Enrofloxacin Permeation Pathways across the Porin OmpC - The

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Enrofloxacin Permeation Pathways across the Porin OmpC Jigneshkumar Dahyabhai Prajapati, Carlos José Fernández Solano, Mathias Winterhalter, and Ulrich Kleinekathöfer J. Phys. Chem. B, Just Accepted Manuscript • DOI: 10.1021/acs.jpcb.7b12568 • Publication Date (Web): 06 Jan 2018 Downloaded from http://pubs.acs.org on January 10, 2018

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The Journal of Physical Chemistry

Enrofloxacin Permeation Pathways across the Porin OmpC Jigneshkumar Dahyabhai Prajapati,† Carlos José Fernández Solano,† Mathias Winterhalter,‡ and Ulrich Kleinekathöfer∗,† †Department of Physics and Earth Sciences, Jacobs University Bremen, 28759 Bremen, Germany ‡Department of Life Sciences and Chemistry, Jacobs University Bremen, 28759 Bremen, Germany E-mail: [email protected]

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Abstract In Gram-negative bacteria, the lack or quenching of antibiotics translocation across the outer membrane is one of the main factors for acquiring antibiotic resistance. An atomic level comprehension of the key features governing the transport of drugs by outer membrane protein channels would be very helpful in developing the next generation of antibiotics. In a previous study [J. D. Prajapati et al, J. Chem. Theory Comput. 2017, 13, 4553–4566], we have characterized the diffusion pathway of a ciprofloxacin molecule through the outer membrane porin OmpC of E. coli by combining metadynamics and a zero-temperature string method. Here, we evaluate the diffusion route through the OmpC porin for a similar fluoroquinolone, i.e., the enrofloxacin molecule, using the previously developed protocol. As a result, it was found that the lowestenergy pathway is similar to that for ciprofloxacin, namely, a reorientation is required in the extracellular side before reaching the constriction region with the carboxyl group ahead. In turn, free energy basins for both antibiotics are located at similar positions in the space defined by selected reaction coordinates and their affinity sites share a wide number of porin residues. However, there are some important deviations due to the chemical differences of these two drugs. On the one hand, a slower diffusion process is expected for enrofloxacin as the permeation pathway exhibits higher overall energy barriers, mainly in the constriction region. On the other hand, enrofloxacin needs to replace some polar interactions in its affinity sites by non-polar ones. This study demonstrates how minor chemical modifications can qualitatively affect the translocation mechanism of an antibiotic molecule.

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1

Introduction

As several studies suggest, 1–3 multi-drug resistant superbugs might globally claim millions of lives in the near future. For instance, the resistance of E. coli bacteria to fluoroquinolones has increased up to a threatening level in recent decades. 4–8 The antibiotic influx across the outer membrane (OM) has been recognized as one of the factors playing a critical role in this resistance. 9 As has been confirmed by several experiments, 10–14 especially the generaldiffusion OM channels of E. coli, i.e., for example the porins OmpF and OmpC, facilitate the antibiotic diffusion towards the periplasmic space. Consequently, the down-regulation of these major porins is associated with a decrease in the intracellular accumulation of fluoroquinolones. 15–19 At the same time, a higher osmotic stress due to the presence of antibiotics favors the expression of OmpC over OmpF. 16,20 Alike, milieus containing high levels of nutrients as for example in mammalian intestines promote the expression of the OmpC porin. 21–23 Therefore, a proper understanding of the antibiotic permeation through OmpC is biologically relevant and might be very helpful in guiding the development of next generation antibiotics. 24 The translocation of antibiotics into Gram-negative bacteria is a key problem in discovering new drugs to treat the infections they cause. 25,26 Molecular dynamics (MD) simulations became a valuable tool for drug discovery in general 27 and in particular when it comes to the ion permeation and substrate translocation through OM pores. These simulations include, for example, studies of OmpF, 28–30 OmpC, 24,31 OprP, 32–34 OprO, 35 and OprD. 36,37 Recently, these simulations include an improved description of the OM, i.e., lipopolysaccharides (LPS)-phospholipid membranes. 38–40 Moreover, the substrate transport through OM channels is often studied in combinations of experiment and simulation. 41–43 Metadynamics simulations 44 have been used to illustrate the permeation of various classes of antibiotics through OmpF 43,45–51 and, in fewer investigations, through OmpC. 24,45,52 The early studies 24,45–50 were conducted based on the ”escaping free energy minima” protocol, 53 i.e., the simulations were stopped after the first permeation event from the extracellular to the periplasmic side of the pore (or vice versa). The respec3



tive estimated first transition paths were considered as the most favorable ones. However, these studies were only able to provide a qualitative and incomplete picture of the antibiotic diffusion pathways as their sampling was very limited by the accessible simulation time a couple of years ago, i.e., the simulations were performed at most for 100 ns. In last years, more extensive simulations have been performed, 43,51,52 where the free energy surfaces (FESs) were reconstructed as a function of predefined collective variables (CVs), i.e., the distance and orientation of the antibiotics with respect to the channel axis. The main goal of these studies was to establish a theoretical foundation for the different kinetic rates of antibiotics in comparison to electrophysiology experiments. Nevertheless, these studies were mainly focused on the antibiotic transport in the vicinity of or inside the constriction region and little information was provided about the full permeation process. On the other hand, co-crystal structures of three antibiotics complexed with the OmpF porin were recently determined using X-ray crystallography. 54 Notably, this study shows three different affinity sites, i.e., one for each antibiotic molecule, which are located at the OmpF vestibules. Therefore, there is still a need to characterize the full diffusion routes of available antibiotics in order to establish useful structure-function relationships for various porins. Recently, we have proposed a computational protocol 55 to characterize the antibiotic permeation pathways across OM channels that combines metadynamics 53,56–58 and a zerotemperature string method. 59,60 As a result, we have been able to construct the minimum free energy permeation path for the ciprofloxacin antibiotic along the OmpC porin. To our knowledge, this was the first study that fully characterized the antibiotic permeation pathway through an OM channel and identified the most relevant affinity sites along the pathway. Here, we study the permeation process for enrofloxacin, namely, a fluoroquinolone molecule very similar to ciprofloxacin, in order to establish the influence of chemical modifications of the drug on the membrane translocation. It has been shown that enrofloxacin is less efficient against E. coli than ciprofloxacin based on a higher minimum inhibitory concentration. 20,61,62 Moreover, enrofloxacin translocation across OmpC has a lower association rate

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constant than ciprofloxacin as estimated based on single channel electrophysiology experiments, 63 but a similar dissociation rate. As a result, the estimated flux through OmpC at -100 mV is lower for enrofloxacin (0.5 ± 0.07 molecules/s) than for ciprofloxacin (3.0 ± 0.3 molecules/s). 63 However, the estimated flux through OmpF based on single channel electrophysiology is very similar for both molecules, i.e., 8.0 ± 1.0 and 7.0 ± 0.8 molecules/s for enrofloxacin and ciprofloxacin, respectively. 63 Thus, this subtle difference in the permeation rate of enrofloxacin through OmpC deserves further studies concerning the main differences in the diffusion mechanism at the molecular level. With the outcome of this study, we provide a very detailed insight at the atomistic level into the permeation paths of two antibiotics which moreover enables us to explain the differences observed in the electrophysiology experiments. The paper is organized as follows: Section 2 is mainly devoted to a description of the system setup and the simulation protocol for studying the enrofloxacin translocation across the OmpC porin of E. coli. In Section 3, we discuss the results and compare with those obtained for ciprofloxacin permeation. Finally, we conclude with some remarks in Section 4.

2 2.1

Material and Methods System setup and metadynamics simulations

This work focuses on the porin OmpC from the Gram-negative bacterium E. coli 21,64,65 . The porin OmpC is classified as a nonspecific protein channel since it allows the passage of ions and metabolites up to 600 Da without any clear specificity. OmpC has a sequence similarity of around 60% with OmpF and 74% of the residues along the pore lumen are identical 64,66 in both porins. As shown in Fig. 1A, the porin OmpC is a trimer in which each monomer forms a hollow 16-stranded β-barrel. All monomers share exactly the same primary and tertiary structure. The constriction region is formed by an inward folded L3 loop. In the constriction region, a strong transversal electric field 31 is created as a consequence of 5



monomer 1

A

C Loop L3

D113 D105 E109 R124

Loop L4

R74 R37 K16

Loop L2

on

m m no

er

om m

2

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

3 er

o

-

B Ethyl substitution

+

Enrofloxacin

Figure 1: (A) An OmpC trimer 64 (PDB ID: 2J1N) is shown in cartoon representation. The loops L2, L3 and L4 are highlighted in yellow, magenta and cyan, respectively. The important negatively charged (D105, E109 and D113) and positively charged (K16, R124, R74 and R37) residues located in the constriction region are shown in stick representation. (B) 2D structure of the enrofloxacin molecule in its zwitterionic form. (C) System setup for well-tempered metadynamics simulations of the enrofloxacin permeation through the OmpC porin. An OmpC trimer (cartoon representation) inserted in a POPE lipid bilayer (surface representation) is shown together with enrofloxacin molecules (van der Waals representation) placed at the EC and PP sides of the porin. Water and ions are shown in surface representation and as balls, respectively. the negatively charged residues on the L3 loop (D105, E109 and D113) and the positively charged residues on the opposite side of the pore wall (K16, R37, R74 and R124) that are separated only by a short distance. The loops L2 and L4 bend over the barrel wall of an adjacent monomer and are held in place by salt-bridges and hydrogen bonds. An overall hourglass shape describes each monomer, where the narrow constriction region separates the extracellular (EC) and periplasmic (PP) vestibules. All amino acids were treated in their standard protonation state except residue D299 that was protonated in order to stabilize the fluctuations of the L3 loop in the constriction region. 55 At pH 7, the enrofloxacin molecule has a zwitterionic configuration with a zero net charge but a permanent dipole moment (see Fig. 1B). The reported pKa values for the carboxyl and the amino group are 5.94 and 8.7, 6


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respectively. 67 The aromatic quinoline scaffold contains polar fluorine and carbonyl groups as well as a non-polar cyclopropyl ring. An ethyl substitution on the N atom from the amino group is the only difference compared to the structure of the ciprofloxacin molecule. The initial force field parameters for enrofloxacin were taken from CGenFF database 68–70 and further optimized using the ffTK toolkit 71 (see SI, Section S1). A similar system setup as in our previous work 55 was deployed as shown in Fig. 1C. In brief, an OmpC trimer was inserted in a fully hydrated POPE bilayer and neutralized with potassium cations that were placed near the edge of the simulation box and restrained by applying harmonic constraints. Two different systems were created by placing an enrofloxacin molecule in the mouth of a given monomer either at the EC or the PP side. Both systems were composed of 135247 atoms, which included 295 POPE lipids, 26618 TIP3P waters and 42 K+ ions. The systems were equilibrated by performing MD simulations with the GROMACS package version 5.1.2 72 and the CHARMM36 force field 73,74 in several consecutive steps. 55 We have employed the same force field for lipid and protein atoms, bond distance constraints and treatment for non-bonded interactions as described in our previous work. 55 A large variety of enhanced sampling methods 44,75–81 has been proposed for exploring and quantifying free energy surfaces (FESs) in a limited number of reaction coordinates often referred to as collective variables (CVs). Here we focus on metadynamics, 53,56–58 a popular and insightful sampling method that iteratively builds a bias potential to keep the system away from already visited regions and thereby increases the rate of transitions between metastable FES basins. The present permeation process is described in terms of two linear CVs 55 labeled as z and zij , which specify the position and orientation of the enrofloxacin molecule with respect to the channel axis. In Section S2 of the SI, the atoms selected for defining the CVs are shown. The convergence of the FES is a critical criterion that needs to be satisfied otherwise the results might be meaningless. Thus, we adopt a two-stage strategy in which a well-converged FES was initially obtained by only biasing the CV z in a multiple walker well-tempered metadynamics (WTmetaD) simulation (see SI, Section S3), and then

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recomputed as a function of CVs z and zij by the aid of the Tiwary-Parrinello reweighting technique. 82 The same WTmetaD parameters as described in our previous work have been employed. 55 Briefly, Gaussian hills were deposited every 4 ps and the initial height was set to 0.72 kcal/mol, leading to a deposition rate of 0.18 kcal/(mol·ps). The bias factor was set to 30 which is equivalent to a tuning temperature of 8700 K. At the same time, the antibiotic movement was restricted inside a monomer by applying half-harmonic walls. Some FES artifacts near the boundaries were relieved with the help of a previously suggested fix. 83 The bias was stored on a mesh grid with a grid size of 0.01 ˚ A which allows for an efficient on the fly estimation of the bias forces by interpolation. A total of sixteen walkers were used with nine and seven of them started from the EC and PP mouths, respectively. The total simulation time was set to 4 µs (250 ns for each walker) which corresponds to a deposition of 1 million Gaussian hills. The metadynamics simulations were performed using the PLUMED plugin version 2.2.3

84

together with GROMACS package. 72 A MD time step of 5 fs was used

with the help of virtual hydrogen sites. 85–87

2.2

Estimation of FES and translocation pathway

After achieving a reasonable convergence in the multiple walker WTmetaD simulation (see SI, section S3), the FES was reconstructed as a function of the CVs z and zij using the Tiwary and Parrinello reweighting technique 82 as implemented in an in-house code 55 with a grid size of 0.5 ˚ A and 0.4 ˚ A, respectively. A reasonable assumption is that antibiotics roughly follow pathways of minimal free energy during the permeation process. Thus, identifying diffusion routes is very similar to finding minimum free energy paths (MFEPs) on the FES. Since metadynamics allows for estimating the FES and deriving its gradient, MFEPs can be computed efficiently using the string method in the available CVs, 59,60 which was implemented in an in-house code. 55 The lowest-energy translocation pathway was estimated as a concatenation of MFEPs that connect the EC and PP side winding through the constriction 8


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region.

2.3

Unbiased MD simulations

Several energy basins along the reconstructed FES were identified and unbiased MD simulations starting from configurations located at these energy basins were performed to evaluate their metastability. 55 Four independent unbiased MD simulations were run for 25 ns each for all basins, where different initial velocities were assigned to the enrofloxacin molecule according to the Maxwell-Boltzmann distribution and an interaction energy was estimated from the non-bonded pairwise interactions between the enrofloxacin and the porin atoms within a cutoff distance of 12 ˚ A. We defined this interaction as the average sum of the electrostatic and van der Waals contributions for those configurations along the trajectories in which the antibiotic molecule remained inside the respective basin. Moreover, those residues located at a distance lower than 4 ˚ A from any atom belonging to the antibiotic molecule were identified in each basin and the respective interaction per-residue energies were also determined.

2.4

Metadynamics simulations in a restricted CV space

As in the case of ciprofloxacin, 55 an enrofloxacin molecule can adopt two main orientations in the mouth of the constriction region at the EC side with either the amino or the carboxyl group in front with respect to the channel axis. In turn, these conformations determine two different pathways in the permeation process. To explore the energy barriers and topologies of these pathways in the eyelet region of the OmpC porin in more detail, we performed two additional multiple walker WTmetaD simulations by biasing the CV z in a reduced region of the (z, zij ) space. To this end, the antibiotic position was restricted by applying halfharmonic walls at z = −10 and 10 ˚ A. Additional half-harmonic walls at zij = −4 and +4 ˚ A were applied in each simulation to restrict the antibiotic orientations to those with either the amino or the carboxyl group ahead. In total ten walkers were used, where the initial position of the enrofloxacin was located at z ∼ −10 ˚ A and at z ∼ +10 ˚ A for five walkers 9



each. The simulation for each walker was carried out for 100 ns, leading to total simulation time of 1 µs. The same above detailed parameters for the metadynamics simulations were used.

3

Results and Discussion

Figure 2: (A) Reweighted FES as a function of the CVs z and zij . The lowest-energy pathway is depicted by a black line. (B) Free energy along the lowest-energy pathway for enrofloxacin and ciprofloxacin. The variable s ∈ [0, 1] is used to parametrize the pathway. (C) Reweighted free energy landscapes as a function of the CVs z and zij from two independent multiple walker WTmetaD simulations performed in restricted CV spaces. The key metastable states are labeled in all panels. The CV z describes the enrofloxacin position along the channel axis. 55 Between the EC (z < −5 ˚ A) and PP (z > 5 ˚ A) vestibules, the constriction region is approximately located 10


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at z ∈ [−5, 5] ˚ A. At the same time, the CV zij provides information about the enrofloxacin orientation with respect to the channel axis. 55 Their limiting values −8 ˚ A (carboxyl group ahead in the z direction) and 8 ˚ A (amino group ahead in the z direction) correspond to parallel and antiparallel orientations with respect to the channel axis. Note that the CVs z and zij are identical to those of the ciprofloxacin molecule studied earlier since the same atoms are involved in defining them. 55 Fig. 2A depicts the reweighted FES in the (z, zij ) space obtained using the Tiwary-Parrinello algorithm. 82 The lowest-energy pathway is depicted as a black line on this FES. The enrofloxacin and ciprofloxacin pathways share remarkable similarities (see SI, Fig. S5A). Namely, the enrofloxacin molecule is captured in the EC mouth (z ∼ −24 ˚ A) with a conformation where the amino group is ahead pointing towards the eyelet region. A reorientation is required, however, in the EC vestibule before reaching the constriction region with its carboxyl group ahead. Significantly, the main FES basins for enrofloxacin and ciprofloxacin are located at similar positions in the CV space enabling us to adopt the same notation as in our previous work. 55 As a main difference, the overall enrofloxacin permeation pathway exhibits energy barriers larger than those for the ciprofloxacin molecule (see Fig. 2B) and especially in the constriction region. This clearly indicates a slower diffusion for the enrofloxacin permeation in agreement with experiments. 63 Unbiased MD simulations were performed in those energy basins identified in Fig. 2. In Fig. 3A, the distribution of enrofloxacin conformations from unbiased MD simulations are mapped into the (z, zij ) space. Some conformations from simulations initiated in basin 1 are able to escape outside the monomer, which supports the idea of an entropic barrier at the mouth of the pore. Only a low-energy barrier separate basin 3b from basin 2 seen by the fact that some conformations from simulations started in energy basin 3b are able to emigrate to basin 2 but not vice versa. A similar behavior was found for the ciprofloxacin molecule 55 (see SI, Fig. S5B). In contrast to ciprofloxacin, the enrofloxacin molecule often moves back to basin 3 when initially located at basin 4. Moreover, basin 5 has a low energy barriers to other basins and hence very fast transitions to either basin 4 or basins located at the PP vestibule

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Figure 3: (A) Distribution of the enrofloxacin conformations in the CV space (z, zij ) from unbiased MD simulations initiated in the different energy basins (see Figs. 2A and B). Different colors are used for each basin. (B) The three panels illustrate representative conformations of the enrofloxacin molecule in each basin. The arrows indicate the transitions into neighboring basins as enrofloxacin translocates from the EC to the PP side. Loops L3 and L4 from monomer 1 are highlighted in magenta and gray, respectively, while loop L2 from monomer 2 and loop L4 from monomer 3 in yellow and cyan, respectively. The enrofloxacin molecule is shown in stick representation with its carboxyl and amino groups in red and blue, respectively. For simplicity, the hydrogen atoms are omitted. The remainder of the antibiotic is shown in the color corresponding to that of the respective basin. The enrofloxacin molecule has been constrained to stay inside monomer 1. were observed. It is worth mentioning that all transitions between minima are in accordance with the predicted translocation pathway. In Fig. 3B, representative enrofloxacin conformations are depicted in Euclidean space for the different energy basins. As in the ciprofloxacin translocation mechanism, 55 two orientations are available when approaching the constriction region from the EC vestibule. In basin 3b, the amino group flips pointing to the L3 loop while the carboxyl group remains in a similar position as in basin 2. In basin 3, the amino 12


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group remains in a similar position as in basin 2 but the carboxyl group flips pointing towards the L3 loop. Our results strongly suggest that enrofloxacin is crossing the constriction region mainly starting from basin 3. Additional multiple walker WTmetaD simulations in restricted regions of the CV space provide evidence that discrimination between pathways passing through minima 3 and 3b is even more drastic for enrofloxacin than for ciprofloxacin (see Fig. 2C).

Figure 4: Average interaction energies for the enrofloxacin and ciprofloxacin molecules in each energy basin. The error bars represent the standard deviation. Performing a detailed analysis of the trajectories generated by unbiased MD simulations, we are able to characterize the affinity sites associated with each energy basin. For comparing the affinity sites of the enrofloxacin and ciprofloxacin, the interaction energies between these molecules and protein residues were estimated in each energy basin (see Fig. 4). The unbiased MD simulations performed for ciprofloxacin molecule in our previous study 55 were used for estimating the respective interaction energies. As can be seen, there are no major differences in the interaction energies for the basins 1, 2, 3, and 8. However, smaller interaction energies are observed in basins 5 and 7 for enrofloxacin compared to ciprofloxacin. In particular, the interaction for basin 5 of enrofloxacin is much more unfavorable than that for the analogous basin of ciprofloxacin, which strongly supports the finding that enrofloxacin needs to overcome higher energy barriers inside the constriction region and that this basin exhibits a poor metastability (see previous discussion). In Fig. 5, the per residue interaction 13



Figure 5: Interaction energies per-residue for the enrofloxacin and ciprofloxacin molecules in each energy basin. The residues are classified in five categories: acidic (red), basic (blue), polar (magenta), aromatic (orange), nonpolar (black). The residues underlined with solid and dotted lines are from the loops L2 and L4 of monomers 2 and 4, respectively. The most prominent residues are indicated by the symbol † and they are depicted in the Fig. 6. Moreover, other relevant residues are indicated by the symbol *. energies are shown for enrofloxacin and ciprofloxacin in each energy basin. The charged and polar residues are found to be the dominating factor for stabilizing the antibiotics in their basins. Furthermore, aromatic and nonpolar residues make significant contributions and the 14


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Figure 6: Representative conformations of the enrofloxacin molecule in each energy basin. The contributing porin residues and enrofloxacin molecule are shown in stick representation. For enrofloxacin, the C atoms are depicted in orange, O atoms in red, N atoms in blue, F atoms in cyan, and H atoms in ice blue. In case of the amino acids, the C atoms are shown in green, O atoms in red, and N atoms in blue. interactions involving these residues are very often mediated by backbone atoms instead of side chains. The relevant porin residues involved in the enrofloxacin affinity sites are listed in Table 1, and representative enrofloxacin conformations are shown in Fig. 6. Enrofloxacin adopts conformations similar to those of ciprofloxacin in the affinity sites as they share a wide number of common residues. For example, π-stacking interactions between the benzene ring of enrofloxacin and some aromatic residues (W72, F161, Y211 and Y305) are observed in the affinity sites corresponding to basins 1, 3, 7 and 8, which are also known to play a critical role in the target mechanism of fluoroquinolone antibiotics. 88 Moreover, there exist

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Figure 7: Comparison between ciprofloxacin and enrofloxacin conformations for the affinity site associated with energy basin 4 in the OmpC porin. The colors are the same as in Fig. 6 except for the hydrophobic pocket formed by residues Y22, F110, L20, V29, and I337 where the C atoms are depicted in cyan. a similar cooperative effect among different monomers since the affinity sites for basins 2 and 3 require some residues belonging to loops L2 and L4 from neighboring monomers. The main differences are observed in basins 3b, 4 and 5 for the interactions involving the amino group as the ethyl substitution decreases the ability to form hydrogen bonding or salt bridges. Instead, the enrofloxacin molecule forms non-polar contacts between the ethyl group and some aliphatic and aromatic residues. In the constriction region, the amino group of enrofloxacin orients itself towards the hydrophobic pocket formed by the residues L20, Y22, V29, F110, and I337. As shown in Fig. 7, enrofloxacin and ciprofloxacin molecules are located at similar positions in the affinity sites associated to basin 4 but with different orientations to favor more suitable interactions. These observations clearly emphasize the key role that non-polar residues play in the transport of antibiotics through a non-specific pore. Finally, we would like to highlight some prominent correlations between previously reported experimental results and our numerical findings. Baslé et al 64 pointed out that OmpC and OmpF mainly differ by a few amino acids located along the pore lumen. Kojima and Nikaido 89 demonstrated how a mutation of all these residues can modify the substrate dif16


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Table 1: Summary of the prominent interactions found between the enrofloxacin functional groups and the OmpC porin residues in each energy basin. For −NH(C2 H5 )+ , the polar interactions, i.e., salt bridges and hydrogen bonds, involve the −NH fragment and the hydrophobic contacts are formed through the −C2 H5 fragment. The star symbol * denotes residues in which the backbone atoms take part in the interactions. Energy basin 1

2

3b

3

Interaction types Salt bridges Hydrogen bonds

π-stacking Hydrophobic contact Salt bridges Hydrogen bonds

Salt bridges Hydrogen bonds Hydrophobic contact Salt bridges Hydrogen bonds

4

π-stacking Salt bridges Hydrogen bonds

5

Hydrophobic contact Salt bridges Hydrogen bonds

6

Hydrophobic contact Salt bridges

7

Hydrogen bonds Hydrophobic contact Salt bridges Hydrogen bonds

8

π-stacking Salt bridges Hydrogen bonds π-stacking

Enrofloxacin interacting groups -NH(C2 H5 )+ -COO− -CO -F Quinoline ring Quinoline, cyclopropyl and piperazinyl rings -COO− -NH(C2 H5 )+ -NH(C2 H5 )+ -F -NH(C2 H5 )+ -COO− -NH(C2 H5 )+ -NH(C2 H5 )+ -COO− -NH(C2 H5 )+ -COO− -CO -F Quinoline ring -COO− -COO− -NH(C2 H5 )+ -NH(C2 H5 )+ -COO− -NH(C2 H5 )+ -CO -NH(C2 H5 )+ -NH(C2 H5 )+ -COO− -NH(-C2 H5 )+ Cyclopropyl ring -NH(C2 H5 )+ -COO− -NH(C2 H5 )+ -CO Quinoline ring -COO− -COO− -F Quinoline ring

Porin residues D171 T208 N155 Q175 F161, Y211 P156, A205, A209, A210, A172 R174, R246 S157, G158∗ , E159∗ , N167, G169∗ (loop L4, monomer 3) N70 N67 (Loop L2, monomer 2) E109 R174, R246 Y22 Y22, V29, F110, I337 R124 N70 Q59 S117 N67 (Loop L2, monomer 2) W72 R74, R124 Q123 Y22 Y22, V29, F110, I337 R37, R74 Y22 R37, R74 Y22, V29, F110, I337 D105 K51 V106∗ , L107∗ , P108∗ , D109∗ , F110∗ , G111∗ Y94, Y98 D105 K308 ∗ V106 , L107∗ , P108∗ R272 Y305 K308 Q266 Q345 Y305

fusion through OmpC to behave like the one of OmpF and vice versa. In case of OmpC, the list of residues is composed of V29, N67, E68, W72, D171, L173, R246, D18, D135 and K317. Here, we have found that residues V29, N67, E68, W72, D171, L173 and R246 make favorable interactions with both ciprofloxacin and enrofloxacin molecules in different affinity sites. In particular, residue V29 belonging to the hydrophobic pocket is responsible for varying the enrofloxacin orientation in basins 3b, 4 and 5 with respect to the ciprofloxacin one. Moreover, the mutation of residue R124 in the mutant-type OmpC33 90 was found to drasti-

17



cally reduce the antibiotics flux relative to wild-type OmpC. 24,52 Again, we have found that this residue makes favorable interactions with both ciprofloxacin and enrofloxacin molecules in basins 4 and 5.

4

Conclusions

We have been able to describe the primary features of enrofloxacin translocation across the OmpC porin of E. coli by using a previously defined theoretical approach. 55 The lowestenergy pathway for enrofloxacin is similar to that for ciprofloxacin, energy basins for both antibiotics are located at similar positions in the two-dimensional CV space, and their affinity sites share a wide range of common porin residues. These facts are very reasonable in view of the minor difference between enrofloxacin and ciprofloxacin structures, namely, an ethyl substitution in the amino group. However, this substitution leads to some relevant modifications. In a comparison of the affinity sites to those of ciprofloxacin, enrofloxacin replaces some interactions between its amino group and polar residues by hydrophobic interactions with aliphatic and aromatic residues. Thus, a hydrophobic pocket is identified in the vicinity of the constriction region. Moreover, the enrofloxacin molecule needs to overcome higher overall energy barriers than the ciprofloxacin molecule during the translocation through the porin OmpC and, thereby, a slower diffusion process is expected. To the best of our knowledge, this is the first theoretical study that demonstrates how minor chemical modifications of an antibiotic can qualitatively affect its translocation mechanism. This finding emphasizes the key role of non-polar interactions in the permeation of large substrates across non-specific porins. Several issues need to be addressed in future studies. First, the influence of various physiologically relevant ionic salts 89,91,92 can modify the permeability through the porin OmpC in a non-trivial manner since ions can strongly interact with substrates and residues involved in the affinity sites. Second, the influence of a transmembrane potential might be

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relevant in the diffusion process although the inclusion of the electric field into the present protocol might be challenging. Third, the consideration of LPS in the outer leaflet of the OM will be required in future to simulate the OM channels in a more realistic environment as the presence of LPS might affect the dynamics of the extracellular loops of OM proteins. 93–95 Finally, simulations for the translocation of different fluoroquinolones and other classes of antibiotics through OM porins would help to provide very valuable theoretical underpinnings concerning the respective structure-function relations. The present study is one of the very few theoretical studies comparing the translocation of similar but different compounds through outer membrane channels. Since understanding the translocation of antibiotics through these nanopores constitutes a major issue in the development of new drugs, 25,26 we hope that the current findings might help to better appreciate which effects minor chemical modifications of antibiotics molecules might have on their permeation properties.

Acknowledgement The research leading to these results was conducted as part of the Translocation consortium (www.translocation.eu) and has received support from the Innovative Medicines Joint Undertaking under Grant Agreement No. 115525, resources which are composed of financial contribution from the European Unions seventh framework programme (FP7/2007- 2013) and EFPIA companies in kind contribution.

Supporting Information Available Supporting figures on computational results are available together with the force fields for the enrofloxacin molecule.

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Enrofloxacin Permeation Pathways across the Porin OmpC - The

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