2. Materials & methods

2.1. Homology model:

Homology modeling of the Neuraminidase of H1N1 was performed using Modeller software

[A. Sali, T.L. Blundell, Comparative protein modeling by satisfaction of spatial restraints, J.

Mol. Biol. 234 (1993) 779–815]. The amino acid sequence of Neuraminidase was retrieved

from GenBank (accession number: ACP41952) in NCBI. The Neuraminidase was then

subjected to a BLAST search [S.F. Altschul, T.L. Madden, A.A. Schaffer, J.H. Zhang, Z.

Zhang, W. Miller, J.T. Lipman, Gapped BLAST and PSI-BLAST: a new generation of

protein database search programs, Nucleic Acids Res. 25 (1997) 3389–3402] in order to

identify the homologous proteins from the Brookhaven Protein Data Bank (PDB). An

appropriate template for SBD was identified based on the e-value and sequence identity. The

template and the target sequences were then aligned using ClustalW [Larkin MA,

Blackshields G, Brown NP, Chenna R, McGettigan PA, McWilliam H, Valentin F, Wallace

IM, Wilm A, Lopez R, Thompson JD, Gibson TJ and Higgins DG. Bioinformatics 2007

23(21): 2947-2948]. Subsequently, homology modeling was carried out for the

Neuraminidase of H1N1 against the chosen template using Modeller. The outcomes of the

modeled structures were ranked on the basis of an internal scoring function, and those with

the least internal scores were identified and utilized for model validation.

2.2. Model validation:

In order to assess the reliability of the modeled structure of Neuraminidase, we calculated the

root mean square deviation (RMSD) by superimposing it on the template structure. The

backbone conformation of the modeled structure was calculated by analyzing the phi (Φ) and

psi (ψ) torsion angles using rampage [S.C. Lovell, I.W. Davis, W.B. Arendall III, P.I.W. de Bakker, J.M.

Word, M.G. Prisant, J.S. Richardson and D.C. Richardson (2002) Structure validation by Calpha geometry:

phi,psi and Cbeta deviation. Proteins: Structure, Function & Genetics. 50: 437-450], as determined by

Ramachandran plot statistics. Finally, the statistics of non-bonded interactions was calculated

by ERRAT [Colovos C, Yeates TO. (1993). Verification of protein structures: patterns of nonbonded atomic

interactions. Protein Sci. 2, 1511-1519].

2.3. Molecular Docking & Virtual screening of Neuraminidase inhibitors:

Oseltamivir and zanamivir were constructed and minimized using the UCSF Chimera

modeling program [UCSF Chimera--a visualization system for exploratory research and

analysis. Pettersen EF, Goddard TD, Huang CC, Couch GS, Greenblatt DM, Meng EC,

Ferrin TE. J Comput Chem. 2004 Oct;25(13):1605-12]. We aligned the structures of the

model and the template (PDB ID: 3B7E), and then used the orientation of zanamivir in the

template to identify the general binding pocket of the model.

The substrates were docked into the active site of the refined A(H1N1) neuraminidase

structure using AutoDock version 3.0.5 [G.M. Morris, D.S. Goodsell, R.S. Halliday, R. Huey,

W.E. Hart, R.K. Belew, A.J. Olson, Automated docking using a Lamarckian genetic

algorithm and an empirical binding free energy function, J. Comput. Chem. 19 (1998) 1639–

1662.]. using the implemented empirical free energy function and the Lamarckian Genetic

Algorithm (LGA). The grid maps were calculated using AutoGrid. In all dockings, a grid

map with 50×50×50 points and a grid-point spacing of 0.375 Å was applied. Because the

location of the ligand in the complex was known, the maps were centered on the ligand's

binding site. One hundred solutions were generated for each docking with the default setting

and clustered with the RMSD cutoff set to 0.5 Å. The solution that has the lowest energy in

the individual cluster was chosen for further analysis.

The software DOCK6.2 software package [T.J.A. Ewing, I.D. Kuntz, Critical

evaluation of search algorithms for automated molecular docking and database screening, J.

Comput. Chem. 18 (1996) 1175–1189] was then applied in the virtual screening. The

molecular modeling program UCSF Chimera [UCSF Chimera--a visualization system for

exploratory research and analysis. Pettersen EF, Goddard TD, Huang CC, Couch GS,

Greenblatt DM, Meng EC, Ferrin TE. J Comput Chem. 2004 Oct;25(13):1605-12] was used

to prepare the receptor (Neuraminidase). The DOCK6 sphgen tool was used to create receptor

spheres with radii between 1.4 Å and 5.5 Å. Spheres within 10 Å of the center of the dimer

interface were selected for use in docking simulation, and a grid box was generated extending

out 5 Å from the spheres. Docking was performed by incorporating ligand flexibility, and

Amber scores were used for analysis. The lead-like compounds(523,366) were obtained from

ZINC database[Irwin and Shoichet, J. Chem. Inf. Model. 2005;45(1):177-82], a free database

of commercially-available compounds for virtual screening, provided by the Shoichet

Laboratory in the Department of Pharmaceutical Chemistry at the University of California,

San Francisco (UCSF).

2.4. Molecular Dynamics simulations:

The GROMACS 4.5.4 package [Hess, B.; Kutzner, C.; van der Spoel, D.; Lindahl, E.

GROMACS 4:Algorithms for highly efficient, load-balanced, and scalable molecular

simulation. J. Chem. Theory Comput. 2008, 4, 435–447] was used to run Molecular

Dynamics simulations with the GROMOS96 43a1 force field [van Gunsteren, W.; Billeter, S.

R.; Eising, A. A.; Hunenberger, P. H.; Kruger, P.; Mark, A. E.; Scott, W. R. P.; Tironi., I. G.

Biomolecular Simulation: The GROMOS96 Manual and User Guide; Vdf Hochschulverlag

AG an der ETH Zurich: Zurich, Switzerland, 1996] and the SPC216 water model [Berendsen,

H. J. C.; Postma, J. P. M.; van Gunsteren, W. F.; Hermans, J. Intermolecular Forces; Reidel,

Dordrecht, The Netherlands, 1981]. The modeled Neuraminidase was energy minimized

using the Optimized Potentials for Liquid Simulations All Atom (OPLS) force field. This

preliminary energy minimization was done to discard the high-energy intramolecular

interactions. The overall geometry and atomic charges were optimized to avoid steric clashes.

Then the whole system was gradually heated from 0 to 300 K over 500 ps using the NVT

ensemble run with the Berendsen procedure[Berendsen, H. J. C.; Postma, J. P. M.; van

Gunsteren, W. F.; Dinola, A.; Haak, J. R. Molecular dynamics with coupling to an external

bath. J. Chem. Phys. 1984, 81, 3684–3690] and, subsequently in 500 ps NPT ensemble run at

pressure of 1atm. The Parrinello-Rahman pressure coupling [Parrinello, M.; Rahman, A.

Polymorphic transitions in single crystals: A new molecular dynamics method. J. Appl. Phys.

1981, 52, 7182–7190] has been used. Finally, an 10 MD simulation was carried out to

examine the changes and dynamic behaviour of the protein were analyzed by calculating the

RMSD and energy.

2.5. ADME Screening

The pharmacokinetic feature which gives idea about Absorption, Distribution,

Metabolism and Excretion/Toxicity (ADME/T) taken into account in this work. In fact, it

would be extremely advantageous if information about the ADME properties of the studied

molecules could be produced in the early stages of the drug discovery process. Once

obtained, this information is expected to help chemists to ameliorate the pharmacokinetic

profile of the compounds.

Results & Discussion

3.1. The Results of Homology modeling of Neuraminidase and its evaluation:

The neuraminidase sequence of A/H1N1/2009 was performed the NCBI BLAST.

Neuraminidase of A/Brevig Mission/1/1918 H1N1 strain was identified as homologous from

Protein Data Bank (PDB) (PDB ID: 3B7E). The automated sequence alignment (Fig. 1) and

analysis of the template and target was carried out using the ClustalW program [Larkin MA,

Blackshields G, Brown NP, Chenna R, McGettigan PA, McWilliam H, Valentin F, Wallace IM, Wilm A, Lopez

R, Thompson JD, Gibson TJ and Higgins DG. Bioinformatics 2007 23(21): 2947-2948. ]. Therefore, 3B7E

was identified as a promising template that had a sequence similarity of 88.8% to the

neuraminidase of A/H1N1/2009. The MODELLER package has been used to model the

structure of A (H1N1) neuraminidase.

3B7E_A|PDBID|CHAIN|SEQUENCE ------VILTGNSSLCPISGWAIYSKDNGIRIGSKGDVFVIREPFISCSH 44A_H1N1__Neuraminidase GQSVVSVKLAGNSSLCPVSGWAIYSKDNSVRIGSKGDVFVIREPFISCSP 50 * *:*******:**********.:*******************

3B7E_A|PDBID|CHAIN|SEQUENCE LECRTFFLTQGALLNDKHSNGTVKDRSPYRTLMSCPVGEAPSPYNSRFES 94A_H1N1__Neuraminidase LECRTFFLTQGALLNDKHSNGTIKDRSPYRTLMSCPIGEVPSPYNSRFES 100 **********************:*************:**.**********

3B7E_A|PDBID|CHAIN|SEQUENCE VAWSASACHDGMGWLTIGISGPDNGAVAVLKYNGIITDTIKSWRNNILRT 144A_H1N1__Neuraminidase VAWSASACHDGINWLTIGISGPDNGAVAVLKYNGIITDTIKSWRNNILRT 150 ***********:.*************************************

3B7E_A|PDBID|CHAIN|SEQUENCE QESECACVNGSCFTIMTDGPSNGQASYKILKIEKGKVTKSIELNAPNYHY 194A_H1N1__Neuraminidase QESECACVNGSCFTVMTDGPSNGQASYKIFRIEKGKIVKSVEMNAPNYHY 200 **************:**************::*****:.**:*:*******

3B7E_A|PDBID|CHAIN|SEQUENCE EECSCYPDTGKVMCVCRDNWHGSNRPWVSFDQNLDYQIGYICSGVFGDNP 244A_H1N1__Neuraminidase EECSCYPDSSEITCVCRDNWHGSNRPWVSFNQNLEYQIGYICSGIFGDNP 250 ********:.:: *****************:***:*********:*****

3B7E_A|PDBID|CHAIN|SEQUENCE RPNDGTGSCGPVSSNGANGIKGFSFRYDNGVWIGRTKSTSSRSGFEMIWD 294A_H1N1__Neuraminidase RPNDKTGSCGPVSSNGANGVKGFSFKYGNGVWIGRTKSISSRNGFEMIWD 300 **** **************:*****:*.********** ***.*******

3B7E_A|PDBID|CHAIN|SEQUENCE PNGWTETDSSFSVRQDIVAITDWSGYSGSFVQHPELTGLDCMRPCFWVEL 344A_H1N1__Neuraminidase PNGWTGTDNNFSIKQDIVGINEWSGYSGSFVQHPELTGLDCIRPCFWVEL 350 ***** **..**::****.*.:*******************:********

3B7E_A|PDBID|CHAIN|SEQUENCE IRGQPKENTIWTSGSSISFCGVNSDTVGWSWPDGAELPFSI-- 385A_H1N1__Neuraminidase IRGRPKENTIWTSGSSISFCGVNSDTVGWSWPDGAELPFTIDK 393 ***:***********************************:*

Fig: 1 Structure-based sequence alignment of A (H1N1) neuraminidase and 3B7E.Active site residues are highlighted with black

triangles.

The modeled A (H1N1) neuraminidase was used for further optimization and validation. The calculated root mean square deviation between the target and template structure was found to be 1.2 Å (Fig. 2a). To assess the quality of the optimized models, Rampage [S.C. Lovell, I.W. Davis, W.B. Arendall III, P.I.W. de Bakker, J.M. Word, M.G. Prisant, J.S. Richardson and D.C. Richardson (2002) Structure validation by Calpha geometry: phi,psi and Cbeta deviation. Proteins: Structure, Function &

Genetics. 50: 437-450] and ERRAT [Colovos C, Yeates TO. (1993). Verification of protein structures:

patterns of nonbonded atomic interactions. Protein Sci. 2, 1511-1519] analyses were also undertaken. The Ramachandran plot(Fig:2b) of our model shows that 94.4% of residues were found in the favored and 5.4% allowed regions and 0.3% were in the outlier region. The quality factor (ERRAT) of our model was equal to 85.417, and thus we consider that the model is acceptable for predicting the binding modes and interactions of oseltamivir and zanamivir with A (H1N1) neuraminidase.

Fig: 2a Superimposition of template (green) and model protein (yellow). 2b Ramachandran plot for the modeled

3.2. The Results of Molecular Dynamics simulations:

The modeled A (H1N1) neuraminidase was subjected to Molecular dynamics, in order to

explain protein structure–function problems, such as folding, conformational flexibility and

structural stability. In the simulations, we monitored the backbone atoms and the C-α-helix of

the modeled protein. The RMSD values of the modeled structure’s backbone atoms were

plotted as a time-dependent function of the MD simulation. The results support our modeled

structure, as they show constant RMSD deviation throughout the whole simulation process.

The time dependence of the RMSD (Å) of the backbone atoms of the modeled protein during

a 10 ns simulation is shown in Fig. 3 and the RMSD value variation with respect to the

simulation time. The RMSD value of the model has a low fluctuation during the entire time

process. The low RMSD and the simulation time indicate that, as expected, the 3D structural

model of A (H1N1) neuraminidase represents a stable folding conformation.

Fig. 3 RMSD of the backbone atoms of the A (H1N1) Neuraminidase over a time period of 10 ns

3.3. Binding modes of antiviral drugs with A (H1N1) Neuraminidase:

The two antiviral drugs, oseltamivir and zanamivir, drugs were docked into the active

site to explore the substrate binding modes. The initial binding modes were obtained by using

AutoDock. The obtained complex results are summarized in Table 1 and Fig. 4a and 4b. For

the zanamivir binding modes, five residues (ASN’172, ASN’219, ASN’268, SER’171, and

ARG’292) form seven hydrogen bonds with the drug. For oseltamivir binding modes, four

residues (ARG’76, SER’171, GLU’201, and ASN’268) form six hydrogen bonds with the

drug, these residues were considered as binding site and the screening has been applied

against zinc database for identification of novel neuraminidase inhibitors.

Fig:4 Binding mode of a) Oseltamivir and b) Zanamivir with A (H1N1) Neuraminidase.

3.4. Results of Virtual screening of Neuraminidase inhibitors

Of the 523,366 compounds subject to the virtual screening with UCSF DOCK, we found that

the DOCK grid scores of ~30 compounds are better than those of the two drugs were shown

in Table 1. The chemical structures of these lead molecules are illustrated in Fig. 5, and the

binding modes of these 30 lead molecules and their interacting residues and docking

conformations of the 30 virtual hits around the binding site of A H1N1 Neuraminidase are

shown in Fig. 6, 7 and Table 1.

In addition, four compounds (ZINC03869914, ZINC03869917, ZINC12502585 and

ZINC53684003, Fig. 9) have best DOCK grid scores, which were nearly twice as low as the

two drugs and all the protein-ligand complexes for these four lead molecules possess multiple

hydrogen bonds when compared with two drugs. Consequently, these four compounds were

selected for subsequent ADMET studies.

Fig. 5. The chemical structures of the 30 candidates

Fig. 6. The docking poses of the 30 candidates

Fig. 7. Docking conformations of the 30 virtual hits (Color sticks) around the binding site (red box) of A H1N1 Neuraminidase (Blue Surface).

Table 1. Dock results for the 30 lead molecules and Oseltamivir and Zanamivir

Drug/Lead

Molecules

DOCK grid

scores (kcal/mol)

Amino acids involved in interactions No.of HBs

Oseltamivir -31.097 ARG’76, SER’171, GLU’201 and ASN’268 6

Zanamivir -31.013 ASN’172, ASN’219, ASN’268, SER’171and ARG’292 7

ZINC03869914 -53.074 ASN’219, GLU’201, ARG’76, ARG’149, ARG’42, ARG’292 and

GLU’202

8

ZINC03869917 -50.829 ASN’219, GLU’202, SER’171 and ARG’76 7

ZINC12502585 -53.833 ARG’76, ASN’219, GLU’201, ARG’149, ARG’292 and ARG’42 7

ZINC53684003 -50.808 SER’171, ARG’76, ARG’217, GLY’269, ARG’292 and ARG’42 8

ZINC00135466 -84.382 N/A N/A

ZINC02172775 -80.925 N/A N/A

ZINC03869234 -52.423 ARG’292, LYS’74 and ARG’42, 4

ZINC 03869916 -50.439 ARG’76, ASP’75, GLU’202, ARG’292, ARG’42 7

ZINC03882070 -50.845 LYS’74, ARG’42 and ARG’292 5

ZINC04096400 -52.128 ASP’75, ARG’42 and ARG’292 5

ZINC05112750 -53.567 LYS’74 and ARG’354 6

ZINC05317111 -91.123 N/A N/A

ZINC12502589 -50.949 GLU’202, ARG’292 and ARG’42 4

ZINC12890057 -51.868 ARG’292, ARG’42, LYS’74 and ASP’75 8

ZINC13059497 -50.168 LYS’74 and ARG’354 2

ZINC13861587 -52.736 ARG’76, ARG’149, ASP’75, ARG’42 and ARG’292 8

ZINC16887666 -50.566 LYS’74, ARG’42 and ARG’292 6

ZINC20459160 -55.286 ASP’75, LYS’74, ARG’42, ARG’354 and ARG’292 5

ZINC23329815 -58.628 ARG’354 2

ZINC27558896 -56.343 ARG’292, ARG’42 and LYS’74 6

ZINC27558898 -58.448 LYS’74 and ARG’354 5

ZINC27558900 -56.515 LYS’74, ARG’42 and ARG’354 5

ZINC27645848 -53.097 LYS’74, ASP’75 and ARG’354 8

ZINC28866114 -51.910 ARG’42, ASP’75 and LYS’74 6

ZINC31392733 -50.755 ARG’149, ASP’75 and LYS’74 6

ZINC35288026 -53.430 ARG’42, ARG’292 and LYS’74 5

ZINC38541426 -60.348 LYS’74, ARG’42 and ARG’292 5

ZINC38665036 -51.376 LYS’74, ASP’75, ARG’292 and ARG’42 6

ZINC43198995 -50.456 GLY’269, ARG’292 and LYS’74 4

ZINC59514262 -50.835 ARG’42, ARG’292 and ARG’354 6

3.5. Prediction of ADME properties