Brigitta Elsässer
email: elsaesse@mail.upb.de

Gregor Fels

Nucleotide docking: prediction of reactant state complexes for Ribonuclease enzymes

Keywords:

Ribonuclease enzymes (RNases) play key roles in maturation and metabolism of all RNA molecules. Computational simulation of the processes involved help understanding the underlying enzymatic mechanism and is often employed in a synergistic approach together with biochemical experiments. Theoretical calculation require atomistic details on starting geometry of the molecules involved which in the absence of crystallographic data can only be achieved from computational docking studies. Fortunately, docking algorithms during the past years have tremendously improved so that today reliable structures of enzyme-ligand complexes can successfully be obtained from computation. However, most docking programs are not particularly developed for nucleotide docking. In order to assist our studies on the cleavage of RNA by the two most important Ribonuclease enzymes, RNase A and RNase H, we have evaluated four docking tools, MOE2009, Glide 5.5, QXP-Flo+0802, and Autodock 4.0 for their ability to simulate complexes between these enzymes and RNA oligomers. To validate our results, we have analyzed the docking results with respect to the known key interactions between the protein and the nucleotide. In addition, we have compared the predicted complexes with X-ray structures of the mutated enzyme as well as with structures of previous calculations. In this manner we could prepare the desired reaction state complex as starting structure for further DFT/B3LYP QM/MM reaction mechanism studies.

Introduction

The genetic information of living cells is encoded in the DNA and is translated into proteins via messenger RNA-molecules (mRNA) that are copied from the DNA during transcription.

Both, messenger RNAs, that carry genetic material for making proteins, as well as non-coding RNAs, that function in varied cellular processes, are degraded by Ribonuclease enzymes (RNase) as part of their life cycle. In addition, active RNA degradation systems are the first defense mechanism against RNA viruses, and provide the underlying machinery for more advanced cellular immune strategies. Therefore, inhibitors of these enzymes could provide new drugs against many diseases. As important biological molecules, both enzymes, human RNase H and RNase A, represent key pharmaceutical targets and their understanding on a molecular basis is a keystone in the development of corresponding inhibitory drugs.

RNase A is part of the human immune responses and is responsible for destroying RNAviruses that could infect the body and it digests RNA in our food. It hydrolyzes the singlestranded RNA behind each cytosyl and uridyl nucleotide and leaves 5'-hydroxy and 3'phosphorylated products (Fig. 1) [1]. Human RNase H is part of the reverse transcriptase (RT) enzyme, which is absolutely necessary for the proliferation of retroviruses. Contrary to RNase A, RNase H specifically cleaves the RNA strand of a DNA/RNA duplex after transcription at position 7-12 nucleotides from the 3´-DNA/5´-RNA terminus (Fig. 1) [2] and leaves 5'phosphorylated and 3'-hydroxy products. A RNase H domain is also present at the C-terminus of retroviral reverse transcriptase which converts a single-stranded retroviral genomic RNA into a double-stranded DNA for integration into host chromosomes, thus playing a significant role in the HIV reverse transcription process [3]. In vivo studies demonstrated that inactivation of RNase H results in non-infectious virus particles [4,5].

<Figure 1>

In order to investigate the hydrolytic cleavage mechanism of the two key Ribonuclease enzymes human RNase H and RNase A, by computational approaches reliable starting geometries of the two enzyme-ligand complexes are indispensable. Here docking approaches can help by predicting binding modes of ligands inside the active site of the enzyme, i.e. the orientation and conformation of an inhibitor at the enzyme cleavage site thereby generating potential structures of enzyme-inhibitor-complexes.

In the last few decades a number of search and placement algorithms have been developed with the conceptual difference that the ligand is either treated in its entirety or it is built up from fragment bases inside the binding site [6]. In addition, most programs can even allow for receptor flexibility. To this end, several publications have recently appeared comparing and evaluating the different docking tools for a given enzyme-ligand combination [6][7][8][9]. Almost all papers, however, consider protein-based docking of small ligand molecules or proteinprotein docking, with the exception of van Dijk et al. who have recently developed a new method for protein-DNA docking [10][11][12]. Predicting the correct binding between proteins and RNA oligonucleotide chains is of growing interest [13][14][15], although rarely described in the literature.

Since our main goal is to investigate the hydrolytic mechanism of the above described enzymes we need to generate starting structures for our calculations which in the absence of crystallographic data can be generated by molecular docking. In order to find an optimal docking procedure we have compared four docking programs (MOE2009 [16], Glide 5.5 [17], QXP-Flo+0802 [18], and Autodock 4.0 [START_REF] Morris | Autodock 40 20[END_REF]) to find the most suitable one for our purposes.

Here we describe our investigation of possible Ribonuclease-ribonucleotide oligomer complexes by molecular docking. Although calculation of RMSD (root mean square deviation) values between docking results and crystal structures is a well-established method for evaluation of docking poses we rather applied the interaction-based accuracy classification (IBAC) method as described by Kroemer et al. [6] since for each complex the necessary protein-ligand interactions are well described in the literature [6,[20][21][22]. Therefore, we have determined the correct docking poses by comparing the hydrogen bond (H-bond) distances between enzyme and nucleotide. In this way we have on the one hand identified the docking program which is most suitable for our case of nucleotide docking and on the other hand we could generate possible starting structure geometries for our calculations. However, we did not intend to establish any ranking between the applied docking tools.

Materials and methods

Protein preparation, in silico

Crystal structures of both Ribonuclease-ribonucleotide complexes were retrieved from the PDB Database [23]. The protein preparation for both Ribonucleases was carried out by using the parallel software package NWChem [24]. After adding hydrogen atoms the protein was solvated in an 80 Å cubic box of water and the system was relaxed using stepwise molecular dynamic calculations and was optimized applying high level B3LYP/DFT QM/MM simulations. Afterwards the ligand (ribonucleotide) was removed and the resulting enzyme was employed for docking.

The three dimensional coordinates of the ligand-free RNase A is also available in the protein database at atomic resolution (PDB code: 2E3W) [25], however, superposition of this structure with other RNase A enzymes complexed with any ligands (e.g. 1RUV, 1RPG) revealed that probably upon ligand binding one of the important active site histidine residues (His119) changes its orientation, since in the ligand-free enzyme the imidazol ring of His119 is flipped over. For this reason, the ligand-free enzyme was not suitable for docking.

In the first set of calculations we started from the productive binding complex of RNase A with deoxycytidyl-3',5'-deoxyadenosine (PDB code: 1RPG, resolution 1.40 Å) [26].

According to the generally accepted mechanism [1,27] His12 was unprotonated, and Lys41 and His119 were protonated. In addition, to evaluate our docking method, we also used the RNase Acyclic uridyl phosphate (CUP) complex from previously published QM/MM calculations [28] to perform docking studies between CUP and the protein to reproduce this structure for verification.

The starting point for the second set of calculations was the crystal structure of human RNase H1 catalytic domain mutant D210N in complex with a 14mer the DNA:RNA duplex (PDB Code: 2QKK) [22]. Prior to protein preparation as described above the residue Asn210 was in silico mutated to Asp210 in order to reproduce the wild-type protein. Moreover, the optimized complex served as comparison for the docking results.

Ligand preparation

To verify the procedure of the RNase A docking we first used the ligands from the original optimized enzyme-substrate complexes described above (deoxycytidyl-3',5'-deoxyadenosine and cyclic uridyl-phosphate, CUP, respectively).

For the desired active reactant state complexes RNA(poly(U)) oligomers (dimer, trimer, tetramer nucleotides) from the PubChem [29] database served as ligands (CID: 439261). The appropriate ligand files were prepared by adding and optimizing the hydrogen atoms using the Protein Preparation Wizard of Maestro 9.0 [17] followed by rebuilding the 3D conformation of each molecule using LigPrep 2.3 [17] at pH of 7.0. Afterwards, the rebuilt ligands were subjected to a conformational search using Macromodel 9.7 [17] with OPLS 2005 force field in a water solvent model. For minimization the "steepest descent" method was applied with a maximum iteration of 500. The energy window for keeping structures was set to 5.02 kcal mol -1 and the RMSD cutoff value to 0.5 Å to generate the lowest energy conformations.

For the docking experiment with RNase H, a tetramer RNA:DNA hybrid duplex was extracted from the original ligand of the X-ray structure. Since none of the docking programs can simultaneously consider two molecules as present in the RNA:DNA double helix, a covalent ether bridge was built between the RNA and the DNA chain without changing the conformation of the double helix. This ligand was used for docking after molecular mechanics optimization in MOE with Amber99 as force field. After docking the ether bridge was removed and the corresponding nucleotide base was optimized to build up the hydrogen bond between the two ribonucleotide chains. Furthermore, additional ligands were generated by using a single stranded dimer, trimer, and tetramer RNA nucleotide chain of the hybrid duplex. These structures were then docked rigidly in order to retain their original geometry.

All figures containing molecular structures were prepared with MOE2009.

Docking programs and parameters

MOE 2009. 10 [16] In the potential energy setup panel Amber99 was chosen as force field.

For solvation the implicit model of "Born" [30] was selected. Two placement methods, "alpha triangle" and "triangle matcher", were employed to find the optimal docking parameters with the result that the alpha triangle method is faster and yields more suitable docking poses, that show the required enzyme-ligand interactions. In all cases the scoring was the "London dG [31] method" and "force field refinement" was applied allowing for flexibility of the catalytic site within 7.0 Å. Each run was adjusted to retain 30 docked conformations as a cut-off unless less suitable poses were found. The top poses were retained for visual analysis (investigating the H-bond distances) for each nucleotide per enzyme. For RNase A the residues Gln11, His12, Lys41 and His119 were defined as binding pocket [1] while for RNase H the residues Asp145, Glu186, Asp210 and Asp274 defined the pocket [22]. "Rotate bond" of "the Docking Simulation" panel was enabled in both cases.

Glide 5.5. [17]

For each protein first a grid box of 30 × 30 × 30 Å with a default inner box (10 × 10 × 10 Å) was centered on the catalytic pocket using the same active site residues to describe the pocket as above. Default parameters were used, and for RNase A four constraints were defined. One positional constraint was set for the phosphate group and three Donor-Acceptor (H-bond) constraints were applied between His12, Lys41 and His119 and the given sugar moiety oxygen atoms, that represent the most important interactions between the enzyme and the ligand. For RNase H only the positional constraint was used, since the amino acids of the catalytic site are not involved in the substrate binding interaction [21]. For all experiments the standard precision mode of GlideScore was selected as scoring function, and the option of "Dock flexibly" was selected for RNase A and "Dock rigidly" for RNase H in order to keep the original helix-like conformation of the RNA strand. The top 10 poses were kept and H-bond between the ligand and the protein analyzed. [18]. In a multistep procedure [7] the full Monte Carlo docking (SDOCK+) was followed by a local Monte Carlo run (MCDOCK), which is also part of the program package. The 25 hits of the full MC run were ranked, rescored and redocked in a local MC simulation as described by Alisaraie et al. [7] The catalytic site water oxygen atoms were colored purple and the hydrogens blue to enable some movement. The ligand was kept rigid for the RNase H docking runs. Docking results were evaluated according to the IBAC scheme [6].

QXP-Flo+0802

Autodock 4.0. [START_REF] Morris | Autodock 40 20[END_REF] The active site residues were defined as flexible residues and the rest of the protein was designated as rigid. The grid maps representing the protein in the docking process were calculated with Autogrid 4.0. The dimension of the grid was 80 × 80 × 80 points with a spacing of 0.375 Å between the grid points and the center close to the ligand. Default docking parameters were used and for the search parameters the "Lamarckian Genetic Algorithm (LGA)" was applied [32]. For the ligands of RNase A the number of rotatable torsion angles was set by "AutoTors". To disable bond rotation for the RNase H substrates the "number of torsions" was set to 0. The resulting structures were automatically ranked according to their mean docking energy by the scoring function of AutoDock. Subsequently, the relevant H-bond lengths were analyzed.

Evaluation of docking results

ProFit V3.1. [33] For the results of docking studies with single stranded RNA RMSD values were calculated using the McLachlan algorithm [34] as implemented in the program. For the simulations with the modified RNA:DNA double helix no RMSD calculation is possible in this form, since the mobile and the reference structure must have the same number of atoms.

Therefore, the ether bridge was removed after docking and the 14mer double helix of the reference structure was shortened to tetramer for the RMSD calculations. [6]). The predicted poses were analyzed with respect to the essential key interactions with the protein. [35]. Extended analysis of all heavy atom contacts was performed using the LPC CSU Server of the Weizmann Institute.

IBAC (Interaction-Based Accuracy Classification

LPC (Ligand-Protein Contacts)

Results and discussion

Software evaluation for docking of nucleotides

The goal of our simulations was to produce reliable starting structures for further QM/MM reaction mechanism studies. Although currently available crystal structures of the PDB data base provide fundamental information about the active site of both RNase A and RNase H, it is not possible to generate the coordinates of their reactant state complexes experimentally since the nucleotide is hydrolyzed immediately upon binding. Therefore, the use of docking programs to build a productive initial complex structure is crucial. Since docking programs are not particularly developed for nucleotide docking we have initially evaluated four docking programs, MOE2009 [16], Glide 5.5 [17], QXP-Flo+0802 [18], and Autodock 4.0 [START_REF] Morris | Autodock 40 20[END_REF] for their accuracy in reproducing the experimentally known crystal structures of non-active RNase-ligand complexes. In all docking simulations we started from the DFT/B3LYP QM/MM optimized complexes (reference molecule) of the available X-ray data as described in the materials and methods section. The ligand of the existing complex was removed from its binding site and docked back into the catalytic pocket (bound docking). This method affords an unbiased setup for the evaluation of the software and the scoring function. The resulting structures were analyzed and the docking accuracy was determined by comparison of the H-bond distances and the distances between the superposed structures of the given docking pose and the reference molecule. Additionally, ProFitV3.1. [33] was applied to calculate the RMSD values between the docking pose and the reference molecule by superposing the complete enzyme-substrate complex.

<Figure 2>

MOE and Glide demonstrated good accuracy in the prediction of binding modes with RMSD values for the best docking hits below 1 Å. Fig. 2 shows the superposition of the top binding pose with the original structure.

<Table 1>

QXP and Autodock, however, could not reproduce the initial structure by bound docking at all. The resulting complex did not match the productive binding structure as the ligand was placed incorrectly into the catalytic pocket and therefore neither a RMSD validation nor the LPC analysis would be applicable to describe these docking results.

<Table 2>

As one can see from Tables 1 and2, although MOE finds fewer correct docking poses than Glide the resulting hits have significantly better RMSD values. Another interesting point is that in both docking studies the order of docking scores does not correlate with the order of RMSD values and hence the reproducibility of the reference structure. In addition LPC analysis [35] revealed that with respect to the X-ray structure MOE could recover 76 % and Glide 61 % of all heavy atom contacts (below 4.5 Å) with a deviation of 0.6 Å or less.

For the docking studies of RNase H and the RNA:DNA hybrid duplex (see Materials and Methods section) the ligand was modified by connecting the RNA and DNA chain with an ether bridge to be able to perform the docking with the double helix. However, the modification did not affect the conformation of the hybrid duplex. Since the original ligand has been modified the comparison of the RMSD values for the whole system was possible only when subsequent to docking simulation the ether bridge was removed (Fig. 3, RMSD=0.711). In addition, the position of the ligand was compared by measuring mechanistically relevant distances between the enzyme and the nucleotide similarly to the IBAC method of Kroemer et al. [6] <Figure 3> Table 3 compares the most relevant distances between the docked ligand and RNase H to the reference structure. Note that although the docked complexes match the low resolution (3.20 Å) experimental structure quite well, the measured distances are slightly over-estimated by both softwares. This might be due to the applied flexible docking, where the active site residues were allowed to move, with the consequence that the binding pocket is a little expanded upon force field optimization of the side chain positions.

<Table 3>

To evaluate MOE and Glide for docking a tetramer RNA:DNA double helix into the active site of RNase H the experimental and docked structures were manually compared by measuring distances of atoms relevant for the mechanism (Table 3). Although, MOE and Glide are both suitable to reproduce the experimental results, again MOE showed significantly better performance in terms of the average accuracy for docking nucleotides.

According to LPC analysis [35] both MOE and Glide recovered roughly 50 % of all heavy atoms contacts (below 4.5 Å) with a deviation of 0.6 Å or less in comparison with the reference structure.

The RNase A reaction state complex

On the basis of these results we have chosen MOE and Glide to find suitable reactant states for our studies of RNase A and RNase H reaction mechanism. For RNase A the literature provides a putative pathway [1] of the transphosphorylation step (Fig. 4) and defines a number of H-bonds between the enzyme and the ligand. The first step in the proposed mechanism involves intramolecular transphosphorylation to form a cyclic phosphate stable intermediate product and displacement of the O5P-nucleotide product as illustrated in Fig. 4.

Since RNase A cleaves single stranded RNA behind uridyl and cytosyl nucleotides only, for the docking simulation dimer, trimer, and tetramer uridyl nucleotide oligomers were used in the presence of crystallographic water molecules.

<Figure 4>

According to the putative reaction mechanism [START_REF] Pauling | The nature of the chemical bond[END_REF] as presented in Fig. 4, the first step involves protonation of His12 by the OH-group of O2' followed by a proton transfer from His119 to O5P. Accordingly, strong H-bonds between (NE2)His12 and O2' as well as between (ND1)His119 and O5P are indispensible and the corresponding distances should therefore be as short as possible in correct docking poses.

<Table 4> <Table 5>

At the intermediate or transition state stage the phosphorane and the partial negative charge on the phosphate oxygens must be stabilized by further interactions between (NZ)Lys41-O2', (NE2)Glu11-O2P and (NE2)His12-O1P. Therefore, the resulting hits were analyzed with respect to the length of the corresponding H-bond distances. Tables 4 and5 show that the alpha-triangle placement method, as implemented in MOE, yielded significantly more possible docking poses than GlideScore SP. The H-bond analysis reveals that aside from the number of hits found the docking efficacy of Glide and MOE are comparable. Fig. 5 illustrates the catalytic pocket with the ligand (uridyl nucleotide dimer) of the docking pose that best fits the desired H-bond interactions.

<Figure 5>

In order to adjust the enzyme ligand complex to the natural structure and to investigate the interactions far-off from the scissile phosphate bond the size of the ligand was increased by docking a trimer and a tetramer uridyl phosphate, respectively, into the active site of RNase A. This resulted in a drastic decrease of meaningful docking poses, but rather yieldedwith both of the two docking tools employedjust one acceptable hit each for each ligand. <Table 6> Surprisingly, the derived structure reproduced the natural structure with all the important interactions between protein and nucleotide quite well (Table 6).

Cation titration experiments suggest that the interaction between the enzyme and a single stranded RNA extends well beyond the phosphate group through Coulombic interactions [START_REF] Record | [END_REF].

The binding subsites of RNase A can be divided into P and B subsites, in which the phosphate and the nucleotide base interact with the protein as described by Raines [1]. In our docking complex the uridyl base of the B1 subsite interacts with Thr45 and the phosphate group of the P2 subsite interacts with Lys7 and Arg10 as illustrated in the ligand interaction map depicted in Fig. 6. This map shows that as well the short as the wide range interactions between the protein and the timer nucleotide could be reproduced in the docking simulation.

<Figure 6>

Lys41 and His12 are both strongly H-bonded to the O2´ oxygen and Gln11 is coordinated to O2P. Furthermore, His12 interacts with the O1P oxygen and His119 with the O5P atom. All these interactions are essential for the reaction mechanism to proceed. In addition not only the active site water molecules but further crystallographic water molecules also play important roles in stabilizing the complex through H-bridges between the protein and the ligand.

To summarize these results, our docking simulations of the uridyl nucleotides and RNase A yields a ligand pose that reproduces all of the important H-bond in the catalytic site as described in the literature [1]. In addition, also the interactions beyond the cleavage site were reproduced correctly. Accordingly, we have used the trimer uridyl docking pose of MOE as the desired reaction state complex as starting structure for further calculation.

The RNase H reaction state complex

Recently, the first crystal structures of the catalytic domain mutant of human RNase H [22] and Bacillus halodurans RNase H [38] complexed with an RNA:DNA hybrid substrate was reported. Nowotny et al. have shown that the RNA strand of the hybrid duplex is recognized by the protein through its interaction with the 2'-OH groups and that the active site of human RNase H consists of the amino acids Asp145, Glu186, Asp210 and Asp274 which are all essential for the required activity [22]. However, the amino acids of the catalytic site are not involved in the substrate binding interaction [21].

In our reaction mechanism studies [39] (Fig. 7) Nowotny´s human RNase H1 catalytic domain mutant D210N in complex with 14-mer RNA/DNA hybrid was used as starting structure for our calculations (PDB code 2QKK [22]). In order to turn the system back to the natural active enzyme-substrate complex we mutated Asn210 to Asp210. Separate QM/MM optimization proved that the mutation hardly affects the structure of the system or the active site. To further confirm the validity of this procedure we have performed docking calculations to generate the corresponding reactant state complex.

<Figure 7>

Since none of the docking tools used can handle a duplex structure like the RNA:DNA double helix we have employed RNA trimer and tetramer nucleotides (cut from the RNA:DNA double helix) for docking into the active site of RNase H in the presence of water molecules and the Mg 2+ ions that exist in the binding site. In order to retain the geometry of the original double helix the ligand was kept rigid during the simulations by allowing no bond rotations at all for the nucleotide. Afterwards the resulting structures were compared with the QM/MM optimized active complex from our previous calculations (reference structure) [39] and the relevant protein-ligand distances were analyzed and are summarized in Table 7.

<Table 7>

Due to the fact that we used single stranded oligomers in our studies the calculation of RMSD values for the whole system is not feasible. Therefore, we compared the distances between the nucleotide and significant residues of the active site with our QM/MM optimized structure.

The number of possible docking poses obtained by MOE is much larger than for Glide but the resulting top hits are comparable as can be judged form the analyzed interactions.

<Figure 8>

Both structures turn out to be very close to the reference structure (Fig. 8). This strongly supports that replacement of the mutated Asn210 to Asp210 in order to construct the active enzyme did not affect the geometry of the catalytic site. As can be seen on Fig. 8 the nucleotides which are in the deeper regions of the pocket fit excellent, however the nucleotide base at the end of the pocket turns rather towards the exit of the pocket due to the fact that in that region there are less interactions with the protein.

Conclusions

With the aim of predicting reactant state structures for reaction mechanism calculation of RNase A and RNase H hydrolysis, we have evaluated four protein-based docking tools with respect to their capability for enzyme-nucleotide docking. To this end different ribonucleotide oligomers were placed into the active sites of RNase A and RNase H. As molecular docking tools were developed originally for placing small ligands into protein binding sites, or for protein-protein interactions, we tested the docking tools Glide, QXP-Flo+, and Autodock as well as the docking algorithm implemented in MOE for their ability to reproduce non-active protein-RNA complexes known from the literature. While QXP and Autodock could not reproduce the crystal structures in a bound docking experiment with a known structure, MOE and Glide demonstrated good accuracy in the prediction of binding modes with RMSD values for the best docking hits below 1 Å even for large ligands, like uridyl tetramer nucleotide.

According to our findings these two docking programs could successfully reproduce the reference experimental structures and the interactions beyond the active site. Since our initial goal was to find suitable active reactant state complexes for our studies of RNase A and RNase H reaction mechanism we have, therefore, chosen MOE and Glide to accomplish our project.

In the docking studies of the mutated RNase H and a modified tetramer RNA:DNA hybrid duplex we could correctly position the ligand into the active site of the enzyme. Therefore, we can assume that docking experiments between the nucleotide and the active enzyme provided a reasonable complex structure, which supports further that the complex in our reaction mechanism studies [39] was the correct starting structure.

The results of the present studies prove that current protein-based docking programs can well be used for nucleotide docking andat least in the special cases we have investigated -can generate reactant state complexes for further theoretical studies. Our simulations with RNase A identify a few appropriate docking poses, which were subjected to further analysis in terms of the important interactions between the enzyme and the tetramer nucleotide. In addition, MOE provided the desired productive initial structure for our intended reaction mechanism studies. Previously, we have studied [28] the second step (hydrolysis step) of the RNase A catalytic cycle, and on the basis of the docked reactant state structure as derived from our docking simulation we can now continue our investigation towards the first step of the reaction mechanism. These calculations should eventually result in the first description of the complete pathway on a high level DFT based QM/MM bases. Reproduced complexes of RNase A and cyclic uridyl-phosphorane RMSD=0.097 (Fig. 2a), and deoxy cytosyl-adenyl-dinucleotide RMSD=0.327 (Fig. 2b). The original pose is colored green and the docking hit is red. The displayed surface illustrates the catalytic pocket, in which purple color identifies H-bond interactions, green color characterizes areas of hydrophobic contacts, and blue color denotes dipole-dipole interactions Proposed reaction pathways [1] for the O3΄-P cleavage of human RNase H

Tables

Figure captions

Fig. 8

Superposition of the reference structure (green) and the top tetramer nucleotide docking hit (red). Color codes are as specified in Fig. 2

Fig. 1 Fig. 2

 12 Fig. 1Cleavage mechanism of the two Ribonuclease enzymes, RNase A and RNase H

Fig. 3

 3 Fig. 3Top hit of bound docking of RNase H and the modified tetramer RNA:DNA hybrid duplex RMSD=0.711 (Fig.2c). The original pose is colored green and the docking hit is red. The displayed surface illustrates the catalytic pocket. Color codes are as specified in Fig.2

Fig. 4 Fig. 5

 45 Fig. 4Putative reaction mechanism of the first step of the RNase A hydrolysis

Fig. 6

 6 Fig. 6Top hit docking pose of trimer (a) and tetramer (b) uridyl nucleotide and RNase A.Corresponding ligand interaction map as generated by MOE (c). The displayed surface illustrates the catalytic pocket. Color codes are as specified in Fig.2

Fig. 7

 7 Fig. 7Proposed reaction pathways[1] for the O3΄-P cleavage of human RNase H

Table 1

 1 RMSD values of the best docking poses of the RNase Acyclic uridyl-phosphate complex. Only RMSD values below 1 Å were considered

		hit1	hit2	hit3	hit4	hit5
	MOE	0.097	0.122	0.117	0.181
	Glide	0.775	0.557	0.748	0.882	0.546

Table 2

 2 RMSD values of the best docking poses of the RNase Adeoxy-cytosyl-adenyldinucleotide complex. Only RMSD values below 1 Å were considered

		hit1	hit2	hit3	hit4	hit5
	MOE	0.392	0.327	0.511	0.494
	Glide	0.860	0.792	0.910	0.869	0.974

Table 3

 3 Comparison of distances (in Å) between docking results (best hit) and the corresponding experimental structure of RNase Htetramer hybrid-duplex (PDB code: 1RPG). proO1P is the O1P atom of the following nucleotide. To measure the distance between the centroids of the sugar rings a dummy atom was placed into the center of the five-

	membered ring
		reference	MOE	Glide
		structure	dist diff. dist diff.
	O3'-(OD1)Asp210	3.35	3.71 0.36 3.83 0.48
	O3'-(OE1)Glu186	3.11	3.21 0.10 3.41 0.30
	O1P-(OE1)Glu186	3.38	3.86 0.48 3.71 0.33
	O1P-(OD1)Asp145	2.87	3.25 0.38 3.66 0.79
	O1P-(OD2)Asp145	3.26	3.73 0.47 3.75 0.49
	O1P-(OD1]Asp274	4.50	4.65 0.15 4.46 -0.04
	proO1P-(OD1)Asp274 3.83	4.28 0.45 4.50 0.67
	P(ref)-P(docked)	-	0.37	0.73
	centroid of sugar ring	-	0.37	1.85
	nucleotide 1
	centroid of sugar ring	-	0.68	2.18
	nucleotide 2

Table 4

 4 Relevant H-bond distances (in Å) between uridyl nucleotide dimer and active site residues of RNase A after docking with MOE using alpha-triangle placement method. Top hit, with the shortest average H-bond distances, is marked blue

	MOE	hit1 hit2 hit3 hit4 hit5 hit7
	(NZ)Lys41-O2'	2.94 2.98 2.97 2.98 3.02 2.94
	(NE2)His12-O2'	3.23 3.19 3.12 3.15 3.26 2.93
	(NE2)Glu11-O2P 2.98 3.01 3.47 2.93 3.15 3.56
	(NE2)His12-O1P	3.54 3.89 3.54 3.30 3.94 3.95
	(ND1)His119-O5P 2.77 3.13 2.70 2.96 2.98 2.82

Table 5

 5 Relevant H-bond distances (in Å) between uridyl nucleotide dimer and active site residues of RNase A after docking with GlideScore SP. Top hit, with the shortest average Hbond distances, is marked blue

	Glide	hit1 hit5 hit8
	(NZ)Lys41-O2'	3.01 2.99 2.86
	(NE2)His12-O2'	2.84 2.87 2.89
	(NE2)Glu11-O2P 2.94 2.84 2.93
	(NE2)His12-O1P	3.76 3.48 3.83
	(ND1)His119-O5P 2.76 2.87 2.88

Table 6

 6 Relevant H-bond distances (in Å) between the ligand and active site residues of RNase A after docking with MOE and Glide, respectively. Top hit is marked in blue

		MOE	MOE	Glide	Glide
		trimerU	tetramerU	trimerU	tetramerU
	(NZ)Lys41-O2'	2.93	3.86	3.00	2.69
	(NE2)His12-O2'	3.05	3.06	2.75	2.72
	(NE2)Glu11-O2P	2.84	3.54	2.96	2.72
	(NE2)His12-O1P	2.95	4.83	3.94	4.36
	(ND1)His119-O5P	2.85	2.97	2.74	3.83

Table 7

 7 Comparison of relevant protein-ligand interactions between docking results (best hit) and the reference structure. proO1P is the O1P atom of the following nucleotide. Distance and different values are given in Å

		ref.	MOE tetramer	MOE trimer	Glide tetramer	Glide trimer
			dist.	diff.	dist. diff.	dist.	diff.	dist. diff.
	O3'-(OD1)Asp210	3.35 3.57	0.22	2.94 -0.41 3.41	0.06	2.88 -0.47
	O3'-(OE1)Glu186	3.11 3.23	0.12	3.16 0.05	3.12	0.01	3.24 0.13
	O1P-(OE1)Glu186	3.38 3.52	0.14	3.63 0.25	3.53	0.15	3.60 0.22
	O1P-(OD1)Asp145	2.87 3.12	0.25	2.72 -0.15 3.02	0.15	2.67 -0.20
	O1P-(OD2)Asp145	3.26 3.44	0.18	3.09 -0.17 3.33	0.07	3.03 -0.23
	O1P-(OD1]Asp274	4.50 4.60	0.10	4.30 -0.20 4.44	-0.06	4.30 -0.20
	proO1P-(OD1)Asp274 3.83 3.86	0.03	4.03 0.20	4.24	0.41	3.96 0.13

Acknowledgments

The QM/MM optimization of the generated complexes was performed using EMSL, a national scientific user facility sponsored by the Department of Energy's Office of Biological and Environmental Research and located at Pacific Northwest National Laboratory.


Claire L Mitchell
email: claire.mitchell@christie.nhs.uk

J P B O'connor

C Roberts

Y Watson

A Jackson

Mitchell Cl

O ' Connor

Roberts

Watson

Cheung

Evans

Parker Gjm

Jayson Gc

Dr Claire Mitchell Mrcp

A two-part Phase II study of cediranib in patients with advanced solid tumours: the effect of food on single-dose pharmacokinetics and an evaluation of safety, efficacy and imaging pharmacodynamics

Keywords: Cediranib, CT enhancement, DCE-MRI, food, pharmacodynamics, pharmacokinetics

published or not. The documents may come   L'archive ouverte pluridisciplinaire

Introduction

Cediranib (RECENTIN™) is an oral, highly potent tyrosine kinase inhibitor that prevents activation of the vascular endothelial growth factor (VEGF) signalling pathway via VEGF receptor (VEGFR) -1, -2 and -3 [START_REF] Wedge | AZD2171: a highly potent, orally bioavailable, vascular endothelial growth factor receptor-2 tyrosine kinase inhibitor for the treatment of cancer[END_REF]. Early clinical data demonstrate that cediranib has antitumour activity across a broad range of tumours both as monotherapy and in combination with certain other agents [START_REF] Batchelor | AZD2171, a pan-VEGF receptor tyrosine kinase inhibitor, normalizes tumor vasculature and alleviates edema in glioblastoma patients[END_REF][START_REF] Drevs | Phase I clinical study of AZD2171, an oral vascular endothelial growth factor signaling inhibitor, in patients with advanced solid tumors[END_REF][START_REF] Mulders | Cediranib (RECENTIN™) in patients with advanced renal cell carcinoma: results of a randomized Phase II study[END_REF][START_REF] Matulonis | Phase II study of Cediranib (RECENTIN™, AZD2171) in recurrent epithelial ovarian cancer[END_REF][START_REF] Sridhar | Activity of cediranib (AZD2171) in patients (pts) with previously untreated metastatic renal cell cancer (RCC). A phase II trial of the PMH Consortium[END_REF][START_REF] Laurie | Phase I and Pharmacokinetic Study of Daily Oral AZD2171, an Inhibitor of Vascular Endothelial Growth Factor Tyrosine Kinases, in Combination With Carboplatin and Paclitaxel in Patients With Advanced Non-Small-Cell Lung Cancer: The National Cancer Institute of Canada Clinical Trials Group[END_REF][START_REF] Shields | AZD2171 in combination with various anticancer regimens: Followup results of a phase I multi-cohort study[END_REF]. Common adverse events in these studies included hypertension, diarrhoea and fatigue and these appear to be manageable. In all studies conducted to date, cediranib has been dosed to fasted patients. The primary objectives of this two-part study (study code 2171L0021) were to compare the pharmacokinetic parameters of cediranib obtained in patients in the fed and fasted state (Part A), and to compare the safety and tolerability of cediranib when given as either a fixed daily dose or an individualised dose-escalation plan (Part B).

An exploratory objective performed at a single participating centre was dynamic contrastenhanced magnetic resonance imaging (DCE-MRI) assessment of tumour microvascular function following cediranib treatment over 4-16 weeks. DCE-MRI has been used in several early phase clinical studies of antiangiogenic agents [START_REF] O'connor | DCE-MRI biomarkers in the clinical evaluation of antiangiogenic and vascular disrupting agents[END_REF] including cediranib [START_REF] Drevs | Phase I clinical study of AZD2171, an oral vascular endothelial growth factor signaling inhibitor, in patients with advanced solid tumors[END_REF], and to assess pharmacodynamic changes following treatment [START_REF] Morgan | Dynamic contrast-enhanced magnetic resonance imaging as a biomarker for the pharmacological response of PTK787/ZK 222584, an inhibitor of the vascular endothelial growth factor receptor tyrosine kinases, in patients with advanced colorectal cancer and liver metastases: results from two phase I studies[END_REF][START_REF] Liu | Dynamic contrast-enhanced magnetic resonance imaging as a pharmacodynamic measure of response after acute dosing of AG-013736, an oral angiogenesis inhibitor, in patients with advanced solid tumors: results from a phase I study[END_REF]. In the present study, DCE-MRI results were compared with those obtained using simple CT enhancement techniques to calculate tumour enhancing fraction (EnF) [START_REF] O'connor | Enhancing fraction predicts clinical outcome following first-line chemotherapy in patients with epithelial ovarian carcinoma[END_REF].

Methods

Study design

Part A was a crossover design in which patients received two single doses of cediranib 45 mg with an 8 days washout period. Patients were randomised 1:1 to receive treatment in either the fed followed by the fasted state, or the fasted then the fed state. In the fed period, patients ate a standard high-fat breakfast (as per FDA guidelines) completed 30 minutes prior to dosing with cediranib. In the fasted state, patients were dosed after an overnight fast (at least 10 hours before and 4 hours after dosing). Blood samples for pharmacokinetic analyses were collected over 168 hours post-dosing on each occasion.

The effect of food on the single-dose pharmacokinetics of cediranib was assessed using the criteria for establishing bioequivalence based on the endpoints of AUC and C max . One In Part B of the study, patients were randomised in a 1:2 ratio to receive daily dosing with cediranib, as either a fixed dose of 45 mg/day or a dose-escalation approach (individualised dosing plan). Patients in either arm could reduce their dose as a result of toxicity. The maximum tolerated dose (MTD) for each patient was defined as the highest dose for which there was continuous dosing for a period of at least 6 weeks, without dose breaks or interruptions, during the first 16 weeks of treatment. In the individualised doseescalation arm, patients received an initial dose of cediranib 30 mg/day for 14 days that was increased by 15 mg after each 14-day period, provided treatment was considered tolerable by the investigator. Toxicity assessments and dose increases continued until the MTD or 90 mg (individualised to the patient), whichever was lower. There was a minimum window of 14 days and a maximum window of 28 days between dose escalations. Treatment continued until withdrawal due to patient request, toxicity or loss of a clinical benefit from continued treatment (Figure I (b)).

This study was approved by a multicentre research ethics committee and by the research governance departments of all participating institutions, and all patients gave written informed consent prior to any study-related procedure.

Eligibility criteria

Eligible patients were those with histologically or cytologically confirmed advanced solid tumours that were refractory to standard therapies, or for which no standard therapy existed. All patients were required to have radiologically measurable disease; World Health Organisation performance status 0-2; adequate bone marrow, renal (creatinine clearance ≥50 ml/min) and liver function; be able to provide informed consent; and have no contra-indications to receiving VEGF inhibitors. Patients were excluded if they had poorly controlled hypertension or other severe or uncontrolled systemic diseases. For participation in the DCE-MRI research component of the study, standard MRI exclusion criteria were employed. Patients were eligible if they had primary or secondary hepatic tumours, or tumours at other sites of between 2-10 cm in diameter that were deemed assessable by the investigator.

Pharmacokinetic assessments

The primary endpoints of C max and AUC were analysed following single doses of cediranib in both the fed and fasted state. In Part A, blood samples for pharmacokinetic assessments were collected at pre-dose, and post dose at 30 minutes, 1, 2, 3, 4, 6, 8, 12, 24 and 36 hours, and on days 3, 4, 5, 6, 7 and 8. In Part B, blood samples for pharmacokinetic assessments were collected pre-dose and 3 hours post dose every 2 weeks until day 70. All samples were analysed for cediranib by high performance liquid chromatography with tandem mass spectrometry using a fully validated method. Sample storage stability for up to 6 months at -20°C has been established. The lower limits of quantification were 1 ng/mL in plasma. Pharmacokinetic parameters were calculated by standard noncompartmental methods using WinNonlin software (WinNonlin professional version 5.2) using standard equations.

Safety and tolerability

Adverse events were recorded throughout the study and graded according to the National Cancer Institute Common Terminology Criteria (CTC) version 3.0.

Electrocardiogram (ECG)

At screening, mean QT with Bazett's correction (QTcB) had to be <470 ms. In Part A of the study, digital ECGs were recorded in triplicate at screening and on day 1 during the fed period of Part A. ECGs were also recorded at pre-dose, on days 1, 2, and 8, and during the fasted period of Part A. The ECG data recorded on day 8 (post 1 week washout, predose) were used as a within patient control. During Part B of the study, ECGs were recorded at screening (if the patient had not participated in Part A of the study) and at pre-dose and 3 hours post dose on day 1, week 2, week 4 and at the discontinuation visit. In Part A and Part B, assessments of QT were corrected using both Bazett's (QTcB) and Fridericia's formulae (QTcF). A single independent cardiologist, who was blinded to time, treatment and patient identifier, evaluated the digital ECGs centrally.

Efficacy

Tumours were evaluated and categorised according to Response Evaluation Criteria for Solid Tumors (RECIST) determined using anatomical CT scans [START_REF] Therasse | New Guidelines to Evaluate the Response to Treatment in Solid Tumors[END_REF]. Scans were performed prior to Part A, at baseline prior to Part B, at week 8, week 16 and then at 8 weekly intervals until disease progression.

Pharmacodynamic assessments

At the Christie Hospital NHS site only, the effects of cediranib on vascular parameters were assessed in 10 patients by DCE-MRI. All patients recruited at this site were eligible to voluntarily enter the DCE-MRI component of the study. To assess reproducibility of the parameters, two baseline DCE-MRI scans were performed within a week of each other prior to Part A, with further scans performed in the week prior to starting continuous therapy (Part B) and at weeks 4, 8 and 16. A previously described standard DCE-MRI acquisition protocol was used on a Phillips 1.5T Intera scanner using Omniscan™ contrast agent was employed [START_REF] Ton | Phase I evaluation of CDP791, a PEGylated di-Fab' conjugate that binds vascular endothelial growth factor receptor 2[END_REF][START_REF] Mullamitha | Phase I evaluation of a fully human anti-alphav integrin monoclonal antibody (CNTO 95) in patients with advanced solid tumors[END_REF][START_REF] O'connor | Quantifying Antivascular Effects of Monoclonal Antibodies to Vascular Endothelial Growth Factor: Insights from Imaging[END_REF]. Whole tumour volumes were selected as regions of interest and defined in 3D manually using the anatomical images by an experienced clinician. Tracer kinetic modelling using the extended Tofts model was applied to each enhancing voxel within the defined whole tumour volume and a median or mean summary value for each parameter was provided for the tumour [START_REF] Tofts | Modeling tracer kinetics in dynamic Gd-DTPA MR imaging[END_REF]. To calculate the parameters, arterial input functions (AIF) were either extracted from the imaging data [START_REF] Parker | Buckley DL Automated Arterial Input Function Extraction for T1-Weighted DCE-MRI[END_REF] or where a suitable artery was not visible within the field of view or it was not possible to use the vessel for AIF calculation, ie due to image artefacts, a previously-derived AIF was employed [START_REF] Parker | Experimentally-derived functional form for a population-averaged high-temporal-resolution arterial input function for dynamic contrast-enhanced MRI[END_REF]. The model provided estimates of tumour microvascular characteristics, including K trans (trans-capillary contrast agent transfer constant), representing tumour capillary blood flow and permeability, V e (fractional size of the extracellular extravascular space) and V p (fractional size of the blood plasma volume). The initial area under the tumour contrast agent-time curve over the first 60 seconds post contrast agent arrival (IAUC 60 ), a semi-quantitative parameter that reflects the amount of contrast agent delivered and retained in the tumour, was also determined [START_REF] Evelhoch | Key factors in the acquisition of contrast kinetic data for oncology[END_REF].

At each CT RECIST assessment patients who participated in the DCE-MRI study had their conventional contrast-enhanced CT scans using Omnipaque 300™ contrast agent analysed using an additional CT threshold technique to calculate tumour EnF [START_REF] O'connor | Enhancing fraction predicts clinical outcome following first-line chemotherapy in patients with epithelial ovarian carcinoma[END_REF]. CT image analysis was performed using MRIcro software [START_REF] Rorden | Stereotaxic display of brain lesions[END_REF] and applied to the same whole tumour volumes used for DCE-MRI analysis. To exclude cystic and calcified areas within the region of interest from analysis, thresholds of <10 HU (Hounsfield units) and >150 HU were applied. The enhancing fraction of the tumour (proportion of enhancing tumour tissues excluding cystic and calcified areas) was determined using four thresholds, 50 HU, 60 HU, 70 HU, and 80 HU to provide an estimate of tumour vascularity.

Statistical analyses

In Part A, food would be considered to have no effect on the pharmacokinetics of cediranib if confidence intervals (CI) for the food effect ratio for the endpoints of AUC and C max of plasma cediranib fell within the acceptance range of 0.8-1.25. The trial was sized to give 90% power with an overall type I error of 5%. As there was little known information on AUC and C max a planned an interim analysis occurred once complete data was available for 12 patients, this determined the group size required (n=60). As the interim analysis was undertaken 94% CIs were constructed to preserve the overall type I error (using a Pocock alpha spending rule). It would be declared there was no effect of food if the 94% CI fell entirely within 0.8-1.25 for both AUC and C max . Pharmacokinetic parameters from the fed and fasted groups were compared statistically using an analysis of variance (ANOVA) model fitting for the effects of sequence, patients within sequence, period and food (fed/fasted). Patients were eligible for the pharmacokinetic population if they had at least one pharmacokinetic sample, although they may not have been assessable for all of the defined pharmacokinetic parameters. Patients who failed to ingest a significant amount of the breakfast as judged by the investigator were excluded with guidelines provided for assessment.

For the ECG assessments the formal comparison was conducted by using an analysis of covariance (ANCOVA) model including factors of sequence (fed/fasted or fasted/fed), treatment (test/control arm) and patient within sequence, and baseline as a covariate.

In Part B, the safety outcome variable of exposure to cediranib over 16 weeks was summarised for each patient. Efficacy and pharmacodynamic data were evaluated on an intent-to-treat (ITT) basis. The safety population consisted of all randomised patients who received at least one dose of study medication.

For the DCE-MRI analysis, all available data from the different parts of the study were used. Where multiple lesions were present within a single patient these were combined into a single measurement for the patient. Whole tumour volume for each patient was the total of the individual volume of lesions; the other DCE-MRI parameters used a geometric mean of lesions within in each patient. For each of the parameters, the percentage change from baseline with associated 95% CI was estimated by using an analysis of covariance (ANCOVA) model including patient as a random effect, visit as a fixed effect, and baseline as a covariate. The analysis was based on log-transformed data, and data were then back-transformed prior to calculation of percentages and the associated 95% CIs. The intra-patient variation of MRI parameters was estimated using a mixed-effects linear model including patients that had at least one MRI assessment for reproducibility. The effects of cediranib on MRI parameters were assessed by analysing the reduction in MRI parameters from baseline over the study period up to 16 weeks via a mixed-effects linear model.

CT EnF enhancement data were assessed per scan visit and non-parametric tests (Wilcoxon signed rank) were used to test for differences between visits from baseline (commencement of Part B) and subsequent visits. To explore the relationship between the CT EnF and DCE-MRI parameters, values were paired for each patient at each visit and non-parametric correlations (Spearman's rank bivariate) were applied.

Results

Patients

Pharmacokinetics

Table II summarises the pharmacokinetic parameters following single oral doses of cediranib 45 mg in the fed and fasted states. The primary objective of Part A showed that both the AUC and C max of cediranib were lower in the presence of food by a mean of 24% and 33%, respectively (94% CI: AUC, 12-34% lower and C max , 20-43% lower).

The CI for AUC crossed the lower equivalence boundary of 0.8, and the upper boundary of the CI was <1. The CI for C max was entirely outside the equivalence boundary, indicating a clear effect.

Steady state pharmacokinetics was a secondary objective within part B of the study. High variability of the pharmacokinetic parameters was seen within the population due to significant proportion of the patients undergoing either escalation or de-escalation during the study period.

Safety and tolerability

The mean (standard deviation, SD) dose per day during Part B of the study was 33.79 (9.35) and 31.16 (9.03) mg in the 45 mg fixed-dose and dose-escalation groups, respectively. In the fixed-dose group (n=16), two patients were able to maintain their 45 mg/day dose longer than 6 weeks while six patients required a dose reduction to 30 mg/day. In the dose-escalation group (n=31), the MTD was 20 mg/day for two patients, 30 mg/day for 10 patients, 45 mg/day for five patients, and 60 mg/day for two patients.

The per protocol MTD was undefined for the remaining patients in the fixed-dose (n=8) and dose-escalation (n=12) groups due to insufficient drug exposure, i.e., <6 weeks continuous treatment.

Diarrhoea and hypertension were the most common adverse events in Part B (Table III).

There was a low overall incidence of CTC grade 3 adverse events, with the majority events occurring as single instances; seven patients experienced a grade 4 adverse event and four patients experienced a grade 5 adverse event. Overall, the incidence of adverse events was similar between the fixed-versus dose-escalation groups. Four cases (two fatal) of bowel perforation occurred during Part B; three in patients receiving 45 mg/day and one receiving 20 mg/day. Three of these patients were known to have disease directly involving the gastrointestinal tract or the abdominal cavity and this was considered to be a confounding factor. The tumour types in these three patients were cancer of the appendix ('other'), ovarian cancer with gastrointestinal metastases, and 'unknown' primary tumour with abdominal metastases.

ECG

Assessment of QTc in this study showed no clinically relevant changes following single or multiple dosing with cediranib 45 mg. The primary analysis in Part A compared baseline subtracted QTcF at the time of individual C max with baseline subtracted QTcF at the corresponding time in the control arm. The day 8 data (post 1 week washout, predose) were used as a within patient control. The mean effect was -3.343 ms (90% CI -9.13, 2.44; P=0.3329), indicating no clinically relevant effect of cediranib on cardiac repolarisation as determined by QTcF. In Part B, the mean change from baseline in QTcF/QTcB was 0.3/-0.7 ms, -7.3/-8.5 ms and 2.4/-1.4 ms for the 45 mg fixed dose, and the 30 mg and 45 mg dose escalation groups, respectively. Assessment of individual patient data did not suggest that multiple daily dosing with cediranib 45 mg causes any increase in QTcF or QTcB over time (note: no ECGs were taken during the short time interval when a small number of patients were receiving a dose higher than 45 mg).

Efficacy

In Part B, four patients experienced a best objective response of partial response (PR); one (7%) in the fixed-dose group and three (10%) in the dose-escalation groups. Stable disease (≥8 weeks) was reported for four (27%) and 9 (31%) patients in the fixed-dose and dose-escalation groups, respectively. PR primary tumour types consisted of ovarian cancer; head and neck; poorly differentiated (grade 3) tumour located in the peritoneum, and adenocarcinoma of unknown primary origin. In both the fixed-dose and doseescalation groups, the majority of patients showed a reduction as their best response in tumour size and there was no suggestion of a dose response (Figure II).

Pharmacodynamic results

Two initial scans were performed prior to Part A to define the reproducibility of the DCE-MRI parameters and volumes. The DCE-MRI parameters IAUC 60 , K trans , V e , whole tumour volume and enhancing tumour volume were shown to have good reproducibility with CVs of approximately 10%; V p was less reproducible with a CV of 38%. There was no difference between the DCE-MRI parameters from the two reproducibility scans performed prior to Part A and the baseline scan for Part B indicating that the two single doses of cediranib given during Part A, whilst known to cause an acute reduction in DCE-MRI parameters [START_REF] Drevs | Phase I clinical study of AZD2171, an oral vascular endothelial growth factor signaling inhibitor, in patients with advanced solid tumors[END_REF] did not have a sustained effect upon the tumour vascularity (data not shown). DCE-MRI data from Part B showed an overall mean reduction from baseline for both median IAUC 60 and median K trans , with a statistically significant mean decrease for K trans at all visits (weeks 4, 8 and 16) and for IAUC 60 at weeks 4 and 8 (Table IV). A parameter map for K trans for a patient with a colorectal liver metastasis is shown in Figure III, demonstrating the reduction in K trans observed after 16 weeks of cediranib therapy. It was noted that in two cases, that patients with stable disease at week 16 did not achieve a reduction in IAUC 60 or K trans until week 8. Statistically significant reductions in V e (extracellular space volume fraction) and V p appeared to occur later (at week 8) returning to previous levels by week 16. When considering these results it should be noted that V p is less reproducible as a parameter and that patient numbers at the later time points were limited to patients coming off study because of progressive disease. Although the reduction in whole tumour volume did not achieve statistical significance, an overall reduction in the enhancing tumour volume on MRI from baseline was observed at weeks 4, 8 and 16 (significant at week 4 and 16 P≤0.05) (Table IV).

The CT EnF was also analysed as an integrated measure of tumour vascularity and means of assessing the effects of cediranib. The data showed statistically significant reductions in CT EnF at all four thresholds, which correlated with the DCE-MRI parameter findings.

Of the patients that participated in DCE-MRI research, five patients with seven assessable tumours had lesions that were suitable for assessment using CT EnF analysis. One patient who participated in the DCE-MRI study for Part B was excluded from analysis due to CT contrast agent allergy. Analysis of the CT data showed that the whole tumour volume defined on standard CT correlated strongly to the equivalent whole tumour volume defined on DCE-MRI (Spearman's correlation ρ=0.955). All four thresholds showed reductions in enhancement with an average reduction in enhancing fraction at week 8 of -17.43% and week 16 -25.41% (P=0.036 and P=0.028 respectively). This is consistent with a sustained antivascular effect of cediranib. The results from the separate visits were pooled to explore the relationship between the CT EnF and DCE-MRI parameters. CT EnF was not observed to correlate with either MRI enhancing tumour volume or enhancing fraction. The CT EnF at each threshold correlated significantly with the MRI modelled parameters of IAUC 60 (Spearman's correlation ρ=0.890, 0.863, 0.812 and 0.678 for 50, 60, 70 and 80 HU, respectively, P≤0.005) and K trans (Spearman's correlation ρ=0.881, 0.869, 0.853, 0.782 for 50, 60, 70 and 80 HU, respectively, P≤0.005), implying that CT EnF may have potential as an alternative measure of tumour vascularity in the assessment of cediranib and other antiangiogenic agents.

Discussion

This two-part Phase II study was designed to determine the effect of food on the pharmacokinetics of cediranib (Part A), and to assess the tolerability and efficacy of multiple doses of cediranib in patients with advanced solid tumours (Part B). In Part A, the pharmacokinetic assessment showed a modest reduction in AUC and C max in the presence of food and it is therefore recommended that cediranib be administered at least 1 hour before, or 2 hours after food. A food effect on pharmacokinetics is not unique to cediranib amongst antiangiogenic agents. The pharmacokinetics of axitinib and sorafenib are also affected by food [START_REF] Rugo | Phase I trial of the oral antiangiogenesis agent AG-013736 in patients with advanced solid tumors: pharmacokinetic and clinical results[END_REF] (NEXAVAR Prescribing information 2009). As with cediranib the recommendation is that sorafenib be administered at least 1 hour before, or 2 hours after food.

Patients generally tolerated cediranib well at the average dose, with some patients tolerating higher doses with the dose escalation arm. The tolerability profile of cediranib in this study was consistent with previous studiesdiarrhoea, nausea and hypertension were the most common adverse events and these were manageable [START_REF] Drevs | Phase I clinical study of AZD2171, an oral vascular endothelial growth factor signaling inhibitor, in patients with advanced solid tumors[END_REF][START_REF] Mulders | Cediranib (RECENTIN™) in patients with advanced renal cell carcinoma: results of a randomized Phase II study[END_REF][START_REF] Batchelor | AZD2171, a pan-VEGF receptor tyrosine kinase inhibitor, normalizes tumor vasculature and alleviates edema in glioblastoma patients[END_REF][START_REF] Trarbach | A phase I, open-label, multicenter study of cediranib and AZD0530 in patients with advanced solid tumors[END_REF][START_REF] Langenberg | Optimal management of emergent hypertension during treatment with a VEGF signaling inhibitor: A randomized phase II study of cediranib[END_REF]. There were no important differences in the safety and tolerability of cediranib when given as either a fixed-dose or using a dose-escalation approach. In both groups, the average daily dose was approximately 30 mg/day. Only a minority of patients were able to tolerate cediranib 45 mg for 6 weeks and for most patients a 30 mg dose appears to be more sustainable for chronic dosing. Importantly, no clinically relevant effect of cediranib on cardiac repolarisation, as determined by QTcF and QTcB, was detected following single oral dose of cediranib 45 mg (Part A), or following multiple daily dosing (Part B). A preliminary assessment of activity provided encouraging results in a broad range of tumours, consistent with results of an earlier Phase I study of cediranib [START_REF] Drevs | Phase I clinical study of AZD2171, an oral vascular endothelial growth factor signaling inhibitor, in patients with advanced solid tumors[END_REF]. The efficacy data provide encouraging evidence antitumour activity in both the fixed-dose and doseescalation groups, with no evidence of a dose response.

An exploratory objective in Part B was to assess the effects of cediranib on tumour blood flow and permeability using DCE-MRI. Our results have shown for the first time that cediranib has a sustained effect upon extra-cranial tumour vasculature up to 16 weeks after starting continuous cediranib therapy in patients. These effects were detected by DCE-MRI scanning and by applying CT enhancement techniques. The effects of cediranib on DCE-MRI parameters on extra-cranial tumour vasculature has previously been established within the Phase I setting [START_REF] Drevs | Phase I clinical study of AZD2171, an oral vascular endothelial growth factor signaling inhibitor, in patients with advanced solid tumors[END_REF]. This earlier study assessed the treatment effect upon liver metastases up to a maximum of 56 days therapy; the acute vascular effects of cediranib were observed in DCE-MRI assessments following 2 days of therapy.

In this study only IAUC 60 and K trans were reported, with IAUC 60 being the primary outcome measure. Our current study applied the 'extended Tofts' model of tracer kinetics allowing the parameters of IAUC 60, K trans , V p and V e to be determined with the period of follow-up on DCE-MRI extending to week 16. The purpose of the trial was to evaluate the effects of chronic dosing of cediranib on tumour vasculature; the earliest assessment within the study was after 4 weeks of continual therapy. At this time point, significant reductions were observed in the average parameters; however, in some individual patients with stable disease up to at least 16 weeks the development of reductions in IAUC 60 , K trans and V p did not occur until later at week 8. These late decreases in the DCE-MRI parameters may potentially represent the effects of VEGF signalling inhibition on blood volume and vessel size similar to those observed in previous studies [START_REF] Batchelor | AZD2171, a pan-VEGF receptor tyrosine kinase inhibitor, normalizes tumor vasculature and alleviates edema in glioblastoma patients[END_REF]. Reduction in blood vessel volume and hence V p in turn could lead to a reduction in the parameter of K trans (the transfer constant co-efficient) due to the impact upon tumour blood flow, as K trans is a composite parameter reflecting both blood flow and capillary permeability. The data potentially could be interpreted to suggest that the early reductions in K trans may relate to the reduction in capillary permeability induced by the drug, whereas the later and persistent decreases in the parameters may reflect vascular normalisation in line with the later reduction in V p. However, the parameter V p is only significantly reduced at week 8, and this is not sustained to week 16 which may relate to the small numbers of patients remaining on the study at the later time point. Ideally studies with a larger number of participants are required in order to test this hypothesis.

The development of late-onset statistically significant imaging effects has not been reported before, and implies that early clinical and biomarker evaluation of antiangiogenic agents should be extended to approximately 8 weeks before concluding that an agent is biologically inert.

The use of CT calculated EnF applied to standard contrast-enhanced anatomical CT scans, which were originally requested for RECIST analysis before entry to the trial, has not been used previously to evaluate the effects of VEGF inhibition on tumour vascularity.

The data demonstrate a reduction in the CT EnF following commencement of continual cediranib therapy up to week 16, with CT EnF values correlating to the DCE-MRI parameters IAUC 60 and K trans . The difference in correlations of CT EnF at the different hounsfield unit thresholds may relate to the difference in specificity of thresholds to tumour vascularity, with the 50HU threshold being the least specific for vascular areas and more likely to incorporate both vascular and non-vascular areas. DCE-MRI parameters represent different compartments and properties of the tumour, therefore the relationship between the DCE-MRI parameters and CT EnF at each threshold will vary.

Although the CT EnF is less physiologically specific than DCE-MRI parameters, it is an attractive method of vascular assessment as it can be performed as a supplementary analysis on routine scans eliminating the need for additional visits or further radiation exposure.

In conclusion, this study showed that food has a modest effect on the pharmacokinetics of cediranib and it is recommended that cediranib be administered at least 1 hour before, or 2 hours after food. Cediranib was generally well tolerated with a manageable safety profile and encouraging antitumour activity was observed in this patient population with advanced disease. The 30 mg dose appeared to be most sustainable for chronic dosing.

  week after completing the second dose of cediranib, eligible patients could progress to Part B of the study. Patients not entered into Part A could enter into Part B directly, once Part A was complete (Figure I (a)).

Between

  June 2006 and October 2008, 60 patients were randomised and 54 received at least one dose of study treatment. Five patients remained on study treatment at data cutoff (the date by which all patients had reached week 16 or had withdrawn). Table I summarises the baseline demographics and patient characteristics in Parts A and B of the study. Ten patients from the Christie Hospital NHS site participated in the DCE-MRI component of the study. Three of these patients did not proceed into Part B of the study and therefore only had reproducibility scans performed. Seven patients were scanned during Part B (continual dosage)two of whom had multiple assessable tumours, leading to a total of eleven tumours assessable by DCE-MRI during the continual administration phase.

  Cediranib did not cause QTc prolongation. Continuous once-daily dosing with cediranib had extended effects upon tumour vascularity up to week 16 as measured by reductions in DCE-MRI parameters, with some patients showing first significant reductions as late as week 8. The retrospective CT enhancing fraction analysis illustrates the potential role this technique may have in the assessment of antiangiogenic agents.

FigI

  Fig I Study scheme (a) Part A and (b) Part B

Table I :

 I Baseline demographics and patients characteristics

				Part A n=45	Part B n=47	Total
			Cediranib 45 mg	Cediranib 45 mg	Cediranib 45 mg	Cediranib 30-90 mg
			Sequence A	Sequence B	fixed dose	dose escalation
			Fed/fasted n=23	Fasted/fed n=22	n=16	n=31	n=60
	Age, years
	mean (SD)	58.6 (10.6)	51.2 (14.8)	56.4 (13.1)	56.0 (13.5)	56.0 (13.0)
	range	32-73	19-70	19-73	22-74	19-74
	Sex, n
	male/female	13/10	12/10	8/8	19/12	32/28
	Race, n
	Caucasian/oriental	23/0		22/0	16/0	30/1	59/1
	Primary tumour location
	Ovary	3 (13.0)	4 (18.2)	2 (12.5)	4 (12.9)	9 (15.0)
	Colon	3 (13.0)	3 (13.6)	2 (12.5)	3 (9.7)	8 (13.3)
	Rectal	4 (17.4)	1 (4.5)	0 (-)	7 (22.6)	7 (11.7)
	Skin/soft tissue	1 (4.3)		1 (4.5)	1 (6.3)	3 (9.7)	5 (8.3)
	Renal	2 (8.7)		2 (9.1)	2 (12.5)	1 (3.2)	4 (6.7)
	Breast	2 (8.7)		1 (4.5)	1 (6.3)	1 (3.2)	3 (5.0)
	Head and neck	1 (4.3)		1 (4.5)	0 (-)	3 (9.7)	3 (5.0)
	Other	†	3 (13.0)	4 (18.2)	4 (25.0)	3 (9.7)	8 (13.3)
	WHO performance status
	0/1/2/missing	11/10/1/1	11/8/0/3	7/9/0/0	15/15/0/1	27/28/1/4
	**Most frequent (≥5% of patients overall);	† includes (n): right anterior thigh (1), melanoma on the right foot (1), left eye (1), chest wall (1), appendix (1),
	unknown primary (2) and chondrosarcoma of lung (1)

Table II :

 II Summary of pharmacokinetic parameters following single oral doses of cediranib 45 mg for fed and fasted states during Part A: pharmacokinetic analysis setFood effect ratio = ratio of cediranib fed Gmean : cediranib fasted Gmean Gmean, geometric mean, CV coefficient of variation.

		Cediranib		Cediranib
		45 mg Fed state	45 mg Fasted state	Point estimate of Gmean ratio of fed	94% CI of Gmean ratio of
	Pharmacokinetic parameter	n	Gmean (CV%)	n	Gmean (CV%)	to fasted	fed to fasted
	AUC (ng*h/mL)	30	1920 (62.03)	32	2392 (57.23)	0.762	0.663, 0.876
	C max (ng/mL)	31	87.3 (66.01)	33	127.9 (60.48)	0.672	0.567, 0.796

Table IV :

 IV Change (%) from baseline in MRI parameters over study period (up to and including week 16) Percentage change and CIs were determined from least squares estimates based on log transformed data. Data was back-transformed prior to the calculation of percentage

	Parameter	Visit	n	% Change from baseline	95% CI	P-value (2-sided)
	IAUC 60	Week 4	6	-30.5	-50.5, -2.4	0.010
		Week 8	4	-33.2	-53.4, -4.4	0.009
		Week 16 4	-13.1	-39.3, 24.4	0.090
	K trans	Week 4	6	-36.2	-57.6, -4.0	0.009
		Week 8	4	-44.0	-65.3, -9.6	0.007
		Week 16 4	-32.6	-58.2, 8.7	0.002
	V e	Week 4	6	-13.8	-29.4, 5.2	0.029
		Week 8	4	-29.4	-44.9, -9.6	0.004
		Week 16 4	-12.9	-32.2, 11.8	0.053
	V p	Week 4	6	-29.5	-61.6, 29.4	0.050
		Week 8	4	-63.9	-82.7, -24.5	0.004
		Week 16 4	-23.0	-64.1, 65.5	0.105
	Whole tumour volume	Week 4	6	-8.2	-29.0, 18.7	0.108
		Week 8	4	-11.1	-35.6, 22.6	0.098
		Week 16 4	-15.5	-39.7, 18.3	0.064
	CT Enhancing Fraction	Week 8	5	-17.43	-68.8, 34.0	0.036
		Week 16 4	-25.14	-53.5, 3.2	0.028
	Note:

Acknowledgements

We would like to thank the patients who entered this study and all the research teams at all the sites. In addition we would like to thank CRUK for there support of the clinical research teams involved within this study.

We thank Dr Jen Lewis, from Mudskipper Bioscience, who provided medical writing support funded by AstraZeneca.

RECENTIN™ is a trade mark of the AstraZeneca group of companies.

Disclosures: None


J Raud

M Laan

I Jõgi

Rotational temperatures of N 2 (C,0) and OH(A,0) as gas temperature estimates in the middle pressure Ar / O 2 discharge

Keywords: Classification numbers (PACS): 52, 70, Kz, 52, 80, Pi

Radiative transitions N 2 (C-B,0-0) and OH(A-X,0-0) were used in order to estimate rotational temperatures of N 2 (C,0) and OH(A,0) in the middle pressure Ar / 0.5% O 2 RF discharge. N 2 (C,0) and OH(A,0) rotational temperature dependence on power density was determined and quenching / rotational relaxation frequencies of N 2 (C,0) and OH(A,0) was calculated. It was found that at our conditions rotational temperature of OH(A,0) can be used for estimation of gas temperature while N 2 (C,0) rotational temperature overestimates the gas temperature.

Introduction

Many plasma characteristics depend on the gas (translational) temperature, T G . There are several T G estimation methods e.g. by using pressure rise in closed systems due to temperature rise, by using thermocouples, spectral methods [1] etc. The gas temperature is frequently estimated on the basis of rotational temperature, T Rot , of some molecules M* (e.g. N 2 , N 2 + , OH, O 2 , CO, CH etc. [2,3]). However, this is possible only when some main conditions are fulfilled. First of all, the population of rotational states should follow the Boltzmann distribution. Besides, one of the next cases should be valid: (1) the initial rotational population distribution (i.e. distribution just after the excitation) of M* corresponds to that equilibrium with T G (hereafter: thermalized distribution). For example reaction, thermalized one [4,5]. Here He m stands for He metastable state atom.

(2) the initial rotational population distribution is non-thermalized but the lifetime of M* is longer than the time needed for the collisional relaxation to thermalized state. As a rule the condition holds better at higher pressures and smaller difference between the initial T Rot and T G . Rotational temperatures T Rot (N 2 ) and T Rot (OH), determined on the basis of spectra of N 2 (C-B,0-0) and OH(A-X,0-0) transitions, are widely used for the estimation of gas temperature [6, 7, 8, 9 etc.]. We used these transitions to investigate the gas temperature of discharge in the argon-oxygen mixture at a low O 2 fraction. In similar mixtures non-thermalized or partly non-thermalized distribution of N 2 (C,0) and/or OH(A,0) have been found [1, 10, 11, 12, 13 etc.]. Thus, it was not clear whether the calculated rotational temperatures characterize the gas temperature or not.

The aim of the study is to clarify whether T Rot (N 2 ) and T Rot (OH) could be used as gas temperature estimates in the positive column region of the RF discharge in middle pressure Ar / 0.5% O 2 mixture.

For this purpose rotational spectra of N 2 (C-B,0-0) and OH(A-X,0-0) transitions were recorded as a function of input power. On the basis of these measurements, the corresponding rotational temperatures were determined and quenching/rotational relaxation frequencies of excited states were calculated.

Set-up

Set-up is described in more details in [14]. Figure 1 presents a sketch of experimental device. When O 2 flow corresponding to 0.5% O 2 concentration was set, the pressure raised up to ca



Torr. Thus, the concentration of N 2 was smaller than 0.5%. The bore diameter of the tube was d=6.5 mm. The discharge was excited with the generator of 40 MHz frequency and 100 W output power. The voltage was applied to the metal strap enveloping the tube. Another electrode, metal cylinder, was grounded and situated inside the tube. The distance between electrodes, L, was changeable but most of the experiments were carried out at the distance of L=80 mm. The electrical characteristics were recorded with oscilloscope TDS-540B. Spectra belonging to the positive column region of the discharge were recorded with spectrometers Ocean Optics 4000 and MDR-23 from lateral direction of the tube. Relative spectral sensitivity was determined by using Ocean Optics DH-2000-Cal calibrated light source. The temperature of the outer surface of the quartz tube was measured with the infrared thermometer Meterman IR608.

Results and discussion

Electrical characteristics

Electrical characteristics are described in more details in [14]. The equivalent circuit of electrical schema consisted from serially connected capacitor and plasma resistance. The capacitor consisted from the capacitance of quartz tube wall and near electrode space charge layer. Registered i-u curves and phase shift, , between i and u allowed to calculate the plasma voltage, R cos( ) uu   . Spectral measurements from different positions between electrodes showed that the intensity of spectral lines did not depend on the recording position. This indicated that electric field strength in the positive column, E PC , was uniform. To determine E PC , i-u curves and were recorded at different distances between powered and grounded electrodes (L = 40, 60 and 80 mm). At a constant current the voltage u R grew linearly with the increase of distance between electrodes, L. The electric field strength E PC was obtained from the slope of the dependence u R = f(L). Electron temperature T e and mobility were determined by taking OH(A,0) rotational temperature as a gas temperature and using code Bolsig+ [15]. Known mobility allowed to calculate electron concentration n e . At our experimental conditions E PC =1-13 V/cm, T e  4 eV, n e 10 12 cm -3 . Current density was calculated as, i j S  , where the cross-section, S, was taken equal to the inner cross-section of the quartz tube. The intensive spectral lines seen in figure 2 belonged to Ar and O. Weak band of trace gas OH(A-X) near 308 nm was also distinguishable in Ar / 0.5% O 2 mixture (figure 2 inset). The intensity of OH band was ca 200 times lower than the intensity of Ar 811.5 nm line. Addition of a small amount of N 2 caused the appearance of N 2 (C-B) bands. Most intense N 2 (C-B) bands belonged to the vibrational transitions 0-0 (bandhead at 337.1 nm), 1-0 (315.9 nm), 0-1 (357.7 nm) and 1-2 (353.7 nm). Intensity of bands N 2 (C, v  2) were very weak. The addition of N 2 did not influence the intensity of Ar lines but the intensity of OH band decreased.

Spectral measurements

Determination of rotational temperature

The rotational temperature was estimated comparing experimental spectrum and synthetic spectrum calculated for different temperatures assuming Boltzmann distribution of rotational states population. The temperature assuring the best fit between experimental and synthetic spectra was taken as rotational temperature. Apparatus function necessary for calculations of synthetic spectrum was measured by using a low pressure mercury lamp. The shape of spectral line fitted satisfactory with a Gaussian profile. Rotational spectrum of N 2 (figure 3(a)) was calculated using data taken from [16]. For the calculation of synthetic spectrum the convolution integral of the apparatus function and the rotational spectrum was calculated. The best fit between synthetic and measured spectra was achived using the least square method. Because of the contribution of NH(A-X) weak emission at   336 nm, the fitting was performed in spectral ranges 334.1 -335.3 nm and 336.5 -337.1 nm.

For the determination of OH(A, v=0) rotational temperature, the spectra comparison was carried out using code LIFBASE [START_REF] Luque | LIFBASE: Database and Spectral Simulation Program (Version 1.5)[END_REF]. The spectrum of OH(A-X, 0-0) in wavelength region 305-311 nm is shown in the figure 3 T Rot (N 2 ) was higher than T Rot (OH) in the whole range of power density values. T Rot (OH) increased with the growing power density as expected, but the decrease of T Rot (N 2 ) at higher power densities suggested that T Rot (N 2 ) was not related to the gas temperature. It should be pointed that there was a linear dependence between T Rot (OH) and the temperature at the outer surface of the tube whereas the correlation coefficient was 0.94. The same dependence in the case of T Rot (N 2 ) gave correlation coefficient 0.54. In order to clarify the remarkable discrepancy of rotational temperatures it is essential to carry out a analysis of factors influencing N 2 (C,0) and OH(A,0) rotational state populations.

Population of N 2 (C,0) and OH(A,0) rotational states

Estimations given in this section are calculated by using following values: concentrations of electrons, Ar and O 2 are respectively n e =10 12 cm -3 , n Ar =4 10 16 cm -3 , n O2 =2 10 14 cm -3 , velocities of electrons and Ar atoms are respectively v e  1 10 6 m s -1 , v Ar  5 10 2 m s -1 . These values are characteristic to our experimental conditions. In the stationary Ar / O 2 / N 2 discharge there are several mechanisms which could populate N 2 (C) state e.g. stepwise electron impact excitation from lower N 2 states, pooling reactions from N 2 (A), cascade population from higher energy levels of nitrogen molecule, energy transfer between N 2 (X) and metastable Ar atoms, Ar m and direct electron impact excitation from N 2 ground state. The latter mechanism produces N 2 (C,0) at rotational temperature close to gas temperature [11]. As in our case the N 2 concentration was low, the population of N 2 (C) by pooling reaction played a negligible role. The ground state and cascade paths of N 2 (C) excitation are also not the main excitation routes as the electric field strength in the positive column in noble gases is considerably lower than that in molecular gases [START_REF] Raizer | Gas Discharge Physics[END_REF]. The most probable N 2 (C) producing mechanism in our conditions is reaction 2 m 2 N (X, 0) Ar N (C, 3) Ar vv      (1). As a rule, the products of the reaction (1) are in vibrational states v  3, whereas ca 80 % are in state v=0 ( [START_REF] Nguyen | [END_REF]20]). We detected bands starting from the vibrational states v=0,1 of N 2 (C), other ones were very weak. According to [START_REF] Nguyen | [END_REF]21,22], high rotational states of N 2 (C,0) are populated by reaction (1). Thus, T Rot (N 2 ) is close to T G only in the case when the time constant of thermalization of N 2 (C,0) rotational states is shorter than the state lifetime. The lifetime of N 2 (C,0) state is determined by the radiative decay and by quenching in collisions with the host gas particles and electrons. Radiative decay frequency of N 2 (C,0) state is ca s -1 [23]. Using the cross-section q_e  10 -15 cm 2 [10],

the quenching frequency by electrons is q_e  10 5 s -1 . Quenching frequency of N 2 (C) by O 2 is only q_O2   5 10 4 s -1 (rate coefficient k q_O2 =2.7 10 -10 cm 3 s -1 , [23]) and quenching frequency of N 2 (C) by Ar is even smaller, q_Ar   10 4 s -1 (k q_Ar =3 10 -13 cm 3 s -1 , [24]). Because of low concentration, can neglect the quenching by N 2 (X). Thus, in our experimental conditions the lifetime of N 2 (C,0) is mainly determined by the radiative lifetime.

The cross-section of N 2 (C,0) rotational relaxation by Ar is Rel  10 -15 cm 2 [25], thus frequency of relaxation in collisions with Ar is Rel   2 10 6 s -1 at our conditions.

As it has been concluded in [26], at low concentrations of H 2 O in Ar, OH(A,0) is formed due to the collisions of H 2 O with excited Ar atoms. In [27] a three-step reaction chain for OH(A) production was proposed. Collisions between H 2 O and Ar m , lead to the formation of H 2 O in a Rydberg state:

31 2 m 2 H O Ar H O( Ryd) Ar( S)    (2)
Due to the collisions with Ar atoms H 2 O( 3 Ryd) relaxes to lower states.

3 1 3 1 2 2 1 H O( Ryd) Ar( S) H O(d A ) Ar( S)    (3)
And finally the dissociation takes place: (4) 70% of OH(A) is produced in the vibrational state v=0, ca 25% -in the state v=1 and 5% -in the state v=2. Reaction (4) produces OH(A,0) at high rotational states [27]. In Ar / O 2 plasma OH(A) could be formed also via H 2 O collisions with metastable O atoms, O m :

m2 O H O 2OH(X)  (5) [28]
OH(X) e OH(A) e    (6) [29] Reaction (5) produces OH(X,0) at high rotational states [28]. When the rotational relaxation of OH(X,0) is negligible then reaction (6) produces OH(A,0) also at high rotational states. In the case of OH(A,0), rotational states N'  23 are mainly predissociated (predissociation frequency PD  10 7 s -1 , [30]). According to [6,31] the lifetime of OH(A,0) depends mainly on radiative decay and quenching in collisions with Ar, O 2 , H 2 O. The frequency of OH(A) radiative decay is Rad   1.3 10 6 s -1 , [32], i.e. it is ca 20 times lower than that of N 2 (C). Quenching by collisions has considerably lower frequencies. The highest rate coefficient (k q_H2O =5.9 10 -10 cm 3 s -1 , [31]), is obtained for quenching with H 2 O, but even with the assumption that there was 1% of H 2 O in the mixture, the quenching frequency is by one order of magnitude smaller than (k q_O2 =5 10 -11 cm 3 s -1 , [33]), and by Ar, q_Ar   4 10 3 s -1 (k q_Ar =8.8 10 -14 cm 3 s -1 , [31]). Thus, the lifetime of OH(A,0) is also determined by the radiative decay. Moutret et al. [7] estimated that the time constant of OH(A,0) rotational relaxation in Ar is 0.4 ns at p=760 Torr and T= 500 K. At our pressure and at the same temperature this gives, Rel   7 10 6 s -1 . By using cross-section Rel   2 10 -15 cm 2 [34], the resulting rotational relaxation in our condition is lower:

Rel   4 10 6 s -1 .

Rotational temperature as a measure of gas temperature

According to estimations given in section 3.4, the frequency of N 2 (C,0) rotational relaxation is ca one order of magnitude smaller than the frequency of quenching. Thus, N 2 (C,0) rotational distribution is close to that formed by reaction (1) and T Rot (N 2 ) does not characterize the gas temperature. Figure 4 demonstrates that the growth of jE  caused a fall of T Rot (N 2 ). The effect is explainable keeping in mind that the growth of jE  is accompanied with an increase of n e . As in the low and middle pressure discharges electrons are dominant quenchers of Ar m [35], the growth of jE  diminishes the contribution of reaction (1). We speculate that the relative importance of direct electron impact excitation from the N 2 ground state increases. As a result the N 2 (C,0) rotational temperature becomes closer to the gas temperature and in our case it is falling with the growth of jE  . In section 3.4 it was found that the frequency of rotational relaxation of OH(A,0) is 3-5 times higher than the frequency of quenching. Thus, the rotational distribution of OH(A,0) should be close to the thermalized one. However, in several works (e.g. [12,13]), where the rotational relaxation frequency was considerably higher than in our case, it has been found that OH(A,0) rotational population distribution is characterized by two values of T Rot . A study of this phenomenon was carried out in [13], (p=760 Torr, glow discharge with a water electrode) in different media. It was found that T Rot (OH) estimated on the basis of rotational states N'<13 was close to T G while for N'>13 it was 2-3 times higher. Deviation from the thermalized distribution was explained with (a) non-thermalized initial distribution, (b) high rate of OH(A,0) quenching by H 2 O which reduces effective lifetime of OH(A) and causes only partially thermalized distribution. Regularities of our spectrum showed that OH(A,0) rotational temperature has only one value. Indeed, when the population of higher rotational states is remarkable, the rotational line R 2 14 should appear in the spectrum presented in the inset of figure 3(b). However, R 2 14 line was not detected whereas the transition probability for R 2 14 is ca 5 times larger than the probabilities for R 2 3 and R 2 4 lines [36] which are presented in the spectrum. This finding is consistent with the calculations: for T Rot =500 K the population of N'>10 rotational states does not exceed 1%. Thus, it indicates that in our case the distribution was thermalized. In comparison with [13] in our case the thermalization of OH(A,0) was more effective because of low H 2 O concentration, therefore the quenching rate of OH(A) should be considerably lower. This explanation is confirmed by regularities in spectra: in our spectrum the intensity of OH band was ca 200 times lower than that of Ar lines while in study [13] OH band intensity was about 2 times higher than that of Ar.

Conclusion

It was found that independently of the input power, in Ar / 0.5% O 2 plasma the rotational temperature of N 2 (C,0) state was remarkable higher than that of OH(A,0). Besides, the growth of the input power led to the decrease of N 2 (C,0) rotational temperature. The analysis showed that N 2 (C,0) was mainly excited via N 2 (X) collisions with Ar metastable atoms which populate higher rotational states. As the lifetime of N 2 (C) is short, the thermalization of rotational distribution did not take place and thus the N 2 (C,0) rotational temperature differed from the gas temperature. Similarly with the case of N 2 (C,0), OH(A,0) was produced at high rotational states, but due to the longer lifetime of OH(A), there was enough time for thermalization. Therefore, in the middle pressure Ar / 0.5% O 2 plasma the rotational temperature of OH(A,0) state corresponded to the gas temperature considerably better than that of N 2 (C,0) state. This conclusion was supported by the finding that with the growth of the input power the rotational temperature of OH(A,0) increased as is expected to be in the case of equality of gas and rotational temperatures.

Figure 1 .

 1 Figure 1. Experimental device. G-generator, Osc-oscilloscope, Sp-spectra recording position.

  in the case of N 2 flow the pressure raised up to ca 23 10 

Figure 2

 2 depicts spectra of Ar / 0.5% O 2 and Ar / 0.5% O 2 / N 2 recorded from the positive column region.

Figure 2 .

 2 Figure 2. Spectrum of Ar / 0.5% O 2 / N 2 . Inset: spectra of Ar / 0.5% O 2 and Ar / 0.5% O 2 / N 2 mixtures in wavelength range 300-400 nm. i =0.1 A.

Figure 3 .

 3 Figure 3. Measured and calculated rotational spectra. (a): N 2 (C-B, 0-0) transition; Ar / 0.5% O 2 / N 2 ; T Rot =790 K; i=0.1A. Full-width at half maximum

  (b). As a rule, individual rotational lines were not resolved because of insufficient spectral resolution and each peak in spectrum represents a sum of overlapped rotational lines. An exception is demonstrated in the inset of figure3(b)where individual lines of R 2 branch are distinguishable. Figure4depicts T Rot (N 2 ) and T Rot (OH), as a function of power density, j E PC .

Figure 4 .

 4 Figure 4. Rotational temperatures of N 2 (C,0) and OH(A,0) as a function of power density.

Rad.

  The frequency of the quenching by O 2 is q_O2   10 4 s -1

Acknowledgment

The study is supported by Estonian Grant Foundation, grant No 7462.