Influence of the Protein Environment on the Electronic Excitation of

Feb 13, 2019 - Chromophores in the Phycoerythrin 545 Light−Harvesting Complex: A Combined MD-QM/MM Method with Polarized Protein−Specific...
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Influence of the Protein Environment on the Electronic Excitation of Chromophores in the Phycoerythrin 545 Light-Harvesting Complex: A Combined MD-QM/MM Method with Polarized Protein-Specific Charge Scheme Zhengqing Tong, Zhe Huai, Ye Mei, and Yan Mo J. Phys. Chem. B, Just Accepted Manuscript • DOI: 10.1021/acs.jpcb.8b11764 • Publication Date (Web): 13 Feb 2019 Downloaded from http://pubs.acs.org on February 14, 2019

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Influence of the Protein Environment on the Electronic Excitation of Chromophores in the Phycoerythrin 545 Light–Harvesting Complex: A Combined MD–QM/MM Method with Polarized Protein–Specific Charge Scheme Zhengqing Tong,† Zhe Huai,† Ye Mei,†,‡,¶ and Yan Mo∗,†,‡,¶ †State Key Laboratory of Precision Spectroscopy, School of Physics and Materials Science, East China Normal University, Shanghai 200062, China ‡NYU-ECNU Center for Computational Chemistry at NYU Shanghai, Shanghai 200062, China ¶Collaborative Innovation Center of Extreme Optics, Shanxi University, Taiyuan, Shanxi 030006, China E-mail: [email protected]

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Abstract To gain better insight into how the fluctuating protein environment influences the site energy ordering of the chromophores in PE545 light–harvesting antenna system, we carried out quantum–mechanics/molecular–mechanics (QM/MM) calculations along the molecular dynamics (MD) trajectory. The Polarized Protein–specific Charge (PPC) scheme was adopted in both the MD simulation and the QM/MM calculations for a more realistic description of the protein environment. The deduced site energy ladder calculated using ZINDO/S-CIS agrees well with the best model extracted from experiments by a simultaneous fit of the steady-state spectra and transient absorption spectra. Three combinations of charge schemes were compared to elucidate how the protein environment modulates the site energy of chromophores. The result indicates that the multi–roles that the protein environment is playing, for instance, by fine-tuning of the conformation of chromophores or by specific pigment–protein interactions, are both crucial for site energy arrangement. Furthermore, we investigated the effects of individual environments and found that the polar residues and water molecules contribute most to the energy shifts.

Introduction During the light–harvesting process, solar energy is captured by light–harvesting complex and then transferred to the reaction center, where the energy is converted into more stable chemical energy for life. Recent studies suggest that the dynamic protein environment might play an essential role in modulating the excitation energy transfer process, enables the pigment–protein complex to achieve remarkably high efficiency. 1–3 Understanding how the protein environment modulates the excitation of chromophores and excitation energy transfer (EET) process has become a vibrant research topic of increasing interest, especially after the observation of quantum beats in the natural light–harvesting complex at ambient temperature. 4,5 PE545 is a water–soluble pigment–protein complex extracted from

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the marine cryptophyte Rhodomonas CS24. The PE545 consists of four polypeptide chains that assemble into α1 α2 ββ heterodimeric form, as illustrated in Fig. 1a. It contains eight bilins, which are linear tetrapyrrole chromophores covalently linked to the protein scaffold. One 15, 16-dihydrobiliverdin (DBV) binds to each α–subunit, and three phycoerythrobilins (PEBs) bind to each β–subunit. The chemical structures of the three types of bilins are shown in Fig. 1b. It is capable of capturing the solar energy at low light intensities and facilitates the excitation energy transfer with very high quantum efficiency. 6 It serves as an ideal model for the study of the impact of protein scaffold on site energy arrangement due to (i) the variety of pigment composition, (ii) the conformational flexibility of bilins compared to chlorophyll (Chl) and bacteriochlorophyll (BChl), and (iii) the pseudosymmetric organization of eight bilins. Recently, the high–resolution crystal structures of PE545 have been solved by X–ray crystallography, revealing details of the conformation of chromophores and the environment, 7,8 providing a molecular basis for elucidating the mechanism of its astonishing energy transfer efficiency. In theoretical studies, models of light-harvesting and energy transfer through PE545 were constructed simply by fitting the steady–state and time–resolved spectra, 9–11 or by combining those spectroscopic results with quantum chemical calculations. 12–14 Models were also built by combining QM/MM 15,16 calculations with molecule dynamics (MD) simulations to account for the impact of thermal fluctuation of protein scaffold on EET parameters. Further improvements were obtained by incorporating the polarization effects of the environment in the evaluations of site energies, transition dipole moments, and electronic couplings. 17–21 These approaches have been extensively used in the studies of light-harvesting and energy transfer processes in other natural pigment–protein complexes. 16,22–30 Among the energy ladders obtained for PE545, those of QM/MMPol calculations show reasonable agreement with the experimental observations, which highlights the importance of electrostatic polarization effect between the chromophores and the protein environment. Further investigations revealed that the protein environment plays multiple roles in facili-

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tating EET, for example, screening the dipole–dipole interactions between chromophores, 20,31,32 fine–tuning the conformation of chromophores with spatial restraints, and individually shifting the site energy via electrostatic interactions. In the present work, we focus on the latter two roles and study the influence of the protein environment on the electronic excitations of chromophores in the PE545 complex. Thus, a reliable description of the protein environment is crucial. The polarized protein–specific charge scheme (PPC), 33–35 rather than the conventional mean-field charge from a pairwise force field (AMBER), was utilized in both the MD simulations and the subsequent electrostatic embedding QM/MM electronic structure calculations. This approach has been successfully used for the accurate description of another photosynthetic model system and several biological systems. 36–38 In the study of Fenna–Matthews–Olson complex, 28,36 in which the pigments are relatively inflexible, the modulation of site energies was believed to be mainly by the pigment–protein interaction. In addition, the polarized MMs are also essential in MD simulations for taking into account the conformational flexibility of the proteins, water molecules, and other chromophores.

Method System preparation The simulated PE545 system was constructed based on the X–ray crystal structure at ultrahigh (0.97˚ A) resolution (PDB ID: 1XG0). 8 All the ions and crystallographic water molecules were reserved. Hydrogen and missing residues, namely MET 1C, LEU 2C, and ASN 11C were rebuilt using LEaP module of AMBER 14. 39 All-atom AMBER03 force field 40 was applied to the protein and ions. The force field parameters for non–standard residues, namely 5–hydroxylysine (LYZ 4A/B) and N–methyl asparagine (MEN 72C/D) were generated using antechamber with atom types being consistent with the standard AMBER parm94/parm99 force fields. The geometries were then optimized at B3LYP/6–31G* level and the atomic partial charges were obtained by the restrained electrostatic potential (RESP) method 41,42 4

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at the same level in continuous dielectric medium with a dielectric constant of 4, which is consistent with the AMBER03 force field. The atom types and atomic partial charges for non-standard residues were listed in Table S1. To generate force field parameters for the bilins, the bilin chromophores were cut through the Cα –Cβ bond to separate from the protein. Three different cutting schemes were compared in the Supporting Information (see Figs. S1 & S2). The force field parameters for bilins were constructed using the general Amber force field (GAFF). 43 The atomic partial charges for bilins were derived using AM1–BCC charge model. 44 The protonation states of the following residues were manually assigned, using the H++ web server as reference: 45–47 The ASP, GLU, LYS, and ARG residues were in standard ionization states; the HIS 16A/B were protonated at N ; all the bilins were protonated at the nitrogen atom on pyrrole C, as shown in Fig. S3. Finally, the whole system was neutralized by adding one Cl− ion, and solvated in a periodic truncated octahedral TIP3P water box with the distance between the complex and the periodic box boundary no less than 12 ˚ A. To provide a reliable description of protein environments, we followed the same procedure as in Ref. 36. The PPC scheme was adopted in both the MD simulations and the subsequent electronic structure calculations. In this scheme, the electrostatic potential of the whole protein was calculated at B3LYP/6–31G* level by molecular fractionation with conjugate caps method. 37 The atomic partial charges were obtained by delta RESP fitting. 35 The method is consistent with that used in the development of AMBER03 force field and has been proven to be compatible with other AMBER parameters in various studies (cf. the review paper in Ref. 34). More detail description of the PPC fitting procedure can be found in the Supporting Information.

Computational details The system was minimized, and then heated up to 300 K in 300 ps with its total volume fixed. A 1–ns isothermal-isobaric (NPT) equilibrium simulation at 300 K and 1 atm was carried out to relax the system. Subsequently, a 30–ns NPT simulation was carried out 5

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with a 1–fs time step. All the covalent bonds involving hydrogen atoms were constrained by SHAKE algorithm during the simulation. Langevin thermostat 48 with a collision frequency of 1.0 ps−1 and Berendsen’s barostat 49 were used for temperature and pressure regulation. The particle–mesh Ewald 50 with a cutoff of 9 ˚ A in real–space was used to handle long-range electrostatic interaction. Finally, a 200–ps production run with a time step of 1 fs was carried out. Conformations were saved every 5 steps. Totally 40,000 snapshots were collected for the subsequent electronic structure calculations. All the MD simulations were carried out using AMBER 14 package. For the electronic structure calculations, a hybrid QM/MM method was employed. Each chromophore molecule was treated quantum mechanically one–by–one, while the environments, including the proteins, water molecules, and all the other chromophore molecules, were treated as background charges that generate an electric field to polarize the chromophore in question. In order to save the computational effort, we chose the Zerner’s Intermediate Neglect of Differential Overlap with parameters for Spectroscopic properties (ZINDO/S) 51,52 with configuration interaction using single excitations only (ZINDO/S–CIS). To verify the reliability of the ZINDO/S–CIS method, time-dependent density functional theory (TDDFT) calculations were also carried out at ωB97X–D/6–31G* level. Only 25 conformations, which were evenly extracted from the 200-ps MD trajectory, were used in the excitation energy calculations for comparison. The ZINDO/S–CIS and TDDFT calculations were carried out using ORCA 4.0.2 53 and Gaussian 09, 54 respectively. To elucidate how the site energies of the chromophores are modulated by the protein environment, we employed three different combinations of charge schemes: (i) PPC scheme was applied in both the MD simulation and the site energy calculations (denoted as PPC/PPC hereafter), (ii) AMBER charge scheme was applied in both the MD simulation and the site energy calculations (AMBER/AMBER), and (iii) PPC scheme was applied in the MD simulation and the AMBER charge was applied for the subsequent site energy calculations (PPC/AMBER).

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Moreover, in order to elucidate the individual environmental effect on the excitation energy, we performed excitation energy calculations for 10,000 snapshots extracted equally distributed in time (with a time interval of 20 fs), by removing the point charges of atoms from specific environment components, such as the polar residues, the water molecules, and the whole environment.

Results and discussion Validation of MD simulations The MD simulations were examined via structural analyses from several aspects. Shown in Fig. 2a is the root mean square deviations (RMSDs) for the backbone heavy atoms of the protein with respect to the crystal structure. For MD trajectory under PPC, the RMSD reaches a plateau in 5 ns and then fluctuates around 1.10 ˚ A, whereas, under the AMBER charge, the RMSD keeps increasing until it reaches 1.60 ˚ A at 15 ns. The averaged RMSDs of the individual chromophores with respect to the crystal structure are plotted in Fig. 2b, for both PPC and AMBER. It can be seen that the RMSD values under PPC are in the range of 0.8 – 1.3 ˚ A, while those under AMBER charge are in the range of 1.0 – 1.8 ˚ A. Further inspection reveals that some residues, which originally coordinated with bilins, undergo significant conformational changes during the simulation using AMBER charge. According to the crystal structure, a water molecule is hydrogen-bonded to the nitrogen atoms of the two central pyrrole rings (NB and NC ) of both DBVs. This water molecule is then hydrogenbonded to the nearby HIS 16 in the α chain. While the NB and NC of each PEB coordinate with a specific ASP residue (cf. the PEB 158C in Fig. 3a). The distances between NB and NC and their coordinated atoms are averaged over the MD trajectories and are listed in Table 1. It shows that all these coordinations remained stable during the MD simulation with PPC. While during the MD simulation with AMBER charge, some of the coordinations broke up rapidly. For instance, the distances between NB /NC of PEB 158C and OD2 of ASP 39C 7

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increases dramatically in 1 ns, as shown in Fig. 3b and Fig. S4. Moreover, the interactions between the PEB 50/61 chromophores and its local environments in two α chains are quite different, due to the asymmetry of the α chains. As depicted in Fig. 3c, the propionate side-chain in pyrrole ring B of PEB 50/61D strongly interacts with GLN 148C. But PEB 50/61C is not in van der Waals–contact with GLN 148D. The distance between CGB of propionate side-chain, which linked to pyrrole B of PEB 50/61D, and NE2 of GLN 148C is very stable in the whole simulation under PPC, as shown in Fig. 3d. However, it broke up quickly under AMBER charge (as shown in Fig. S5). Therefore, it can be inferred that the whole system remains stable under PPC scheme. It thus provides a more realistic structural ensemble, which is critical for the subsequent electronic structure calculations.

Site energy Based on the Frenkel exciton model, the dynamics of excitation energy of the natural lightharvesting system is mainly determined by the site energies of chromophores, their electronic couplings and the spectral density that describes pigment–protein interactions. Note that the QM method we chose for site energy calculations is the semi-empirical method, ZINDO/S–CIS, which is relatively inexpensive computationally. Although this method has been extensively used in the evaluation of site energies for various photosynthetic systems, a higher–level QM method was used for the site energy calculations on 25 selected MD conformations of PE545 to validate those obtained by ZINDO/S-CIS. The results from TDDFT (ωB97X–D/6–31G*) calculations are shown in Fig. S6, in comparison with those obtained from ZINDO/S calculations. It is worth mentioning that what we focus here is the relative energy ordering of the eight chromophores. Thus, although the MD–averaged site energies obtained from ZINDO/S–CIS calculations are relatively lower than those from TDDFT calculations, the energy ladders agree well with each other. Unless stated otherwise, all the analyses were based on the calculations at ZINDO/S level hereafter. The averaged site energies and transition dipole moments for each chromophore are tab8

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ulated in Table 2. Our calculations show that the two DBVs exhibit the lowest site energies, owing to the additional conjugation in pyrrole ring A. It makes them the candidates of energy trap. This result is consistent with previous studies. 12,16,20,21 The PEB 50/61D has the highest site energy, which is also consistent with the experimental observation. 12 The transition dipole moment averaged over eight chromophores is 11.64D, which agrees well with the experimental measurement of 11.25D. 13 The obtained site energy ladder is compared to those obtained from previous studies, as shown in Fig. 4. The one with blue squares is the best model fitted from steady-state and time-resolved spectra, proposed by Novoderezhkin et al. 12 . The site energies obtained by Agthar et al. (purple diamonds) combines the QM/MM method with classical MD simulation, 16 whereas the results by Curutchet et al. (green triangles) incorporates the polarizable effects of protein environment and water, with minor adjustment according to the experimental spectra. 19 It should be noted that the absolute value of site energy varies from method to method. Taking into account the polarization effect results in an overall redshift of the site energies. It can be seen that the relative site energy ordering of our work (red circles) show a similar trend to the experimental fitting result. The difference between these two energy sets is the absolute energy value and slightly smaller energy spread of our work. The two DBVs are the red-most chromophores in all four studies, due to the extra double bond in pyrrole ring A. The major difference among those energy sets is that PEB 50/61C possesses the highest site energy in Curutchet et al.’s work, whereas PEB 50/61D possesses the highest site energy in the current work and other two works.

The impact of fluctuating environments on Excitation energy It has been shown that the protein environment may play an important role in facilitating light–harvesting and energy transfer processes. 3,20,25,26,36 Especially for PE545 complex we interested, the energy tuning by the protein scaffold is suggested to be much more complicated due to its structural characteristics. In addition, there is a cavity filled with ordered 9

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water molecules between two αβ monomers, leading to a polar environment. To get a better understanding of how the protein environment modulates the site energies of chromophores, comparisons are made among three combinations of charge schemes as described in the previous section (shown in Fig. 5). It can be seen that simply replacing PPC with AMBER charge in site energy calculations with conformations collected along the MD simulation with PPC does not make much difference. Both of the two schemes predict a reasonable site energy ladder, in good agreement with experimental observations. But the site energy arrangement obtained by AMBER/AMBER exhibit a large deviation from the other two. It has a much narrower distribution and the differences among these six PEB chromophores were smoothed out during the MD simulation. This is because the conventional mean–field charge scheme failed to provide a reliable structural ensemble. From this point of view, it can be concluded that adopting PPC scheme in the MD simulation is essential to provide a reliable conformation ensemble for subsequent electronic calculations. Furthermore, we studied in detail the effect of specific components of local environments, i. e., water and polar residues in particular, on the site energies of each chromophores (as shown in Fig. 6). It can be seen that the influences of water and polar residues on the DBV pair are roughly of the same magnitude, so are the PEB 82 pair. Thus the overall effect of water and polar residues for these two pairs are also similar. For instance, water and polar residues together lower the site energies by about 0.01 eV for DBV pair and 0.12 eV for PEB 82 pair, respectively. However, the individual effects on the other two pseudosymmetric pairs, PEB 50/61 pair or PEB 158 pair, are quite different. These differences arise from their asymmetric local environment, namely the different sequence of the α chains. 8 The central 50/61 pair locates at the surface of the water cavity between two αβ monomers. The PEB 50/61C is closely packed by the A and C chains (cf. Fig. S7), whereas the PEB 50/61D is more exposed to the solvent. By averaging over the MD trajectory, we found that the number of water molecules within 3.5 ˚ A of PEB 50/61D is 18.9, while those of PEB 50/61C is only 12.5. Similarly, the PEB 158 pair that resides at the edge of water slot also have

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asymmetric local environments, for instance, PEB 158D is in the vicinity of the extra loop of the α chain A. Thus it experiences a more remarkable energy shift while including the polar residues as shown in Fig. S8. Shown in Fig. 7 are the calculated site energies with or without the MM charges, for the crystal structure, the optimized structure (energy minimization from the crystal structure) and the ensemble average over the MD trajectory, respectively. PPC is adopted. Firstly, we compare the three sets of site energies in the absence of the polarization from the environment (dotted lines). In this case, the energy differences are mostly originated from the conformational differences. It can be seen that the site energies from the crystal structure are much higher than others. This may be caused by distortions in their structures. The six PEBs show widely distributed site energies. After minimization, the energy differences among PEBs are largely smoothed out. And the ensemble averaged curve shows that the site energies of PEBs are almost the same, with PEB 50/61C being the only exception. The smoothing of conformational difference might originate from the dynamical tuning by protein environment or the biased force field. The conformational differences between each chromophore pair from the crystal structure are shown in Fig. 8a, while those from MD are shown in Fig. 8b. It is worth noted that the major differences between each pair of chromophores can be characterized by four torsion angles as illustrated in Fig. 1c. τB and τC define the relative orientations of the propionate side–chains linked to the two central pyrrole rings B and C, respectively. τAB describes the torsion angle between the pyrrole rings A and B, while τBC is the torsion angle between the pyrrole rings B and C. The MD–averaged torsion angles and the corresponding standard deviations are listed in Table 3. Those from the crystal structure are shown in parentheses. It can be seen that τAB and τBC fluctuate around their corresponding values in the crystal structure. There are only minor changes in the values of τAB and τBC . The most significant changes of τAB are about 17 ∼ 21◦ for the PEB 50/61D, PEB 50/61C and PEB 158C. In contrast, the values of τB and τC for some chromophores are significantly changed while including the dynamical effects of local

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environments. For DBV pair, although the τC s are remarkably changed, their conformations remain symmetric during the MD simulation. For PEB 82 pair, the conformations also remain symmetric. Thus the slight energy differences between these two pairs mainly come from the electrostatic interactions with their local environments. However, the conformation difference of PEB 158 pair is greatly smoothed out during the MD simulation. Hence the energy difference mostly originates from the highly asymmetric environment. Remarkably, the PEB 50/61 pair maintains highly asymmetric conformations, which can explain the relatively lower energy that PEB 50/61C possess. The conformational asymmetry of the PEB 50/61 pair lies in the relative orientation of the propionate side–chain. Finally, all MM effects are taken into account and give a reasonable energy ladder. That is, pigment–protein interactions are essential to determine the energetic ordering, hence play an important role in facilitating the EET. In conclusion, the excitation state of chromophores are determined by their own configurations, especially the orientations of the propionate side-chains in ring B, and the electrostatic interaction of environment also has great influence on the distribution of site energies. Thus, it is crucial to give a reliable description of the protein environment not only for sampling a reasonable conformational ensemble but also for accurately accounting for the pigment–protein interaction.

Conclusion To investigate how the dynamic environment modulates the excitation energies of individual chromophores, we have carried out electronic structure calculations at a QM/MM level of theory over the configurations sampled from MD simulations. The PPC scheme was adopted not only in the QM/MM calculations to provide a more realistic description of electrostatic pigment–protein interactions, but also in the MD simulation stage that allows us to sample a more reliable conformational ensemble. The result shows that the whole

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complex remains stable during MD simulation under PPC, while the MD simulation under the AMBER mean–field charge scheme shows that part of the complex experiences dramatic conformational changes. The site energy ladder obtained in this work is in good agreement with the one obtained by fitting the experimental spectra. Upon further analysis of the electronic calculations based on the whole complex with atomic detail, we found that the site energy tuning of each chromophore is mainly due to the spatial constraint of conformational flexibility by the protein scaffold, the electrostatic interaction between each chromophore and its local environment, especially the polar environment. In contrast to the previous study, which suggests that the former one is the key factor, our present work indicates that both factors are critical to the determination of the energy ordering and, hence, the efficient energy transfer characteristics of PE545 light–harvesting complex. Furthermore, we examined the specific components of the environment and found that asymmetric local environments are responsible for a wide range of energy shifts. This allows the bilins to harvest a broad range of solar energy compared to the Chl– and BChl–containing light harvesting complexes.

Supporting Information Available Force field parameters for non–standard residues, validation of the cutting scheme for bilin chromophores and QM method we adopted, the local environment and the pigment–protein interactions for specific pseudosymmetric pairs, comparison of PPC and Amber charge schemes, are available in the Supporting Information.

Acknowledgement This work is supported by the National Natural Science Foundation of China (Grant No. 21203064 and 21773066) and the Fundamental Research Funds for the Central Universities. We thank Prof. Y. J. Yan for helpful discussion. We also thank the Supercomputer Center of East China Normal University for CPU time support. 13

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References (1) Adolphs, J.; M¨ uh, F.; Madjet, M. E.-A.; Renger, T. Calculation of Pigment Transition Energies in the FMO Protein. Photosynth. Res. 2008, 95, 197–209. (2) Rivera, E.; Montemayor, D.; Masia, M.; Coker, D. F. Influence of Site-dependent Pigment-Protein Interactions on Excitation Energy Transfer in Photosynthetic Light Harvesting. J. Phys. Chem. B 2013, 117, 5510–5521. (3) Zhang, L.; Silva, D.-A.; Zhang, H. D.; Yue, A.; Yan, Y. J.; Huang, X. Dynamic Protein Conformations Preferentially Drive Energy Transfer along the Active Chain of the Photosystem II Reaction Centre. Nat. Commun. 2014, 5, 4170. (4) Engel, G. S.; Calhoun, T. R.; Read, E. L.; Ahn, T.-K.; Man˘cal, T.; Cheng, Y.-C.; Blankenship, R. E.; Fleming, G. R. Evidence for Wavelike Energy Transfer through Quantum Coherence in Photosynthetic Systems. Nature 2007, 446, 782–786. (5) Lee, H.; Cheng, Y.-C.; Fleming, G. R. Coherence Dynamics in Photosynthesis: Protein Protection of Excitonic Coherence. Science 2007, 316, 1462–1465. (6) Collini, E.; Wong, C. Y.; Wilk, K. E.; Curmi, P. M. G.; Brumer, P.; Scholes, G. D. Coherently Wired Light-Harvesting in Photosynthetic Marine Algae at Ambient Temperature. Nature 2010, 463, 644–647. (7) Wilk, K. E.; Harrop, S. J.; Jankova, L.; Edler, D.; Keenan, G.; Sharples, F.; Hiller, R. G.; Curmi, P. M. G. Evolution of a Light-Harvesting Protein by Addition of New Subunits and Rearrangement of Conserved Elements: Crystal Structure of a Cryptophyte Phycoerythrin at 1.63-˚ A Resolution. Proc. Natl. Acad. Sci. USA 1999, 96, 8901–8906. (8) Doust, A. B.; Marai, C. N. J.; Harrop, S. J.; Wilk, K. E.; Curmi, P. M. G.; Scholes, G. D. Developing a Structure-Function Model for the Cryptophyte Phycoerythrin 545 Using 14

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Ultrahigh Resolution Crystallography and Ultrafast Laser Spectroscopy. J. Mol. Biol. 2004, 344, 135–153. (9) MacColl, R.; Lam, I.; Choi, C. Y.; Kim, J. Exciton Splitting in Phycoerythrin 545. J. Biol. Chem. 1994, 269, 25465–25469. (10) MacColl, R.; Eisele, L. E.; Dhar, M.; Ecuyer, J.-P.; Hopkins, S.; Marrone, J.; Barnard, R.; Malak, H.; Lewitus, A. J. Bilin Organization in Cryptomonad Biliproteins. Biochemistry 1999, 38, 4097–4105. (11) MacColl, R.; Eisele, L. E.; Marrone, J. Fluorescence Polarization Studies on Four Biliproteins and a Bilin Model for Phycoerythrin 545. BBA-Bioenergetics 1999, 1412, 230–239. (12) Novoderezhkin, V. I.; Doust, A. B.; Curutchet, C.; Scholes, G. D.; van Grondelle, R. Excitation Dynamics in Phycoerythrin 545: Modeling of Steady-State Spectra and Transient Absorption with Modified Redfield Theory. Biophys. J. 2010, 99, 344–352. (13) Doust, A. B.; Wilk, K. E.; Curmi, P. M.; Scholes, G. D. The Photophysics of Cryptophyte Light-Harvesting. J. Photoch. Photobio. A 2006, 184, 1–17. (14) Novoderezhkin, V. I.; van Grondelle, R. Physical Origins and Models of Energy Transfer in Photosynthetic Light-Harvesting. Phys. Chem. Chem. Phys. 2010, 12, 7352–7365. (15) Aghtar, M.; Kleinekath¨ofer, U. Environmental Coupling and Population Dynamics in the PE545 Light-Harvesting Complex. J. Lumin. 2016, 169, 406–409. (16) Aghtar, M.; Str¨ umpfer, J.; Olbrich, C.; Schulten, K.; Kleinekath¨ofer, U. Different Types of Vibrations Interacting with Electronic Excitations in Phycoerythrin PE545 and Fenna-Matthews-Olson Antenna Systems. J. Phys. Chem. Lett. 2014, 5, 3131–3137. (17) Kaukonen, M.; S¨oderhjelm, P.; Heimdal, J.; Ryde, U. Proton Transfer at Metal Sites in

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Proteins Studied by Quantum Mechanical Free-Energy Perturbations. J. Chem. Theory Comput. 2008, 4, 985–1001. (18) Curutchet, C.; Mu˜ noz Losa, A.; Monti, S.; Kongsted, J.; Scholes, G. D.; Mennucci, B. Electronic Energy Transfer in Condensed Phase Studied by a Polarizable QM/MM Model. J. Chem. Theory Comput. 2009, 5, 1838–1848. (19) Curutchet, C.; Novoderezhkin, V. I.; Kongsted, J.; Mu˜ noz Losa, A.; van Grondelle, R.; Scholes, G. D.; Mennucci, B. Energy Flow in the Cryptophyte PE545 Antenna Is Directed by Bilin Pigment Conformation. J. Phys. Chem. B. 2013, 117, 4263–4273. (20) Curutchet, C.; Kongsted, J.; Mu˜ noz Losa, A.; Hossein-Nejad, H.; Scholes, G. D.; Mennucci, B. Photosynthetic Light-Harvesting Is Tuned by the Heterogeneous Polarizable Environement of the Protein. J. Am. Chem. Soc. 2011, 133, 3078–3084. (21) Aghtar, M.; Kleinekath¨ofer, U.; Curutchet, C.; Mennucci, B. Impact of Electronic Fluctuations and Their Description on the Exciton Dynamics in the Light-Harvesting Complex PE545. J. Phys. Chem. B. 2017, 121, 1330–1339. (22) Kolli, A.; O’Reilly, E. J.; Scholes, G. D.; Olaya-Castro, A. The Fundamental Role of Quantized Vibrations in Coherent Light Harvesting by Cryptophyte Algae. J. Chem. Phys. 2012, 137, 174109. (23) Hossein-Nejad, H.; Curutchet, C.; Kubica, A.; Scholes, G. D. Delocalization-Enhanced Long-Range Energy Transfer between Cryptophyte Algae PE545 Antenna Proteins. J. Phys. Chem. B. 2011, 115, 5243–5253. (24) Mirkovic, T.; Doust, A. B.; Kim, J.; Wilk, K. E.; Curutchet, C.; Mennucci, B.; Cammi, R.; Curmi, P. M. G.; Scholes, G. D. Ultrafast Light Harvesting Dynamics in the Cryptophyte Phycocyanin 645. Photochem. Photobiol. Sci. 2007, 6, 964–975.

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(25) Viani, L.; Curutchet, C.; Mennucci, B. Spatial and Electronic Correlations in the PE545 Light-Harvesting Complex. J. Phys. Chem. Lett. 2013, 4, 372–377. (26) Viani, L.; Corbella, M.; Curutchet, C.; O’Reilly, E. J.; Olaya-Castro, A.; Mennucci, B. Molecular Basis of the Exciton-Phonon Interactions in the PE545 Light-Harvesting Complex. Phys. Chem. Chem. Phys. 2014, 16, 16302–16311. (27) Olbrich, C.; Str¨ umpfer, J.; Schulten, K.; Kleinekath¨ofer, U. Theory and Simulation of the Environmental Effects on FMO Electronic Transitions. J. Phys. Chem. Lett. 2011, 2, 1771–1776. (28) Olbrich, C.; Jansen, T. L. C.; Liebers, J.; Aghtar, M.; Str¨ umpfer, J.; Schulten, K.; Knoester, J.; Kleinekath¨ofer, U. From Atomistic Modeling to Excitation Transfer and Two-Dimensional Spectra of the FMO Light-Harvesting Complex. J. Phys. Chem. B 2011, 115, 8609–8621. (29) Gao, J.; Shi, W.-J.; Ye, J.; Wang, X.; Hirao, H.; Zhao, Y. QM/MM Modeling of Environmental Effects on Electronic Transitions of the FMO Complex. J. Phys. Chem. B 2013, 117, 3488–3495. (30) Chandrasekaran, S.; Pothula, K. R.; Kleinekath¨ofer, U. Protein Arrangement Effects on the Exciton Dynamics in the PE555 Complex. J. Phys. Chem. B. 2017, 121, 3228–3236. (31) Curutchet, C.; Scholes, G. D.; Mennucci, B.; Cammi, R. How Solvent Controls Electronic Energy Transfer and Light Harvesting: Toward a Quantum-Mechanical Description of Reaction Field and Screening Effects. J. Phys. Chem. B 2007, 111, 13253–13265. (32) Scholes, G. D.; Curutchet, C.; Mennucci, B.; Cammi, R.; Tomasi, J. How Solvent Controls Electronic Energy Transfer and Light Harvesting. J. Phys. Chem. B 2007, 111, 6978–6982.

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(33) Ji, C.; Mei, Y.; Zhang, J. Z. H. Developing Polarized Protein-Specific Charges for Protein Dynamics: MD Free Energy Calculation of pKa Shifts for Asp26/Asp20 in Thioredoxin. Biophys. J. 2008, 95, 1080–1088. (34) Ji, C.; Mei, Y. Some Practical Approaches to Treating Electrostatic Polarization of Proteins. Accounts Chem. Res. 2014, 47, 2795–2803. (35) Zeng, J.; Duan, L.; Zhang, J. Z. H.; Mei, Y. A Numerically Stable Restrained Electrostatic Potential Charge Fitting Method. J. Comput. Chem. 2013, 34, 847–853. (36) Jia, X.; Mei, Y.; Zhang, J. Z. H.; Mo, Y. Hybrid QM/MM Study of FMO Complex with Polarized Protein-Specific Charge. Sci. Rep. 2015, 5, 17096. (37) Zhang, D. W.; Xiang, Y.; Zhang, J. Z. H. New Advance in Computational Chemistry: Full Quantum Mechanical ab Initio Computation of Streptavidin-Biotin Interaction Energy. J. Phys. Chem. B 2003, 107, 12039–12041. (38) Mei, Y.; Li, Y. L.; Zeng, J.; Zhang, J. Z. H. Electrostatic Polarization is Critical for the Strong Binding in Streptavidin-Biotin System. J. Comput. Chem. 2012, 33, 1374–1382. (39) Case, D. A.; Berryman, J. T.; Betz, R. M.; Cerutti, D. S.; Cheatham, T. E., III; Darden, T. A.; Duke, R. E.; Giese, T. J.; Gohlke, H.; Goetz, A. W. et al. AMBER 2015, University of California, San Francisco. 2015. (40) Duan, Y.; Wu, C.; Chowdhury, S.; Lee, M. C.; Xiong, G.; Zhang, W.; Yang, R.; Cieplak, P.; Luo, R.; Lee, T. et al. A Point-Charge Force Field for Molecular Mechanics Simulations of Proteins Based on Condensed-Phase Quantum Mechanical Calculations. J. Comput. Chem. 2003, 24, 1999–2012. (41) Cieplak, P.; Cornell, W. D.; Bayly, C.; Kollman, P. A. Application of the Multimolecule and Multiconformational RESP Methodology to Biopolymers: Charge Derivation for DNA, RNA, and Proteins. J. Comput. Chem. 1995, 16, 1357–1377. 18

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(42) Bayly, C. I.; Cieplak, P.; Cornell, W.; Kollman, P. A. A Well-Behaved Electrostatic Potential Based Method Using Charge Restraints for Deriving Atomic Charges: The RESP Model. J. Phys. Chem. 1993, 97, 10269–10280. (43) Wang, J.; Wolf, R. M.; Caldwell, J. W.; Kollman, P. A.; Case, D. A. Development and Testing of a General AMBER Force Field. J. Comput. Chem. 2004, 25, 1157–1174. (44) Jakalian, A.; Bush, B. L.; Jack, D. B.; Bayly, C. I. Fast, Efficient Generation of HighQuality Atomic Charges. AM1-BCC Model: I. Method. J. Comput. Chem. 2000, 21, 132–146. (45) Anandakrishnan, R.; Aguilar, B.; Onufriev, A. V. H++ 3.0: Automating pK Prediction and the Preparation of Biomolecular Structures for Atomistic Molecular Modeling and Simulation. Nucleic. Acids. Res. 2012, 40, W537–W541. (46) Myers, J.; Grothaus, G.; Narayanan, S.; Onufriev, A. A Simple Clustering Algorithm Can be Accurate Enough for Use in Calculations of pKs in Macromolecules. Proteins 2006, 63, 928–938. (47) Onufriev, A.; Gordon, J. C.; Myers, J. B.; Heath, L. S.; Folta, T.; Shoja, V. H++: A Server for Estimating pKas and Adding Missing Hydrogens to Macromolecules. Nucleic. Acids. Res. 2005, 33, W368–W371. (48) Langevin, P. Sur la Th´eorie du Mouvement Brownien. C. R. Acad. Sci. (Paris) 1908, 146, 530–533. (49) Berendsen, H. J. C.; Postma, J. P. M.; van Gunsteren, W. F.; DiNola, A.; Haak, J. R. Molecular Dynamics with Coupling to an External Bath. J. Chem. Phys. 1984, 81, 3684–3690. (50) Darden, T.; York, D.; Pedersen, L. Particle Mesh Ewald: An N·log(N) Method for Ewald Sums in Large Systems. J. Chem. Phys. 1993, 98, 10089–10092. 19

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(51) Ridley, J.; Zerner, M. An Intermediate Neglect of Differential Overlap Technique for Spectroscopy: Pyrrole and the Azines. Theor. Chem. Acta. 1973, 32, 111–134. (52) Thompson, M. A.; Zerner, M. C. A Theoretical Examination of the Electronic Structure and Spectroscopy of the Photosynthetic Reaction Center from Rhodopseudomonas Viridis. J. Am. Chem. Soc. 1991, 113, 8210–8215. (53) Petrenko, T.; Neese, F. Analysis and Prediction of Absorption Band Shapes, Fluorescence Band Shapes, Resonance Raman Intensities, and Excitation Profiles Using the Time-Dependent Theory of Electronic Spectroscopy. J. Chem. Phys. 2007, 127, 164319. (54) Frisch, M. J.; Trucks, G. W.; Schlegel, H. B.; Scuseria, G. E.; Robb, M. A.; Cheeseman, J. R.; Scalmani, G.; Barone, V.; Mennucci, B.; Petersson, G. A. et al. Gaussian 09, Revision B.01, Gaussian, Inc.: Wallingford, CT. 2010.

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(a)

(b)

chain A

DBV 19 α

chain D

DBV 19A

PEB 82D

COOH

S

PEB 50/61D

PEB 158C

HOOC

CYS

O

A

B

C

N H

N H

N

H

D N H

O

PEB 158 β , 82 β PEB 158D

PEB 50/61C

HOOC

CYS

COOH

S

chain C

PEB 82C

DBV 19B

chain B

(c)

HOOC

N H

B

τAB

N H

C

τBC

C

N H

N

N

HOOC

CYS

τC

H

D O

N H

H

D

A

O

N H

COOH

CYS

S

R"

A

B

PEB 50/61β

R'

O

N H

COOH

τB

H

A O

O

N H

S

H

B

C

N H

N

H

D N H

O

Figure 1: (a) Structure of PE545 complex based on the crystal structure. The four subunits are colored with green, cyan, magenta and yellow, respectively. (b) The chemical structures of the three types of bilins. (c) Schematic diagram of the linear tetrapyrrole arrangement of bilins. The four dihedral angles characterize the conformational flexibility of bilins.

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(a)

2.5

PPC AMBER

RMSD (Å)

2

1.5

1

0.5

0

(b)

5

10

15 Time (ns)

20

25

2 .5

30

PPC AMBER

2

RMSD (Å)

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

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1 .5

1

0 .5

0

19A

19B

50/61C

158C

82C

50/61D

158D

82D

Figure 2: (a) RMSD of the protein backbone along MD simulations using PPC (red) and AMBER charge (green), respectively. (b) Average RMSDs of the individual chromophores. The standard deviations are indicated with error bars.

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(b)

(a) (a) PEB 158C

Distance (Å)

C

B

D

A

10

NB - OD2 NC - OD2

8

6

4

2 ASP 39C

0

5

10

(d)

(c)

15 Time (ns)

20

14

25

30

PPC AMBER

PEB 50/61C

12 GLN 148C B

ARG 129C C

10

A

D D A

Distance (Å)

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

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C

8 6

B

4

PEB 50/61D GLN 148D

2

ARG 129D

0

5

10

15 Time (ns)

20

25

30

Figure 3: (a) The interaction between two central nitrogen atoms (NB and NC ) of PEB 158C and ASP 39C. (b) Temporal evolution of the distances between NB (purple) and NC (blue) of PEB 158C and their originally coordinated atom, OD2 of ASP 39C, along the trajectories under AMBER charge. (c) The asymmetric interactions between the protein and the propionate side-chain of pyrrole B of PEB50/61 pair. (d) Temporal evolution of the distances between CGB of propionate side-chain linked to the pyrrole B of PEB 50/61D and its originally coordinated atom (NE2 of GLN 148C) along the MD trajectories under both PPC (red) and AMBER charge (green).

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2.6

2.4

Site energy (eV)

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

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2.2

2

Our work PPC Aghtar et al. QM/MM Curutchet et al. QM/MMPol Novoderezhkin et al. Mode E

1.8

1.6

19A

19B

50/61C

158C

82C

50/61D

158D

82D

Figure 4: Comparison of site energy ladder obtained in this work (red circles) with previous results from Agthar et al. 16 (purple diamonds), Curutchet et al. 19 (green triangles) and Novoderezhkin et al. 12 (blue squares).

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2.1

2.05

Site energy (eV)

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

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2

1.95

1.9

1.85

PPC/PPC PPC/AMBER AMBER/AMBER 19A

19B

50/61C

158C

82C

50/61D 158D

82D

Figure 5: The site energies for three combinations of charge schemes: PPC/PPC (red circles), AMBER/AMBER (green squares) and PPC/AMBER (blue diamonds).

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0 .1 2

water polar residues

0 .0 8

Δ E (E_Vac-Env)

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

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0 .0 4

0

-0 .0 4

19A

19B

50/61C 50/61D

158C

158D

82C

82D

Figure 6: Electrostatic polarization effect of water (red) and polar residues (green) on the site energy of each chromophore.

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2 .4

2 .3

Site energy (eV)

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crystal_MM(PPC) crystal_w/o MM optimized_MM(PPC) optimized_w/o MM MD_MM(PPC) MD_w/o MM

2 .2

2 .1

2

1 .9

19A

19B

50/61C 50/61D

158C

158D

82C

82D

Figure 7: The site energies of chromophores calculated with MM (PPC, solid lines) or without MM (w/o MM, dotted lines) base on crystal structure (green circles), the optimized structure (blue squares) and conformations extracted from MD trajectory under PPC (red triangles), respectively.

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(a)

DBV 19

PEB 50/61

PEB 158

PEB 82

(b) DBV 19

PEB 50/61

PEB 158

PEB 82

Figure 8: Conformations of each chromophore pairs (a) based on the crystal structure, (b) based on a selected conformation from MD simulation under PPC. For each chromophore pair, the chromophore linked to chain A/C is shown in green and linked to chain B/D is shown in pink.

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The Journal of Physical Chemistry

Table 1: The averaged distances between two central nitrogen atoms (NB and NC ) of each chromophores and their coordinated atoms for each chromophore (˚ A). In the case of DBVs, the coordinated water molecule is also hydrogen-bonded to a corresponding HIS. The averaged distances between OW and NHIS are also listed.

AMBER PPC

NHIE -OW 2.89 2.81

AMBER PPC

NHIE -OW 2.89 2.81

DBV 19A NB -OW 2.92 2.94 DBV 19B NB -OW 2.90 2.94

NC -OW 2.93 2.93 NC -OW 2.93 2.90

PEB 50/61C NB -OD2 NC -OD2 2.73 2.82 2.67 2.68 PEB 50/61D NB -OD2 NC -OD2 2.74 2.84 2.73 2.70

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PEB 158C NB -OD2 NC -OD2 5.25 5.42 2.71 2.73 PEB 158D NB -OD2 NC -OD2 2.84 2.83 2.69 2.69

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PEB 82C NB -OD2 NC -OD2 2.88 2.81 2.70 2.70 PEB 82D NB -OD2 NC -OD2 2.88 2.81 2.74 2.70

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Table 2: The site energies in units of eV, the transition dipole moments (TDM) in units of Debye for the individual chromophores, and the TDM averaged over eight chromophores. The experimentally measured TDM is shown in boldface. 13 DBV 19A

DBV 19B

PEB 50/61C

PEB 158C

PEB 82C

PEB 50/61D

PEB 158D

PEB 82D

site energy

1.879

1.893

1.997

2.016

1.980

2.064

1.981

2.001

TDM

12.68

12.97

11.09

11.49

11.22

10.87

11.51

11.27

averaged TDM (expt.)

11.64 (11.25)

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The Journal of Physical Chemistry

Table 3: The MD-averaged dihedral angles (as illustrated in Fig. 1(c)) and their standard deviations. The values in parentheses are the corresponding values from the crystal structure.

19A 19B 50/61C 50/61D 158C 158D 82C 82D

τB

τC

τAB

τBC

-50.8±7.6 (-55.0) -54.5±9.4 (-54.9) 167.9±8.7 (176.4) -58.5±11.2 (-70.1) -167.7±9.2 (-67.0) -167.3±9.6 (68.4) -171.8±5.9 (-179.5) 172.5±5.8 (173.7)

170.8±9.6 (78.7) 163.5±11.9 (76.4) 167.5±8.5 (176.0) 170.5±7.3 (178.1) 69.7±8.9 (69.8) 65.0±8.9 (-62.6) 63.7±19.5 (60.3) 61.7±15.8 (57.5)

24.3±8.0 (31.4) 17.0±10.0 (33.1) 25.6±7.5 (42.2) 25.4±8.2 (46.7) -25.9±7.7 (-43.5) -25.5±7.5 (-33.8) -14.5±8.1 (-23.2) -14.4±7.9 (-22.5)

174.7±4.0 (167.1) 173.0±5.0 (162.0) -174.3±4.4 (-176.3) 174.3±4.3 (-178.1) 174.4±4.1 (179.4) 174.3±4.3 (-178.1) 174.5±4.2 (178.1) 173.5±4.8 (-179.9)

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Graphical TOC Entry chain A

2 .1

chain D

DBV 19A

PEB 82D

2 .0 5

PEB 50/61D

PEB 158C

PEB 158D

PEB 50/61C

Site energy (eV)

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

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2

1 .9 5

1 .9

chain C

PEB 82C

DBV 19B

1 .8 5

chain B

32

PPC/PPC PPC/AMBER AMBER/AMBER 19A

19B

50/61C 158C

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82C

50/61D 158D

82D