paper however are the peaks that are visible in the SU5402 + FGFR1 spectrum but not detectable in the BSA + FGFR1 spectrum and the amide-associated features centred at ~1650/3300.

The amide features provide an immediate indication of the action of the drug. The change in the amide region of the FGFR1 spectrum suggests that FGFR1 undergoes a degree of structural rearrangement which affects the amide features, and therefore presumably elements of the protein backbone. In contrast, the absence of any changes to the BSA amide region upon addition of the drug indicates that the presence of SU5402 does not affect the BSA backbone structure at all, presumably because SU5402 does not bind to BSA at any specific site.

In general, addition of SU5402 to the proteins increases the number of detectable peaks substantially. After subtracting the spectrum 1A (FGFR1 only) from 1B (FGFR1 + SU5402) we produce a difference spectrum which was fitted to a sum of 2D Gaussian features. Aside from the

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amide features, this revealed 63 features in the difference spectrum. Similarly, the spectra of BSA with and without SU5402 (1D and 1E) were subtracted which produced a difference spectrum containing 57 Gaussian features. The crucial point here is that all 57 features in the BSA difference spectrum are also found in the FGFR1 difference spectrum, but there are an additional 6 peaks clearly seen in the case of the FGFR1 spectrum. The location of these features are marked on the difference spectra (Fig 1C and 1F) with pink crosses.

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Figure 1 Experimental EVV 2DIR spectra of a) FGFR1, b)FGFR1+SU5402 c) the difference spectrum of FGFR1+SU5402 and FGFR1, d) BSA, e)BSA+SU5402 f) the difference spectrum of BSA+SU5402 and BSA. The difference spectrum from BSA contains spectral features of SU5402 in a non-specifically bound state, whilst the difference spectrum from FGFR1 contains features arising from SU5402 in the protein bound state. The difference spectrum from FGFR1 contains all drug peaks present in the difference spectrum from BSA as well as an additional 6. These can be ascribed to be binding dependant. The frequency locations of these 6 binding-dependant peaks have been marked on both difference spectra.

The difference spectra can contain features from three sources. Firstly, those spectral features arising from intramolecular vibrational coupling within SU5402, secondly those arising from changes in the protein spectrum as a result of inhibitor binding induced protein structural changes, such as those observed in the amide bands and finally as a result coupling between the protein and the drug.

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The 57 peaks which are common to both FGFR1 and BSA difference spectra are assigned to intramolecular coupling within SU5402. Since BSA has no binding site for SU5402, this is a reasonable assumption. The changes in the broad amide region for FGFR1 are assigned to changes in protein structure caused by drug binding while the additional 6 peaks in the FGFR1 spectrum are tentatively assigned to changes caused by drug-protein interactions. It is not in general possible to definitively tell whether such new crosspeaks are due to coupling between drug modes and protein modes, new collective modes of the bound drug-protein complex, or changes in protein structure caused by drug biding. Distinguishing these possibilities is the motivation for the QM calculations which are described later.

ωα ωβ

1400 cm-1 3030 cm-1

1400 cm-1 2975 cm-1

1400 cm-1 2810 cm-1

1400 cm-1 2705 cm-1

1400 cm-1 2680 cm-1

1660 cm-1 3240 cm-1

Table 1. The frequencies of the binding dependant peaks seen in the FGFR1/SU5402 difference spectrum, rounded to the nearest 5cm-1. These are the peaks that are seen exclusively in the specifically bound (FGFR1) difference spectrum and

absent in the non-specifically bound (BSA) difference spectrum.

It is clear from inspecting the experimental spectra, that five of the six peaks come from coupling of one fundamental vibration at 1400cm-1 to a range of different vibrations while the sixth is in the vicinity of the amide vibrations.

To confirm the identification of these six peaks as binding-dependent we performed an additional independent measure of their binding-dependent behaviour. EVV 2DIR spectra of the FGFR1/SU5402 mixture was measured across a range of molar ratios. At the high concentrations of protein and drug used in these experiments, the expectation is that the intensity of truly binding-dependent peaks should not continue to increase linearly beyond a 1:1 molar ratio as the binding sites become saturated. Conversely, features that are caused simply by intramolecular couplings within SU5402 should continue to increase in intensity linearly with concentration of the drug.

EVV 2DIR spectra of 1mM FGFR1 and 0 mM, 0.5 mM, 0.75 mM, 1 mM, 1.5 mM and 2 mM SU5402 were recorded, their difference spectra calculated, and the difference spectra fitted to extract peak intensities as described above. All six of the peaks present exclusively in the FGFR1 difference

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spectrum show a plateau in signal strength. In contrast, the 65 difference spectrum peaks common to both the FGFR1/SU5402 and BSA/SU5402 difference spectra all displayed linear increases in intensity with inhibitor: protein ratio, as would be expected for features that are not associated with binding. This confirms the non-binding peaks as intramolecular modes of the drug and therefore proportional to the drug concentration only. The average fitted peak intensities plotted as a function of inhibitor to protein molar ratio can be seen in Figure 2. The data are normalisation to the 1:1 fitted intensity for ease of comparison. The total number of proteins bound continues to increase beyond the 1:1 molar ratio as is normal in drug-protein binding curves, as not all ligands are bound when the sample ratio is 1:1. It is very clear from this data that the six peaks not present in the BSA difference spectrum and therefore due to the presence of both FGFR and SU5402, all have distinctly different concentration-dependent behaviour from the other 57 peaks, which provides a second form of verification, over and above their absence in the control measurements with BSA.

Figure 2 The average peak responses as a function of SU5402:FGFR1 molar ratio for the binding dependant and non-binding difference spectrum peaks. The levelling off of the 6 binding-dependent signals as a function of increasing drug

concentration confirms them as being binding dependant, due to the saturation of available protein binding sites. As the signal depends on the square of the number of molecules, the square root of the fitted peak intensity is plotted against

the SU5402:FGFR1 molar ratio.

In order to assign the six binding-dependent cross peaks to the coupled pairs of vibrations which gave rise to them, we performed ab inito calculations of the vibrational couplings of the drug in the binding site and compared this with the isolated drug.

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The structure of the protein-drug complex used for calculations is shown in Figure 3 below. We also calculated the spectrum of SU5402 in free space as a guide to the spectrum of SU5402 not bound into the protein active site. Although this free-space calculation does not contain water molecules, the difference between the calculated spectra for bound and unbound species was expected to be instructive, which proved to be the case as can be seen below.

Figure 3 The geometry of the SU5402 molecule along with the five partial amino acid residues and one water molecule used for calculating the EVV 2DIR spectrum of SU5402 bound to FGFR1. The carbon atoms of the SU5402 molecule are shown is orange whilst the included protein carbon atoms are shown in pink.

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Figure 4 a) the calculated spectrum of SU5402 and the FGFR1 binding site, b) the experimental bound FGFR1/SU5402 difference spectrum, c) the calculated SU5402 in free space spectrum, d) the experimental non-specifically bound

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BSA/SU5402 difference spectrum. From comparisons, the binding dependant peak at 1660/3240 can be assigned to the coupling of Mode E, an amide mode of the protein, and Mode C of SU5402. Mode B is present in the calculated spectra, with and without the inclusion of the binding site, meaning experimental binding dependence of its peaks must arise from lifetime effects. The black dotted line is the overtone diagonal and all features lying on this line are overtones, which is why it passes through the intersection of lines of the same colour, representing the same mode coupled to itself as an overtone.

As EVV 2DIR probes vibrational couplings between fundamental modes (mode #1 at ωα) and their combinations (modes #1 + #2 at ωβ), peaks with common mode #1 fall in columns of equal ωα, whilst peaks with common mode #2 fall in diagonal lines of gradient 1. By following the location of these lines of mode commonality and by inspecting the motions of the calculated modes, corresponding columns of equivalent mode #1 and diagonals of equivalent mode #2 can be found between the two calculated spectra and the experimental difference spectrum of the FGFR1-SU5402 complex. Key lines of mode equivalence have been marked on Figure 4. Each vibrational mode can give rise to peaks in both a column and a diagonal, as it can participate as both the #1 and the #2 modes. An example of this is Mode C marked with the magenta lines in Figure 4. The overtone peaks, in which a given mode forms both the #1 and #2 modes fall on the intersection of the column and diagonal of a given mode and form a new diagonal with a 2:1 gradient and has been marked on Figure 44 as a dotted black line.

Calculated modes that contribute to the binding-dependent peaks are assigned numbers 1-7 in the supplementary information to distinguish them from the labeled experimental modes identified as A-E in figure 4. Images of the modes showing the major atomic motions are found in the supplementary information as Figures S-2 to S-8 as are the corresponding animations of the modes.

It can also be seen from Figure 4, the column of equivalent mode D which appears in both in the calculated spectra, cannot be seen in either of the two experimental spectra. To understand this, it is important to note that the method used to produce the calculated spectra does not take account of lifetimes of the states involved. In fact with EVV 2DIR spectroscopy, it is not unusual to find that some of the expected cross-couplings between vibrations cannot be seen experimentally. This is essentially because some of the state lifetimes are too short to be observed using a method with an effective time resolution of ~1ps. In practise this means that experimental spectra are usually slightly sparser than those calculated.

As can be seen from Figure 4a and c, the frequencies of several equivalent modes are slightly shifted between the two calculated spectra. These shifts range from 3 to 43 cm-1 such as mode A which appears at 1330.03cm-1 in the binding site calculation and at 1322.41cm-1 in the free space calculation. In contrast no shift in frequency is observed between the bound and non-specifically bound experimental spectra. This can be attributed to weak interactions with the protein binding site slightly shifting the frequency of inhibitor modes compared to those of the free space inhibitor molecule. The lack of shift between the bound and non-specifically bound experimental spectra can be attributed to the chemical environment of the inhibitor is more similar between the two than to free space.

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The calculated binding site inhibitor complex spectra also includes peaks arising from protein modes, such as the Amide 1 overtone peak seen at ωα = 1702.5 cm-1 / ωβ = 3405.0 cm-1. The line of equivalent ωα for the amide 1 mode has been marked on Figure 4a and b as Mode E. This amide 1 mode can be seen to be coupled to an inhibitor mode of calculated frequency 1558.62cm-1 as a peak at ωα = 1702.5 cm-1 / ωβ = 3261.15 cm-1 in Figure 4a. This inhibitor mode gives rise to a diagonal of peaks which has been marked on Figure 4 as Mode C. Mode C corresponds to an Amide- associated motion of the 5-membered lactam ring with some motion on the adjoined benzene ring. The experimental binding dependant peak at ωα = 1660 cm-1 / ωβ = 3240 cm-1 can be assigned to the coupling of this lactam ring mode, Mode C, to the protein Amide 1 mode, Mode E, and is the equivalent of the calculated peak at 1702.5 cm-1 / ωβ = 3261.15 cm-1. This vibrational coupling is mediated by a hydrogen bond formed between NH group of the SU5402 lactam ring and the amide carbonyl of the proximal amino acid of the binding site.

Calculated equivalents of the 5 experimental binding sensitive peaks at ωα= 1400 cm-1 are observed in both the calculated spectra, with and without the inclusion of the protein binding site. These have been marked as Mode B in Figure 4. The vibrational modes calculated to give rise to them exhibit motion exclusively on the SU5402 molecule. The apparent experimental binding-dependence of the intensity of these peaks must therefore be attributed to lifetime effects. In the non- bound case, the SU5402 molecules are in a different chemical environment to those bound in the kinase binding site and it is perfectly reasonable that they are exposed to different environmental fluctuations. This can easily result in increased dephasing and decreased lifetimes of these vibrational coherences in the non-specifically bound case, compared to that of the protein inhibitor complex. Mode B corresponds to a complex motion involving atom displacements across the entire molecule from the fused benzene ring to methyl substituent of the pyrrole ring. We speculate that the extensive nature of the mode which runs across many chemical groups. provides more opportunities for ‘environmental’ coupling (e.g. coupling to water), to influence coherence lifetimes through either pure or population dephasing. However, given that most of the modes here are spread over many chemical groups it is somewhat surprising that more modes are not affected in a similar way.

Animations of the seven modes assigned to the 6 binding-dependent features can be found in the supplementary information along with figures S-2 to S-7 showing the main atomic displacements. In summary the 1400cm-1 mode labelled B in figure 4 and corresponding to mode 1 shown in figure S-2, is entirely located on the SU5402, supporting the idea that the appearance of this column of crosspeaks upon binding is due to a change of dephasing rate for this mode due to sequestration of the SU5402 in the binding site. Presumably this is due to exclusion of a solvent interaction which reduces the state lifetime. All other modes are collective motions of the drug and the protein binding site and show substantial motion of amide groups.

In some ways the most striking feature of our data is that none of the intramolecular SU5402 modes, with the exception of the amide-associated cross peaks, are lost or show substantial frequency shifts when the drug is bound to FGFR1, compared with the non-bound situation with

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BSA. This suggests that the average structure of the solvated drug is very similar, if not more or less identical, to the structure of the drug in the binding site. This would certainly reduce the conformational entropy cost of binding and make the drug a more potent inhibitor and is thought to be a fairly common feature of heterocyclic aromatic drugs which tend to have relatively rigid planar components to their structures.

There is a substantial change in the amide region of the FGFR spectrum when SU5402 is added, but no change at all to the amide region of BSA upon addition of the drug. This further highlights the utility of BSA as a non-binding control and suggests that a subset of FGFR structures is stabilised by the binding of SU5402. There is good precedent for this. Many kinases contain a regulatory loop comprising a Asp–Phe–Gly sequence known as the DFG loop. This loop can either be in the ‘in’ form, within the protein where the phenylalanine resides deep within a hydrophobic pocket, or the ‘out’ form whereby it protrudes into the surrounding environment. SU5402 is a Type 1 kinase inhibitor which binds to and stabilises only to the DFG in form and this could indeed lead to a net change in protein structure upon binding. It is not possible to determine from our data whether it is in fact the DFG transition that is being observed, or whether some other structural variation is stabilised by SU5402 binding. As proteins do explore a range of structural configurations at equilibrium, observing a change in this structural equilibrium upon drug binding is expected, but these observations do highlight the sensitivity of EVV 2DIR to global structural changes in a protein, as well as local variations in coupling due to the drug-protein contacts.

One of the binding-dependent peaks has been more or less unequivocally assigned to a drug-protein contact. This is the feature found experimentally at ωα = 1660 cm-1 / ωβ = 3240 cm-1 . Its proximity to the amide 1 mode suggests that it is likely to be due to the known hydrogen bonding between SU5402 and a carbonyl of the protein backbone. This intuitive assignment is supported by quantum mechanical calculations which predict the presence of this feature. It is caused by coupling between a mode of the drug and a protein mode which contains considerable amplitude of motion of the carbonyl in the binding site (see Supplementary Information Figure S-5), a chemical group which is known to hydrogen bond to the drug molecule. As this is a feature common to many kinase-drug interactions where the drug targets the ATP binding site, we anticipate that this feature would be a general and generic means to identify and monitor the details of drug binding to these kinase active sites.

In picking the most congested spectral region available to EVV 2DIR spectroscopy, namely the region containing the overtone couplings, we have set a particularly difficult challenge to the separation of binding-dependent peaks from binding-independent features. The reasoning here is that if it can be done for such congested spectra, it can certainly be done for less congested spectral regions. Despite the relatively high levels of congestion from ~ 200 protein peaks and ~ 60 drug peaks, the spectra are both sufficiently decongested and sufficiently precise to allow six binding-dependent features to be identified. The spectral region measured here is approximately 1/20th of the total spectral region accessible by our EVV 2DIR apparatus. It is therefore extremely likely that a wider survey of the total accessible spectral space will yield other binding-dependent features too.

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Indeed, calculations suggest that there are at least 12 more binding-dependent peaks present in the wider accessible spectral space, arising from vibrational couplings between SU5402 and FGFR1 binding site modes. There will presumably also be a significant number of features which experimentally display binding dependence, such as changes in the global protein structure in response to drug binding. As we have only calculated the vibrational coupling in the drug binding site, these are not predicable using the approach employed here.

The ability of EVV 2DIR demonstrated here to detect the binding of a drug to a binding site of a target protein of commercial interest bodes well for the utility of the technique in drug discovery in future. The spectra shown here were the result of signal averaging for 90 minutes. The spectrometer was driven by a 1kHz laser engine and data was collected at this 1kHz rate. Laser engines capable of driving an EVV 2DIR spectrometer at 100kHz now exist which would potentially reduce the collection time for an entire spectrum to approximately one minute. Moreover, if only a part of the spectrum is required for a binding study, such as the amide region, the speed of collection for a particular drug-protein combination could be reduced to a few seconds. We therefore suggest that high throughput versions of this experiment would be entirely possible to establish and that the high data density produced would enable mining of the data into ‘contact’ modes able to be assigned to classes of protein-drug contact, even without the requirement for detailed structural analysis.

The prognosis for direct structural analysis is also good. We have previously shown that collecting data at two different polarisations of the beams allows the geometry of the mode interaction to be determined(18, 21). As each binding-dependent peak provides one angular constraint, it would only require a few such features to provide quite tight structural constraints for the drug-protein interaction geometry. Similarly, it has been shown the intensity of these peaks can be used to determine the distances between atomic contacts, providing further structural detail.

Conclusion

We have shown that it is possible to detect the binding of a drug to a clinically important drug target, namely the protein kinase FGFR1. Of the six binding-dependent peaks one can be assigned directly to coupling caused by the drug binding to a carbonyl in the protein active site. This assignment is supported by ab initio calculations of vibrational couplings in the enzyme active site when occupied by the drug molecule.

Supporting Information Description

The supporting information comprises a document detailing the modes assigned to the binding peaks. There are seven GIF animations of the vibrational modes associated with the binding-dependent cross peaks and a document describing the modes and their contributions.

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Acknowledgements

We would like to thank EPSRC for support through grants EP/I017887/1 and EP/C530187/1. This work was also supported by the Rosalind Franklin Institute. Hugh Sowley was supported by a BBSRC AstraZeneca CASE studentship. W.Z thanks the supports from the National Key Research and Development Program of China (2017YFA0206801) and the NSFC Grants (21373201 and 21433014).

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TOC image: Experimental EVV 2DIR spectra of a) FGFR1, b) FGFR1+SU5402 and c) the difference spectrum of FGFR1+SU5402 and FGFR1.

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