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Computational design of novel, high-affinity neuraminidase inhibitors for H5N1 avian influenza virus
European Journal of Medicinal Chemistry 45 (2010) 536–541
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European Journal of Medicinal Chemistry journal homepage: http://www.elsevier.com/locate/ejmech
Original article
Computational design of novel, high-affinity neuraminidase inhibitors for H5N1 avian influenza virus Jin Woo Park, Won Ho Jo* Department of Materials Science and Engineering, Seoul National University, Kwanak-ku Seoul 151-742, Republic of Korea
a r t i c l e i n f o
a b s t r a c t
Article history: Received 6 March 2009 Received in revised form 16 October 2009 Accepted 27 October 2009 Available online 31 October 2009
To propose more effective inhibitors for neuraminidase subtype N1, four potential inhibitors were molecularly designed by substitution at the C3 position of oseltamivir to give additional interaction with the 150-cavity, since a new cavity known as the ‘150-cavity’ adjacent to the well-known active site has been found in the neuraminidase subtype N1. We calculated the binding free energy of both oseltamivir and the newly designed inhibitors for subtype N1, using molecular dynamics simulations, to predict their drug effectiveness. When the drug effectiveness of four potential inhibitors is compared with that of oseltamivir, we discovered a highly potent neuraminidase inhibitor, which exhibited much higher binding affinity to subtype N1 than oseltamivir (17.77 vs. 8.06 kcal/mol). Ó 2009 Elsevier Masson SAS. All rights reserved.
Keywords: H5N1 avian influenza Neuraminidase inhibitor Oseltamivir Molecular dynamics simulation 150-Cavity
1. Introduction Neuraminidase is one of the major surface glycoproteins of the influenza virus. This viral enzyme cleaves the terminal sialic acid from the cellular receptor, to which newly formed virions are attached. This cleavage releases the progeny virions from the infected cell, enabling them to infect other cells. By blocking this releasing mechanism, the virus completes replication only once, preventing further infection. Therefore, neuraminidase has been considered a suitable target for designing anti-influenza drugs, and structure-based design of neuraminidase inhibitors has become an important area of research that could potentially yield promising drug candidates [1,2]. Oseltamivir [3] is an efficacious and commonly used neuraminidase inhibitor for influenza treatment due to its good oral availability [4]. However, oseltamivir is not as effective against the neuraminidase subtype N1 as it is against subtypes N2 and N9 [5,6]. Luo [7] has already reported that influenza viruses with the neuraminidase subtype N1 would be resistant to oseltamivir because the side chains of Glu119 and Asp151 might not have the precise alignment required to bind the oseltamivir tightly. The two amino acids in subtypes N2 and N9, Glu119 and Asp151, are known to form strong interactions with neuraminidase inhibitors [3]. Recently,
* Corresponding author. Tel.: þ82 2 880 7192; fax: þ82 2 885 1748. E-mail address: [email protected] (W.H. Jo). 0223-5234/$ – see front matter Ó 2009 Elsevier Masson SAS. All rights reserved. doi:10.1016/j.ejmech.2009.10.040
computational studies using homology-modeled structures of subtype N1 have been performed to elucidate the reason why it cannot be used for inhibition of neuraminidase subtype N1 [8,9]. Aruksakunwong et al. [8] observed dramatic changes of 1-ethylpropoxy (–OCHEt2) and acetylamino (–NHAc) groups of oseltamivir in the binding site of subtype N1 through molecular dynamics (MD) simulation and proposed that rotation of those groups could be an important reason for low affinity of oseltamivir to subtype N1. Wang et al. [9] concluded that the changes of the hydrophobic and hydrophilic environment around 1-ethylpropoxy group of oseltamivir might be the main reason. Although zanamivir [10] is still effective against subtype N1 [5], a novel, orally active drug should be developed for treatment of highly pathogenic H5N1 avian influenza virus because zanamivir has poor oral bioavailability. According to Russell et al. [11], the active site in the N1-oseltamivir complex crystal structure differs from the active site in either the N2-oseltamivir or N9-oseltamivir complexes. More specifically, there is a large cavity, called the ‘150-cavity’, adjacent to the active site in subtype N1, but this cavity is not present in either N2 or N9. In addition to the 150-cavity, the 430-cavity was also identified only in subtype N1 by MD simulation [12]. Based on this simulation study, the 150- and 430-cavities were proposed as novel targets for developing high-affinity inhibitors [12–16]. Du et al. [15] designed neuraminidase inhibitors based on the 150-cavity in the recently determined N1 crystal structure; however, bioavailability and binding free energies of the inhibitors were not considered. Although interaction energies calculated by scoring function are
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useful in guiding inhibitor design, the binding free energy of inhibitors is required to quantitatively predict binding affinities. Estimation of the binding free energies for inhibitors to subtype N1 is useful in identifying molecules that can bind to target enzymes and act as inhibitors; these values are also useful for comparing potential of designed inhibitors. Moreover, prediction of absorption, distribution, metabolism, and excretion (ADME) properties is mandatory for developing drug-like molecules [17–19]. Recent studies on designing inhibitors targeting simultaneously several binding sites of the neuraminidase have been reported [13,16]. However, these studies focused primarily on enhancing the binding affinity of inhibitors, and therefore did not consider pharmacokinetic properties such as oral bioavailability to propose large sized molecules. Hence, we have designed potent inhibitors by modifying the molecular structure of oseltamivir to maintain the pharmacokinetic properties of oseltamivir. In this study, four new inhibitors of subtype N1 were designed to overcome the low binding affinity of oseltamivir to subtype N1 (Fig. 1). To compare their binding affinities with that of oseltamivir, the binding free energy of these inhibitors was calculated via MD simulation. In designing the inhibitors, chemical groups were introduced into oseltamivir with the proper shape and atomic charge so as to fit into the 150-cavity in subtype N1. Furthermore, Lipinski’s rule [20] was considered to anticipate the possibility for bioavailability of these inhibitors in humans. Results from this study of computer-aided molecular design of inhibitors enabled us to suggest an advanced, potent anti-influenza drug for H5N1 avian influenza. 2. Computational details 2.1. Parameter assignment of oseltamivir The atomic charges of oseltamivir were collected from Supporting Information of Masukawa’s work [21]. All equilibrium bond lengths, bond angles, and dihedral angles for oseltamivir were calculated using the DMol3 program based on the density functional theory (DFT) [22]. Electronic configurations of molecular systems were described by restricted double-numerical basis sets with polarization functions for nitrogen and oxygen, and without polarization function for carbon and hydrogen. The general gradient approximation correction was applied to the energy
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calculation with the exchange functional of Becke [23] and the correlation functional of Perdew and Wang [24]. The conductor-like screening model [25] implemented into DMol3 was used for incorporating the solvent effect into the DFT calculation [26]. The dielectric constant for the water considered in this study is 78.4. The missing force field parameters for oseltamivir were assigned based on existing similar molecules already parameterized. 2.2. MD simulations We calculated the binding free energy of a system that consists of oseltamivir-bound neuraminidase subtype N1 (Protein Data Bank, PDB ID code 2HU0) [11] embedded in a water box using the linear interaction energy (LIE) method [27]. The final structure containing 90 795 atoms was energy-minimized by the conjugate gradient method. Subsequently, the structure was initially heated from 0 to 310 K during 25 ps and equilibrated at this final temperature during another 3 ns as an NPT ensemble, using the Nose´-Hoover method at a temperature T ¼ 310 K and a pressure P ¼ 1 atm. A tetramer of neuraminidase was simulated without any restraints during the first 0.5 ns of equilibration because the MD simulation of a monomer only resulted in large fluctuation at protein terminal regions. As the 2HU0 structure had a single oseltamivir molecule bound to the active site of one monomer considered, the other three monomers were fixed during the subsequent 2.5 ns to focus our computational efforts on the calculation of the binding free energy of oseltamivir. Electrostatic interactions were computed with the particle mesh Ewald algorithm [28], and Lennard–Jones interactions were truncated at 12 Å. A time step of 1 fs was used throughout and the trajectory was sampled every 10 ps. The MD simulation program NAMD [29] was used with the CHARMM27 parameter set [30]. To design more effective inhibitors against subtype N1, we introduced new functional groups at the C3 position of oseltamivir (Fig. 1). Force field parameters and atomic charges of the attached groups of inhibitors 1, 2, 3, and 4 in Fig. 1 were obtained based on information from serine, lysine, asparagine, and glutamine, respectively. We conducted MD simulation by replacing oseltamivir with the designed inhibitors in the active site of subtype N1 using the same procedure described above. 2.3. Calculation of binding free energy (DGbind) The LIE method enables us to estimate the binding free energy from MD simulation with substantially lower computational cost. This LIE approach has recently been used to successfully investigate the prediction of binding affinity in various models of receptors and ligands [31]. The LIE method assumes that the binding free energy can be extracted from simulations of the free and bound state of the ligand. This simple approach is regarded as a good alternative to the more expensive free energy perturbation calculations [32]. The LIE equation optimized for neuraminidase inhibitors has been well investigated [33]. Wall et al. [33] has applied the LIE method to the calculation of the binding free energy of neuraminidase inhibitor using a set of 15 diverse inhibitors. They have optimized and determined the most predictive LIE weight parameters based on the N2 subtype. It is reasonable to use their LIE weight parameters to calculate the binding free energy of inhibitor with N1 subtype in this study, because their active sites are well conserved in all subtypes of neuraminidases. The equation used in this study is
Fig. 1. Schematic representation of inhibitor bound to the active site and amino acid residues lining the 150-cavity of neuraminidase subtype N1. Attachment of different chemical groups at the C3 position of oseltamivir can make additional interaction with the 150-cavity and potentially improve the binding affinity to subtype N1.
DGbind ¼ 0:122DUelec þ 0:472DUvdw þ 2:603 where DUelec and DUvdw are the differences in the averaged inhibitor-environment electrostatic and van der Waals energies,
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respectively, between the two simulations. Free ligand simulation was performed during 100 ps in NPT ensemble and then 400 ps in NVT ensemble with respect to each inhibitor. 3. Results and discussion 3.1. Design of novel inhibitors for neuraminidase subtype N1 The main objective of the present research is to design more effective N1 inhibitors using oseltamivir as a template. A recent study reported that a new cavity consisting of residues, Arg118, Glu119, and Asp151, is present in the N1 crystal structure [11] (Fig. 1). Therefore, we hypothesized that more effective inhibitors could be developed by substitution at the C3 position of oseltamivir (X in Fig. 1). It was reported that a C3-methyl analogue of oseltamivir exhibits over a 1000-fold decrease in inhibitory activity compared with the parent compound [34] while a C4-amino analogue of oseltamivir has enhanced the binding affinity due to hydrogen bonds with adjacent amino acid residues [35,36]; therefore, we assumed that the potency of the N1 inhibitors could be enhanced by attaching hydrophilic groups that is expected to favorably interact with the charged Arg118, Glu119, and Asp151 residues. Four different groups attached to oseltamivir were designed using the side chains of standard amino acids. To generate hydrogen bonds to carboxylate groups of either Glu119 or Asp151, the side chain of serine, –CH2OH, was attached to the C3 position (1 in Fig. 1). The side chain of lysine, –CH2NHþ 3 , was also attached to the C3 position because the amino group was hypothesized to have a strong interaction with the negatively charged residues of the 150-cavity (2 in Fig. 1). To design more effective inhibitors that can interact not only with the carboxylate groups of either Glu119 or Aps151, but also with the guanidino group of Arg118, we attached the side groups of asparagine (–CH2CONH2) and glutamine (–CH2CH2CONH2) to the C3 position of oseltamivir (3 and 4 in Fig. 1). Five MD simulations were performed on subtype N1 with oseltamivir and the four designed N1 inhibitors 1–4, respectively. First, the root-mean-square deviation (RMSD) profiles of the ligand and the binding monomer among the four monomers of subtype N1 excluding hydrogen atoms were analyzed relative to the initial structure (Fig. 2). This result indicates that each system had reached equilibrium, because no significant RMSD change was found after 1 ns of the MD simulation. Thus, trajectories were collected for the last 2 ns of the MD simulation to calculate interaction energies.
Fig. 2. Root-mean-square deviation (RMSD) profiles of all atoms of each inhibitor and the binding monomer except hydrogen atoms. All five systems reached the equilibrated states after 1.0 ns and the structures after 1.0 ns were used for the calculation of binding free energies.
designed to interact with the carboxylate group, strongly interacts with Arg118. However, this inhibitor 1 shows slight repulsion with Glu119 and Asp151 (Fig. 4). The oxygen atom of the –CH2OH group forms a hydrogen bond with the guanidino group of Arg118, whereas the terminal hydrogen atom points away from the carboxylate group of Glu119 (Fig. 5a). In case of inhibitor 2, the –CH2NHþ 3 group simultaneously exhibits a significantly strong charge–charge interaction with Glu119 and Asp151 (Fig. 4). On the other hand, the side chain of Arg118 moves away from the ligand due to repulsion (Figs. 4 and 5b). The –CH2CONH2 group of inhibitor 3, designed to interact well with Arg118 and Glu119 through hydrogen bonding, exhibits favorable interactions with Arg118 and Glu119, as can be seen in Fig. 4. The terminal –NH2 group of inhibitor 3 simultaneously forms hydrogen bonds with the guanidino group of Arg118 and carboxylate group of Glu119 (Fig. 5c). The
3.2. Interaction between inhibitors and adjacent amino acids lining the 150-cavity of neuraminidase subtype N1 We calculated the nonbonded (electrostatic and van der Waals) interaction energy between each inhibitor and its environment to gain insights into which chemical groups strongly interacted with amino acids in the 150-cavity (Fig. 3). While van der Waals energies of all inhibitors are nearly equal, each inhibitor shows different value of electrostatic energy, as shown in Fig. 3, because the active site of neuraminidase subtype N1 is highly charged. Since it has been known that electrostatic term strongly correlates to the binding free energy of neuraminidase inhibitor [37–39], the electrostatic energy must be considered in developing high-affinity inhibitors of neuraminidase. Fig. 4 shows the electrostatic energy between each attached chemical group (X) in the designed inhibitor and side chains of neighborhood residues located within 7 Å from X. This analysis helps to identify chemical groups that interact more favorably with the 150-cavity. The –CH2OH group of inhibitor 1, originally
Fig. 3. Nonbonded interaction energy between each inhibitor and its environment, protein and water molecules. The thick lines and thin lines correspond to electrostatic energies and van der Waals energies, respectively. The colour representation is the same as in Fig. 2.
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Fig. 4. Electrostatic energy between modified group (X) of inhibitor and the side chains of adjacent amino acid residues located within 7 Å from X.
–CH2CH2CONH2 group of inhibitor 4 was designed for the purpose of enhancement of interaction with Arg118 and Glu119 by inserting an additional –CH2– group into the inhibitor 3. However, it reveals that the inhibitor 4 interacts less favorably with Glu119 than the inhibitor 3, although it shows more favorable interaction with Arg118. Furthermore, the inhibitor 4 interacts unfavorably with Asp151.
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Binding free energies were computed using the LIE method [27]; the results are summarized in Table 1. The calculated binding free energy for oseltamivir with subtype N1 is 8.06 kcal/mol. This value is in reasonable agreement with the experimental free energy of 10.60 to 10.36 kcal/mol for oseltamivir, which was originally obtained based on a mean IC50 value of oseltamivir ranging from 36.1 to 53.2 nM for subtype N1 [5], and this agreement indicates that the parameters used in our calculation are quite reasonable. Table 1 also shows that the binding free energies for the newly designed inhibitors are lower than oseltamivir, indicating that the introduced chemical groups enhance the binding affinities of the ligands for subtype N1. The binding affinity of inhibitor 1 is slightly improved compared with oseltamivir (8.51 vs. 8.06 kcal/mol). Notably, the binding energy of inhibitor 2 was more than double (17.77 kcal/mol) that for oseltamivir. This dramatically increased affinity is believed to be a consequence of the additional charge– charge interaction due to the attached amino group. The binding affinity of inhibitor 3 is slightly lower than that of inhibitor 2 (13.95 vs. 17.77 kcal/mol), nevertheless still higher than those of oseltamivir and inhibitor 1. Surprisingly, inhibitor 4 exhibits significantly reduced affinity when compared with inhibitor 3 (9.36 vs. 13.95 kcal/mol). Trajectories from MD simulation show that inhibitor 4 is slightly slipped out of the binding site compared with oseltamivir (Fig. 6), indicating that there is a limit to the size of the attaching group that can fit snugly in the 150-cavity. 3.4. Potential for oral bioavailability of inhibitors 1–4
3.3. Binding free energy of inhibitor for neuraminidase subtype N1 Although calculation of nonbonded interaction energy between introduced chemical groups and neighboring residues lining the 150-cavity provided us with useful information about binding strength of inhibitors, it is necessary to calculate the binding free energy of each designed inhibitor to compare binding affinities.
Bioavailability is critical to the development of bioactive molecules as therapeutic agents because oral administration is the most convenient way for patients to receive medication. When a drug is administered orally, it has to be absorbed across the epithelium of the small intestine. Molecular polar surface area (PSA) is one of the most important descriptor for the prediction of intestinal
Fig. 5. The final structures of MD simulations for inhibitors and neighboring residues in the 150-cavity of subtype N1. Inhibitors 1–4 in the active pocket are shown in (a)–(d), respectively. The residues and inhibitors are depicted in the stick model. The elements C, N, O, and H are shown in green (yellow in inhibitors), blue, red, and grey, respectively. Interactions between the modified group and neighboring residue atoms are shown as blue dashed line. Water molecules were eliminated for clarity. (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)
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Table 1 Binding free energy (kcal/mol) of oseltamivir and inhibitors 1–4 for neuraminidase subtype N1. Inhibitor
DUeleca
DUvdwb
DGbindc
Oseltamivir 1 2 3 4
47.26 56.19 140.99 144.03 62.48
10.37 9.03 6.71 5.60 9.19
8.06 (10.60 to 10.36)d 8.51 17.77 13.95 9.36
a b c d
Difference of electrostatic energy between bound and free simulations. Difference of van der Waals energy between bound and free simulations. Change of free energy in binding. Converted from the IC50 value of 36.1–53.2 nM [5] by DGbind ¼ RT ln IC50.
absorption [19,40–42]. Compounds that have PSA equal to or less than 140 Å2 and 10 or fewer rotatable bonds have been proposed to have high oral bioavailability [41,42]. Because various methods for rapid computation of PSA have been developed [42,43], we could easily calculate the PSA of each designed inhibitor. Inhibitors 1 and 2 as well as oseltamivir meet the two criteria (Table 2). Moreover, there is no danger that inhibitors 1 and 2 may affect the central nervous system through blood–brain barrier penetration, considering that their PSAs are larger than 100 Å2 [17]. ADME properties are important for evaluating the potential of a drug to be orally active in humans because the body will try to eliminate xenobiotics, including drugs. Unfortunately, there is currently no rigorous computational method to predict oral bioavailability in humans [44]. However, there has been much effort to correlate molecular properties with the bioavailability [17,18,20,41,45]. Among them, the most popular rule-based prediction model for oral bioavailability is Lipinski’s ‘rule of five’, which describes molecular properties important for desirable pharmacokinetics in the human body, including their ADME properties [20]. According to this rule, if two out of the following criteria are into the range, then poor bioavailability is possible: the molecular weight is over 500 g/mol, the number of hydrogen bond donors is more than 5, the number of hydrogen bond acceptors is more than 10, and the calculated octanol–water partition coefficient (log P) is over 5. In addition, it has also been proposed that drug-like molecules must have the log P value between 0.4 and 5.6 [46]. Table 2 summarizes physicochemical properties of the designed inhibitors as well as oseltamivir, and shows that inhibitors 1 and 2 meet the criteria; however these inhibitors will need to be analyzed in an in vivo experiment to examine their true potential for oral bioavailability. According to the above analysis, the inhibitor 2 is expected to be a good drug candidate because it has the possibility for oral
Table 2 Physicochemical properties of oseltamivir and the designed inhibitors 1–4. Inhibitor
MWa
NHB-Db
NHB-Ac
Log Pd
TPSAe
Nrotf
Oseltamivir 1 2 3 4
284 314 314 341 355
4 5 7 6 6
6 7 7 8 8
0.45 0.44 0.23 0.46 0.14 0.46 0.71 0.48 0.64 0.47
106.10 126.33 133.74 149.19 149.19
6 7 7 8 9
a
Molecular weight (g/mol). Number of hydrogen bond donors. Number of hydrogen bond acceptors. d Octanol–water partition coefficients, log P, were calculated using the ACD/Log P Freeware. e Topological polar surface area (Å2) [42]. f Number of rotatable bonds. b
c
bioavailability as well as a strong binding affinity. However, there are numerous enzymatic processes in the human body such as hepatic metabolism that may not be encompassed by the prediction models [44]. Future synthesis and clinical studies examining inhibitor 2 as a lead compound are required to assess the oral bioavailability. 4. Conclusions Based on the recently revealed crystal structure of neuraminidase subtype N1, four new inhibitors, 1–4 (see Fig. 1), were designed to obtain a potent antiviral drug against H5N1 avian influenza. Attachment of chemical groups at the C3 position of oseltamivir successfully improved the binding affinity with neuraminidase subtype N1. We found that calculated affinities of inhibitors 2 and 3 to subtype N1 are much stronger than oseltamivir. Considering both the binding affinity and bioavailability, we recommend the inhibitor 2 as a drug-like molecule for H5N1 avian influenza virus, although further experimental investigation regarding the oral bioavailability should be pursued to confirm that the inhibitor 2 can function effectively in humans. Acknowledgments The authors thank the Ministry of Education, Science and Technology (MEST), Korea for financial support through the Global Research Laboratory (GRL) program. Appendix. Supplementary data Supplementary data associated with this article can be found in the online version, at doi:10.1016/j.ejmech.2009.10.040. References
Fig. 6. Superposition of binding poses of oseltamivir (green) and inhibitor 4 (magenta). Inhibitor 4 is slipped out of the binding site (2.7 Å on the average) compared with oseltamivir. (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)
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Contents lists available at ScienceDirect
European Journal of Medicinal Chemistry journal homepage: http://www.elsevier.com/locate/ejmech
Original article
Computational design of novel, high-affinity neuraminidase inhibitors for H5N1 avian influenza virus Jin Woo Park, Won Ho Jo* Department of Materials Science and Engineering, Seoul National University, Kwanak-ku Seoul 151-742, Republic of Korea
a r t i c l e i n f o
a b s t r a c t
Article history: Received 6 March 2009 Received in revised form 16 October 2009 Accepted 27 October 2009 Available online 31 October 2009
To propose more effective inhibitors for neuraminidase subtype N1, four potential inhibitors were molecularly designed by substitution at the C3 position of oseltamivir to give additional interaction with the 150-cavity, since a new cavity known as the ‘150-cavity’ adjacent to the well-known active site has been found in the neuraminidase subtype N1. We calculated the binding free energy of both oseltamivir and the newly designed inhibitors for subtype N1, using molecular dynamics simulations, to predict their drug effectiveness. When the drug effectiveness of four potential inhibitors is compared with that of oseltamivir, we discovered a highly potent neuraminidase inhibitor, which exhibited much higher binding affinity to subtype N1 than oseltamivir (17.77 vs. 8.06 kcal/mol). Ó 2009 Elsevier Masson SAS. All rights reserved.
Keywords: H5N1 avian influenza Neuraminidase inhibitor Oseltamivir Molecular dynamics simulation 150-Cavity
1. Introduction Neuraminidase is one of the major surface glycoproteins of the influenza virus. This viral enzyme cleaves the terminal sialic acid from the cellular receptor, to which newly formed virions are attached. This cleavage releases the progeny virions from the infected cell, enabling them to infect other cells. By blocking this releasing mechanism, the virus completes replication only once, preventing further infection. Therefore, neuraminidase has been considered a suitable target for designing anti-influenza drugs, and structure-based design of neuraminidase inhibitors has become an important area of research that could potentially yield promising drug candidates [1,2]. Oseltamivir [3] is an efficacious and commonly used neuraminidase inhibitor for influenza treatment due to its good oral availability [4]. However, oseltamivir is not as effective against the neuraminidase subtype N1 as it is against subtypes N2 and N9 [5,6]. Luo [7] has already reported that influenza viruses with the neuraminidase subtype N1 would be resistant to oseltamivir because the side chains of Glu119 and Asp151 might not have the precise alignment required to bind the oseltamivir tightly. The two amino acids in subtypes N2 and N9, Glu119 and Asp151, are known to form strong interactions with neuraminidase inhibitors [3]. Recently,
* Corresponding author. Tel.: þ82 2 880 7192; fax: þ82 2 885 1748. E-mail address: [email protected] (W.H. Jo). 0223-5234/$ – see front matter Ó 2009 Elsevier Masson SAS. All rights reserved. doi:10.1016/j.ejmech.2009.10.040
computational studies using homology-modeled structures of subtype N1 have been performed to elucidate the reason why it cannot be used for inhibition of neuraminidase subtype N1 [8,9]. Aruksakunwong et al. [8] observed dramatic changes of 1-ethylpropoxy (–OCHEt2) and acetylamino (–NHAc) groups of oseltamivir in the binding site of subtype N1 through molecular dynamics (MD) simulation and proposed that rotation of those groups could be an important reason for low affinity of oseltamivir to subtype N1. Wang et al. [9] concluded that the changes of the hydrophobic and hydrophilic environment around 1-ethylpropoxy group of oseltamivir might be the main reason. Although zanamivir [10] is still effective against subtype N1 [5], a novel, orally active drug should be developed for treatment of highly pathogenic H5N1 avian influenza virus because zanamivir has poor oral bioavailability. According to Russell et al. [11], the active site in the N1-oseltamivir complex crystal structure differs from the active site in either the N2-oseltamivir or N9-oseltamivir complexes. More specifically, there is a large cavity, called the ‘150-cavity’, adjacent to the active site in subtype N1, but this cavity is not present in either N2 or N9. In addition to the 150-cavity, the 430-cavity was also identified only in subtype N1 by MD simulation [12]. Based on this simulation study, the 150- and 430-cavities were proposed as novel targets for developing high-affinity inhibitors [12–16]. Du et al. [15] designed neuraminidase inhibitors based on the 150-cavity in the recently determined N1 crystal structure; however, bioavailability and binding free energies of the inhibitors were not considered. Although interaction energies calculated by scoring function are
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useful in guiding inhibitor design, the binding free energy of inhibitors is required to quantitatively predict binding affinities. Estimation of the binding free energies for inhibitors to subtype N1 is useful in identifying molecules that can bind to target enzymes and act as inhibitors; these values are also useful for comparing potential of designed inhibitors. Moreover, prediction of absorption, distribution, metabolism, and excretion (ADME) properties is mandatory for developing drug-like molecules [17–19]. Recent studies on designing inhibitors targeting simultaneously several binding sites of the neuraminidase have been reported [13,16]. However, these studies focused primarily on enhancing the binding affinity of inhibitors, and therefore did not consider pharmacokinetic properties such as oral bioavailability to propose large sized molecules. Hence, we have designed potent inhibitors by modifying the molecular structure of oseltamivir to maintain the pharmacokinetic properties of oseltamivir. In this study, four new inhibitors of subtype N1 were designed to overcome the low binding affinity of oseltamivir to subtype N1 (Fig. 1). To compare their binding affinities with that of oseltamivir, the binding free energy of these inhibitors was calculated via MD simulation. In designing the inhibitors, chemical groups were introduced into oseltamivir with the proper shape and atomic charge so as to fit into the 150-cavity in subtype N1. Furthermore, Lipinski’s rule [20] was considered to anticipate the possibility for bioavailability of these inhibitors in humans. Results from this study of computer-aided molecular design of inhibitors enabled us to suggest an advanced, potent anti-influenza drug for H5N1 avian influenza. 2. Computational details 2.1. Parameter assignment of oseltamivir The atomic charges of oseltamivir were collected from Supporting Information of Masukawa’s work [21]. All equilibrium bond lengths, bond angles, and dihedral angles for oseltamivir were calculated using the DMol3 program based on the density functional theory (DFT) [22]. Electronic configurations of molecular systems were described by restricted double-numerical basis sets with polarization functions for nitrogen and oxygen, and without polarization function for carbon and hydrogen. The general gradient approximation correction was applied to the energy
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calculation with the exchange functional of Becke [23] and the correlation functional of Perdew and Wang [24]. The conductor-like screening model [25] implemented into DMol3 was used for incorporating the solvent effect into the DFT calculation [26]. The dielectric constant for the water considered in this study is 78.4. The missing force field parameters for oseltamivir were assigned based on existing similar molecules already parameterized. 2.2. MD simulations We calculated the binding free energy of a system that consists of oseltamivir-bound neuraminidase subtype N1 (Protein Data Bank, PDB ID code 2HU0) [11] embedded in a water box using the linear interaction energy (LIE) method [27]. The final structure containing 90 795 atoms was energy-minimized by the conjugate gradient method. Subsequently, the structure was initially heated from 0 to 310 K during 25 ps and equilibrated at this final temperature during another 3 ns as an NPT ensemble, using the Nose´-Hoover method at a temperature T ¼ 310 K and a pressure P ¼ 1 atm. A tetramer of neuraminidase was simulated without any restraints during the first 0.5 ns of equilibration because the MD simulation of a monomer only resulted in large fluctuation at protein terminal regions. As the 2HU0 structure had a single oseltamivir molecule bound to the active site of one monomer considered, the other three monomers were fixed during the subsequent 2.5 ns to focus our computational efforts on the calculation of the binding free energy of oseltamivir. Electrostatic interactions were computed with the particle mesh Ewald algorithm [28], and Lennard–Jones interactions were truncated at 12 Å. A time step of 1 fs was used throughout and the trajectory was sampled every 10 ps. The MD simulation program NAMD [29] was used with the CHARMM27 parameter set [30]. To design more effective inhibitors against subtype N1, we introduced new functional groups at the C3 position of oseltamivir (Fig. 1). Force field parameters and atomic charges of the attached groups of inhibitors 1, 2, 3, and 4 in Fig. 1 were obtained based on information from serine, lysine, asparagine, and glutamine, respectively. We conducted MD simulation by replacing oseltamivir with the designed inhibitors in the active site of subtype N1 using the same procedure described above. 2.3. Calculation of binding free energy (DGbind) The LIE method enables us to estimate the binding free energy from MD simulation with substantially lower computational cost. This LIE approach has recently been used to successfully investigate the prediction of binding affinity in various models of receptors and ligands [31]. The LIE method assumes that the binding free energy can be extracted from simulations of the free and bound state of the ligand. This simple approach is regarded as a good alternative to the more expensive free energy perturbation calculations [32]. The LIE equation optimized for neuraminidase inhibitors has been well investigated [33]. Wall et al. [33] has applied the LIE method to the calculation of the binding free energy of neuraminidase inhibitor using a set of 15 diverse inhibitors. They have optimized and determined the most predictive LIE weight parameters based on the N2 subtype. It is reasonable to use their LIE weight parameters to calculate the binding free energy of inhibitor with N1 subtype in this study, because their active sites are well conserved in all subtypes of neuraminidases. The equation used in this study is
Fig. 1. Schematic representation of inhibitor bound to the active site and amino acid residues lining the 150-cavity of neuraminidase subtype N1. Attachment of different chemical groups at the C3 position of oseltamivir can make additional interaction with the 150-cavity and potentially improve the binding affinity to subtype N1.
DGbind ¼ 0:122DUelec þ 0:472DUvdw þ 2:603 where DUelec and DUvdw are the differences in the averaged inhibitor-environment electrostatic and van der Waals energies,
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respectively, between the two simulations. Free ligand simulation was performed during 100 ps in NPT ensemble and then 400 ps in NVT ensemble with respect to each inhibitor. 3. Results and discussion 3.1. Design of novel inhibitors for neuraminidase subtype N1 The main objective of the present research is to design more effective N1 inhibitors using oseltamivir as a template. A recent study reported that a new cavity consisting of residues, Arg118, Glu119, and Asp151, is present in the N1 crystal structure [11] (Fig. 1). Therefore, we hypothesized that more effective inhibitors could be developed by substitution at the C3 position of oseltamivir (X in Fig. 1). It was reported that a C3-methyl analogue of oseltamivir exhibits over a 1000-fold decrease in inhibitory activity compared with the parent compound [34] while a C4-amino analogue of oseltamivir has enhanced the binding affinity due to hydrogen bonds with adjacent amino acid residues [35,36]; therefore, we assumed that the potency of the N1 inhibitors could be enhanced by attaching hydrophilic groups that is expected to favorably interact with the charged Arg118, Glu119, and Asp151 residues. Four different groups attached to oseltamivir were designed using the side chains of standard amino acids. To generate hydrogen bonds to carboxylate groups of either Glu119 or Asp151, the side chain of serine, –CH2OH, was attached to the C3 position (1 in Fig. 1). The side chain of lysine, –CH2NHþ 3 , was also attached to the C3 position because the amino group was hypothesized to have a strong interaction with the negatively charged residues of the 150-cavity (2 in Fig. 1). To design more effective inhibitors that can interact not only with the carboxylate groups of either Glu119 or Aps151, but also with the guanidino group of Arg118, we attached the side groups of asparagine (–CH2CONH2) and glutamine (–CH2CH2CONH2) to the C3 position of oseltamivir (3 and 4 in Fig. 1). Five MD simulations were performed on subtype N1 with oseltamivir and the four designed N1 inhibitors 1–4, respectively. First, the root-mean-square deviation (RMSD) profiles of the ligand and the binding monomer among the four monomers of subtype N1 excluding hydrogen atoms were analyzed relative to the initial structure (Fig. 2). This result indicates that each system had reached equilibrium, because no significant RMSD change was found after 1 ns of the MD simulation. Thus, trajectories were collected for the last 2 ns of the MD simulation to calculate interaction energies.
Fig. 2. Root-mean-square deviation (RMSD) profiles of all atoms of each inhibitor and the binding monomer except hydrogen atoms. All five systems reached the equilibrated states after 1.0 ns and the structures after 1.0 ns were used for the calculation of binding free energies.
designed to interact with the carboxylate group, strongly interacts with Arg118. However, this inhibitor 1 shows slight repulsion with Glu119 and Asp151 (Fig. 4). The oxygen atom of the –CH2OH group forms a hydrogen bond with the guanidino group of Arg118, whereas the terminal hydrogen atom points away from the carboxylate group of Glu119 (Fig. 5a). In case of inhibitor 2, the –CH2NHþ 3 group simultaneously exhibits a significantly strong charge–charge interaction with Glu119 and Asp151 (Fig. 4). On the other hand, the side chain of Arg118 moves away from the ligand due to repulsion (Figs. 4 and 5b). The –CH2CONH2 group of inhibitor 3, designed to interact well with Arg118 and Glu119 through hydrogen bonding, exhibits favorable interactions with Arg118 and Glu119, as can be seen in Fig. 4. The terminal –NH2 group of inhibitor 3 simultaneously forms hydrogen bonds with the guanidino group of Arg118 and carboxylate group of Glu119 (Fig. 5c). The
3.2. Interaction between inhibitors and adjacent amino acids lining the 150-cavity of neuraminidase subtype N1 We calculated the nonbonded (electrostatic and van der Waals) interaction energy between each inhibitor and its environment to gain insights into which chemical groups strongly interacted with amino acids in the 150-cavity (Fig. 3). While van der Waals energies of all inhibitors are nearly equal, each inhibitor shows different value of electrostatic energy, as shown in Fig. 3, because the active site of neuraminidase subtype N1 is highly charged. Since it has been known that electrostatic term strongly correlates to the binding free energy of neuraminidase inhibitor [37–39], the electrostatic energy must be considered in developing high-affinity inhibitors of neuraminidase. Fig. 4 shows the electrostatic energy between each attached chemical group (X) in the designed inhibitor and side chains of neighborhood residues located within 7 Å from X. This analysis helps to identify chemical groups that interact more favorably with the 150-cavity. The –CH2OH group of inhibitor 1, originally
Fig. 3. Nonbonded interaction energy between each inhibitor and its environment, protein and water molecules. The thick lines and thin lines correspond to electrostatic energies and van der Waals energies, respectively. The colour representation is the same as in Fig. 2.
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Fig. 4. Electrostatic energy between modified group (X) of inhibitor and the side chains of adjacent amino acid residues located within 7 Å from X.
–CH2CH2CONH2 group of inhibitor 4 was designed for the purpose of enhancement of interaction with Arg118 and Glu119 by inserting an additional –CH2– group into the inhibitor 3. However, it reveals that the inhibitor 4 interacts less favorably with Glu119 than the inhibitor 3, although it shows more favorable interaction with Arg118. Furthermore, the inhibitor 4 interacts unfavorably with Asp151.
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Binding free energies were computed using the LIE method [27]; the results are summarized in Table 1. The calculated binding free energy for oseltamivir with subtype N1 is 8.06 kcal/mol. This value is in reasonable agreement with the experimental free energy of 10.60 to 10.36 kcal/mol for oseltamivir, which was originally obtained based on a mean IC50 value of oseltamivir ranging from 36.1 to 53.2 nM for subtype N1 [5], and this agreement indicates that the parameters used in our calculation are quite reasonable. Table 1 also shows that the binding free energies for the newly designed inhibitors are lower than oseltamivir, indicating that the introduced chemical groups enhance the binding affinities of the ligands for subtype N1. The binding affinity of inhibitor 1 is slightly improved compared with oseltamivir (8.51 vs. 8.06 kcal/mol). Notably, the binding energy of inhibitor 2 was more than double (17.77 kcal/mol) that for oseltamivir. This dramatically increased affinity is believed to be a consequence of the additional charge– charge interaction due to the attached amino group. The binding affinity of inhibitor 3 is slightly lower than that of inhibitor 2 (13.95 vs. 17.77 kcal/mol), nevertheless still higher than those of oseltamivir and inhibitor 1. Surprisingly, inhibitor 4 exhibits significantly reduced affinity when compared with inhibitor 3 (9.36 vs. 13.95 kcal/mol). Trajectories from MD simulation show that inhibitor 4 is slightly slipped out of the binding site compared with oseltamivir (Fig. 6), indicating that there is a limit to the size of the attaching group that can fit snugly in the 150-cavity. 3.4. Potential for oral bioavailability of inhibitors 1–4
3.3. Binding free energy of inhibitor for neuraminidase subtype N1 Although calculation of nonbonded interaction energy between introduced chemical groups and neighboring residues lining the 150-cavity provided us with useful information about binding strength of inhibitors, it is necessary to calculate the binding free energy of each designed inhibitor to compare binding affinities.
Bioavailability is critical to the development of bioactive molecules as therapeutic agents because oral administration is the most convenient way for patients to receive medication. When a drug is administered orally, it has to be absorbed across the epithelium of the small intestine. Molecular polar surface area (PSA) is one of the most important descriptor for the prediction of intestinal
Fig. 5. The final structures of MD simulations for inhibitors and neighboring residues in the 150-cavity of subtype N1. Inhibitors 1–4 in the active pocket are shown in (a)–(d), respectively. The residues and inhibitors are depicted in the stick model. The elements C, N, O, and H are shown in green (yellow in inhibitors), blue, red, and grey, respectively. Interactions between the modified group and neighboring residue atoms are shown as blue dashed line. Water molecules were eliminated for clarity. (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)
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Table 1 Binding free energy (kcal/mol) of oseltamivir and inhibitors 1–4 for neuraminidase subtype N1. Inhibitor
DUeleca
DUvdwb
DGbindc
Oseltamivir 1 2 3 4
47.26 56.19 140.99 144.03 62.48
10.37 9.03 6.71 5.60 9.19
8.06 (10.60 to 10.36)d 8.51 17.77 13.95 9.36
a b c d
Difference of electrostatic energy between bound and free simulations. Difference of van der Waals energy between bound and free simulations. Change of free energy in binding. Converted from the IC50 value of 36.1–53.2 nM [5] by DGbind ¼ RT ln IC50.
absorption [19,40–42]. Compounds that have PSA equal to or less than 140 Å2 and 10 or fewer rotatable bonds have been proposed to have high oral bioavailability [41,42]. Because various methods for rapid computation of PSA have been developed [42,43], we could easily calculate the PSA of each designed inhibitor. Inhibitors 1 and 2 as well as oseltamivir meet the two criteria (Table 2). Moreover, there is no danger that inhibitors 1 and 2 may affect the central nervous system through blood–brain barrier penetration, considering that their PSAs are larger than 100 Å2 [17]. ADME properties are important for evaluating the potential of a drug to be orally active in humans because the body will try to eliminate xenobiotics, including drugs. Unfortunately, there is currently no rigorous computational method to predict oral bioavailability in humans [44]. However, there has been much effort to correlate molecular properties with the bioavailability [17,18,20,41,45]. Among them, the most popular rule-based prediction model for oral bioavailability is Lipinski’s ‘rule of five’, which describes molecular properties important for desirable pharmacokinetics in the human body, including their ADME properties [20]. According to this rule, if two out of the following criteria are into the range, then poor bioavailability is possible: the molecular weight is over 500 g/mol, the number of hydrogen bond donors is more than 5, the number of hydrogen bond acceptors is more than 10, and the calculated octanol–water partition coefficient (log P) is over 5. In addition, it has also been proposed that drug-like molecules must have the log P value between 0.4 and 5.6 [46]. Table 2 summarizes physicochemical properties of the designed inhibitors as well as oseltamivir, and shows that inhibitors 1 and 2 meet the criteria; however these inhibitors will need to be analyzed in an in vivo experiment to examine their true potential for oral bioavailability. According to the above analysis, the inhibitor 2 is expected to be a good drug candidate because it has the possibility for oral
Table 2 Physicochemical properties of oseltamivir and the designed inhibitors 1–4. Inhibitor
MWa
NHB-Db
NHB-Ac
Log Pd
TPSAe
Nrotf
Oseltamivir 1 2 3 4
284 314 314 341 355
4 5 7 6 6
6 7 7 8 8
0.45 0.44 0.23 0.46 0.14 0.46 0.71 0.48 0.64 0.47
106.10 126.33 133.74 149.19 149.19
6 7 7 8 9
a
Molecular weight (g/mol). Number of hydrogen bond donors. Number of hydrogen bond acceptors. d Octanol–water partition coefficients, log P, were calculated using the ACD/Log P Freeware. e Topological polar surface area (Å2) [42]. f Number of rotatable bonds. b
c
bioavailability as well as a strong binding affinity. However, there are numerous enzymatic processes in the human body such as hepatic metabolism that may not be encompassed by the prediction models [44]. Future synthesis and clinical studies examining inhibitor 2 as a lead compound are required to assess the oral bioavailability. 4. Conclusions Based on the recently revealed crystal structure of neuraminidase subtype N1, four new inhibitors, 1–4 (see Fig. 1), were designed to obtain a potent antiviral drug against H5N1 avian influenza. Attachment of chemical groups at the C3 position of oseltamivir successfully improved the binding affinity with neuraminidase subtype N1. We found that calculated affinities of inhibitors 2 and 3 to subtype N1 are much stronger than oseltamivir. Considering both the binding affinity and bioavailability, we recommend the inhibitor 2 as a drug-like molecule for H5N1 avian influenza virus, although further experimental investigation regarding the oral bioavailability should be pursued to confirm that the inhibitor 2 can function effectively in humans. Acknowledgments The authors thank the Ministry of Education, Science and Technology (MEST), Korea for financial support through the Global Research Laboratory (GRL) program. Appendix. Supplementary data Supplementary data associated with this article can be found in the online version, at doi:10.1016/j.ejmech.2009.10.040. References
Fig. 6. Superposition of binding poses of oseltamivir (green) and inhibitor 4 (magenta). Inhibitor 4 is slipped out of the binding site (2.7 Å on the average) compared with oseltamivir. (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)
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