Short-Range Solvation Effects on Chiroptical Properties: A Time

Nov 24, 2014 - ... 28) consisting of Dunning's [5s3p/3s] contraction of Huzinaga's primitive [10s6p/5s] set with two sets of polarization functions (Î...
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Short-Range Solvation Effects on Chiroptical Properties: A TDDFT and ab initio MD Computational Case Study on Austdiol Daniele Tedesco, Riccardo Zanasi, Barbara Kirchner, and Carlo Bertucci J. Phys. Chem. A, Just Accepted Manuscript • DOI: 10.1021/jp511428v • Publication Date (Web): 24 Nov 2014 Downloaded from http://pubs.acs.org on November 28, 2014

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The Journal of Physical Chemistry

Short-Range Solvation Effects on Chiroptical Properties: a TD-DFT and ab initio MD Computational Case Study on Austdiol

Daniele Tedesco,† Riccardo Zanasi,‡ Barbara Kirchner,§ and Carlo Bertucci*,†



Department of Pharmacy and Biotechnology, University of Bologna, via Belmeloro 6, I-40126

Bologna, Italy. ‡

Department of Chemistry and Biology, University of Salerno, via Giovanni Paolo II 132, I-

84084 Fisciano, Italy. §

Mulliken Center for Theoretical Chemistry, University of Bonn, Beringstraße 4+6, D-53115

Bonn, Germany.

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ABSTRACT. The description of solvation effects on the chiroptical properties of chiral molecules is still a difficult challenge in the field of computational spectroscopy: this issue is critical in stereochemical characterization, since a reliable assessment of absolute configuration requires high accuracy. The present case study reports the huge effect of solvation on the chiroptical properties of austdiol, a fungal metabolite of known stereochemistry: standard protocols based on TD-DFT calculations failed to reproduce its experimental chiroptical properties in methanol. When short-range solvation effects are explicitly considered by means of AIMD, the correlation between calculated and experimental data is greatly improved due to a better description of the chiral environment around the ketone chromophore, showing that the modeling of subtle solvent-induced perturbations may require the most accurate computational methods.

KEYWORDS. Absolute stereochemistry – Hydrogen bonding – Electronic circular dichroism – Optical rotation – Density functional theory – Molecular dynamics

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INTRODUCTION The assignment of absolute configuration is a pivotal stage in the characterization of chiral molecules, which is particularly important in medicinal chemistry: absolute stereochemistry, in fact, affects both the therapeutic and toxicological properties of chiral drugs.1-3 The impressive advances in the field of computational spectroscopy prompted the interest for new strategies aimed at the prediction of experimental chiroptical properties, such as optical rotatory dispersion (ORD), electronic circular dichroism (ECD) and vibrational circular dichroism (VCD).4,5 However, despite the increasing accuracy of quantum mechanical (QM) methods, a reliable stereochemical characterization remains a difficult task:6,7 the modeling of short-range solvation effects is one of the challenges which are still limiting a straightforward and broader application of these methods. The influence of short-range solvation effects on chiroptical properties can be described explicitly by performing QM calculations on solvation clusters.8-11 Different strategies may be employed for the generation of input structures, which are either generated by direct optimization of solvation clusters at the QM level or by extraction of sample geometries from molecular dynamics (MD) simulations. The number and position of solvent molecules included in the clusters depend on the nature of the system: the general trend is to consider the solvent molecules closest to strong interacting groups of the solute (e.g., H-bond acceptors in alcohols or H-bond donors in acetone), or to include the whole first solvation shell(s). Moreover, the inclusion or exclusion of solvent molecules in chiroptical properties calculations is still an open matter of debate.12 ORD calculations are likely to benefit the most from the inclusion of solvent molecules, due to the dispersive nature of optical rotation; non-chiral, UV-absorbing solvents may strongly contribute to the observed optical rotation of the system (or even be the main source of it) if the

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first solvation shells are highly organized and their chromophores absorb at lower energies than the chromophores of the solute. This phenomenon, named chiral imprint, was crucial to rationalize the ORD profile of 2-methyloxirane in benzene.13,14 ECD calculations may be relatively less sensitive to the inclusion of solvent molecules, since typical solvents for ECD spectroscopy are transparent in the UV region, but the inclusion of solvent molecules may result in a better description of local perturbations to the electronic structure of chromophores, which is particularly important for the n → π* transition of carbonyl groups. A new series of natural compounds, named mycoleptones A–C, was recently isolated and characterized from cultures of Mycoleptodiscus indicus.15 The stereochemistry of mycoleptone A, a methylene-bridged dimer of the polyketide austdiol (Figure 1), was investigated by ECD spectroscopy and time-dependent density functional theory (TD-DFT) calculations, in order to confirm the (7R,8S) absolute configuration of the two monomer units; TD-DFT calculations correctly predicted the high-energy region of the ECD spectrum but failed to reproduce the lowenergy region. This behavior is probably due to a wrong description of the chiral environment around the carbonyl chromophores in solution: methanol, for instance, may induce perturbations to the electronic structure and equilibrium conformations of austdiol through intermolecular hydrogen bonding with carbonyl and hydroxyl groups. The present study investigates the effect of solvation on the chiroptical properties of austdiol (1) in methanol through a combination of ECD spectroscopy, polarimetry, QM calculations at the DFT16,17 and TD-DFT level18-20 and ab initio MD (AIMD)21-23 simulations; the different computational strategies currently available were applied and compared. Although the combination of AIMD and TD-DFT calculations has been proposed as a possible strategy to investigate solvation effects on chiroptical properties, such a strategy is successfully employed here on a system of considerable size for the first time.

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Figure 1. Chemical structure and main geometric parameters of austdiol (1).

EXPERIMENTAL AND COMPUTATIONAL METHODS Experimental spectroscopy Compound 1 was extracted from cultures of Mycoleptodiscus indicus according to a recently reported procedure15 and kindly provided by the research group led by Prof. Jairo K. Bastos (Faculty of Pharmaceutical Sciences of Ribeirão Preto, University of São Paulo, Brazil). The experimental ECD and UV spectra of 1 (concentration: 44.4 µM; pathlength: 1 cm; λ: 500–215 nm) were recorded in methanol (Sigma-Aldrich, Milan, Italy) at room temperature on a Jasco (Tokyo, Japan) J-810 spectropolarimeter, using a 1 nm spectral bandwidth, a 0.2 nm data interval, a 20 nm min−1 scan rate and a 4 s time constant. The experimental [α]D value of 1

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(concentration: 0.401 g L−1; pathlength: 1 dm; λ: 589 nm) was measured in methanol at room temperature (measured temperature: 22.8 °C) on a Jasco P-2000 polarimeter, using a 5 s time constant over 350 acquisition cycles. [α]D22.8 (MeOH): +147 deg cm3 g−1 dm−1 (relative standard deviation: 2.1%).

TD-DFT calculations TD-DFT calculations for the theoretical determination of [α]D values and electronic spectra were carried out using the PBE0 functional24-26 and the TZ2P basis set,27,28 consisting in Dunning’s [5s3p/3s] contraction of Huzinaga’s primitive [10s6p/5s] set with 2 sets of polarization functions (αp = 1.5, 0.375 for H; αd = 1.5, 0.375 for C; αd = 1.7, 0.425 for O); the IEFPCM continuum solvation model29 for methanol, as implemented in Gaussian 09,30 was employed in all calculations. Input geometries for TD-DFT calculations were generated using the protocols described in the next subsections. Rotational strengths in dipole velocity formalism (Rj), oscillator strengths (fj) and excitation wavelengths (λj) were determined for the first lowestenergy excited states of each input structure; the theoretical spectra were then determined by approximation of all Rj and fj values to Gaussian band shapes, centered at the corresponding λj values with a band width (∆σ) of 0.25 eV,31 and summation over all calculated excited states.

Standard DFT calculations A preliminary conformational search was performed at the MM level using the MMFF94s force field.32 DFT geometry optimization was performed on MM conformers within a relative energy (∆EMM) threshold of 5 kcal mol−1 using the B97D functional33,34 and the TZ2P basis set;27,28 the IEFPCM continuum solvation model29 for methanol, as implemented in Gaussian

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09,30 was employed in all calculations. TD-DFT calculations were carried out on the optimized geometries of the resulting 3 conformers for the first 50 excited states; the overall theoretical spectra of 1 were derived by conformational averaging according to the Boltzmann population of conformers at 298.15 K and 1 atm based on relative free energies (χG).

DFT conformational scans The effect of the orientation of O–H bonds on the chiroptical properties of 1 was investigated by two independent conformational scans at the DFT level, one on the hydroxyl group in αposition to the ketone chromophore and one on the hydroxyl group in β-position. The optimized structure of conformer 1.01 was systematically modified by rotation of the O–H bond by steps of +30°, yielding 11 new rotamers for each conformational scan, which were labeled 1.01a–k for the rotation of the α-hydroxyl group and 1.01l–v for the rotation of the β-hydroxyl group. After B97D/TZ2P/IEFPCM(MeOH) optimization, PBE0/TZ2P/IEFPCM(MeOH) calculations for the first 50 excited states were performed on all the rotamers.

DFT solvation cluster The input structure for a solvation cluster of 1 with methanol was generated by a preliminary MMFF94s energy minimization on a system consisting of conformer 1.01 and 50 methanol molecules randomly distributed around the solute; molecules of methanol not interacting with 1 were removed. Repeated cycles of energy minimization and removal of redundant solvent molecules led to the identification of a solvation cluster with 6 molecules of methanol interacting with 1 through hydrogen bonding; the selected input structure was then optimized at the B97D/TZ2P/IEFPCM(MeOH) level. Subsequently, PBE0/TZ2P/IEFPCM(MeOH) calculations

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were performed on the whole solvation cluster and separately on 1 and methanol, in order to evaluate their separate contribution to the calculated properties of the solvation cluster; the first 50 excited states were considered.

Classical MD simulations Preliminary classical MD simulations were used to create the starting structure of the subsequent AIMD simulation of the solvation dynamics of 1 in methanol. The system consisted of one molecule of 1 inside cubic solvation boxes of different sizes under periodic boundary conditions (PBC). 5 ns (∆t = 0.8 fs) simulations were carried out in a NVT ensemble, using a velocity rescaling thermostat35 at different temperatures ranging from 273 K to 323 K (τT = 0.05 ps). The OPLS-AA force field36 was employed in combination with PME electrostatics.37 The standard parameters for methanol were previously employed for accurate simulations of the solvent bulk properties,38 while several sets of customized OPLS-AA parameters were prepared and tested for their accuracy in reproducing the main geometric features of 1; the best combination was chosen for further calculations (see Supporting Information). Partial charges for 1 were determined by a RESP fit39 at the HF40/6-311++G**41-43 level; bond lengths and angles were also modified according to the optimized geometry of 1 at the HF/6-311++G** level. After the optimization of force field parameters, a PBC cubic box consisting of 1 and 128 molecules of methanol was employed for a 5 ns (∆t = 2 fs) simulation in a NPT ensemble, using the NoséHoover (NH) thermostat44-46 at 298 K (τT = 1 ps) and the Parrinello-Rahman barostat47,48 at 1 bar (τP = 5 ps), in order to obtain a starting structure for the AIMD simulation.

AIMD simulation

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The AIMD simulation (∆t = 0.5 fs) was carried out in a NVT ensemble, using the NH thermostat at 300 K (tT =50 ps), on a PBC cubic box consisting of 1 and 128 molecules of methanol, which was taken from the optimized classical MD simulation. Born-Oppenheimer molecular dynamics (BOMD) based on the Gaussian and plane wave (GPW) method21-23 was performed using the BLYP49,50 functional with the DFT-D351 empirical corrections for dispersion in combination with GTH pseudopotentials52-54 for core electrons and nuclei and the DZVP-MOLOPT-SR basis set55 for valence Kohn-Sham orbitals. The cut-off for the plane wave representation of electron density was set to 280 Ry, while the SCF convergence criterion was set to 10−6.56 Massive equilibration (5.09 ps) was carried out with chains of 3 NH thermostats coupled to each degree of freedom; subsequently, a single NH chain was used for global equilibration (5.00 ps) and production runs (51.97 ps). Despite the size of the system, the tight SCF convergence criterion ensured a good conservation of energy throughout the trajectory. TDDFT

calculations

of

chiroptical

properties

were

subsequently

carried

out

at

the

PBE0/TZ2P/IEFPCM(MeOH) level on 100 solvation clusters randomly sampled from the production run of the AIMD simulation. Each solvation cluster consisted in 1 and the 5 molecules of methanol closest to the oxygen atoms of 1. Similarly to the previous protocol for the DFT solvation cluster, TD-DFT calculations for the first 30 excited states were performed on the whole cluster and separately on 1. The overall chiroptical properties of 1 were finally determined by averaging over all 100 input structures.

Software DFT and TD-DFT calculations were performed using Gaussian 09,30 while AIMD and RESP fit calculations were carried out using CP2K.57,58 Preliminary MM and MD calculations were

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performed using Spartan’0259 and GROMACS,60 respectively. MD trajectories were analyzed with TRAVIS.61

RESULTS Conformational analysis Austdiol (1) is the main secondary metabolite produced by the mould Aspergillus ustus. The (7R,8S) stereochemistry of 1 has been characterized by 1H-NMR analysis, Horeau's partial resolution method with racemic α-phenylbutyric acid and X-ray analysis on the 5-bromoderivative; the crystal structure of 1 and a collection of physico-chemical data are also available.62-66 The extended conjugate system endows 1 with a large degree of planarity: the conformational flexibility of 1 (Figure 1) is limited to the orientation of the α- and β-hydroxyl groups (dihedrals α and β), the puckering of the cyclohexenone ring (dihedral γ) and the twist of the α,β-unsaturated aldehyde moiety (dihedral δ). Standard DFT optimization at the B97D/TZ2P27,28,33,34 level using the IEFPCM solvation model29 for methanol (Table 1) shows that the bi-equatorial arrangement of hydroxyl groups and the cis orientation of the aldehyde moiety are largely favored, with the hydroxyl groups oriented to form intramolecular hydrogen bonds (conformer 1.01). The intra- and intermolecular interactions of 1 were already characterized by a combined experimental and theoretical study on its crystal packing;67 interestingly, the topological analysis of the calculated electronic density, ρ(r), identifies a bond critical point for the interaction between the ketone moiety and the αhydroxyl group, which is not found in the experimental ρ(r) for the crystal.

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Table 1. Relative free energies, Boltzmann populations at 298.15 K and 1 atm, [α]D values and geometric parameters for the conformers of austdiol at the PBE0/TZ2P//B97D/TZ2P level (IEFPCM model for methanol).

a

Conformer

∆G (kcal mol−1)

χG (%)

[α]D a

γ (deg)

δ (deg)

1.01

0.00

99.6

−31

61.4

−1.8

1.02

4.23

0.1

+356

178.1

3.2

3.46

0.3

+505

60.6

170.6

1.03 Units: deg cm3 g−1 dm−1.

TD-DFT calculations without explicit solvation TD-DFT calculations at the PBE0/TZ2P/IEFPCM(MeOH)24-29 level predict a negative specific rotatory power for conformer 1.01, leading to a conformationally-averaged value for 1 ([α]D = −29 deg cm3 g−1 dm−1) not in agreement with the experimental value in methanol ([α]D = +147), even though the calculated [α]D values for conformers 1.02 (bi-axial arrangement of the hydroxyl groups) and 1.03 (trans orientation of the aldehyde moiety) are both positive. The influence of ring puckering and aldehyde orientation is clearly evident from the theoretical spectra of the conformers of 1: in particular, the ECD spectra of conformers 1.01 and 1.02 (reported in the Supporting Information) are almost opposite, although the absolute stereochemistry of chiral centers is retained. The conformationally-averaged spectra of 1 (Figure 2) show a better correlation with experimental data, mainly in the high-energy spectral region (λ < 300 nm) where the effect of the chiral centers on the π → π* transitions of the conjugated system is stronger; nevertheless, the low-energy spectral region (λ > 300 nm), where the n → π* transitions of carbonyl chromophores are observed, show a lower degree of correlation. Both behaviors are consistent to

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what previously observed with mycoleptone A15 and are not dependent on the functional and basis set employed in the calculations (see Supporting Information for more details).

Figure 2. Experimental and PBE0/TZ2P/IEFPCM calculated ECD spectra of austdiol in methanol, as obtained after standard B97D/TZ2P/IEFPCM optimization.

Conformational scans on the hydroxyl groups The strong influence of small geometric perturbations on the chiroptical properties of 1 was confirmed by DFT conformational scans at the B97D/TZ2P/IEFPCM(MeOH) level on the orientation of hydroxyl groups. The rotation of the α-hydroxyl group elicits a dramatic change in the calculated [α]D values for different rotamers, due to its direct perturbation of the electronic properties of the ketone chromophore; moreover, most of the rotamers display positive [α]D values (Figure 3). Standard DFT optimization could not identify these geometries as possible equilibrium conformers, due to the stabilizing effect of the intramolecular hydrogen bond with the ketone moiety.

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Figure 3. Dependence of calculated [α]D values in methanol (PBE0/TZ2P/IEFPCM) upon the rotation of the α-hydroxyl group of conformer 1.01, as obtained by B97D/TZ2P/IEFPCM conformational scan.

On the other hand, the orientation of the β-hydroxyl group affects the overall chiroptical properties of 1 to a relatively smaller extent, and most of the rotamers display negative [α]D values. The theoretical properties of rotamer 1.01c, for which the O-H bond of the α-hydroxyl group is syn to the geminal methyl group, display a particularly good agreement with the experimental data of 1 in solution: the calculated [α]D (+136) is very close to the experimental value, and the description of the low-energy ECD spectrum is improved. Full details are reported in the Supporting Information.

TD-DFT calculations with explicit solvation

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A preliminary calculation with explicit treatment of solvation was carried out by direct DFT optimization of a solvation cluster of 1 with 6 molecules of methanol close to strong interacting groups. Such a strategy fails to sample the possible arrangements of the solute and solvent molecules in solution, and therefore does not describe the dynamic nature of solvation properly. However, calculated properties were clearly improved when TD-DFT calculations were performed on the solute without solvent molecules (calculated [α]D = +210); this behavior can be explained by the conformational perturbations on the hydroxyl groups due to the interaction with methanol in the solvation cluster, in agreement to what was observed by DFT conformational scan. TD-DFT calculations on the whole cluster did not perform as well, since the conformational sampling was inadequate; the direct contribution of solvent molecules was negligible (further details in the Supporting Information). MD simulations were therefore employed to increase the number and quality of solvation clusters for TD-DFT calculations. The conformational analysis of classical MD (OPLS-AA)36 and AIMD (BLYP-D3/DZVP-MOLOPT-SR-GTH)49-55 simulations performed on cubic solvation boxes of 1 and 128 molecules of methanol (797 atoms) showed that the two techniques describe the orientation of hydroxyl groups in a different fashion (Figure 4). While results from the OPLS-AA simulation are similar to the DFT optimized geometry of 1.01, where hydroxyl groups are oriented to favor intramolecular interactions, the AIMD simulation predicts the occurrence of different orientations for both the α- and the β-hydroxyl groups, consistent with the occurrence of intermolecular interactions with solvent molecules. The puckering of the cyclohexenone ring and the orientation of the aldehyde moiety are described in the same fashion by both techniques, confirming the limited conformational flexibility of 1 observed in standard DFT optimizations.

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Figure 4. Dihedral distribution functions (DDF) for the dihedral angles of austdiol in methanol obtained by conformational analysis on the OPLS-AA and AIMD trajectories.

The theoretical chiroptical properties of 1 in methanol were then determined as an average over 100 TD-DFT calculations on solvation clusters randomly sampled from the AIMD simulation; clusters consisted of 1 and the 5 molecules of methanol closest to the 5 oxygen atoms of the solute, in order to obtain a reasonable description of short-range interactions around strong interacting groups. The inclusion of solvation effects by this technique allows a clear improvement in the agreement between experimental properties of 1 and TD-DFT calculations on the solute (calculated [α]D = +88), which is further improved when solvent molecules are included in TD-DFT calculations (calculated [α]D = +111). The calculated ECD spectrum obtained by calculations on the solvation clusters (Figure 5) clearly shows a better correlation with experimental data in the low-energy spectral region due to a bathochromic shift of the lowest-energy excited states compared to standard TD-DFT calculations. This behavior is also responsible for the improvement of the calculated [α]D value, since the relative contribution of each excited state to the overall optical rotation is described more correctly.68

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Figure 5. Experimental and PBE0/TZ2P/IEFPCM calculated ECD spectra of austdiol in methanol, averaged over 100 solvation clusters taken from the AIMD trajectory.

DISCUSSION The present study investigated the performance of different computational methods in the description of short-range solvation effects on chiroptical properties. The high sensitivity of the chiroptical properties of austdiol to short-range solvation effects is due to the presence of two hydroxyl groups in α- and β-position to a ketone moiety: a common strategy in stereochemical studies on similar systems is the chemical derivatization of hydroxyl groups by eterification or esterification, which facilitates the assignment of absolute configuration by reducing the conformational flexibility of the molecule and by preventing the formation of intra- and intermolecular hydrogen bonds. The features of austdiol, however, were suitable for a case study on the current capabilities of computational methods when dealing with short-range solvation effects: the absolute stereochemistry was already known and the conformational flexibility was very limited, which is usually an ideal situation for standard TD-DFT calculations. However, very small perturbations to the electronic structure and molecular geometry of 1 induced by

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solvation result in a dramatic change of chiroptical properties for this system (Table 2): standard TD-DFT calculations would have led to an ambiguous or wrong assessment of the absolute configuration of 1, if the stereochemistry of the system had not been fully characterized before.

Table 2. Experimental and theoretical [α]D values for austdiol, as calculated with the different computational strategies; the orientation of hydroxyl groups is also reported. [α]D a Experimental in methanol

α (deg)

β (deg)

+147

TD-DFT b on DFT geometries c conformational average

−29

conformer 1.01

−31

13.7

−60.7

rotamer 1.01c

+136

103.7

−53.9

solvation cluster, solute only

+210

103.6

−74.1

f

f

whole solvation cluster

0

solvation cluster, solvent only

+1

TD-DFT b on AIMD geometries d solute only e

+88

whole solvation clusters e +111 a Units: deg cm3 g−1 dm−1. b PBE0/TZ2P/IEFPCM(MeOH). c B97D/TZ2P/IEFPCM(MeOH). BLYP-D3/DZVP-MOLOPT-SR-GTH. e Averaged over 100 geometries. f Reported in Figure 4.

d

The chiral environment of the carbonyl chromophore in solution is dramatically influenced by the network of short-range interactions with solvent molecules, e.g. hydrogen bonds in the case of methanol, involving both the chromophore and the hydroxyl groups. Such interactions cannot be described by continuum solvation models, and an accurate description of the system could only be obtained by means of an AIMD simulation of the solvation dynamics of 1. This

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observation is a very powerful example showing the paramount importance of a proper and accurate description of the system for stereochemical studies on chiral molecules of unknown stereochemistry. The size of the investigated system (solvation box of 797 atoms) is particularly large and represented a very challenging task for AIMD; unfortunately, the huge computational requirements of the technique cannot allow to expect a routine applicability of AIMD to stereochemical studies on solvated systems in the foreseeable future. However, the present study on 1 showed that the accuracy of AIMD in the description of short-range solute-solvent interactions may eventually be necessary in order to fully understand and characterize subtle solvent-related perturbations to the calculated chiroptical properties of chiral molecules.

CONCLUSIONS The present case study reported the huge effect of solvation on the chiroptical properties of austdiol: standard protocols based on TD-DFT failed to reproduce its experimental properties in methanol. When short-range solvation effects were explicitly considered by means of ab initio MD, the correlation between calculated and experimental data was greatly improved, due to a better description of the chiral environment around the ketone chromophore.

ASSOCIATED CONTENT Supporting Information. Complete results from the computational study, supplementary tables and figures, and input structures in XYZ format. This material is available free of charge via the Internet at http://pubs.acs.org.

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AUTHOR INFORMATION Corresponding Author * Telephone: +39 051 2099 731. E-mail: [email protected] Notes The authors declare no competing financial interests.

ACKNOWLEDGMENT The authors thank Prof. J. K. Bastos (University of São Paulo, Brazil) for providing austdiol, CINECA (Italy; ISCRA project HP10CRFD44) and the University of Leipzig (Germany) for computational resources, the University of Bologna and the Marco Polo funding program for financial support.

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(63) Vleggaar, R.; Steyn, P. S.; Nagel, D. W. Constitution and Absolute Configuration of Austdiol, the Main Toxic Metabolite from Aspergillus Ustus. J. Chem. Soc., Perkin Trans. 1 1974, 1974, 45-49. (64) Engel, D. W.; Kruger, G. J. The Crystal Structure of 5-Bromoaustdiol, C11H11O4Br. Acta Crystallogr. B 1976, 32, 2545-2548. (65) IUPAC Commission On Food Chemistry; Pohland, A. E.; Schuller, P. L.; Steyn, P. S.; Van Egmond, H. P. Physicochemical Data for Some Selected Mycotoxins. Pure Appl. Chem. 1982, 54, 2219-2284. (66) Lo Presti, L.; Soave, R.; Destro, R. The Fungal Metabolite Austdiol. Acta Crystallogr. C 2003, 59, o199-o201. (67) Lo Presti, L.; Soave, R.; Destro, R. On the Interplay between CH···O and OH···O Interactions in Determining Crystal Packing and Molecular Conformation:  An Experimental and Theoretical Charge Density Study of the Fungal Secondary Metabolite Austdiol (C12H12O5). J. Phys. Chem. B 2006, 110, 6405-6414. (68) Pecul, M.; Ruud, K. In Advances in Quantum Chemistry, Vol. 50: Response Theory and Molecular Properties (a Tribute to Jan Linderberg and Poul Jørgensen); Jensen, H. J. A., Ed.; Academic Press: London, 2005, pp 185-212. TOC GRAPHICS

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Chemical structure and main geometric parameters of austdiol (1). 101x125mm (300 x 300 DPI)

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Experimental and PBE0/TZ2P/IEFPCM calculated ECD spectra of austdiol in methanol, as obtained after standard B97D/TZ2P/IEFPCM optimization. 63x48mm (300 x 300 DPI)

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Dependence of calculated [α]D values in methanol (PBE0/TZ2P/IEFPCM) upon the rotation of the α-hydroxyl group of conformer 1.01, as obtained by B97D/TZ2P/IEFPCM conformational scan. 78x75mm (300 x 300 DPI)

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Dihedral distribution functions (DDF) for the dihedral angles of austdiol in methanol obtained by conformational analysis on the OPLS-AA and AIMD trajectories. 44x11mm (300 x 300 DPI)

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Experimental and PBE0/TZ2P/IEFPCM calculated ECD spectra of austdiol in methanol, averaged over 100 solvation clusters taken from the AIMD trajectory. 63x48mm (300 x 300 DPI)

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