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Simulated Docking of Zanamivir with the 2009
Pandemic Strain Influenza A/H1N1
Neuraminidase Active Site
Abstract
Influenza neuraminidases are glycoproteins that facilitate the transmission of the influenza virus from cell
to cell. Zanamivir is a widely used neuraminidase inhibitor. Here I provide a computational docking
analysis of zanamivir with the active site of the neuraminidase of the 2009 Influenza A/H1N1 strain. The
computed inhibitor/receptor binding energy suggests that zanamivir would be only marginally effective
against that strain.

Keywords: Influenza, H1N1, neuraminidase, zanamivir

1.0 Introduction
glycoproteins that facilitate the transmission the group-1 N1, N4 and N8 neuraminidases of the influenza virus from cell to cell. ([1]) reveal that the active sites of these dimensional structure from that of group-2 enzymes. The differences lie in a loop of amino acids known as the "150-loop", which conformation that opens a cavity not present pyran-2-carboxylic acid; [10]) is a widely loop contains an amino acid designated Asp 151; the side chain of this amino acid has a carboxylic acid that, in group-1 enzymes, points away from the active site as a result of the 'open' conformation of the 150-loop. related sero-subtypes, and these subtypes The side chain of another active-site amino correspond at least roughly to differences in conformation in group-1 enzymes compared neuraminidases. The subtypes fall into two with the group-2 neuraminidases (8]).
groups ([3]): group-1 contains the subtypes acid side chains form critical interactions with neuraminidase inhibitors. For neuraminidase subtypes with the “open conformation” 150-loop, the side chains is a structural description of most of the inhibitors tightly ([8]). The active site ([10]) using AutoDock Tools v 4.2 (ADT, docking of zanamivir to the receptor. More outside the active site. This means that against another with the same active-site extracted. (3TI3 identifies the active site of with some group 2-like features in its active torsions in the ligand and active site were 2.0 Method
to be flexible wherever that assumption is assess the binding energy of the active site physically possible, was auto-docked to the of crystallized A/California/04/2009(H1N1)) active site, assumed to be rigid, using the Lamarckian genetic algorithm implemented otherwise noted, all processing described in configuration from the analysis was saved, Inspiron 545 with an Intel Core2 Quad CPU and the distances between the receptor and ligand in 3TI3, and those computed here, RAM, running under the Windows Vista docking are shown in Figure 1. Most values are, or are a consequence of, ADT defaults.
________________________________________________________________________
autodock_parameter_version 4.2 # used by autodock to validate parameter set
outlev 1 # diagnostic output level
intelec # calculate internal electrostatics
seed pid time # seeds for random generator
ligand_types C HD OA N # atoms types in ligand
fld 3TI3_active.maps.fld # grid_data_file
map 3TI3_active.C.map # atom-specific affinity map
map 3TI3_active.HD.map # atom-specific affinity map
map 3TI3_active.OA.map # atom-specific affinity map
map 3TI3_active.N.map # atom-specific affinity map
elecmap 3TI3_active.e.map # electrostatics map

desolvmap 3TI3_active.d.map # desolvation map
move zanamivir.pdbqt # small molecule
about -29.5772 12.7517 -20.6465 # small molecule center
tran0 random # initial coordinates/A or random
axisangle0 random # initial orientation
dihe0 random # initial dihedrals (relative) or random
tstep 2.0 # translation step/A
qstep 50.0 # quaternion step/deg
dstep 50.0 # torsion step/deg
torsdof 9 # torsional degrees of freedom
rmstol 2.0 # cluster_tolerance/A
extnrg 1000.0 # external grid energy
e0max 0.0 10000 # max initial energy; max number of retries
ga_pop_size 150 # number of individuals in population
ga_num_evals 2500000 # maximum number of energy evaluations
ga_num_generations 27000 # maximum number of generations
ga_elitism 1 # number of top individuals to survive to next
generation
ga_mutation_rate 0.02 # rate of gene mutation
ga_crossover_rate 0.8 # rate of crossover
ga_window_size 10 #
ga_cauchy_alpha 0.0 # Alpha parameter of Cauchy distribution
ga_cauchy_beta 1.0 # Beta parameter Cauchy distribution
set_ga # set the above parameters for GA or LGA
sw_max_its 300 # iterations of Solis & Wets local search
sw_max_succ 4 # consecutive successes before changing rho
sw_max_fail 4 # consecutive failures before changing rho
sw_rho 1.0 # size of local search space to sample
sw_lb_rho 0.01 # lower bound on rho
ls_search_freq 0.06 # probability of performing local search on
individual
set_psw1 # set the above pseudo-Solis & Wets parameters
unbound_model bound # state of unbound ligand
ga_run 10 # do this many hybrid GA-LS runs
analysis # perform a ranked cluster analysis

Figure 1. ADT parameters for the docking in this study
______________________________________________________________________________
3.0 Results
processor (with occasional bursts to 40% of peak), and required a constant 2.9 GB of memory. which assumes familiarity with the general neuraminidase "landscape", took about 20 minutes in ADT; the docking proper, about energy of binding under these conditions is ~ -8.7 kcal/mol; the estimated inhibition monitor suggested that the calculation was more or less uniformly distributed across the
four processors at ~25% of peak per
______________________________________________________________________________
MODEL 1
USER Run = 1
USER Cluster Rank = 1
USER Number of conformations in this cluster = 10
USER
USER RMSD from reference structure = 56.144 A
USER
USER Estimated Free Energy of Binding = -8.72 kcal/mol [=(1)+(2)+(3)-(4)]
USER Estimated Inhibition Constant, Ki = 408.13 nM (nanomolar) [Temperature =
298.15 K]

USER
USER (1) Final Intermolecular Energy = -11.40 kcal/mol
USER vdW + Hbond + desolv Energy = -8.30 kcal/mol
USER Electrostatic Energy = -3.10 kcal/mol
USER (2) Final Total Internal Energy = -2.75 kcal/mol
USER (3) Torsional Free Energy = +2.68 kcal/mol
USER (4) Unbound System's Energy [=(2)] = -2.75 kcal/mol
USER
USER
USER
USER DPF = 3TI3_zanamivir.dpf
USER NEWDPF move

zanamivir.pdbqt
USER NEWDPF about -29.577200 12.751700 -20.646500
USER NEWDPF tran0 29.961176 14.781299 -20.419074
USER NEWDPF axisangle0

-0.004045 -0.391949 0.919978 3.081993
USER NEWDPF quaternion0
-0.000109 -0.010540 0.024740 0.999638
USER NEWDPF dihe0 4.89 175.54 139.90 180.00 67.18 1.07 -179.74 0.58 -36.96
USER
USER x y z vdW Elec q RMS
ATOM 1 C2 ZMR A1001 29.610 13.398 -22.778 -0.14 +0.09 +0.144 56.144
ATOM 2 C3 ZMR A1001 30.901 13.720 -22.564 -0.34 +0.01 +0.045 56.144
ATOM 3 C4 ZMR A1001 31.277 14.664 -21.442 -0.27 -0.00 +0.150 56.144
ATOM 4 C5 ZMR A1001 30.226 14.586 -20.317 -0.17 +0.04 +0.143 56.144
ATOM 5 C6 ZMR A1001 28.817 14.747 -20.891 -0.14 +0.08 +0.185 56.144
ATOM 6 O6 ZMR A1001 28.541 13.810 -21.924 -0.14 -0.22 -0.335 56.144
ATOM 7 NE ZMR A1001 32.576 14.369 -20.810 -0.22 +0.04 -0.217 56.144
ATOM 8 HE ZMR A1001 32.843 13.389 -20.711 -0.26 -0.16 +0.178 56.144
ATOM 9 CZ ZMR A1001 33.401 15.265 -20.371 +0.01 +0.06 +0.665 56.144
ATOM 10 NH1 ZMR A1001 33.240 16.579 -20.493 -0.24 +0.05 -0.235 56.144
ATOM 11 NH2 ZMR A1001 34.493 14.843 -19.724 -0.31 -0.14 -0.235 56.144
ATOM 12 2HH1 ZMR A1001 32.407 16.900 -20.987 +0.08 -0.07 +0.174 56.144
ATOM 13 1HH1 ZMR A1001 33.890 17.285 -20.148 -0.38 -0.08 +0.174 56.144
ATOM 14 2HH2 ZMR A1001 34.617 13.835 -19.630 -0.39 +0.16 +0.174 56.144
ATOM 15 1HH2 ZMR A1001 35.144 15.549 -19.378 -0.44 +0.11 +0.174 56.144
ATOM 16 N5 ZMR A1001 30.437 15.627 -19.309 -0.02 -0.20 -0.352 56.144
ATOM 17 H5 ZMR A1001 30.130 16.576 -19.525 +0.10 +0.07 +0.163 56.144
ATOM 18 C10 ZMR A1001 31.013 15.406 -18.112 -0.24 +0.22 +0.214 56.144
ATOM 19 C11 ZMR A1001 31.268 16.657 -17.329 -0.34 +0.13 +0.117 56.144
ATOM 20 O10 ZMR A1001 31.344 14.278 -17.729 -0.74 -0.41 -0.274 56.144
ATOM 21 C1 ZMR A1001 29.129 12.658 -23.951 -0.19 +0.35 +0.233 56.144
ATOM 22 O1A ZMR A1001 30.010 12.129 -24.683 -1.05 -1.46 -0.642 56.144
ATOM 23 O1B ZMR A1001 27.908 12.571 -24.177 -1.03 -1.48 -0.642 56.144
ATOM 24 C7 ZMR A1001 27.690 14.594 -19.863 -0.09 +0.13 +0.180 56.144
ATOM 25 C8 ZMR A1001 26.561 15.617 -20.084 -0.25 +0.09 +0.173 56.144
ATOM 26 O8 ZMR A1001 25.343 14.887 -20.303 -0.20 -0.19 -0.391 56.144
ATOM 27 H8 ZMR A1001 24.662 15.515 -20.514 -0.40 -0.11 +0.210 56.144
ATOM 28 C9 ZMR A1001 26.902 16.556 -21.266 -0.21 +0.02 +0.198 56.144
ATOM 29 O9 ZMR A1001 25.780 16.637 -22.140 -0.01 -0.06 -0.398 56.144
ATOM 30 H9 ZMR A1001 25.104 16.044 -21.835 -0.35 -0.03 +0.209 56.144
ATOM 31 O7 ZMR A1001 27.148 13.287 -19.968 +0.01 -0.32 -0.390 56.144
ATOM 32 H7 ZMR A1001 27.094 13.052 -20.887 +0.08 +0.19 +0.210 56.144
TER
ENDMDL

Figure 2. ADT's zanamivir energy and position predictions.
______________________________________________________________________________

Figure 3 is a rendering of the active-site/inhibitor configuration computed in this study.
Figure 3. Rendering of zanamivir computationally docked with the active site of PDB 3TI3.
The molecular surface of the receptor is shown in white; the inhibitor, in stick form in grey.

Only the interior, inhibitor-containing region of the molecular surface of the active site can
be compared to in situ data: the surface distal to the interior is a computational artifact,
generated by the assumption that active site is detached from the rest of the receptor.
______________________________________________________________________________
The distances between ligand and receptor
however, be more effective than oseltamivir distances in the present computation were assumes that the receptor is rigid. This assumption is appropriate for the binding 4.0 Discussion
However, the calculation does not reflect what receptor "flexing" could contribute to The method described in Section 2.0 and the the interaction of the ligand with native Sections 2.0 and 3.0 assumes receptor is in a computed in this study (~408 nanoMolar at crystallized form. In situ, at physiologically ~298 K) is comparable inhibition constant of normal temperatures (~310 K), the receptor clinically effective ([10], [11], [13], [14], [15]) against several H1N1 genotypes. This therefore, may not be identical to their genetic algorithm used in this work could be [5] Butler D. Avian flu special: The flu models could be applied to this problem, and pandemic: were we ready? Nature 435 (26 its own active site. The work described in this paper was performed on Chain A only. highly similar to the Chain A active site. Future work will assess the ligand/receptor Summary: Interim Recommendations for the Use of Influenza Antiviral Medications in the Setting of Oseltamivir Resistance among Circulating Influenza A (H1N1) Viruses, 5.0 Acknowledgements
2008-09 Influenza Season. 19 December 2008. This work benefited from discussions with [8] Luo M. Structural biology: antiviral drugs fit for a purpose. Nature 443 (7 6.0 References.
[1] Russell RJ et al. The structure of H5N1 opportunities for drug design. Nature 443 (6 the accounts: global mortality of the 1918-1920 "Spanish " influenza pandemic. Bulletin of the History of Medicine 76 X, Zhu X, Dwek RA, Stevens J, Wilson IA. [3] World Health Organization. A revision Journal of Virology 82 (2008), 10493- of the system of nomenclature for influenza viruses: a WHO memorandum. Bulletin of the World Health Organization 58 (1980), efficacies of RWJ-270201, oseltamivir, and avian influenza viruses. Antimicrobial M, Liu Y, Gao F, Liu J, Feng E, He J, Wang Agents and Chemotherapy 45 (2001), 2723- J, Liu H, Jiang H, and Gao GF. Structural and functional analysis of laninamivir and its octanoate prodrug reveals group specific AutoDock 4 with AutoDock Tools: A neuraminidase active site. Proceedings of the 2011 International Conference on Genetic and Evolutionary Methods. CSREA Relationship between the inhibition constant (Ki) and the concentration of inhibitor which causes 50 per cent inhibition (I50) of an Pharmacology 22 (December 1973), 3099– site. Proceedings of the 2011 International Conference on Genetic and Evolutionary Methods. CSREA Press. pp. 136-142. oseltamivir with the 1918 pandemic strain

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