Unravelling ProteinâDNA Interactions at Molecular Level: A DFT and

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Unravelling Protein-DNA Interactions at Molecular Level: A DFT and NCI Study Jorge Gonzalez, Irene Baños, Iker León, Julia Contreras-Garcia, Emilio J. Cocinero, Alberto Lesarri, Jose A. Fernandez, and Judith Millán J. Chem. Theory Comput., Just Accepted Manuscript • DOI: 10.1021/acs.jctc.5b00330 • Publication Date (Web): 14 Jan 2016 Downloaded from http://pubs.acs.org on January 17, 2016

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Journal of Chemical Theory and Computation

Unravelling Protein-DNA Interactions at Molecular Level: A DFT and NCI Study

J. González,1 I. Baños,2 I. León,1 J. Contreras-García,3,4 E.J. Cocinero,1 A. Lesarri,5 J. A. Fernández,*,1 and J. Millán*,2 1

Departamento de Química Física, Facultad de Ciencia y Tecnología, Universidad del País Vasco-UPV/EHU, Barrio Sarriena s/n, Leioa, 48940 Spain. 2

Departamento de Química, Facultad de Ciencias, Estudios Agroalimentarios e Informática, Universidad de La Rioja, Madre de Dios, 53, Logroño, 26006 Spain. 3

Sorbonne Universités, UPMC Univ. Paris 06, UMR7616, Laboratoire de Chimie Théorique, F-75005, Paris, France. 4

CNRS, UMR 7616, Laboratoire de Chimie Théorique, F-75005, Paris, France.

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Departamento de Química Física y Química Inorgánica, Facultad de Ciencias, Universidad de Valladolid, 47011 Valladolid, Spain. e-mail: [email protected] [email protected]

Keywords: DNA, amino acid, molecular structure, DFT, non-covalent interactions, computational chemistry

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ABSTRACT

Histone-DNA interactions were probed computationally at a molecular level, by characterizing the bimolecular clusters constituted by selected amino acid derivatives with polar (asparagine and glutamine), non-polar (alanine, valine and isoleucine) and charged (arginine) side chains and methylated pyrimidinic (1-methylcytosine and 1methylthymine) and puric (9-methyladenine and 9-methylguanine) DNA bases. The computational approach combined different methodologies: a molecular mechanics (MMFFs forced field) conformational search and structural and vibrational densityfunctional calculations (M06-2X with double and triple zeta Pople’s basis sets). In order to dissect the interactions, intermolecular forces were analyzed with the Non-Covalent Interactions (NCI) analysis. The results for the twenty four different clusters studied show a noticeable correlation between the calculated binding energies and the propensities for protein-DNA base interactions found in the literature. Such correlation holded even for the interaction of the selected amino acid derivatives with Watson and Crick pairs.

Therefore, the balance between hydrogen bonds and van der Waals

interactions (specially stacking) in the control of the final shape of the investigated amino acid-DNA base pairs seems to be well reproduced in dispersion-corrected DFT molecular models, reinforcing the idea that the specificity between the amino acids and the DNA bases play an important role in the regulation of DNA.

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INTRODUCTION

Interactions between proteins and DNA are ubiquitous in the cell, and play a crucial role in recognition and synthetic processes, such as protein fabrication or DNA methylation and reparation.1 One of the most puzzling interactions takes place between histones and DNA and is the basis of nucleosome formation,2 the building blocks of the eukaryotic chromatin. Such superstructures are formed by a histone octamer with a superhelix of 146 base pairs of DNA around it, as demonstrated by X-ray studies.3 Apart from having a clear structural function, they play a regulatory role in the expression of DNA2,4,5,6,7 and their structural changes can be inherited by the next generations.8 The mechanism leading to the formation of the histone-DNA complex is not clear. Statistical studies on the contact propensity between the amino acids of the histones and the DNA bases show large variations in the number of contacts between the residue of the amino acids and the nucleobases,9,10,11,12,13,14,15 depending on the nature of the amino acid: those with polar or charged lateral chains present a significantly larger number of contacts than those with non-polar residues.15 Such differences may be pointing to the existence of a specialized language that the histones use to recognize a specific sequence of DNA to interact with. In such case, the sequence of amino acids of the histones would be determined by the DNA segment to which a given histone is designed to bind and its 3D-structure would have evolved to attach to a particular sequence of the DNA strain with which to interact. Using a reductionist approach, it is possible to divide the histone-DNA interactions in amino acid-DNA base pairs, which may be studied in great detail using high-level quantum chemistry procedures. Certainly, the interaction between the two 3



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supermolecules is the result of all the interactions in the individual amino acid-base pairs, which are of weak non-covalent nature (hydrogen bond and van der Waals). However, if this reductionist approach is able to correlate the magnitude and the structure of the individual interactions with the statistical observations, it would demonstrate that the driving forces behind the aggregation of the superstructures have their origin precisely in such individual pairs and determine the large-scale coupling between the two superstructures. In our work we tried to elucidate the role of the polar and non-polar character of the lateral chain in the interaction between the amino acids and the DNA bases. Following these questions, we chose six non-aromatic amino acids, three with non-polar side chains (alanine, valine and isoleucine) and three with polar or charged side chains (asparagine, glutamine and arginine) because they present the lower and higher respectively number of interactions between the amino acids and the base.15 We faced the selected amino acids with the four DNA bases (cytosine, thymine, adenine and guanine) to probe together the role of the amino acid side chain polarity and pyrimidinic/puric character respectively, in the formation of amino acid-DNA base dimers. We introduced a peptide bond on both sides of the amino acid to represent the peptide chain in which the amino acid is immersed and a methyl group in the DNA base to reproduce the nucleoside. The atom labelling for the amino acids (with a side chain R), the definition of the Ramachandran16 torsional angles  and , and the selected DNA

bases

(1-methylcytosine,

1-methylthymine,

9-methyladenine

and

9-

methylguanine) may be found in Scheme 1. Our methodology combined an exhaustive exploration of the conformational landscape of each dimer using molecular mechanics (MM), followed by quantum mechanical 4


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calculations based in density-functional theory (DFT).17-18 Since we are especially interested in highlighting the underlying pattern behind histone-DNA complex formation, we carried out a posteriori analysis of the electron density and its reduced density gradient for the optimized structures.19 The Non-Covalent Interactions (NCI) plots allowed us to characterize the non-covalent interactions in the amino acid-DNA clusters and, in particular, provided a generalization of hydrogen bonds by extending the analysis of electron density not only at the bond critical points, but also on the surrounding regions,20-21 while revealing also the role of van der Waals interactions. We will present the most relevant interactions found for the most stable structure of each of the model systems, focusing on the nature of the binding partners. Our results will demonstrate a correlation between stability of the interacting pairs and the statistics of contacts between histones and DNA, as the bimolecular clusters reproduced satisfactorily the propensities found in protein-DNA complexes. Thus, the reductionist approach could be applied to help understanding the interactions that stabilize proteinDNA interfaces in biological systems.

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METHODS A first exploration of the conformational landscape using the Merck Molecular Mechanics force field (MMFFs)22 was carried out to locate all the relevant structures for each interacting pair within an energy window of 30 kJ mol-1. The conformational map was generated through advanced search algorithms combining Monte Carlo procedures and a “Large-scales Low-Mode” method based in vibrational normal mode analysis, as implemented in Macromodel.23 The DFT calculations used the recent Minnesota functionals developed by Truhlar’s group (M06-2X), that have a broad applicability in Chemistry,24-25 and are specially designed to account for dispersive interactions. Pople’s double- and triple- basis sets with polarization and diffused orbitals (6-31+G(d), 6311++G(d,p)) were used throughout this work, as a compromise between accuracy and speed. Previous experiments proved that this theoretical level is reliable for clusters of sizes similar to the amino acid-DNA base dimers.25-26 All the optimizations were accompanied by normal-mode analysis, as implemented in Gaussian09,27 to confirm that the resulting structures were true minima. The relative energy values given in the present work are zero-point energy (ZPE) corrected. The clusters binding energy values were estimated by subtracting the energy of the components from the cluster’s total energy, correcting the basis set superposition error (BSSE) with the counterpoise method.28 Moreover, the cluster formation induced a significant distortion in the geometry of the amino acids, and therefore the dissociation energy was affected of a difference at least equal to the deformation energy which had to be added in the calculation of the dissociation energy. This deformation energy was calculated as the difference between the energy of the amino acid in the same geometry that it adopts in the cluster and its closest minimum. 6


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An NCI analysis was also carried out on the most stable structure of each amino acid-DNA base cluster investigated. The Non-Covalent Interaction approach evaluates the intermolecular interactions, based on the behaviour of the reduced density gradient, s, with respect to the electron density:

The NCI approach localizes the non-covalent interactions between atoms, which appear as peaks in the s() diagram. These interactions are then classified.19 The limiting cases, i.e., strongly attractive like hydrogen bonds, van der Waals and steric repulsions are reflected here with a coloring scheme (blue, green, red, respectively). The NCI plots were constructed using the NCIPLOT program and their visualization was done with Visual Molecular Dynamics (VMD).29-30 Finally, an estimation of the dispersion energy calculated applying Grimme D3 correction was done for the most stable structures, as performed using Gaussian09.27,31 As M06-2X functional includes dispersion effect, B3LYP and B3LYP-D methods were used to calculate this contribution.

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RESULTS

Following the above-described computational strategy, the constituents of the amino acid-DNA base dimers were first characterized. An exploration of the conformational landscape of the modified amino acids alanine (aA), valine (aV), isoleucine (aI), asparagine (aN), glutamine (aQ) and arginine (aR) was thoroughly carried out in the investigated energy window of 30 kJ mol-1. The amino acids showed a large conformational flexibility: 23 structures were found for aA, 29 for aV, 66 for aI, 51 for aN, 46 for aQ and 44 for aR. For the DNA bases 1-methylcytosine (mC), 1methylthymine (mT), 9-methyladenine (mA) and 9-methylguanine (mG) only the biologically-relevant tautomers were considered. Nevertheless, the conformational search strategy employed for the clusters would allow us to find amino acid-base clusters with a different tautomeric core. A large number of structures (108-407) was then found for each complex within our energy window. As an example, (ball&stick) representation of the 20 most stable structures for each cluster, together with their energetics, can be found in Figures S01S24 (Supporting Information). The final stable structures are named as aXmYn, where aX= aA, aV, aI, aN, aQ and aR denotes the amino acid, mY= mC, mT, mA and mG denotes the DNA base, and n=1, 2, etc., indicates the relative stability of a given conformational isomer, starting with the most stable. Since the differences between some of the cluster structures were not significant, they were grouped into families using the XCluster tool.32 After this step, the number of structures was reduced to more manageable numbers without loss of relevant information (32 aAmC, 42 aVmC, 45 aImC, 43 aNmC, 56 aQmC, 40 aRmC, 44 aAmT, 58 aVmT, 61 aImT, 55 aNmT, 48 aQmT, 44 aRmT, 39 aAmA, 43 aVmA, 46 aImA, 42 aNmA, 45 aQmA, 47 aRmA, 21 8


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aAmG, 21 aVmG, 32 aImG, 26 aNmG, 48 aQmG, 52 aRmG). All of them were fully optimized using M06-2X/6-31+G(d) and reoptimized at M06-2X/6-311++G(d,p) calculation level, without finding relevant differences in the geometry of the clusters. Hence, only the results at the M06-2X/6-311++G(d,p) level will be presented. The energetics of the three most stable structures for each cluster, including the electronic and thermal free energy at 310.15 K (standard body temperature), are collected in Tables S01-S04 (Supporting Information). The results of the NCI analysis are also compiled in the Supporting Information. Figures S25-S32 collect the most stable structure found for each complex, highlighting the hydrogen bonds and the most relevant van der Waals interactions, together with three views of the NCI plots to facilitate spatial visualization. Tables S05-S12 gather all structural parameters of the interactions found in the second and third most stable species for all the investigated clusters, classified as hydrogen bond or van der Waals interactions. Non-polar amino acids···pyrimidinic DNA bases According to statistical studies, the amino acids with non-polar residues present a lower number of contacts between the lateral chain and the DNA bases.15 Figure 1 displays the most stable structure found for aAmC, aVmC, aImC, aAmT, aVmT and aImT, together with their binding energies. The amino acids of these clusters (aA, aV and aI) have a hydrophobic (non-polar) side chain (-CH3 in aA, -CH-(CH3)2 in aV and – CH(CH3)-CH2-CH3 in aI). The most relevant interactions and their distances are also shown for comparison. Figure 1 additionally collects the NCI plots for the most stable structure of each cluster. The NCI plots characterize the non-bonded interactions as stabilizing/ destabilizing with RGB (Red-Green-Blue) 3-D isosurfaces, which classify limiting 9



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cases. In this figure, destabilizing interactions (such as steric crowding) with 2>0, are colored in red. Strongly stabilizing interactions, like hydrogen bond, for which 2 5.6 kJ mol-1, aNmC, aVmC, aQmC, aNmA and aQmA), or the second most stable structure is still of the same type as the global minimum (aAmC, aImC, aRmC, aAmT, aVmT, aImT, aQmT, aRmT, aAmA, aVmA, aImA, aRmA, aAmG, aVmG, aImG, aNmG and aRmG), and therefore even if an alteration of the energetic order is produced with an increase in the calculation level, the conclusions reached in the present work would still be valid. The only two exceptions 16


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were aNmT and aQmG, where a change in the type of the interactions occurs between the two most stable structures, which are relatively close in energy. The conformational data in Figures 6 and 7 lead to additional conclusions, correlating the number and type of intermolecular interactions and the constituents of each cluster. The preference of the DNA bases to interact with the peptidic bond of non-polar amino acids (denoted by the blue color of the symbols in the figures) contrasts with the clusters of polar species, for which the structures present a collection of interactions, including pure side chain-base (green symbols), peptidic bond-base (blue) and combinations of both interactions (red symbols). The symbols in Figures 6 and 7 also depict the dispersive or hydrogen bond nature of the observed intermolecular interactions. The selected clusters display one to four different hydrogen bonds and additional interactions by dispersive forces. Clearly, those structures with one or more hydrogen bonds dominate the surroundings of the global minima, except for aNmA. To quantify the importance of the dispersive forces in the aggregation process, the Grimme’s dispersion interaction was calculated comparing the interaction energy values obtained using B3LYP and B3LYP-D functional (Fig. 5b). Clearly, the values calculated at M06-2X and B3LYP-D functionals are in a good agreement, showing that M06-2X is a good method to investigate the systems where dispersive interactions are present (Figure 5a). According to the calculation, the contribution of the dispersion to the binding energy for mC and mG aggregates is small (Figure 5a), ranging from 16 % for aRmC1 to 41 % for aImG1, indicating that hydrogen bonds are the main interaction for these mC and mG complexes, as highlighted also in the NCI plots. The contribution of the dispersion becomes more relevant in mT aggregates and the calculation predicts a contribution between 52 to 78 %. Finally, the contribution of the dispersion is the highest in the mA aggregates, where it accounts for 85-90 % of the total dissociation 17



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energy, highlighting the importance of the dispersive forces in these complexes. Arginine aggregates with thymine and adenine represent a special case and the importance of the dispersive forces in the cluster formation is smaller (34 % for aRmT1 and 29 % for aRmA1) than in the rest of the aggregates studied, due to the strong propensity of the amino acids towards hydrogen bond formation. Comparison with crystallographic statistical studies Figure 8 plots the propensity of contacts between each amino acid and the DNA bases derived from crystallographic studies15 as a function of the mean binding energies for the most stable amino acid-base dimers investigated in this work. There is a clear correlation between both magnitudes: the amino acids with aliphatic side chains exhibit both a lower number of contacts and smaller dissociation energy values. On the other hand, the amino acids with hydrophilic side chains exhibit an increasing number of contacts with the dissociation energy of each individual pair. The results in Figure 8 clearly highlight that the interaction between the superstructures of histones and DNA is primarily controlled by the individual amino acid-DNA base pair interactions. Therefore, it may be argued that the sequence of amino acids in the histones is designed to reinforce the interaction with some sections of DNA, and therefore that each histone is designed to bind to a specific section of DNA. Such specificity may well be related to their role in their regulation of DNA expression. At this stage a question remains still open: several amino acids interact with the NH and CO moieties that are usually involved in formation of hydrogen bonds with the complementary base and therefore those places will not be available when the base is part of a DNA double strand. Thus, a further set of calculations was carried out, on the structures of the complexes between each of the six amino acid derivatives selected in 18


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this work and the two pairs of Watson and Crick base pairs (Figures 9 and 10). As can be seen, the same tendency than for the interaction with a single DNA base is observed: while the non-polar amino acids present their peptidic chain to the base pair, there is a direct interaction between the side chain of polar amino acids and the base pair. The resulting correlation between stabilization energy values of the global minimum and the propensity contact (Figure S33 of the supporting information) is surprisingly similar to that in Figure 8, reinforcing the conclusions extracted from the analysis of the amino acid-DNA base interactions.

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CONCLUSIONS

We investigated the molecular basis of the DNA-histone interactions through a reductionist bimolecular approach, using a combination of computational methods which included molecular mechanics, DFT calculations and Non-Covalent Interaction (NCI) analysis. Two kinds of intermolecular interactions, moderate hydrogen bonds and van der Waals dispersive forces, control the aggregation properties of the twenty four selected dimers, for which we provided a comprehensive conformational map and molecular properties. An analysis of the interactions found for the most stable clusters shows that the interaction between non-polar amino acids (alanine, valine and isoleucine) and DNA bases always takes place at the peptidic bond. For polar or charged amino acids, the results show that all of them and the bases interact by the peptidic bond and the lateral chain, except glutamine and 9-methyladenine for which the interaction takes only place at the peptidic bond and asparagine with 9-methyladenine and 1-methylthymine, that interacts only with the side chain. For all these aggregates, the correlation between the calculated binding energy and the propensities protein-DNA base found in the literature is noticeable. Therefore, the balance between hydrogen bonds and van der Waals interactions in the control of the final shape and binding energies of amino acid-DNA base pairs is satisfactorily accounted for in dispersion-corrected DFT molecular models. The computational data offer chemical insight into the dominant interactions representing the DNA-histone interaction, offering a chemical tool for the prediction of aggregation properties of DNA. Moreover, the characterization of the interactions which take place between the amino acids and the DNA bases could help to elucidate the

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language that rules the process of recognition for the amino acids of a particular histone and specific sequences of DNA.

Acknowledgements The research leading to these results has received funding from the Spanish MICINN and MINECO (CTQ2011-22923 and CTQ2009-14364), FEDER and UPV/EHU (UFI 11/23). J.G. thanks the UPV/EHU for a predoctoral fellowship. I.L. thanks the GV for predoctoral and postdoctoral fellowships. Computational resources from the SGI/IZOSGIker network were used for this work.

Supporting Information The 20 most stable structures of each amino acid-DNA base complexes are collected in Figures S1-S24. Different views of the NCI plots are collected in Figures S25-S32. The correlation between mean binding energy of amino acid-WC base pair complexes and the protein-base contact propensity has been collected in Figure S33. A set of tables with relative energies, ZPE and BSSE contributions, binding energies, the sum of electronic and thermal free energies and structural parameters are collected in Tables S01-S12. This information is available free of charge via the Internet at http://pubs.acs.org.

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Scheme 1. (a) Structure and atom labelling for the studied amino acids (R: side chain). The torsional angles  and  are noted.16 Structure and atom labelling of the pyrimidinic DNA bases (b) 1-methylcytosine, (c) 1-methylthymine; and puric DNA bases (d) 9methyladenine and (e) 9-methylguanine.

(a)

(b)

(c)

(d)

(e)

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Figure 1. The most stable structure for non-polar amino acids-pyrimidinic DNA bases complexes with distances (Å) of the hydrogen bonds and most relevant van der Waals interactions and NCI plots (Red: destabilizing interactions, blue: hydrogen bonds and green: delocalized weak interactions). The binding energy values (kJ mol-1) are shown. The set of twenty most stable conformers for these complexes can be found in Tables S01-S06.

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Figure 2. The most stable structure for polar amino acids-pyrimidinic DNA bases complexes with distances (Å) of the hydrogen bonds and most relevant van der Waals interactions and NCI plots (Red: destabilizing interactions, blue: hydrogen bonds and green: delocalized weak interactions). The binding energy values (kJ mol-1) are shown. The set of twenty most stable conformers for these complexes can be found in Tables S07-S12.

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Figure 3. The most stable structure for non-polar amino acids-puric DNA bases complexes with distances (Å) of the hydrogen bonds and most relevant van der Waals interactions and NCI plots (Red: destabilizing interactions, blue: hydrogen bonds and green: delocalized weak interactions). The binding energy values (kJ mol -1) are shown. The set of twenty most stable conformers for these complexes can be found in Tables S13-S18.

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Figure 4. The most stable structure for polar amino acids-puric DNA bases complexes with distances (Å) of the hydrogen bonds and most relevant van der Waals interactions and NCI plots (Red: destabilizing interactions, blue: hydrogen bonds and green: delocalized weak interactions). The binding energy values (kJ mol-1) are shown. The set of twenty most stable conformers for these complexes can be found in Tables S19-S24.

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Figure 5. (a) Comparison between interaction energies calculated at B3LYP-D/6-311++G(d,p) () and B3LYP/6-311++G(d,p) () levels and an estimation of the contribution of the dispersive forces to the binding energy (). (b) Comparison between binding energies calculated at M062X/6-311++G(d,p) () and B3LYP-D/6-311++G(d,p) () levels.

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Figure 6. Conformational distribution of the most relevant interactions found for the first 20 isomers formed with methylpirimidine DNA bases. Blue: Interaction between the peptidic bond and the base. Green: Interaction between the lateral chain and the base. Red: Both interactions, peptidic bond and lateral chain, with the base, are relevant. Types of interactions: HB: hydrogen bond (: four, : three, : two, and : one hydrogen bond), vdW: van der Waals interactions ().

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Figure 7. Conformational distribution of the most relevant interactions found for the first 20 isomers formed with methylpuric DNA bases. Blue: Interaction between the peptidic bond and the base. Green: Interaction between the lateral chain and the base. Red: Both interactions, peptidic bond and lateral chain, with the base, are relevant. Types of interactions: HB: hydrogen bond (: four, : three, : two, and : one hydrogen bond), vdW: van der Waals interactions ().

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Figure 8. Correlation between the mean binding energy of amino acid-DNA bases and the protein-base contact propensity15 for the most stable amino acid-base dimers investigated.

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Figure 9. The most stable structure for each of the non-polar amino acids - WC base pair complexes studied in this work, with the hydrogen bond distances (in Å). The binding energy values (kJ mol-1) are also shown.

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Figure 10. The most stable structure for each of the polar amino acids - WC base pair complexes studied in this work, with the hydrogen bond distances (in Å). The binding energy values (kJ mol-1) are also shown.

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Table 1. Distances (Å) and angles (º) of the intermolecular interactions observed for the clusters aAmC1, aVmC1, aImC1, aAmT1, aVmT1 and aImT1 (H bond: hydrogen bond, vdW: van der Waals).

Interaction type H bond aAmC1 aVmC1 aImC1 aAmT1 aVmT1 aImT1

C1=O···H(NH)

N5H···O(C)

1.846/168.3 1.848/169.13 1.853/169.5

1.922/168.9 1.924/168.4 1.921/169.5

N2H···O=C2

vdW N5H···O=C2

N2H···O=C4

C3H···N3

C4=O···π

R:H···π

2.390/129.6 2.333/138.9 2.333/138.7 2.042/142.7

~2.900/1.999/167.0

~2.700/1.984/156.9

33


~2.800/-


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Table 2. Electron density (a.u.) of the hydrogen bonds observed for the clusters aAmC1, aVmC1, aImC1, aAmT1, aVmT1 and aImT1. Calculated from the NCI grid with 0.1x0.1x0.1 increments.

H bond aAmC1 aVmC1 aImC1 aAmT1 aVmT1 aImT1

C1=O···H(NH)

N5H···O(C)

0.0281 0.0279 0.0276

0.0253 0.0252 0.0255

N2H···O=C2

N5H···O=C2

N2H···O=C4

0.0207 0.0186 0.0223

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Table 3. Distances (Å) and angles (º) of the interactions observed for the clusters aNmC1, aQmC1, aRmC1, aNmT1, aQmT1 and aRmT1 (H bond: hydrogen bond, vdW: van der Waals). Interaction type H bond N5H···O(C) C4=O···H(NH) aNmC1 aQmC1 aRmC1

2.018/148.3 2.110/140.1

N2H···N3

C1=O···HN3

R: H···O(C)

R: O(C)···HN3

1.979/165.8 1.953/170.6 1.928/149.0 1.883/154.5

aNmT1 aQmT1 aRmT1

1.816/168.6 2.032/144.7 1.809/165.6

Interaction type vdW C3H···N1H

aNmC1 aQmC1 aRmC1 aNmT1 aQmT1 aRmT1

R: H···N3

R: C =O···π

2.507/165.7

2.479/159.0

R: O(C)···H(NH) 1.826/178.6 1.836/173.2

1.872/168.5

H5N···O=C4

R: H(NH)···O=C2

~3.000/-

2.130/132.6

35


2.040/155.6 1.987/151.0 2.015/145.0 2.107/146.9


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Table 4. Electron density (a.u.) of the hydrogen bonds observed for the clusters aNmC1, aQmC1, aRmC1, aNmT1, aQmT1 and aRmT1. Calculated from the NCI grid with 0.1x0.1x0.1 increments.

H bond

aNmC1 aQmC1 aRmC1

N5H···O(C) C4=O···H(NH) 0.0209 0.0175

N2H···N3 0.0269

C1=O···HN3

R: H···O(C)

R: O(C)···HN3

R: H(NH)···O=C2

0.0286

R: O(C)···H(NH) 0.0288 0.0281

0.0297

0.0265 0.0258 0.0324

aNmT1

0.0197

aQmT1

0.0194

0.0216

aRmT1

0.0313

0.0217 0.0174

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Table 5. Distances (Å) and angles (º) of the intermolecular interactions observed for the clusters aAmA1, aVmA1, aImA1, aAmG1, aVmG1 and aImG1 (H bond: hydrogen bond, vdW: van der Waals).

Interaction type H bond C1=O···H(NH)

C1=O···HN1

vdW N5H···O=C6

O···π

N···π

aAmA1

2.033/151.4

3.100/ -

~3.200/ -

aVmA1

2.016/151.7

3.100/ -

~3.300/ -

aImA1

2.046/151.1

3.100/ -

3.100/ -

aAmG1

2.020/147.2

1.979/153.4

2.056/157.3

aVmG1

2.061/145.7

1.918/155.1

2.054/157.7

aImG1

2.039/147.2

1.990/146.9

2.105/160.4

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Table 6. Electron density (a.u.) of the hydrogen bonds observed for the clusters aAmA1, aVmA1, aImA1, aAmG1, aVmG1 and aImG1. Calculated from the NCI grid with 0.1x0.1x0.1 increments.

H bond C1=O···H(NH)

C1=O···HN1

N5H···O=C6

aAmA1

0.0199

aVmA1

0.0198

aImA1

0.0187

aAmG1

0.0187

0.0233

0.0169

aVmG1

0.0174

0.0261

0.0171

aImG1

0.0185

0.0227

0.0159

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Table 7. Distances (Å) and angles (º) of the intermolecular interactions observed for the clusters aNmA1, aQmA1, aRmA1, aNmG1, aQmG1 and aRmG1 (H bond: hydrogen bond, vdW: van der Waals). Interaction type H bond N5H···N7

C4=O···H(NH) N5H···O=C6 C4=O···HN1

aNmA1 aQmA1 1.920/163.6 aRmA1 aNmG1 aQmG1 aRmG1

1.970/167.9

R: H···N1

R: H···O=C6

2.112/146.1 2.073/150.7

2.014/145.9

1.930/147.2

2.620/139.9

1.888/159.8

2.202/141.1

1.867/155.7

vdW aNmA1 aQmA1

C4=O···H(NH) 2.374/117.9

1.847/147.2 2.016/150.3

Interaction type N5···H(NH)

R: O(C)···H(NH) R: O(C)···HN1 R: H(NH)···N7

O···π

R: H···N7 2.275/143.7

N···π

2.700/3.300/-

2.350/159.3

aRmA1 aNmG1 aQmG1 aRmG1

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Table 8. Electron density (a.u.) of the hydrogen bonds observed for the clusters aNmA1, aQmA1, aRmA1, aNmG1, aQmG1 and aRmG1. Calculated from the NCI grid with 0.1x0.1x0.1 increments.

H bond N5H···N7 aNmA1 aQmA1 aRmA1 aNmG1 aQmG1 aRmG1

C4=O···H(NH) N5H···O=C6 C4=O···HN1

R: H···N1

R: H···O=C6

R: O(C)···H(NH) R: O(C)···HN1 R: H(NH)···N7

0.0312 0.0219

0.0236 0.0211

0.0206

0.0245

0.0263

0.0275

0.013

0.0247

0.0307 0.0253

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References 1

Nelson, D.L.; Cox, M.M. Lehninger Principles of Biochemistry; Worh: New York, 2000 2 Downs, J.A.; Nussenzweig, M.C.; Nussenzweig, A. Nature 2007, 447, 951-957 3 Luger, K; Mäder, A.W.; Richmond, R.K.; Sargent, D.F.; Richmond, T.J. Nature 1992, 389, 251-259 4 Strahl, B.D.; Allis, C.D. Nature 2000, 403, 41-45 5 Jenuwein, T.; Allis, C.D. Science 2001, 293, 1074-1080 6 Luger, K. Chromosome Res. 2006, 14, 5-16 7 Berger, S.L. Nature 2007, 447, 407-412 8 Fensenfeld, G.; Groudine, M. Nature 2003, 421, 448-453 9 Jones, S.; van Heyningen, P.; Berman, H.M.; Thornton, J.M. J. Mol. Biol. 1999, 287, 877-896 10 Luscombe, N.M.; Laskowski, R.A.; Thornton, J.M. Nucleic Acids Res. 2001, 29, 2860-2874 11 Lejeune, D.; Delsaux, N.; Charloteaux, B.; Thomas, A.; Brasseur, R. Proteins 2005, 61, 258-271 12 Coulocheri, S.A.; Pigis, D.G.; Papassiliou, K.A.; Papassiliou, A.G. Biochimie 2007, 89, 1291-1303 13 Schneider, B.; Cerny, J.; Svozil, D.; Cech, P.; Gelly, J-Ch.; de Brevern, A.G. Nucleic Acids Res. 2014, 42, 3381-3394 14 Sathyapriya, R.; Brinda, K.V.; Vishveshwara, S. J. Chem. Inf. Model. 2006, 46, 123129 15 Sathyapriya, R.; Vishveshwara, S.; Vijayabaskar, M.S. PLoS Comput. Biol. 2008, 4, e1000170 16 Ramachandran, G.N.; Ramakrishnan, C.; Sasisekharan, V. J. Mol. Biol. 1963, 7, 9599 17 Leon, I.; Millan, J.; Castano, F.; Fernandez, J.A. ChemPhysChem 2012, 13, 38193826 18 Leon, I.; Cocinero, E.J.; Millan, J.; Rijs, A.M.; Usabiaga, I.; Lesarri, A.; Castano, F.; Fernandez, J.A. J. Chem. Phys. 2012, 137, 074303 19 Chaudret, R.; de Courcy, B.; Contreras-García, J.; Gloaguen, E.; Zehnacker-Rentier, A.; Mons, M.; Piquemal, J.-P. Phys. Chem. Chem. Phys. 2014, 16, 9876-9891 20 Miller, B.J.; Lane, J.R.; Kjaergaard, H.G. Phys. Chem. Chem. Phys. 2011, 13, 1418314193 21 Lane, J.R.; Contreras-Garcia, J.; Piquemal, J.-P.; Miller, B.J.; Kjaergaard, H.G. J. Chem. Theory Comput. 2013, 9, 3263-3266 22 Halgren, T.A. J. Comput. Chem. 1999, 20, 730-748 23 MacroModel, version 9.9 (Suite 2012); Schrödinger, LLC: New York, 2012 24 Zhao, Y.; Truhlar, D.G. Theor. Chem. Acc. 2008, 120, 215-241 25 Zhao, Y.; Truhlar, D.G. Acc. Chem. Res. 2008, 41, 157-167 26 Hohestein, E.G.; Chill, S.T.; Sherrill, C.D. J. Chem. Theory Comput. 2008, 4, 19962000 27 Frisch, M.; Trucks, G.W.; Schlegel, H.B.; Scuseria, G.E.; Robb, M.A.; Cheeseman, J.R.; Scalmani, G.; Barone, V.; Mennucci, B.; Petersson, G.A.; Nakatsuji, H.; Caricato, M.; Li, X.; Hratchian, H.P.; Izmaylov, A.F.; Bloino, J.; Zheng, G.; Sonnenberg, J.L.; 41



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

Hada, M.; Ehara, M.; Toyota, K.; Fukuda, R.; Hasegawa, J.; Ishida, M.; Nakajima, T.; Honda, Y.; Kitao, O.; Nakai, H.; Vreven, T.; Montgomery, J.A., Jr.; Peralta, J.E.; Ogliaro, F.; Bearpark, M.; Heyd, J.J.; Brothers, E.; Kudin, K.N.; Staroverov, V.N.; Kobayashi, R.; Normand, J.; Raghavachari, K.; Rendell, A.; Burant, J.C.; Iyengar, S.S.; Tomasi, J.; Cossi, M.; Rega, N.; Millam, J.M.; Klene, M.; Knox, J.E.; Cross, J.B.; Bakken, V.; Adamo, C.; Jaramillo, J.; Gomperts, R.; Stratmann, R.E.; Yazyev, O.; Austin, A.J.; Cammi, R.; Pomelli, C.; Ochterski, J.W.; Martin, R.L.; Morokuma, K.; Zakrzewski, V.G.; Voth, G.A.; Salvador, P.; Dannenberg, J.J.; Dapprich, S.; Daniels, A. D.; Farkas, Ö.; Foresman, J.B.; Ortiz, J.V.; Cioslowski, J.; Fox, D.J. Gaussian 09, revision A.02, Gaussian Inc., Wallingford CT, 2009 28 Boys, S.F.; Bernardi, F. Mol. Phys. 1970, 19, 553-556 29 Contreras-García, J; Jonhson, E.R.; Keinan, S.;Chaudret, R.; Piquemal, J.-P.; Beratan, D.N.; Yang, W., J. Chem. Theory Comput. 2011, 7, 625-632 30 Humphrey, W.; Dalke, A.; Schulten, K. J. Molec. Graphics 1996, 14, 33-38. 31 Grimme, S.; Antony, J.; Ehrlich, S.; Krieg, H. J. Chem. Phys. 2010, 132, 154104 32 MacroModel XCluster, version 9.7 (Suite 2012); Schrödinger, LLC: New York, 2012

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For Table of Contents use only Unravelling Protein-DNA Interactions at Molecular Level: A DFT and NCI Study by J. González, I. Baños, I. León, J. Contreras-García, E.J. Cocinero, A. Lesarri, J. A. Fernández, and J. Millán

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Unravelling ProteinâDNA Interactions at Molecular Level: A DFT and

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