text:
2-Amino-6-[(2,6-dichlorophenyl)imino]-3-oxocyclohexa-1,4-dienecarbaldehyde

The title compound, C13H8Cl2N2O2, was obtained by the oxidation of diclofenac {systematic name: 2-[2-(2,6-dichlorophenylamino)phenyl]acetic acid}, an anti-inflammatory drug, with hydrogen peroxide catalysed by chlorido[5,10,15,20-tetrakis(2,6-dichlorophenyl)porphyrinato]manganese(III), using ammonium acetate as co-catalyst. The asymmetric unit contains two crystallographically independent molecules of the title compound (Z′ = 2). The close packing of individual molecules is mediated by a series of strong and rather directional N—H⋯Cl and N—H⋯O hydrogen bonds, plus weak π–π [distance between the individual double bonds of symmetry-related iminoquinone rings = 3.7604 (13) Å] and Cl⋯O interactions [3.0287 (18) Å].

We are grateful to the Fundaçã o para a Ciê ncia e a Tecnologia (FCT/FEDER, Portugal) for their general financial support to QOPNA and CICECO, and for the post-doctoral research grant No. SFRH/BPD/63736/2009 (to JAF). Thanks are also due to the FCT for specific funding toward the purchase of the single-crystal diffractometer. The possibility of using synthetic metalloporphyrins as biomimetic catalysts, which are able to mimic cytochrome P450 enzymes, has attracted the interest of many research groups (Othman et al., 2000;Bernadou et al., 2004;Mansuy, 2007), including ours (Neves et al., 2011;Simões et al., 2009;Rebelo et al., 2004aRebelo et al., , 2004bRebelo et al., , 2005. In particular, our current research is focused on the preparation of putative metabolites by the in vitro oxidation of drugs. These studies will allow the production of metabolites in the amounts of milligrams, the isolation and identification of unstable intermediates and the understanding of the mechanism of action of drugs (Bernadou et al., 2004). The title compound, C 13 H 8 Cl 2 N 2 O 2 , was obtained by the oxidation of 2-(2-(2,6-dichlorophenylamino)phenyl)acetic acid (diclofenac), an anti-inflammatory drug, with hydrogen peroxide catalysed by chloro [5,10,15,20-tetrakis(2,6-dichlorophenyl)porphyrinato]manganese(III) using ammonium acetate as co-catalyst. Following our on-going interest on the structural features of compounds with biological activity (Fernandes et al., 2010Loughzail et al. 2011) here we wish to report the crystal structure of the oxidation product of diclofenac.
The asymmetric unit of the title compound comprises two whole molecules of C 13 H 8 Cl 2 N 2 O 2 (Fig. 1). A comparison between the geometrical features of the two molecules reveals that bond distances and angles involving equivalent atoms are very similar (deviations smaller than 0.012 Å and 1.6°, respectively). There are, however, some considerable differences concerning torsion angles, namely those subtended by the two six-membered rings in each molecule: 71.97 (10)° for molecule A and 75.89 (10)° for molecule B.
The crystal is rich in supramolecular interactions, namely π-π (involving the individual double bonds of the iminoquinone rings), Cl···O and hydrogen bonding interactions. The π-π interactions occur between pairs of molecules A involving the aromatic and the iminoquinone rings, or two iminoquinone rings [distance between centroids of 3.7604 (13) and 3.9595 (13) Å, respectively -purple dashed bonds in Figure 2]. A pair of B molecules also exhibits a short Cl···O interaction (Cl···O distance 3.0287 (18) Å, not shown].
The two crystallographically independent molecules have a different behaviour concerning the hydrogen bonding network in which they are involved ( Figure 2 and Table 1 for geometric details). Molecule A is engaged in a bifurcated N-H···(O,O) hydrogen bond, which is shared by the aldehyde group (intramolecular) and the ketone group of a neighbouring B molecule. The remaining N-H moiety of molecule A donates the hydrogen atom to a Cl atom of a neighbouring A molecule. The NH 2 group of molecule B participates in two N-H···O aldehyde interactions, of which one is intramolecular and the other occurs with molecule A. The hydrogen bonds form discrete clusters (violet dashed lines in Fig. 2) which can be described as the merging of two rings with a graph set notations R 1 1 (6) and R 2 2 (11), respectively (Grell et al., 1999).
Unequivocally, the strongest connection among adjacent molecules corresponds to that of the latter graph set, which leads to the formation of dimers as depicted in Fig. 2. The crystal packing is, thus, promoted by the close packing of such dimers: firstly, and mediated by the aforementioned weak π-π contacts, dimers form columnar arrangements along the c-axis of the unit cell. Secondly, columns pack in the ab plane in a typical brick-wall-type fashion as depicted in Fig. 3.
supplementary materials sup-2 Experimental All chemicals were purchased from commercial sources and were used as received without further purification.
The oxidant employed was aqueous hydrogen peroxide 30% (w/w) (Riedel-de Haën) diluted 1:5 in CH 3 CN. The oxidant (0.05 mmol) was added to the reaction mixture every 15 min. After 8 h of reaction, the mixture was extracted with dichloromethane and purified by preparative TLC using the same solvent as eluent. The product was dissolved in a minimum amount of dichloromethane and crystallized in hexane at around -16 °C to isolate crystals of the title compound.

Refinement
Hydrogen atoms bound to carbon were placed at their idealized positions and were included in the final structural model in riding-motion approximation with C-H = 0.95 Å. The isotropic thermal displacement parameters for these hydrogen atoms were fixed at 1.2×U eq of the respective parent carbon atom.
Hydrogen atoms bound to nitrogen were directly located from difference Fourier maps and included in the final structural model with the N-H and H···H distances restrained to 0.95 (1) and 1.55 (1) Å, respectively. The U iso of these hydrogen atoms was fixed at 1.5×U eq of the nitrogen atom to which they are attached. two graph set motifs: R 1 1 (6) and R 2 2 (11). On the right, weak π-π contacts involving double bonds of the iminoquinone and aromatic rings further ensure supramolecular connections among A molecules. For geometric details on the represented hydrogen bonds see Table 1. Symmetry transformations used to generate equivalent atoms have been omitted for simplicity.


extfieldsofstudy: Chemistry Medicine

text:
Molecular Arrangement in Self-Assembled Azobenzene-Containing Thiol Monolayers at the Individual Domain Level Studied through Polarized Near-Field Raman Spectroscopy

6-[4-(phenylazo)phenoxy]hexane-1-thiol self-assembled monolayers deposited on a gold surface form domain-like structures possessing a high degree of order with virtually all the molecules being identically oriented with respect to the surface plane. We show that, by using polarized near-field Raman spectroscopy, it is possible to derive the Raman scattering tensor of the ordered layer and consequently, the in-plane molecular orientation at the individual domain level. More generally, this study extends the application domain of the near-field Raman scattering selection rules from crystals to ordered organic structures.

Introduction
Raman spectroscopy is an extremely useful and widespread technique for material characterization [1,2]. Apart from offering distinctive spectral signatures allowing for the rapid identification of the chemical nature of the sample, even more detailed information on the molecular (or crystalline) order can be retrieved by studying the signal dependence on the polarization of the two involved photons (incident and scattered), as formally defined by the Raman scattering tensor [3].

OPEN ACCESS
Thus, domain orientation in crystals can be effectively assessed by polarized Raman spectroscopy featuring high sensitivity and spatial resolution (few hundreds of nanometers) while requiring small sample volumes and little, if any, sample preparation [4,5]. Thus, Raman polarization studies have been performed to determine the orientation [6,7] and structure [8] of molecular thin films, a required characterization step for the deposition of organic films to be used in technical applications such as organic light emitting diodes, flat panel displays and thin film transistors [9].
Further, higher spatial resolution, below the diffraction limit, can be attained by taking advantage of near-field optical techniques. The best performing approach for Raman spectroscopy is the aperture-less configuration [10] in which the local electromagnetic field generated upon light scattering on a metal tip apex can be strongly enhanced by a localized surface plasmon excitation. Within such Tip Enhanced Raman Spectroscopy (TERS) [11], an Au or Ag tip kept at nanometer distance from the sample surface is externally illuminated and the Raman signal from the sample region directly below the tip, usually dominating the undesired far-field background, is collected. The lateral resolution of TERS is thus not related to the exciting laser spot size but rather to the physical dimensions of the tip apex (typically less than 50 nm) [12][13][14]. Noticeably, the metal tip not only enhances the local field, and consequently, the Raman scattering process in the analyte, but also modifies the polarization state of both the exciting and scattered photons. This is due to a preferential enhancement of the field component parallel to the tip axis (i.e., the surface-normal component) [15,16]. This -polarization sensitivity‖ property has been proposed as a possible way to discriminate between near-field and far-field components when probing crystalline materials, which present a strongly polarized Raman response [17][18][19]. Our group proposed a phenomenological model to account for the polarization dependence of the TERS signal from crystalline silicon based on the introduction of the concept of tip amplification tensor [20]. Recently, this formalism has been adopted to spatially resolve ferroelectric domains in individual BaTiO 3 nanocrystals, introducing the concept of a nanocrystollography based on near-field Raman selection rules [21]. Clearly, it would be interesting to extend the application fields of TERS to thin organic layers whenever these exhibit, at least locally, an ordered, crystalline-like structure.
Chemical modification of a planar gold surface with molecules exhibiting a thiol anchor group leads to the formation of highly ordered Self Assembled Monolayers (SAM), in which virtually all the anchored molecules are equally tilted with respect to the surface normal [22,23]. For the 6-[4-(phenylazo)phenoxy]hexane-1-thiol (an azobenzene-containing thiol) SAMs, an in-plane order is further established due to the interaction between the phenyl rings of neighboring units. While reflection-absorption infrared spectroscopic and ellipsometric measurements confirmed a nearly perpendicular orientation of the azobenzene moieties [24][25][26], scanning probe microscopy studies revealed the presence of small domains having the azobenzene groups arranged in regular lattice structures. The formation of such domains is possible due to the flexibility of the (sulfur terminated) alkyl chain linking the aromatic system to the surface (so-called bundle model) [27][28][29][30][31]. This makes azobenzene derivative SAMs particularly interesting for polarized TERS studies to test the capability of Raman spectroscopy in the near-field optical regime while aiming at the determination of the crystalline domain orientation with sub-diffraction limited lateral resolution. Surface enhanced Raman spectroscopy (SERS) has also been used to report on the monolayer formation of the azobenzene-containing thiol on electrochemically roughened gold electrodes or on nanostructured substrates formed by electron beam lithography [32,33].

Experimental Section
Our TERS set-up consists of a confocal Raman microscope (Labram HR800, HORIBA Jobin Yvon) with a 633 nm HeNe laser source optically coupled in an oblique backscattering geometry to a scanning probe microscope or SPM (XE-100, Park Systems). The long-working-distance objective (50×, NA = 0.45) is oriented at 65° with respect to the sample normal and produces an elliptical laser spot with approximate axis lengths 2.5 µm × 1 µm. Note that in the oblique incidence (off-axis) backscattering geometry, the scattering plane is defined by the direction of the incident/scattered radiation and the sample normal (coinciding with the tip axis). The opto-mechanical coupling is motorized along the x, y and z axes and allows for the accurate alignment of the exciting light spot with respect to the tip apex. The SPM is operated in scanning tunneling microscopy (STM) mode; the tips used were prepared from Au wire pieces of 250 µm diameter and 99.99% purity (from Goodfellow) by electrochemical etching in a concentrated HCl/ethanol 1:1 solution according to an existing procedure [34]. Tunneling parameters were 100 mV bias voltage, tip positive, and 40-30 pA currently.
The polarization state of the incident beam can be continuously varied between 0° (s polarization or s-pol; electric field perpendicular to the scattering plane) and 90° (p polarisation or p-pol; electric field parallel to the scattering plane) by using a half-wave plate in a motorized rotating mount (0.5° azimuth uncertainty) inserted in the excitation laser beam path. During the TERS experiments, laser power was kept below 0.5 mW at the sample surface to avoid any possible heating and -bleaching‖ side-effects.
The atomically flat Au(111) substrates were purchased from Arrandee. Synthesis of the 6-[4-(phenylazo)phenoxy]hexane-1-thiol closely followed the procedure reported in [30]. A 5 mM solution in ethanol was used for the monolayer absorption on the freshly flame annealed Au (111) substrates. An absorption time of 6 h proved to be sufficient to reach full coverage [35]. After removal from the solution, the sample was rinsed in pure ethanol and distilled water, and dried with N 2 .

Results and Discussion
Polarized TERS experiments were mainly conducted on smooth regions of the supporting metal film: Adsorption at an atomically flat surface is needed for the formation of the ordered thiol layer. Before starting the spectral acquisitions, the topography of the surface was systematically checked through STM mode mapping and the tip was moved over a flat region. The observed Au(111) terraces typically size up to few hundreds of nm [35]. The lower spectrum in Figure 1 reports the Raman spectrum (lower curve) collected in 30 s (0.5 mW incident laser power; p-pol) from an azobenzene-containing thiol layer adsorbed onto the gold film. This weak-intensity signal originates from the whole illuminated spot area while the tip is retracted few microns above the surface. The upper spectrum (1 s acquisition time) is relative to the same illuminated sample area but with the gold tip in tunneling mode. The estimated tunneling gap distance between the underlying gold surface and the tip is ~3 nm, including the 2 nm-thick organic layer [35]. The tip-down-tip-up contrast ratio derived from the two spectra is about 10. The far-field elliptical spot area is approximately 7 µm 2 and the tip radius produced by the etching procedure is usually ~30 nm, as estimated from SEM images. If considering to a first instance the circular area directly below the tip apex as uniformly affected by the enhanced field and a uniform coverage of the thiol layer, a TERS enhancement factor of the order of 1 × 10 4 can be estimated. Similar absolute signal levels (not shown) and contrast ratios could be obtained on several different regions of the sample surface. Six major spectral features assigned to the vibrations of the anchored double-ring system in a trans configuration [36,37] are clearly seen in the TERS spectrum. More specifically, all bands observed correspond to in-plane vibrations with A g symmetry that mostly couple with the surface-normal local electric field component. Next, the intensity of the strongest peak (ν 15 ) at 1141 cm −1 , assigned to the in-phase stretching of the two C-N bonds, was monitored while changing stepwise the incident polarization from s-to p-pol and back to s-pol, for both the far-field (tip retracted) and the near-field (tip tunneling) cases. Before discussing the resulting polarization curves, we shall describe the relations necessary for modeling the polarized near-field Raman scattering experiment.
The influence of the incident light polarization on the intensity of the Raman signal scattered by the thiol layer in the presence of the local field enhancing tip can be quantitatively described by adopting the same model we originally proposed and tested on bulk crystalline samples [20]. In the following, only the basic relationships will be recalled; more details on the simulation procedure can be found in [20,38]. Within the classical formalism of normal (i.e., non-resonant) Raman scattering [1,2], the far field scattered intensity is given by the well-known selection rule 2 e T s ff in which K is a proportionality constant, e e and e s are the exciting (or incident) and scattered electric field vectors, respectively, and R is the Raman scattering tensor of the involved molecular (or crystal) vibration. Note that the matrix expression for the scattering tensor R entering Equation 1 depends on the reference frame used. In particular, if the sample is rotated about its normal, the tensor R will change accordingly; this change can be formally described by rotating the matrix of R by a rotation matrix. As a consequence, the scattered intensity given by Equation 1 depends not only on the polarization states e e and e s of the exciting and scattered radiations, but also on the sample azimuth (or orientation) through the tensor R.
To describe the near-field scattering process, a phenomenological tip-amplification tensor A, accounting for the enhancement of the local electric field by the tip, is introduced [20]. The tensor A expresses the fact that the electric field component parallel to the tip axis is preferentially amplified compared to that perpendicular to it. Its matrix representation in the tip-sample reference frame (with x and y axes perpendicular to the tip axis, i.e., parallel to the sample plane; z axis along the tip axis) is in which a and b (with a > b) are phenomenological coefficients expressing the different amplification ratios of the electric field components parallel and perpendicular to the tip axis. The tip geometry (i.e., form, radius of curvature, apex angle) and material dielectric constant determine the actual values of the amplification factors. The near-field (tip-enhanced) scattered intensity I nf is given by in which the near-field proportionality constant K' is generally different from K, the far-field one, and R' is the modified (or effective) Raman scattering tensor taking into account the action of the tip. Within the near-field scattering process, the polarization state of the exciting radiation is first altered by the tip, then molecular vibrations excited by this enhanced field generate the scattered radiation, and finally a second tip-scattered-radiation interaction takes place. As a result, the expression for the effective scattering tensor R' becomes in which A is the tip-amplification tensor from Equation 2.
Finally, the total scattered field intensity, I tf , measured in -tip down‖ position, is given by the sum of the far-field, Equation 1, and the near-field, Equation 3, contributions, since the two signals superimpose incoherently on the detector. The azobenzene molecule in its trans conformation belongs to the C 2h spatial point group [36], which results in a Raman scattering tensor with four independent components for A g -symmetry active modes. Taking the z axis along the surface normal, also corresponding to the molecular long axis, and identifying the xz plane as the molecular plane (i.e., assuming an upright orientation of the azobenzene moieties), the Raman tensor R Ag of a single azobenzene molecule has the general form As reported by Pedersen et al. [39] for the azobenzene chromophore in the trans configuration, both the absorption cross-section along the y axis and the polarizability tensor component normal to the molecular plane, i.e., the yy component, are negligible at the exciting wavelength used in our experiments (note the different labeling of the molecular axes used here with respect to that of the cited reference). Keeping in mind that the Raman tensor is the spatial derivative of the polarizability tensor with respect to the normal mode vibrations (here, the  15 mode), we assume the yy polarizability component to change only weakly with the  15 molecular vibration analyzed here, allowing to simplify the above tensor form by setting  yy = 0 in Equation 6. Further, the Raman tensor for the monolayer may be obtained from a superposition of the Raman tensors of the single molecules within the unit cell of the type of lattice formed [40]. Azobenzene-containing thiols having different molecular structures may form different types of regular domains extending over several tens of nanometers: (a) domains of centered hexagonal lattice with a rectangular unit cell and two molecules per unit cell, producing herringbone structures, i.e., alternate horizontal rows of canted molecules are formed by HS(CH 2 ) 11 OC 6 H 4 N=NC 6 H 5 , having a longer anchoring tail than the azobenzene derivative studied here [27] and (b) domains with an (oblique) nearly rectangular lattice likewise having two molecules per unit cell are formed by HS(CH 2 ) 6 OC 6 H 4 N=NC 6 H 5 [28][29][30][31]. In this second case, the two molecules in the unit cell may be almost parallel or form an angle. For a parallel dimer the molecular lattice tensor retains the single-molecule form (6). In the second case of two molecules forming an angle of approximately 40° between their short molecular axes (the longer axis being along the z axis) [30], the resulting unit cell tensor is obtained by summing the individual tensors of the two molecules, the second tensor being rotated at the angle of 40° with respect to the first one, still leaving only two -free‖ parameters,  xx and  xz (the element  zz is set equal to unity because of the The tensor form (7) is used in the modeling procedure described above to fit the -tip tunneling‖ response of the azobenzene derivative layer. To account for the various possible orientations of the domain lattice with respect to the scattering plane, R Azo is further rotated about the z axis at the appropriate domain azimuth angle  by using a transformation matrix of the same form as Considering that the TERS intensity comes from the highly localized region below the tip apex, it can be expected that its polarization-dependent response reflects the local domain structure and, furthermore, that it differs substantially from its far-field counterpart whereby a much larger area encompassing a large number of differently oriented domains with, possibly, disordered zones is probed. Figure 2a,b reports the experimental data obtained with the gold tip consecutively located at two positions on the surface separated by approximately 300-400 nm; note that there was no analyzer in the output beam (so-called -depolarized‖ or, more correctly, unanalyzed scattering configuration). With 1 s integration time for each TERS acquisition, a complete polarization curve takes about 20 s to be obtained. Considering the thermal drift of our set-up (0.1 nm/s), the tip creeps negligibly over the organic layer during this time. It is to be noted that the maximum of the TERS signal is observed at two different values of the incident polarization, both slightly shifted from the expected p-pol (represented by a dotted line in both figures): an upshift, for the curve in Figure 2a, and a downshift, for the curve in Figure 2b. Three other curves (not shown) recorded with different tips likewise showed a small (but non-negligible) shift of the maximum intensity position from the 90° value for incident p-polarization. This behavior is reproduced by our model by considering different azimuthal orientations  of the probed molecular domain (described by the rotated R Azo () tensor; see Equation 9) with respect to the scattering plane. Indeed, the magnitudes and the signs of the shifts are functions of the domain azimuth angle reflecting the local orientation of the domains. The solid lines are the best fits obtained with the model described above for the set of component values  xx ≈ 0.5 and  xz ≈ 0.3 and at two different domain azimuth angles . The polarized tip-enhanced Raman signal is thus clearly shown to be sensitive to the local in-plane order. Note that the single molecule tensor form (6) also reproduces the experimental curves for different domain azimuth angles. Therefore, it is not possible, from these measurements, to distinguish between the two possible molecular orientations within the unit cell. It should be also noted that the possibility of the field-enhanced region to extend over few contiguous domains rather than a single one cannot be ruled out a priori and the retrieved values for the tensor components would then represent a local average. The far-field spectra shown in Figure 3 were acquired at higher laser power (5 mW) and at a much longer acquisition time (20 s per point) to attain a sufficient signal level, including for the weaker response to the incident s-polarization. In contrast to the TERS curves from Figures 2a,b, the far-field (tip retracted) response always peaked at 90° corresponding to p-polarization (shown by the dotted line; within the 3° azimuth offset of the half-wave plate fast axis) as can be seen from Figure 3. This fact clearly indicates that over the large illuminated area, most of the planar molecules chemisorbed at the metal surface have their long axes oriented parallel to the sample normal, but with no other detail regarding the presence of an in-plane order, i.e., the presence of regular domains To reproduce the far-field behavior (the solid line in Figure 3), the Raman tensor (9) was again used and the intensity contributions for four equally spaced domain azimuth angles (0°, 90°, 180° and 270°) were summed up incoherently to account for the random orientation of the domains and the possible presence of disordered zones within the large illuminated area. Indeed, over a µm-scale laser spot, a great number of ordered (nano-) domains are probed and their relative orientations remain spatially unresolved in the far-field response. As a result, the far-field polarization curve peaks at 90°, in accordance with the random domain orientation in the xy plane.
Comparison of the Raman signal intensity recorded at incident s-polarization (0° and 180° values in Figures 2 and 3) for the near-field and far-field cases shows that a non-negligible signal enhancement is also present for this polarization. Within the TERS community, it is usually accepted that a more efficient plasmonic excitation and, consequently, a greater tip enhancement are achieved with incident p-polarization (having a significant electric field component oriented along the tip axis) while almost no enhancement is expected for incident s-polarization [41]. Nonetheless, in a series of experiments performed on bulk crystalline materials, [42][43][44] it has been clearly shown that metal tips convert, to a certain extent, the incident field polarization from s-to p-pol. and vice versa. This -depolarization‖ (more correctly, cross-polarization) phenomenon is intrinsically related to the metal tip scattering, and may have also affected our measurements, although we believe only to a minor degree owing to the very small thickness of the thiol layer as compared to the micrometer penetration depth of visible light into bulk crystalline materials for which the phenomenon has been reported. Also, a feature that is sometimes overlooked when considering the preferential tip enhancement for radiation having the electric field parallel to the tip axis is that the Raman process involves two photons: the polarization state of the incident photon is directly defined by the polarizer setting, while the polarization state of the Raman scattered photon further depends on the Raman scattering tensor. Depending on the tensor form (presence of non-zero off-diagonal elements), certain vibration modes can be (also) excited with s-polarized light and generate p-polarized light that will then be enhanced by the tip, the net effect resulting in a near-field signal enhancement with s-polarized excitation. This is exactly our case with R Ag from (6)-and R Azo from (7)-having  xz ≠ 0. This fact is most possibly responsible for the unexpectedly high TERS intensity recorded at incident s-polarization.
To further support the conclusion of the TERS polarization curves being mainly affected by the molecular order at a sub-micrometer length scale, we present the results obtained when probing (with the same tip) two regions on the sample surface having different local morphology of the underlying gold substrate. Figure 4a reports the STM topography of a sample region on which two distinct TERS measurements were performed: the tip was first located on the flat area near the trench (position marked with a square) and second, the tip was moved inside the depression (position marked with a triangle). The experimental points (squares and triangles) shown in Figure 4b refer to the corresponding TERS signal intensity. As readily seen, when the tip is located over a flat region, a well pronounced modulation of the detected signal by the incident polarization is observed (squares). Note that the curves in Figure 2a,b exhibit similar modulation amplitudes; however, in this case the signal intensity peaks quite close to 90° incident polarization (this particular value is obtained in the simulated near-field curve when the scattering plane accidentally coincides with the xz molecular plane). In contrast, the signal intensity recorded with the tip located inside the depression (triangles in Figure 4b) appears to be much less influenced by the incident polarization; moreover, its behavior is not a clearly sinusoid-like one, unlike the previous ones. This situation may arise whenever the probed molecules do not have a well-defined orientation with respect to the tip axis, i.e., when it is no more possible to define a unique substrate plane and the azobenzene molecular planes are more or less randomly oriented in space (but their responses still add coherently because of the local nature of the TERS signal). This is the situation whenever probing a very rough region of the gold substrate that cannot support the formation of a highly ordered molecular overlayer (having all molecular planes parallel to the tip axis). A TERS signal generated from the coherent contributions of the thiol molecules adsorbed at gold sites is still recorded but the short-range order is partially or even completely lost, with the disorder being inherently related to the topography of the supporting metal. Further, we need also to consider the local geometry of the gold tip-gold surface gap. With the tip located over a flat region, a well defined gap is formed between the lower (curved) surface of the tip apex and the opposite metal surface (the gap axis essentially coincides with the tip axis) whereas with the tip located inside a shallow trench, differently oriented gaps may be formed between the sides of the approximately spherical apex and the sloping surface. This picture points out the critical role played by the underlying gold surface in defining not only the magnitude of the field enhancement but also its influence on the orientation of the enhanced field. Remarkably, we have noted that by allowing the single-molecule tensor from Equation 6 to be tilted away from the z (tip) axis, one can also reproduce (for certain values of the tilt and azimuth angles) an almost flat polarization dependence curve (not shown), qualitatively similar to the TERS response from a rough sample region.

Conclusions
Azobenzene-containing thiol molecules self assembling on a Au(111) substrate can arrange in two-dimensional ordered (nano-)domains. The related in-plane arrangement and domain orientation affect the intensity of the Raman signal recorded at various incident polarizations, provided that the probed area has a size comparable to that of the domains. This was observed in polarized TERS measurements in which only the molecules located in the close proximity of the nanometer-sized tip apex contributed to the enhanced signal. We applied the tip amplification tensor model to describe the polarization response of the locally ordered monolayer, thus extending the validity of the model from crystal structures to ordered organic layers. A different behavior was observed when probing disordered regions on the sample surface and especially when micrometer-large areas were probed in the far field, whereby signal response averaging from several domains occurred, thus confirming the spatially localized nature of the TERS signal.


text:
Towards crystal structure prediction of complex organic compounds – a report on the fifth blind test

The results of the fifth blind test of crystal structure prediction, which show important success with more challenging large and flexible molecules, are presented and discussed.

Following on from the success of the previous crystal structure prediction blind tests (CSP1999, CSP2001, CSP2004 and CSP2007), a fifth such collaborative project (CSP2010) was organized at the Cambridge Crystallographic Data Centre. A range of methodologies was used by the participating groups in order to evaluate the ability of the current computational methods to predict the crystal structures of the six organic molecules chosen as targets for this blind test. The first four targets, two rigid molecules, one semi-flexible molecule and a 1:1 salt, matched the criteria for the targets from CSP2007, while the last two targets belonged to two new challenging categories -a larger, much more flexible molecule and a hydrate with more than one polymorph. Each group submitted three predictions for each target it attempted. There was at least one successful prediction for each target, and two groups were able to successfully predict the structure of the large flexible molecule as their first place submission. The results show that while not as many groups successfully predicted the structures of the three smallest molecules as in CSP2007, there is now evidence that methodologies such as dispersion-corrected density functional theory (DFT-D) are able to reliably do so. The results also highlight the many challenges posed by more complex systems and show that there are still issues to be overcome.

Introduction
This paper reports on the results of the fifth blind test of crystal structure prediction (CSP), an international test hosted periodically by the Cambridge Crystallographic Data Centre (CCDC). We refer to this fifth blind test as CSP2010.
Over the last several decades there has been much research in the field of crystal structure prediction. The grand aim is to develop the ability to reliably predict, by computational methods, how a molecule will crystallize in the solid state, with only the chemical diagram and the crystallization conditions known. This would allow for the prediction of solid-state properties before the molecule or molecules in question had even been synthesized, and could also help determine the likelihood that different polymorphic forms, or as yet unseen polymorphs of currently known structures, exist. This application is of particular importance in the pharmaceutical industry where the presence of different polymorphs can lead to very different and potentially undesirable physical properties of new drugs.
For the last decade the CCDC has held periodic blind tests to assess the current reliability and capabilities of the techniques available in the field. Four blind tests, starting in 1999 and every 2 or 3 years thereafter, have previously been held. Each has required the identification of a set of molecules with known but previously unpublished crystal structures to use as targets for the participants to predict using the various techniques they have developed. This approach is similar to that adopted to monitor and test advances in other areas of predictive modelling, such as protein structure prediction (Moult et al., 2007). Recently there has also been a blind test for search methods for the crystal structure prediction of purely inorganic systems (Oganov, 2010). Repeating the blind test periodically helps to evaluate advances that have been made in methodologies since the last test, as well as establish the reliability of the techniques which have been successful in previous tests for a given category of target; the small number of targets in any one blind test introduces the possibility of a slightly easier or harder molecule (whose difficulty cannot be easily judged prior to commencement of the test) influencing the results.
This fifth blind test was therefore held to assess the reproducibility of the good results Day et al., 2009) from the previous blind test, CSP2007, and also to assess the developments in methodologies when applied to more challenging targets than the relatively simple rigid molecules mostly studied thus far. These additional targets better represent cases that would be more likely to be encountered in the pharmaceutical industry.

Organization and approach
The organization for this latest blind test, CSP2010, was similar to that used for the previous four evaluations of the field, the results of which have been previously published: CSP1999 (Lommerse et al., 2000), CSP2001 (Motherwell et al., 2002), CSP2004 (Day et al., 2005) and CSP2007 (Day et al., 2009). Invitations to participate were sent to 24 research groups known to be active in the field. The test was also advertised through various websites and meetings.
The previous blind test puts forward targets for prediction in the following four categories: (1) Small, rigid molecules; only the elements C, H, N and O; Z 0 = 1 in any space group; up to 25 atoms.
(2) Rigid molecules; unusual functional groups or elements such as halogens, S, P and B; Z 0 = 1 in any space group; up to 30 atoms.
(3) Moderately flexible molecule with 2-4 internal degrees of freedom; Z 0 = 1 in any space group; up to 40 atoms.
These four categories were left the same as those used in CSP2007 so as to facilitate comparison of results. In addition, it was decided to add two new categories that would provide greater challenges: (5) Molecule with 4-8 internal degrees of freedom; Z 0 2 in any space group; 50-60 atoms.
(6) Molecule for which more than one polymorph is known, and which roughly falls into one of the first four categories.
The new fifth category presents a much greater challenge in terms of flexibility than previously encountered in earlier blind tests, with a large flexible molecule intended to represent those often associated with modern pharmaceuticals. The new sixth category gives an opportunity to study the challenging effects of polymorphism by introducing a molecule for which more than one polymorph is known.
Crystallographers were contacted in August 2009 with a request for unpublished crystal structures that matched one or more of the six categories for the fifth blind test. Crystal structures were collected at the CCDC and assessed for the possibility of inclusion in one of the six possible categories. To be suitable, a crystal structure had to be of high quality and have all atoms located with no disorder. The crystal structure had to be unpublished and the donor crystallographer had to agree to postpone any publication for the duration of the blind test. Collection of suitable candidates for all six categories proved exceptionally difficult, especially for category 1, where the target molecule is very small with a very restricted set of constituent elements, and also for category 6 where few suitable candidates were available that were not of sufficient interest to be withheld from publication for the duration of this test. Almost 30 submitted crystal structures had to be rejected either due to not conforming to any of the six categories, or the presence of refinement issues such as disorder.
After considerable effort, one candidate was collected for category 1, four for category 2, eight for category 3, three for category 4, three for category 5 and one for category 6. For those categories where there was more than one candidate, the final target choice was made randomly.
For category 6, the one candidate that was submitted was gallic acid monohydrate, for which two new polymorphs had been found. These complemented the two previously published polymorphs for gallic acid monohydrate, which are located in the Cambridge Structural Database (CSD; Allen, 2002) under the KONTIQ CSD reference code family. For the purposes of this blind test, these known forms are referred to as forms (1) and (2). Of the two new forms submitted as candidates for prediction, one [form (4), as recently published by Clarke et al., 2011] had one formula unit in the asymmetric unit (i.e. one gallic acid and one water molecule). The other, form (3), was originally solved with two formula units per asymmetric unit. However, analysis after the blind test submissions showed that this solution contained a disordered hydrogen-bonding network and the crystal structure could also be described with an ordered hydrogen-bonding network by doubling the unit cell, as now published (Clarke et al., 2011). For the purposes of this blind test, form (3) was therefore deemed inappropriate as a target crystal structure. The main aim for this category, then, was to predict form (4), whose structure has been recently independently published (Demirtaş et al., 2011) and see where (if at all) forms (1) and (2) appeared in the ranked list of predictions.
The molecular diagrams and crystallization conditions were sent by e-mail to 15 participant groups on 16 November 2009. Immediately after circulation of the target crystal structures we were made aware that the crystal structure of the molecule research papers selected for category 1 (4-ethynylbenzonitrile) had been solved, was undergoing publication and so would soon be in the public domain. The decision was therefore made to remove this candidate for category 1 and attempt to locate a suitable replacement. Thankfully a suitable candidate was quickly provided and the revised list of target molecules, as detailed in Table 1, was distributed to participants on 23 November 2009. Following the numbering used in the previous blind tests we refer to these molecules by the Roman numerals (XVI)-(XXI).
The format of this blind test was kept broadly the same as the last blind test, with the exception that a greater length of time was allowed before submission of results. Participants were requested to forward their three 'official' predictions for each target molecule to the CCDC, where the experimentally determined crystal structures were held for the duration of the test. As well as these three main predictions, participants were urged to submit an extended list of the crystal structures they generated in order to help postanalysis and to provide insight into the performance of the various methods. The deadline for submissions was 20 August 2010. The experimentally determined crystal structures for all six categories were then circulated to all participants on 23 August 2010 to allow post-analysis of their predictions. Lastly, a workshop was held at the CCDC mid-September 2010 to discuss the results.
We present here results from the 14 participating groups that agreed to publish their results. Details of these 14 participating groups, together with a summary of which targets they attempted and if a match with the experimental structure was observed in their submission, are presented in Table 2(a).

Methodologies
Methodologies for the participating research groups vary significantly. A summary of the techniques used by each of the groups is presented in Table 2(b), together with key references for most of the methods used. More detailed descriptions are also provided in the associated supplementary material. 1 In general, each of the methods employed involved three general steps: (i) building a three-dimensional molecular structure from the supplied two-dimensional chemical diagrams; (ii) searching for plausible crystal packing arrangements of the molecule; (iii) ranking the generated crystal structures in order of likelihood of formation.

Methods of generating the molecular structure
There are two main approaches that can be used for treating the molecular structure during crystal structure prediction. Firstly, the molecule can be treated as rigid throughout the Structures generated using a low discrepancy Sobol' sequence P1, P " 1 1, P2 1 , P2 1 /c, P2 1 2 1 2 1 , P2 1 2 1 2, P2 1 /m, P2/c, P2 1 3, P4 1 , P4/n, P4 2 /n, P4 1 2 1 2, P " 4 42 1 c, P3 1 , calculations, assuming that the packing forces are too small to significantly distort the molecular geometry. In this case the method used to determine the rigid molecular structure is vitally important, as the effect of the molecular structure on crystal energy calculations can be large (Beyer & Price, 2000).

Flexible throughout
Atomic charges GAFF 6-12  analysis of conformational preferences using software such as Mogul (Bruno et al., 2004).

Generating trial crystal structures
There are many diverse methods for generating crystal packing arrangements in order to achieve a variety of plausible packing arrangements. Most participants in this blind test opted to generate large numbers of crystal structures with random or quasi-random variables such as unit-cell parameters and positions and orientations of the molecules. Several groups also elected to use a low-discrepancy Sobol' sequence (Sobol', 1967;Press et al., 1992). This helps ensure a more uniform and thus efficient sampling and avoids the problems of gaps and clusters that purely random sampling can exhibit. Other groups used Monte Carlo types of search, genetic algorithms, grid-based systematic searches or firstprinciples ab initio random structure searching which allows the possibility of a change in covalent bonding (Pickard & Needs, 2006, 2011. For the majority of these methods, space-group symmetry is used. These methods search each space group and Z 0 separately and so in order to help reduce the computing time required, many groups chose to restrict their search to only the most commonly adopted space groups. This blind test saw two groups electing to search all 230 space groups for some or all of their predictions. Other groups used the alternative approach of generating P1 crystal structures with varying numbers of independent molecules (up to 8) in the unit cell. Space-group symmetry was then identified in the resulting crystal structures, after energy minimization, using packages such as PLATON (Spek, 2009).

Ranking of crystal structures
The final ranking of the crystal structures is still almost exclusively based on the calculated lattice energies of the structures generated by the crystal structure search. Often tens, if not hundreds, of possible structures can exist within a few kJ mol À1 of the calculated global minimum (Day et al., 2004) and therefore extreme accuracy is needed. One successful approach to generating these lattice energies is the DFT-D method, which can give more accurate lattice energies (Neumann & Perrin, 2005) or re-minimization of the structures with more sophisticated force fields such as distributed multipoles (Stone, 2005) and additional flexibility Day & Cooper, 2010;Gö rbitz et al., 2010). Moreover, additional or alternative criteria may be used to discriminate between likely and unlikely crystal structures. Such approaches include lattice dynamic contributions ( Anghel et al., 2002) or comparisons to known crystal structures in the CSD (Dey et al., 2006), exploiting any isostructurality relationships (Asmadi et al., 2010a,b).  Packing diagram of the crystal structure of molecule (XVI). Grey = carbon, white = hydrogen, red = oxygen and blue = nitrogen. Contacts shorter than the sum of van der Waals radii are shown as blue lines.

Figure 2
Packing diagram of the crystal structure of molecule (XVII). Grey = carbon, white = hydrogen, red = oxygen, blue = nitrogen and green = chlorine. Contacts shorter than the sum of van der Waals radii are shown as blue lines. N 2 O) was chosen as the blind test target for category 1 after the initial target, 4-ethynylbenzonitrile, was found to have been previously solved. Molecule (XVI) was crystallized by slow evaporation from ethanol and the crystal structure was solved from X-ray diffraction data collected at 174 K (Britton, 2010). The molecule crystallizes with Z 0 = 1 in the orthorhombic space group Pbca. The crystal packing shows diazidecarbonyl and CHÁ Á ÁO interactions (Fig. 1).

Molecule (XVII)
. 1,2-Dichloro-4,5-dinitrobenzene (C 6 H 2 Cl 2 N 2 O 4 ) was chosen as the blind test target for category 2, although it deviates somewhat from the criteria for this category as the molecule is not truly rigid; the nitro groups allow for some degree of rotational freedom. Crystals were obtained by slow evaporation of methanol and X-ray diffraction data were collected at 174 K (Britton, 2010). The molecule crystallizes in the monoclinic space group P2 1 /c with Z 0 = 1 (Fig. 2).
(C 9 H 7 -ClN 2 O 3 S) was the target for category 3. Molecule (XVIII) was crystallized by slow evaporation from ethyl acetate (EtOAc) and the crystal structure was solved from X-ray diffraction data collected at 150 K (Blake, 2010). The crystal structure was solved in the orthorhombic space group Pbca with Z 0 = 1. The conformational flexibility can be described by three exocyclic torsion angles, as shown in Table 1. The CN 2 CO moiety adopts a mostly planar trans configuration (Fig. 3).
4.1.4. Molecular salt (XIX). 1,8-Naphthyridinium fumarate (C 8 H 7 N 2 , C 4 H 3 O 4 ) was chosen as the target for category 4. This 1:1 salt was formed by slow evaporation from methanol and the crystal structure was solved in the orthorhombic space group Pca2 1 from data collected at 200 K (MacGillivray, 2010) with Z 0 = 1. The packing in this crystal structure is dominated by hydrogen bonds, with linear chains of fumarate and naphthylpyridinium ions forming alternating connections to these chains (Fig. 4). The crystal structure is isostructural with the entry RABYID in the CSD (Shan et al., 2003) where quinolinium is substituted for 1,8naphthyridinium (i.e. one nitrogen is replaced by a C-H group).

Figure 5
Packing diagram of the crystal structure of molecule (XX). Grey = carbon, white = hydrogen, red = oxygen, blue = nitrogen, green = chlorine and yellow = sulfur. Contacts shorter than the sum of van der Waals radii are shown as blue lines.

Figure 3
Packing diagram of the crystal structure of molecule (XVIII). Grey = carbon, white = hydrogen, red = oxygen, blue = nitrogen, green = chlorine and yellow = sulfur. Contacts shorter than the sum of van der Waals radii are shown as blue lines. the monoclinic space group P2 1 /n with Z 0 = 1 (Blake, 2010). The conformational flexibility can be described with eight exocyclic torsion angles ( Table 1). The molecule adopts an elongated S shape, with the central part of the molecule mostly planar, the greatest deviation from planarity being between the phenyl and thiazol groups with an angle of 13 . The mostly planar mid-section of the molecule forms stacks via a series of weak interactions with CH and NHÁ Á ÁOS as well as CHÁ Á ÁOC atom-atom contacts (i.e. shorter than the sum of van der Waals radii), as shown in Fig. 5.
4.1.6. Polymorphic hydrate (XXI). Gallic acid monohydrate (C 7 H 6 O 5 ÁH 2 O) was chosen as the target for the new category 6. Gallic acid monohydrate had two previously known forms, (1) (Jiang et al., 2000) and (2) (Okabe et al., 2001). Form (4) of hydrate (XXI) was observed from crystals grown by slow evaporation from methanol in the presence of sarcosine and crystallized in the monoclinic space group P2 1 /c with Z 0 = 1 (Clarke et al., 2011). The crystal structure is dominated by an extensive hydrogen-bonding network. Unlike forms (1) and (3), no carboxylic acid dimer units are formed, with forms (2) and (4) instead having hydrogen bonds from the carboxylic acid to both water and adjacent gallic acid molecules (Fig. 6).

Comparison of the predictions with the experimental crystal structures
The submitted predictions were compared with each experimentally determined crystal structure using the 'Crystal Structure Similarity' feature of the Materials Module of Mercury (Macrae et al., 2008). The algorithm used by this feature allows comparison of the molecular packing environment between two or more crystal structures. The reference crystal structure, in this case the experimentally determined crystal structure, is analysed and represented by a reference molecule and a coordination shell of its 14 closest neighbours. This set of distances is then searched for in the predicted crystal structures and if they match to within the default geometric tolerances (distances within 20% and angles within 20 ) then the coordination shells are overlaid and a rootmean-squared deviation (RMSD 15 ) of the atomic positions is calculated for all matching molecules. As with previous blind tests, this search was configured to ignore H atoms due to the uncertainty of their positions in X-ray determined crystal structures. If all 15 molecules of the reference and predicted crystal structure matched within the standard tolerances, the crystal structure was determined as having been successfully predicted.
For hydrate (XXI) it became apparent that some predictions matched all non-H atoms but not the H-atom positions as located in the target crystal structure. For this molecule we therefore re-ran the crystal structure comparison, but this time elected to include H atoms in the calculation in order to determine if an exact match was present.
Overlays of the X-ray determined crystal structure with some of the predicted structures for targets (XVI)-(XX) can be found in the supplementary material.  Table 3 Lattice parameter deviations (predicted À experimental), ÁE and RMSD for the experimental and predicted structures of molecule (XVI). = = = 90 in all structures.

Figure 6
Packing diagram of the crystal structure of hydrate (XXI). Grey = carbon, white = hydrogen and red = oxygen. Hydrogen bonds are shown as blue lines.

Predictions results
4.3.1. Molecule (XVI). All of the participating research groups attempted predictions for molecule (XVI), two of whom predicted the observed crystal structure within their three predictions (Table 3). One of these successes (Neumann, Leusen, Kendrick and van de Streek) was submitted as the group's first prediction, while the other (van Eijck) was submitted as the participant's second prediction. Both of these successful predictions gave RMSD 15 deviations from the experimentally determined crystal structure of less than 0.25 Å .
Outside of the three official predictions, the observed crystal structure was present in the extended lists of five other research groups. The success rates here are comparable to the first three blind tests, while not quite as high as the results observed in the fourth blind test. This may be attributed to some methods having difficulties with many structures close in energy. The very small ÁE in Table 3, even when the observed structure is found outside of the first three predictions, shows how closely spaced the energies are for this molecule, and the accuracy in lattice energy required for a successful prediction.

Molecule (XVII)
. 13 of the participating research groups attempted predictions for molecule (XVII), two of which predicted the observed crystal structure within their three official predictions (Table 4). As with molecule (XVI), one of these successes (Neumann, Leusen, Kendrick and van de Streek) was submitted as the group's first prediction, while the other (Price and Habgood) was submitted as that group's second prediction. Both of these successful predictions gave RMSD 15 values of less than 0.13 Å .
Four other research groups submitted the observed crystal structure in their extended list of solutions, with energies between 3.2 and 6.4 kJ mol À1 above their global minimum. The slightly lower rate of success for this category than for the last blind test may be attributed to the fact that molecule (XVII) is not truly rigid, with flexibility in the nitro groups having to be taken into consideration. Despite these additional challenges, the observed crystal structure was still successfully predicted. 4.3.3. Molecule (XVIII). 13 research groups attempted predictions for the category 3 target, molecule (XVIII), with one group (Neumann, Leusen, Kendrick and van de Streek) successfully predicting the observed crystal structure within their three predictions (  Table 5 Lattice parameter deviations (predicted À experimental), ÁE and RMSD for the experimental and predicted structures of molecule (XVIII). = = = 90 in all structures.

Rank
ÁE  submitted as this group's first submission, with an RMSD 15 from the observed crystal structure of just 0.12 Å . Three other groups also reported the correct crystal structure in their extended lists of solutions, with one group (Orendt, Grillo, Ferraro and Facelli) close to having a successful prediction as their number 4 structure is a close match to the experimental structure with an RMSD 15 value of 0.252 Å .
4.3.4. Molecular salt (XIX). 11 participants attempted predictions for the molecular salt (XIX) and two of these predicted the observed crystal structure within the three official predictions (Table 6): van Eijck as the second prediction and Neumann, Leusen, Kendrick and van de Streek as the third prediction, with RMSD 15 values of 0.15 and 0.22 Å . Two other participants located the crystal structure within their extended lists of submissions.
The rate of success in searching for structures with two independent molecules in the asymmetric unit is broadly comparable with that of the last blind test. However, the energetic ranking of the salt structures provided a greater challenge than was experienced with the cocrystal used in 2007. The most successful prediction relied on the use of a supramolecular dimer owing to difficulties with modelling individual ions. Comparison with predictions and the known crystal structure of the similar compound present in CSD entry RABYID also helped to weight some predictions, including the third placed submission made by Neumann, Leusen, Kendrick and van de Streek, which would have been ranked at position 20 by energy alone. 4.3.5. Molecule (XX). Ten participants attempted predictions for molecule (XX) and two of these predicted the observed crystal structure as their top submission (Day and Cruz-Cabeza; Price, Kazantsev, Karamertzanis, Adjiman and Pantelides). One other group (Neumann, Leusen, Kendrick and van de Streek) also located the observed crystal structure in its extended list of solutions (Table 7) at rank 7.
This category was introduced in this blind test as a new challenge and so there are no results from any previous blind tests with which to compare. However, this does appear to be the first case of a molecule of this complexity having been successfully predicted under blind test conditions and then detailed in a refereed publication. The key dependence was on the conformation of the molecule and with eight internal degrees of freedom the problem became one of completeness of the search. One team resolved this by taking into account CSD observations for each of the flexible components to reduce the search to a more manageable size.  Table 7 Lattice parameter deviations (predicted À experimental), ÁE and RMSD 15 for the experimental and predicted structures of molecule (XX). = = 90 in all structures.   (b) Lattice parameter deviations (predicted À experimental), ÁE and RMSD 15 for the predicted structures of hydrate (XXI) with alternative H-atom placement to the experimental structure. = = 90 in all structures.
Expt. (T = 150 K) --1.639 9.790 (7) 3.609 (3)  4.3.6. Polymorphic hydrate (XXI). Ten participants attempted predictions for the hydrate (XXI). This category featured the opportunity to find and locate both an unknown polymorph and two polymorphs whose crystal structures had previously been determined. During analysis of the results it became apparent that there is an alternative proton arrangement in the hydrogen-bonding network of form (4) involving the central OH moiety of the acid and the water molecules (see Fig. 7). Solutions with both proton conformations were generated by some groups, but no agreement was observed in which form had the lower energy.
In previous blind tests, H-atom placement has been ignored in determining if a participant's entry matches the target crystal structure, but in this case it was evident that the two groups that submitted a match within their top three submissions (Price and Braun; van Eijck) did so with the phydroxy conformation of form (4) alt , not that of the target crystal structure form (4) expt (Fig. 8). As the p-hydroxy gallic acid proton shows enlarged displacement parameters, it could be argued that some disorder is present in the structure.
Given this, we present here results for both exact matches including H-atom placement (Table 8a) and matches for non-H atoms only (Table 8b). No groups submitted an exact match in their top three solutions. Four groups (Day; van Eijck; Neumann et al.; Price and Braun) had exact matches within their extended lists of submissions. For matches involving only the non-H atoms, two groups located the target crystal structure within their top three solutions (van Eijck; Price and Braun) as their first and third submissions respectively. Both of these groups also located the exact match, but at significantly higher energies of approximately 12 kJ mol À1 above their global minimum. Three other groups (Desiraju et al.; Day; Neumann et al.) also located this crystal structure in their extended lists of submissions.
Tables 8(c) and (d) show successful matches for the existing polymorphs [forms (1) and (2) in this test]. Six groups located form (1) in their extended lists of submissions, and five groups located form (2). These were generally predicted at high relative energies and rankings, and with no consistency between groups on the stability order between form (1) and (2). This highlights problems in modelling the stability of hydrates. Table 9 summarizes the approximate computational resources used by some of the participants. Of particular note is the disparity between some of the groups; the range of computational expense seen in CSP2010 varies from a few thousand CPU hours to almost 200 000 CPU hours (which translates to over 22 CPU years). Clearly the resources required for this blind test have increased. A large portion of the total CPU time was devoted to targets (XX) and (XXI), and is therefore clearly dependent upon the complexity of the molecule. Fortunately, the computer systems required to meet this increased need are also now more readily accessible, as shown by several groups reporting increases of computing resource of over an order of magnitude (and sometimes almost two orders of magnitude) over the resources used for their CSP2007 submissions. As computers get progressively faster and with greater numbers of computing cores per processor, the real time required for these computations is decreasing. This makes modern computers more viable for fast prediction of the simpler targets.

Overall success rates
The success rate for previous blind tests has shown a fluctuating, but generally upward trend, with  particular success shown in the fourth blind test (Day et al., 2009). This fifth blind test was designed to see if the successes of the fourth test could be repeated, and also to provide more challenging targets to try to stretch the techniques that have thus far been developed. This test therefore saw the introduction of more flexible molecules, as well as hydrates and salts, significantly increasing the complexity of the challenge.
Success for these tests is a combination of two factors: Firstly the ability to generate all possible crystal structures, and secondly the ability to evaluate and rank those crystal structures. The search performance can be impacted by methods that are presently unable to search for crystal structures in space groups with higher values of Z, or simply through a lack of computing time and resources. This will lead to an incomplete search space, which may cause the correct solution to be missed entirely. For flexible molecules the conformation of the molecule is also of great importance. Failure to use the correct conformation or to allow for flexibility during the search will lead to failure to predict the correct crystal structure, and this problem becomes greater the more flexible the target molecule. Lastly, the crystal structures generated must be ranked, which is often complicated by the fact that most molecules tend to have many distinct crystal packing possibilities within a small energy range (Day et al., 2004), so that the energy differences between crystal structures are generally very small. The identification and use of accurate energy models can often prove to be the most challenging aspect of successful crystal structure prediction. Ranking is further complicated by thermodynamic kinetic aspects, i.e. energies alone may not be sufficient; entropies and nucleation kinetics could also be relevant.
Of  Table 9 Summary of computational resources used by some of the participants in CSP2010. blind test. Overall, the success rates for these four targets were a little lower than for CSP2007, but generally at least as good if not better than the results obtained for CSP1999, CSP2001 and CSP2004. What these results do show, however, is that just as in CSP2007, the method adopted by Neumann, Leusen, Kendrick and van de Streek again excelled, with this group able to successfully predict the crystal structures of the first three categories with their number 1 submission, as well as the fourth category with their number 3 submission. They were the only participants able to generate all target crystal structures within their extended list of submissions. They did so with the lowest RMSD 15 values for all except the hydrate crystal structure. This demonstrates the reliability of DFT-D methods to predict the crystal structures of small organic molecules (Asmadi et al., 2009;Chan et al., 2011). For the fourth category, complete crystal-structure prediction studies were performed for (XIX) and for model compound RABYID from the CSD. The energy landscapes of these two systems were analysed and showed significant similarities. Based on these similarities, it had to be concluded that the experimental structure of (XIX) could be isostructural to the experimental structure of RABYID, and this structure, even though it was ranked 20th by energy (22nd for RABYID), was submitted as the third candidate structure .
More complex systems such as salts continue to provide some challenge, perhaps suggesting that a salt should be considered a new, more challenging category than the current 'cocrystal' definition of category four.
This test also introduced two new categories that provided much greater challenges to the participants and 11 out of the participating groups attempted at least one of the targets (XX) and (XXI). Particularly encouraging was that two groups (Price et al.; Day et al.) successfully predicted the crystal structure for the largest, most flexible molecule to be included in this series of blind tests. The hydrate target (XXI) proved to be a considerable challenge, even to methods that have been successful for hydrates of o-dihydroxybenzoic acids (Braun et al., 2011), and highlights the many difficulties that such a system can pose to characterization as well as successful structure prediction. However, this is a system that needs to be tackled; water is one of the most complex solvents to model, yet it is also one of the most important.
This blind test has also once again highlighted that the use of generic standard force fields does not lead to good crystal structure prediction results. We have also observed that the more extensive search methods are adequate within the limitations (Z 0 , no disorder etc.) implicit in the blind test categories, but have to assume the covalent bonding in the chemical diagram and rely on a sufficient number of search structures being refined by the more accurate and expensive model for the lattice energy. Successful prediction of small molecule crystal structures has been shown to require both accuracy of energies and the ability to coordinate the interand intramolecular force field contributions. The methods that gave the greatest success were varied and were modified to take on these tougher challenges.

Challenges faced
Molecule (XVI), while the simplest of the rigid molecule targets, proved to have many crystal structures close in energy. Transferable empirical potentials had difficulty coping with diazide-carbonyl interactions with induction being a problem. Simple point-charge models used by some groups failed completely for this molecule, although van Eijck did find in post-analysis that one set of charges predicted the observed structure.
This system is the first to be tackled by an ab initio random search method (Misquitta, Pickard and Needs) which does not fix the chemical bonding and uses electronic structure methods during the search, although this approach results in a significant increase in the computing resources required when compared with the methods employed by the other participating groups. This method failed as the search was not extended to eight formula units in the cell. Many of the numerous minima, including the global minimum, corresponded to an isomer with the formation of a bond to give a heterocyclic ring with the two N atoms, showing the promise of this method for cases, such as tautomers, where the covalent bonding is uncertain.
Molecule (XVII) was perhaps not well selected as a target for its category as the molecule was not truly rigid; the orientation of the nitro groups may be affected by intermolecular interactions in the crystal structure. As a result participants were forced to first consider how to deal with this flexibility. The electrostatic potentials of the nitro groups also proved to be unusually challenging to model successfully, although the dispersion proved to be a very important contribution to the lattice energy. These additional issues lead to molecule (XVII) being a significantly more difficult problem than previous targets in this category. Despite these extra challenges, the success rate for this category was good compared with previous blind tests.
For molecule (XVIII) flexibility proved to be the key to successfully locating the crystal structure in the search. Some searches missed the crystal structure, with the most fundamental reason being the wrong conformation of the C(N 2 )C(O) bond. The relative energies of the cis and trans configurations were sufficiently sensitive to the methods being used to cause mis-assignment.
For the salt (XIX), there were again some difficulties with flexibility with the relative orientation of the two fragments; for the acid there is considerable conformational flexibility and the calculated stability of the conformers alters between the gas and solid.
All groups encountered significant problems with developing suitable methods of evaluating the relative lattice energies of structures containing the different conformers. Plane-wave ab initio methods do not cope well with isolated ions in a vacuum, causing problems with ion-specific reference data calculated with DFT-D methods for force-field parameterization. Induction and charge transfer, which are stronger in molecular salts, limited the transferability of exp-6 potentials which had been fitted to crystal structures of neutral research papers molecules. Successful prediction based on energy (van Eijck) was achieved by the use of a supramolecular dimer, rather than two ions as individual molecules.
Other groups noted the similarity of an existing crystal structure in the CSD, RABYID, the crystal structure of which consisted of the same fumarate ion but with a quinolinium counterion instead of 1,8-naphthyridinium (i.e. where the unprotonated nitrogen is instead a CH moiety). The energy landscapes generated for both salts proved similar enough to encourage the speculation that the two crystal structures could be isostructural and one group (Neumann et al.) submitted a successful prediction based on this approach .
Molecule (XX) was the first large flexible molecule to feature in the blind tests and proved a considerable challenge. For such highly flexible molecules there is a key dependence on the conformation of the molecule and successful prediction involved succeeding at this early step. One of the main difficulties is the computing power required to make a complete search for all available space groups with a flexible molecule; when all standard orientations about the exocyclic single bonds are considered, there are over one thousand possible conformations. The two successful strategies (Day and Cruz-Cabeza; Price, Kazantsev, Karamertzanis, Adjiman and Pantelides) reduced the search space to a more manageable level, producing innovations in methodology that have been described and contrasted in detail elsewhere (Kazantsev, Karamertzanis, Adjiman, Pantelides, Price, Galek, Day & Cruz-Cabeza, 2011). Day et al. used geometry data for similar systems from the CSD to help limit the search further and considered a set of predefined conformations. Price et al. identified likely ranges of values for the flexible torsions and used an extension to the CrystalPredictor methodology and databases of the ab initio calculations on the isolated molecule to allow the crystal structures and conformations to be simultaneously refined . Neumann et al. employed a fully flexible molecule, allowing all conformations to be explored during the crystal structure generation step. Use of multipoles and empirical potentials performed better than DFT-D in this case, with both groups using this method (Day et al.; Price et al.) successfully predicting the crystal structure in first place.
Hydrate (XXI) proved to be one of the most challenging systems in the blind test. For this molecule two known polymorphs already existed. However, the difficulty in predicting this crystal structure was not due to the availability of two already known polymorphs, but rather that the representation of water-water and water-gallic acid interactions is extremely difficult to model, making the successful prediction of even the known polymorphs a difficult task.
As a hydrate, the hydrogen-bonding network enabled by the water molecules and the various hydrogen-bond donors and acceptors in the acid proved key to successfully predicting the crystal structure, but it is also obvious that the sheer number of different possible hydrogen-bond networks make the problem a difficult one. The results obtained for form (4) show that with the same placement of non-H atoms there is more than one set of hydrogen positions that is possible. Energetically, the OH conformation observed in the experimental structure is not the most favourable in isolation and, given the nature of X-ray diffraction, the positions of these protons cannot be deemed as unequivocally determined. Indeed, there is evidence of large displacement parameters for the protons involved in the two alternative hydrogen-bond networks. This leads us to consider that the structure is best described as disordered with respect to which network is present. This matter would only be resolved with an in-depth temperature-dependent X-ray and NMR study. A post-blind test polymorphism screen (Braun, Personal communication) showed that the ordered form (2) structure is the most stable polymorph at room temperature.
Overall, the systems that gave the most difficulty are those where the molecules can adopt very different low-energy conformations, where current methods may not accurately reflect the energy differences between the conformations in the solid state. Work on improving the estimates of polymorphic energy differences in challenging cases where the polymorphs have different numbers of inter-and intramolecular hydrogen bonds (Karamertzanis et al., 2008) shows that improving the theoretical basis of the methods used to evaluate the lattice energies will lead to further progress.

Conclusion
This fifth blind test has built upon the successes of previous blind tests and shows that a state-of-the-art method for crystal structure prediction is able to reliably predict crystal structures of small rigid and slightly flexible molecules, and methods are emerging that are able to tackle larger more flexible molecules and complex systems such as salts and hydrates.
For each of the six target crystal structures, there was at least one successful prediction under the criteria stated for success at the start of the test [although for the hydrate (XXI) certain protons were incorrectly placed]. The number of successful predictions for each of the first four categories was broadly comparable with the first three blind tests, but slightly less than the great successes observed with CSP2007. This may be due to the difficulty of easily gauging a target's difficulty based on its molecular diagram alone -several of the targets in this blind test showed additional challenges not faced in CSP2007 even though the target molecule met the same selection criteria. One observation that is easily made, however, is that the DFT-D method continues to perform very well for these molecule types, although it does not yet supply a comprehensive solution, as observed by the inability to predict some targets [such as (XIX)] by energy methods alone. Most other successes were based on using realistic models for the intermolecular forces (Stone, 1996), which included a distributed multipole representation of the molecular charge distribution.
For the large flexible molecule [target (XX)] it is promising that two groups were able to successfully predict the crystal research papers Acta Cryst. (2011). B67, 535-551 structure as their first place entry. In both cases success was achieved by systematic reduction of the problem to more manageable proportions, such as through the use of CSD geometry data to determine the more likely conformations in the experimental crystal structure. More methodological and program development should allow the most thermodynamically stable crystal structures to be computed more readily for molecules of this complexity in the future. The best approach for such complex systems may well be the use of experimental data, including polymorph screening, alongside the calculations to move towards a predictive technology for the understanding and anticipation of polymorphism.
The difficulties faced in this blind test have helped push the participating teams to adopt novel approaches in an attempt to successfully predict the experimental crystal structures. While some challenges remain, such as the need to include a direct consideration of temperature (thermodynamics prescribes that relative stability is a function of temperature), the results achieved in this blind test demonstrate that crystal structure prediction can now be performed reliably for small molecules using a state-of-the-art method. Furthermore, results on the large molecule [target (XX)] as well as the salt [target (XIX)] and the hydrate [target (XXI)] provide encouragement that crystal structure prediction can move on from prediction of small rigid molecules to more complex systems, while highlighting deficiencies in current methods where key developments are still required.


Phytochemical constituents and preliminary toxicity evaluation of leaves from Rourea induta Planch. (Connaraceae)

Most active plants are toxic at high doses and it is therefore important to investigate the preliminary toxicity of plant extracts. The Rourea induta species is a potential drug with no phytochemical or biological studies registered in the literature. Thus, a phytochemical study and a toxicity analysis of the ethanolic extract obtained from the leaves of Rourea induta Planch., Connaraceae, was run. A long chain hydrocarbon, n-tetracosane, and four flavonoids were identified: quercetin, and three glycosylated derivates, quercetin-3-O-α-arabinofuranoside, quercetin-3-O-β-xyloside and quercetin-3-O-β-galactoside. This is the first time these have been isolated in this species. The structures were elucidated by 13C NMR, 1H NMR, UV and IR spectroscopy. The toxicity evaluation of extracts was performed by the brine shrimp method and determination of hemolytic activity. The samples demonstrated no toxic potential by the analyzed methods.

INTRODUCTION
The Connaraceae family comprises approximately 16 genera among 300 to 350 species distributed throughout tropical areas of the world; that consists of the angiosperms characterized by ligneous, trees or shrub species. In America, five genera can be found: Bernardinia, Cnestidium, Connarus, Pseudoconnarus and Rourea (Forero, 2007).
Connaraceae family native species are spread mainly in the Amazon, and the shrubby species are common in "cerrado" (Brazilian ecosystem composed of short trees and shrubs) and are similar to legume species (Lorenzi, Souza, 2005). In "cerrado", the family is represented by seven shrubby-arboreal species distributed around the genera Rourea and Connarus (Lenza et al., 2008). The cerrado is the second biggest Brazilian and Latin American biome, and has many potential medicinal species that have not yet been subject to scientific study (Recor, 2009).
Rourea is a pantropical genus and comprises 42 species and 19 varieties; the Amazon is its dispersion center (Forero, 1976;Fonseca, Proença, 2002). The Rourea induta Planch. species is characterized by small trees and shrubs that grow to a maximum height of 4 meters. It bears greenish and densely ramified young shrubs. Its cork is widely known for the treatment of Rheumatism (Fonseca, Proença, 2002).
Some important biological activities have been described for species of the Connaraceae family, whereas the Rourea induta species has no registered studies in the literature. Phytochemical and biological activity studies are a starting point contributing toward the valuable detection of the species and its isolated compounds.
Most active plants are toxic at high doses and it is thus important to investigate the preliminary toxicity of plant extracts. To achieve a toxicological evaluation, the brine shrimp method and hemolytic activity determination techniques have been employed for different groups . Against this background the aims of this study were to explore and isolate chemical constituents from the ethanol extract of Rourea induta Planch., Connaraceae, and to perform a toxicity evaluation of the extract and fractions.

Plant material
The leaf samples from R. induta Planch., Connaraceae were collected in Rondonópolis city, Mato Grosso State, Brazil, in November 2007. The material was identified by Gert Hatschbach, botanist of Curitiba Botanical Museum, Brazil, and the exsiccate was registered under voucher number 261574.

Extraction and isolation
The total amount of ethanol extract was obtained from 2 kg of plant material in 95% ethanol, with the use of Soxhlet equipment, and then filtered, concentrated in a rotary evaporator to 300mL, and fractioned by liquid-liquid partition with solvents of different polarities. From this mixture, hexane, ethyl acetate and chloroform fractions were obtained. The hexane fraction was used to dissolve the filtered residue, and this was fractioned with hexane in a silica column on the Soxhlet equipment. The fractions hexane 1 and hexane 2 were obtained as a result, yielding 5.7834g (0.289%) for hexane 1, 4.9818g (0.249%) for hexane 2, 39.92g (1.99%) for chloroform and 54.3579g (2.717%) for ethyl acetate, at the end of this procedures.
The chloroform fraction was also submitted to silica column chromatography with a hexane/ethyl acetate eluent system at 5% gradient. It attained ethyl acetate to 100% followed by an ethyl acetate/methanol system at 5% gradient. The samples that had some crystallization were submitted to thin-layer chromatography in mobile phase with ethyl acetate, formic acid, acetic acid, water (100:11:11:27) and reactive NEU (reactive 2-aminoethylbutyrate). A pure compound (compound 2) (0.1171 g) was identified between sub-fractions 11-16. Sub-fractions 30-36 and 37-44 were submitted to Sephadex LH-20 with 70% methanol as the eluent, and two compounds were obtained denominated 3 (0.0095 g) and 4 (0.022 g).
During the concentration of ethyl acetate fraction, yellow crystals precipitated, which were purified by vacuum filtering and identified as compound 5 (1.5494 g).

Compound identification
The 13 C NMR and 1 H NMR spectrums were obtained on a Brucker ® spectrophotometer model AC200 at 300 MHz. Ultraviolet spectroscopy was carried out on a UV-1601 Shimadzu® spectrophotometer from 200 to 450 nm following the Mabry, Markham & Thomas (1970) methodology. IR spectrums were carried out on pastilles of anhydrous potassium bromide (KBr) compressed on Bomem-Hartmann & Braum MB-series equipment and analyzed on a Biored® FTS 3500 GX, 400 to 4000 cm -1 . The melting point was measured on Koffler-Reichert Austria equipment.

Brine shrimp bioassay
The brine shrimp (Artemia salina) method was first described by Meyer et al. (1982). The eggs of brine shrimp hatched within 48 hours in artificial sea water, producing a large number of larvae. The samples, ethanolic extract, and all the fractions, were tested at concentrations of 1000, 100 and 10 μg/mL. Ten shrimps were transferred to the samples and after 24 hours survivors were counted and percentage of deaths at each dose recorded. Quinidine sulfate was used as a positive control and the solvent used to prepare the samples as the negative control. The test was run in triplicate and the data was analyzed by the Probitos method to determine LD 50 with a 95% confidence interval.

Hemolytic activity
Ethanolic extract and fractions were submitted to hemolytic activity tests. The first method tested was based on the WHO (1998) and Carvalho et al. (2009). For this method, a 2% sheep red blood cell suspension (Newprov ® ) was prepared in pH 7.4 phosphate buffer. The samples were diluted in 10% ethanol with NaCl 0.9% and tested at concentrations of 1000, 500, 200 and 100 μg/mL. A volume of 1.0 mL of the blood suspension was added to the samples which were then mixed slowly and left to rest for 30 minutes, mixed again and kept at rest for a further 150 minutes. Subsequently, the samples were centrifuged for 5 minutes at 3000 rpm. Distilled water was used as a positive control and solvent and phosphate buffer as a negative control. The result was reported as presence or absence of hemolysis based on the supernatant tonality after centrifugation. The presence of a red blood cell precipitate indicated a negative result.
The second method tested was agar diffusion using plates with sheep red blood cell agar (Newprov ® ). The samples were prepared at 1000 μg/mL and impregnated in sterile discs (Whatmann n o 1, diameter 7 mm). After solvent evaporation, the discs were distributed in the plates, which were incubated at 36 o C for 24 hours. Hemolytic halos were then measured and results expressed as mean halos found in duplicate. Discs with the solvents used for sample dilution were used as a negative control and Triton X-100 at 1000μg/mL as a positive control (Efing, 2008).

RESULTS AND DISCUSSION
The hexane fraction of ethanol extract from the leaves of R. induta was subjected to a chromatographic step over silica gel to yield compound 1 (n-tetracosane), while the chloroform fraction was subject to multiple chromatographic steps over silica gel to yield compounds 2, 3 and 4 (quercetin, quercetin-3-O-α-arabinofuranoside and quercetin-3-O-β-xyloside, respectively). Compound 5 (quercetin-3-O-β-galactoside) was obtained during ethyl acetate fraction concentration.
The 1 H NMR signals for compound 1, in the range 0.8 -1.7ppm, indicated a region characteristic of aliphatic alicyclic compounds with three hydrogen at δ0.8, whereas the signal integration at δ1.26 indicated about 32 hydrogen, corresponding to CH 2 . The 13 C NMR spectrum characterized five signals in the range 14-32ppm. The mass spectrum showed a characteristic fragmentation of aliphatic hydrocarbons, with 14 mass units between peaks. The fragmentation standard is determined by C-C fragmentation because hydride (H-) elimination is difficult. The spectrum showed higher intensity peaks (44 and 57) that represented the fragments with three and four carbons, and a low intensity molecular ion (m/z) of 338, characteristic of long chain. The melting point was 65 o C a typical value for a hydrocarbon. These results were in line with those of Siddiqui et al. (2004) and denoted that compound 1 was n-tetracosane (C 24 H 50 ).
For compounds 2-5, the UV spectrum showed typical results for flavonoids, with bands between 256-259 nm relative to ring A and 348-360 relative to ring B (Mabry, Markham, Thomas, 1970), which suffers a hypsochromic effect in comparison to quercetin due to C-3 substitution for compounds 3, 4 and 5 (Santos, Schripsema, Kuster, 2005). For all samples, the addition of NaOAc produced a bathochromic effect of band II, which indicated a free hydroxyl in position 7. H 3 BO 3 led to a bathochromic shift of band I in the presence of an orthodihydroxyl group in ring B. For 3, 4 and 5, the spectrum with HCl revealed a bathochromic shift for bands I and II. The addition of AlCl 3 caused a bathochromic effect of band I between 35-55nm compared with methanol spectrum, typically shifted for 5-hydroxyflavons with position 3 replaced. For compound 2 this effect was 57nm, a typical result for 3,5-hydroxyflavons (Mabry, Markham, Thomas, 1970).
The infrared spectrum revealed two absorption bands in 3430 and 3300 cm -1 that typically result from the OH link axial deformation. Moreover, the existence of an aromatic ring may be observed, evidenced by a set of bands that range between 1600 and 1400 cm -1 , which denotes the axial deformation of the aromatic C=C. Bands close to 1650 cm -1 suggest the presence of carbonyl (Silverstein, Bassler, Morril, 1994).
The 13 C NMR signals for these compounds were in good agreement with those of quercetin, the difference between them was located at the glycoside linked to the C-3 of the aglycone. This glycoside was identified by the signals at sugar region (60-80ppm) in the spectrum by comparing against those described in the literature. For compound 2, no signals were identified at this region (Andersen, Markham, 2006). The signals for compound 3 indicated arabinofuranoside (Vvdenskaya et al., 2004), for compound 4 xyloside (Yan et al., 2002) and for the isolated 5 galactoside (Jiang et al., 1990). The 1 H NMR signals for these compounds were found in the aromatic region (6-8ppm) and sugar region (3-4.2 ppm). The configuration of the sugars were determined by the coupling constant of the anomeric hydrogen, where compound 3 showed the anomeric hydrogen at δ5.58 with J=1.00 Hz, indicating that arabinofuranoside is α (Zhang et al., 2005), compound 4 was δ5.17 with J=7.2 Hz, showing a β configuration for xyloside (Yan et al., 2002), and compound 5 was δ5.39 with J=7.8 Hz, a β configuration for galactoside (Santos, Schripsema, Kuster, 2005).
The toxicity evaluation against Artemia salina  (Table IV) demonstrated that all the samples showed a median lethal concentration greater than 1000 μg/mL, the maximum concentration for a sample to be considered active (Meyer et al., 1982).
This bioassay is used to evaluate the acute toxicity and is considered essential as a preliminary assay in the study of compounds with potential biological activities (Amaral, Silva, 2008). Analyzing the results, it can be concluded that neither the ethanolic extract, nor the fractions from R. induta exhibited toxic potential against the brine shrimp.
For the hemolytic tests, the tested sample showed no hemolytic ability according to the two methods analyzed. In the test using the red blood cell suspension, none of the supernatants showed red coloration and all had a red blood cell precipitate at the tested doses and therefore caused no hemolysis in red blood cells. This result indicates that neither the fractions nor the ethanolic extract are toxic against red blood cells. These results were confirmed by the agar 60.14 Note: s= singlet; ls= large singlet, d=doublet, dd= double doublet, dt = double triplet, m= multiplet, J= coupling constant diffusion method, on which none of the samples had a hemolytic halo around the impregnated disc, confirming the absence of hemolytic activity. Similarly, the negative controls exhibited no hemolytic halo, whereas the Triton X-100 had a halo of 2 cm.
Red blood cell lyses can cause an elevation in plasma hemoglobin leading to harmful effects in the kidneys (nephrotoxicity), and in the cardiovascular system (vasomotor effect) (Carvalho et al., 2007). Therefore, negative hemolytic activity is a good indicator because it confirms no toxicity to erythrocyte membrane.
The acute toxicity results showed that the Rourea induta extracts had no toxic potential, thus favoring the species for further study such as pharmacological analyses, to determine therapeutic properties of this species.