1

Journal of Biomolecular Structure & Dynamics, ISSN 0739-1102 Volume 28, Issue Number 4, (2011) ©Adenine Press (2011)

*Phone: +005525467055Fax: +005525467055E-mail: tanos@ime.eb.br

Ana P. Guimarães1

Aline A. Oliveira1

Elaine F. F. Cunha2

Teodorico C. Ramalho2 Tanos C. C. França1,*

1Laboratory of Molecular Modeling

Applied to the Chemical and Biological

Defense – Military Institute of

Engineering, Praça General Tibúrcio 80,

22290-270 – Rio de Janeiro, Brazil 2Chemistry Department, Federal

University of Lavras, 37200-00,

UFLA/MG – Brazil

Design of New Chemotherapeutics Against the Deadly Anthrax Disease. Docking and Molecular

Dynamics studies of inhibitors Containing Pyrrolidine and Riboamidrazone Rings on

Nucleoside Hydrolase from Bacillus anthracis

http://www.jbsdonline.com

Abstract

Anthrax is a disease caused by Bacillus anthracis, a dangerous biological warfare agent already used for both military and terrorist purposes. An important selective target for che-motherapy against this disease is nucleoside hydrolase (NH), an enzyme still not found in mammals. Having this in mind we have performed molecular docking studies, aiming to analyze the three-dimensional positioning of six known inhibitors of Trypanosoma vivax NH (TvNH) in the active site of B. anthracis NH (BaNH). We also analyzed the main inter-actions of these compounds with the active site residues of BaNH and the relevant factors to biological activity. These results, together with further molecular dynamics (MD) simula-tions, pointed out to the most promising compounds as lead for the design of potential inhibi-tors of BaNH. Most of the docking and MD results obtained corroborated to each other. Additionally, the docking results also suggested a good correlation with experimental data.

Keywords: Anthrax; Bacillus anthracis; Nucleoside hydrolase; Docking; Molecular Dynamics.

Introduction

The use of biological warfare agents is not new. Bacteria, viruses, fungus, pro-tozoan and toxins have been employed since ancient times by men in battles or sabotage operations. Today the risk of use of such agents in wars is quite low but their use in terrorist attacks is a very real menace considering their potential of causing panic in civilian populations and its low cost of production, allied to the vast amount of information available on internet (1). Thus, the constant drug devel-opment becomes a crucial issue for the improvement of countermeasures against biological warfare emergencies.

B. anthracis is one of the most dangerous biological warfare agents and has been used by both military and terrorist groups (2). This bacteria causes anthrax, a highly infectious disease for domestic and wild animals and also for humans. Infection with B. anthracis can occur by skin contact, inhalation or contact with the gastro-intestinal tract, inhalation being the most critical, since it is fatal (3). Despite the existence of chemotherapy available against anthrax, the occurrence of resistance and, also, the constant risk of development of genetically modified strains of this agent, drive the constant search for new molecular targets as well as the develop-ment of new and more selective drugs.

2

Guimarães et al.

Among the several possible targets for the development of chemotherapy against anthrax, NH, the enzyme responsible for the hydrolysis of nucleosides, playing a fundamental role in the recovery process of purines and pyrimidines (4), and still not detected in mammals, sounds like a promising target (5).

In recent years, computer-aided drug design has been a promising strategy for identifying potential lead compounds and molecular structural features that are related to biological activity. Structure-based investigations have been widely used to study ligand and receptor interaction and have been applied in drug design (6-15). Molecular dynamics simulation, too, has been widely applied to investigate biological system (16-30). There has been development of new scor-ing function (31) and successful implementation of computer-aided drug design into development of new therapeutics (32-35). Thus, one is in a good position to apply such technologies to develop new chemotherapy against deadly diseases like anthrax.

In this work, we applied docking and MD techniques, already used in former publications (36-43), to study the interactions of six TvNH inhibitors, contain-ing pyrrolidine and riboamidrazone rings and developed by Goeminne et al. and Boutellier et al. (44-46), in the active site of BaNH. The compounds were first docked to analyze their three-dimensional positioning as well as the main inter-actions with the amino acids of the active site, in order to evaluate the relevant factors to the biological activity. Subsequently, we investigated the dynamic behavior of these compounds in the active site of BaNH with the purpose of selecting the most promising compounds as lead for the design of potential BaNH inhibitors. Most of the docking and MD results obtained corroborated to each other. Additionally the docking results also suggested a good correlation with experimental data.

Figure 1: Structures of the NH inhibitors studied.

3

New Chemotherapeutics Against the Deadly

Anthrax Disease

Methodology

NH Inhibitors Studied

The inhibitors used in this study (Figure 1) were selected from a number of inhibi-tors developed by Goeminne et al. and Boutellier et al. (44-46), whose inhibition constants (Ki) were determined for Tripanossoma vivax NH (TvNH) expressed in E.coli. In addition we also studied the natural substrates of NH: inosine, uridine and adenosine, whose respective values of affinity with TvNH (KM) were determined by Versées et al. (47).

To verify the similarity between the residues of BaNH and TvNH (48) active sites and to determine the degree of identity between them, we aligned BaNH and TvNH structures (PDB codes 2C40 and 2FF2 respectively) (49) using the Swiss-Pdb-viewer program (50).

Docking Energies Calculations

The coordinates of the crystal structure of BaNH, including the cofactor Ca+2 and ribose, with resolution of 2.2 Å, were obtained from the Protein Data Bank (41) and the co-crystallized water molecules were removed using the program Molegro Virtual Docker (MVD)® (51).

The tridimensional structures of each compound in Figure 1 were built using the program PC Spartan Pro® (52) and their partial atomic charges calculated by the PM3 semi-empirical method. The compounds were docked in the BaNH binding site using MVD® (51) using the same procedure adopted in the works by Josa et al. (53), Ramalho et al. (14) and Cunha et al. (11). The binding site was restricted into a sphere with a radius of 7 Å and the residues within a radius of 11 Å were considered flexible. Due to the stochastic nature of the docking algorithm, about 20 runs were performed for each compound with 30 poses (conformation and ori-entation of the ligand) returned to the analysis of the overlap with the ribose pres-ent in the crystal structure of BaNH and the ligand-protein interactions. The best conformation of each compound was selected according to its degree of structural similarity to ribose and evaluating the best energy of interaction with the enzyme. The selected conformations were used for the further steps of molecular dynamics (MD) simulation.

MD Simulations

Before performing the MD simulations it was necessary to parameterize the ligands so that they could be recognized by the forcefield GROMOS96 from the program GROMACS 4.0 (54). The parameterization was carried out in the Dundee PRODRG Server (55) and the charges distributions were calculated by the ChelpG method at HF/6-31G (d,p) using the Gaussian 98® (56) program. The enzime/Ca+2/ligands complexes were simulated using the GROMACS 4.0 package (54), in cubic boxes of approximately 365,000 nm3 containing around 10,600 water molecules. These systems were minimized using the force field GROMOS 96 (54). The minimization algorithms used were steepest descent with position restrained (PR) of the ligands and convergence criterion of 100.00 Kcal.mol–1.Å–1, followed by steepest descent without PR, conjugate gradients and finally, quasi Newton Raphson until an energy of 1.00 Kcal.mol–1.Å–1. The minimized complexes were then submitted to MD simulations in two steps. Initially, we performed 500 ps of MD at 300 K with PR for the entire system, except the water molecules, in order to ensure a balance of the solvent molecules around the residues of the protein. Subsequently, there were per-formed 6,000 ps of MD at 300 K without any restriction, using 2 fs of integration time and a cutoff of 10 Å for long-distance interactions. A total of 300 conforma-tions were obtained during each simulation. In this step, the lists of pairs (pairlists)

Table iResidues belonging to the active sites of BaNH and TvNH.

BaNH TvNH BaNH TvNH

Asp9 Asp10 Thr125 Thr137Asp13 Asp14 Asn160 Asn173Asp14 Asp15 Glu171 Glu184Ala37 Ala39 Asn173 Asn186Asp38 Asp40 Trp246 Trp260Lys75 Lys81 Asp247 Asp261Trp77 Trp83 – Arg252Asp85 Asp91 – Asp255

4

Guimarães et al.

distance, the variation of RMSD and H-Bonds formed along the MD simulation were generated with the Origin program (58). Qualitative spatial RMSD pictures were generated in the MolMol (59) and the figures of the frames of MD simulations were generated in the PyMOL program (60).

Results and Discussion

Docking Studies

Analysis of the Identity Degree (ID) between the BaNH and TvNH active sites shows high similarity. Among a total of 16 residues, 14 are identical. As can be seen in Table I and in the alignment in Figure 2, the only residues of TvNH active site not observed in BaNH are Arg252 and Asp255. These residues belong to a loop at the entrance of the active site not observed in BaNH and, according to Versées et al. (48), contribute to stabilization of the ligand by means of secondary interactions mediated by water molecules. Additionally, the backbones of BaNH and TvNH superposes very well to each other with a RMS of 1, 20 Å and very few non matching points as can be seen in Figure 3. Thus, taking into account the big similarity between the active sites and the backbones, it is possible to propose that the TvNH inhibitors might be used as starting points in the drug design of BaNH inhibitors.

Figure 2: Alignment between BaNH and TvNH. Residues belonging to the active sites are shown in red.

were updated every 500 steps, all Arg and Lys residues were assigned with positive charges and the residues Glu and Asp were assigned with negative charges.

To analyze the structures generated after the optimization and MD steps, we used the VMD (57) and Swiss-Pdbviewer (50) programs. Plots of variation of total energy,

Figure 3: Superposition of the 3D structures of BaNH (blue) and TvNH (red).

5

New Chemotherapeutics Against the Deadly

Anthrax Disease

Table ii Docking results and Ki values for the compounds studied.

Compound Residue Distance (Å)Energy

(Kcal.mol-1)

IntermololecularEnergy

(Kcal.mol–1)

H-Bond eEnergy

(Kcal.mol–1) aKi (µM)

1 Asn160

Asn173Thr125Asp247

Asp38

3.363.502.603.053.403.303.053.10

–0.81–0.48–2.50–2.50–0.45–1.43–2.50–2.50

–99.40 –13.78 1.80 x 101

2 Glu71Asn173

Asp247Thr125Asp9

2.652.193.382.433.193.013.06

–2.500.97

–1.11–1.12–2.04–2.50–2.50

–108.63 –10.80 7.00 x 100

3 Glu171Asn173

Thr125Asp247

Asp14Asp38

Val12His80

2.662.663.502.792.913.483.063.113.243.443.373.473.093.373.503.52

–2.50–2.50–0.37–2.50–2.41–0.24–2.50–2.41–1.78–0.19–1.16–0.621.28

–0.09–0.25–0.38

–110.51 –16.97 6.20 x 10–3

4 Asn160Glu171Asn173Thr125Asp247

Asp9Asp38

3.432.812.792.793.202.983.543.172.64

–0.82–2.50–2.50–2.50–0.07–2.50–0.29–2.16–2.50

–67.05 –15.85 10.00 x 100

5 Asn160Glu171Asn173Thr125Asp247

Asp14Asp38

3.372.812.642.623.463.212.863.282.60

–1.16–2.50–2.50–2.50–0.14–1.97–2.50–1.61–2.50

–103.85 –17.38 2.10 x 10–1

6 Asn160Asn173

Glu171Thr125Asp38

Asp247

Asp13

3.432.843.483.362.902.603.273.073.343.123.12

–0.85–2.50–0,25–0.08–2.50–1.670.15

–2.50–0.01–2.38–2.38

–121.48 –20.40 1.00 x 10–2

Val12

Tyr243His80

3.473.013.163.112.31

–0.63–2.89–2.17–2.45–0.08

aExperimental data (14-16).

6

Guimarães et al.

The cavity of the BaNH active site was calculated by MVD® (51) as being 119,296 Å2. Results of the docking studies of the inhibitors 1-6 (Table II) inside this cavity, allowed us to identify the relevant H-Bonds that occur between each inhibitor and the amino acid residues of the active site in order to obtain the con-formations adopted with these molecules, compare them to the conformations of the natural substrates (Table III) and thus get subsidies for the proposition of possible structures for prototypes of BaNH inhibitors.

The interaction energies ligand-protein (electrostatic and H-Bond) were calculated in order to get a better understanding of the variations between the binding modes of each compound in the active site of the enzyme and the molecular factors responsi-ble for the activity. Table II lists the residues present in these interactions and their distances to the ligand, the energy values and the experimental inhibition constants obtained by Goeminne et. al. and Boutellier et al. (44-46), for each compound with TvNH. From Table II, it can be noticed a very good correlation between the theo-retical results and experimental data considering that the compounds presenting the lowest values of intermolecular interaction and total H-Bond energies (compounds 6 and 3 respectively) also presents the lowest values of Ki. Besides, the highest val-ues of intermolecular interaction and total H-Bond energies (compounds 4 and 1 respectively) also correspond to the highest values of Ki

Compound 3 (imucilim A), interacts with BaNH by means of 16 H-Bonds (Figure 4), 09 more than compound 2 that interacts with the same residues, except Asp9 (Table II). The interactions of compound 3 with residues Thr125 and Glu171 present the same energy values when compared to compound 2 but the interactions of compound 3 with Asn173 and Asp247 are stronger, presenting lower values of energy and thus more stable connections. The hydroxyl group 2 in compound 3, despite not interacting with Asp9 and Asn173 (interaction present in compound 2), interacts with residues Asp14, Asp38 and Asp247. Besides, interactions with residues Val12 and His80 (absent in compound 2) are also observed, justifying the best docking results for compound 3 (intermolecular energy of –110.51 kcal–1mol–1 and total H-Bond energy of –16.97 kcal–1mol–1) when compared to compound 2 (intermolecular energy of –108.63 kcal–1mol–1 and total H-Bond energy of –10.80

Table iiiDocking results and KM values for the substrates studied.

Compound Residue Distance (Å)Energy

(Kcal.mol–1)

IntermolecularEnergy

(Kcal.mol–1)

H-Bond energy*

(Kcal.mol–1) aKM (µM)

Inosine

Asn160Glu171Asn173Thr125Asp38Asp247

His80

3.163.802.793.233.223.503.292.77

–2.21–2.50–2.50–1.83–1.91–0.09–1.53–0.77

–110.57 –13.33 5.37

Uridine

Asn160Asn173

Asp38Tyr243His80

3.433.143.272.733.103.30

–0.86–2.32–0.29–2.50–2.50–0.68

–91.32 –9.15 586

Adenosine

Asn173Thr125Asp247

Asp38His80

2.783.233.583.342.913.21

–2.50–1.86–0.01–1.31–2.50–1.95

–106.97 –10.13 8

aExperimental data (9).

7

New Chemotherapeutics Against the Deadly

Anthrax Disease

kcal–1mol–1). These results suggest that compound 3 is a more promising inhibitor of BaNH than compounds 1 and 2. Result reflected also by the best value of dock-ing energy (–110.51 kcal-1mol-1) compared to compounds 1 and 2. This value was too close to the result obtained to inosine (–110.57 kcal–1mol–1) and better than uridine (–91.32 kcal-1mol-1) and adenosine (–106.97 kcal–1mol–1) results.

Compound 6 (p-nitro-phenyl-riboamidrazone) holds 16 hydrogen bonds with BaNH, 07 more than compound 5 (phenyl-riboamidrazone). Its 29, 39 and 59 hydroxyl groups interact with residues Thr125, Asn160, Asn173 and Asp247 in the same way as for compound 5 (Table II). However, the hydroxyl group 2’ also inter-acts with residue Asp13, while for compound 5, this interaction occur with Asp14. The nitro group of compound 6 approached residues Val12, His80 and Tyr243, thus allowing the interaction and the consequent formation of H-Bonds (Figure 5). These interactions can be an important factor to explain the higher inhibitory power observed experimentally by Boutellier et al. (46). It is worth noting that among all the compounds studied, compound 6 showed the lowest value of total H-Bond energy (-20.40 kcal-1mol-1) and lower intermolecular energy (-121.48 kcal-1mol-1). We observed that compound 6 was the inhibitor which adopted the best conforma-tion in the binding site of BaNH (Figure 6), occupying the entire cavity (Figure 7), and probably performing interactions with the main residues responsible for the inhibitory power. This compound was the most stable in the active site, performing all the interactions observed in the natural substrates inosine, uridine and adenos-ine, and presented the best results of intermolecular energy and lower value of Ki (Tables II and III). These results suggest that, compared to the other compounds studied, compound 6 would be the most promising inhibitor of BaNH.

Figure 4: H-Bonds among compound 3 and the active site residues of BaNH.

Figure 5: H-Bonds among compound 6 and the active site residues of BaNH.

8

Guimarães et al.

Moreover, compounds with the higher values of Ki (compounds 1 and 4 in Table II) corresponded to the highest values of intermolecular energy, suggesting that these ligands have less interactions with the enzyme being less stable and therefore candidates for less efficient inhibitors of BaNH. Compound 1 interacts with BaNH by means of 08 H-Bonds, as well as inosine, and 02 more than adenosine (Tables II and III). These interactions occur between the hydroxyl groups 3’ and 5’ and resi-dues Asp38, Thr125, Asn160 and Asn173. The guanidine NH2 group also makes interaction with Asp38 but does not interact with His80. That may have contributed to the worst result of intermolecular energy (-99.40 kcal/mol) relative to inosine (-110.57 kcal / mol) and adenosine (-106.97 Kcal.mol-1).

Compound 4 (riboamidrazone) interacts with BaNH by means of 09 hydrogen bonds with the same residues as inosine, uridine and adenosine, except for interac-tions with His80 and Tyr243. This compound was the inhibitor with the lowest value of intermolecular energy (-67.05 Kcal.mol–1). This result is in fully agree-ment with the experimental data proposed by Boutellier et al. (46) (Table II). Com-pound 4 also did not adopt an appropriate conformation within the active site. A possible explanation for that is the small size (or volume) of its substituent that

Figure 6: Superposition of compound 6 (blue) and ribose (red) after docking.

Figure 7: Compound 6 inside the active site of BaNH after docking. Hydrophilic regions are shown in red; Hydrophobic regions are shown in blue and the cavity is shown in green.

9

New Chemotherapeutics Against the Deadly

Anthrax Disease

avoided interactions with residues Val12, His80 and Tyr243, considering that inter-actions with these residues are essential to increase the inhibitory power, since the most promising compounds in this study, compounds 3 and 6, held strong interac-tions with them.

Molecular Dynamics Simulations

After the docking studies, compounds 1-6 and the natural substrates were submit-ted to MD simulations. The goal of these simulations was to observe the dynamic behavior of these compounds in the active site of BaNH, in order to compare it to the docking results, obtaining additional information for supporting the proposal of new potential inhibitors for BaNH.

The plots for the variation of the total energy along the MD simulation showed that for both enzyme/inhibitor and enzyme/substrate systems, the total energy tends to stability after 2,000 ps of simulation (as shown for the system BaNH/compound 6 in Figure 8), with an energy variation of about -0.04 kJ.mol–1, indicating that the average energy remains constant, thus suggesting structural stabilization. The same behavior was observed for all the 09 systems simulated.

RMSD analysis can give an idea of how much the three-dimensional structure has fluctuated over time as well as allow monitoring local fluctuations, for exam-ple, the residues with increased mobility along the MD simulation. The tem-poral RMSD calculations were performed on all the atoms of each complex to 300 frames at every 20 ps, along the 6,000 ps of simulation. Considering that the complexes could fluctuate in the box, each frame was adjusted by the least squares method to its previous one for the calculation of the standard deviation. In Figure 9, we can observe the equilibration for the simulation of the system BaNH/com-pound 6 around the initial 200 ps. This behavior was common to all simulations, with deviations never exceeding 0.33 nm (3.5 Å) and 0.31 nm (3.1 Å) for protein and ligand, respectively. This result suggests that the compounds accommodate well inside the active site along the MD simulation, showing stabilization of the system and confirming the results obtained by the total energy calculations previously described. The spatial RMSD on each amino acid was also calculated as illustrated in Figure 10. It provides a qualitative and quantitative view of

0 1000 2000 3000 4000 5000 6000-390000

-389000

-388000

-387000

-386000

-385000

-384000

-383000

-382000

En

erg

y (

kJm

ol-1

)

Time (ps)

Figure 8: Total energy variation for the system BaNH/compound 6 along the MD simulation.

10

Guimarães et al.

all regions of the protein along the dynamics. We can observe that the regions that most floated along the MD simulations (larger values of RMSD and major thickening of the tubes in Figure 10) correspond to the C and N-terminal extremi-ties and the regions of loops. Moreover, the residues in the active site region, the alpha helices and beta sheets present lower fluctuation, revealing to be the more stable regions, as expected. This behavior observed in the temporal and spatial RMSD calculations was common to all the 09 systems simulated.

To facilitate the visualization of the dynamic behavior of each inhibitor within the active site, we selected and evaluated the variation of the distances of the residues directly involved in interactions with each inhibitor for each system, according to the results obtained in the docking studies.

The succession of frames for compound 3 inside the active site of BaNH (Figure 11) showed that this compound stayed among residues Val12, His80 and Trp238 along all the simulation time, close enough to make H-Bonds and hydrophobic interactions. It was thus possible to confirm the good interaction with the enzyme, because compound 3 fitted well into the cavity of the active site of BaNH along the simulated time, showing stabilization of the system and confirming results sug-gested by total energy and RMSD calculations. Similar results were observed in the docking studies, suggesting the greater stability of this molecule in the active site of BaNH. This stability can be an important factor to explain the better inhibi-tory power observed experimentally by Goeminne et al. (45). Besides, it was also observed that Trp238 stay at about 5 Å from compound 3. This residue, although

Figure 10: Spatial RMSD of the system BaNH/compound 6.

Figure 9: Temporal RMSD to the MD simulation of the system BaNH/compound 6. The enzyme curve is shown in black and the inhibitor curve is shown in red.

11

New Chemotherapeutics Against the Deadly

Anthrax Disease

not carrying any hydrogen interactions (according to the docking), can contrib-ute further, by hydrophobic interactions, to the stabilization of compound 3 inside BaNH active site, due to its proximity.

The docking results showed that compound 3 formed H-Bonds with 8 residues of BaNH active site. Similar result was obtained by the MD simulation that showed the formation of up to 08 H-Bonds with the permanence of 4 to 6 H-Bonds until the end of the simulation as can be seen in Figure 12. The stability of these H-Bonds during the dynamics also confirms the greater inhibitory power of this compound in comparison to the others.

The succession of frames for compound 6 inside the active site of BaNH (Figure 13) showed that this compound, beyond being among Val12, His80 and Trp238, also interacted with Asp38 and Tyr243 along all the simulation time, staying close enough to make H-Bonds and hydrophobic interactions. In the same way as for compound 3 it was also possible to confirm the good interaction with the enzyme, because compound 6 fitted well into the cavity of the active site of BaNH along the simulated time. This stability, also observed in the docking studies, can contribute to explain the better inhibitory power observed experi-mentally by Boutellier et al. (46). Besides, it was also observed that Trp238 stay at about 8.5 Å from compound 6 along the MD simulation. This residue may be

Figure 11: Frames of compound 3 inside the active site of BaNH along the MD simulation.

Figure 12: Number of H-Bonds between compound 3 and BaNH along the MD simulation.

12

Guimarães et al.

contributing further to the stabilization of compound 6 inside BaNH active site by means of π-stacking interactions as shown in Figure 14.

The docking results showed that compound 6 formed H-Bonds with 10 residues of BaNH active site. Similar result was obtained by the MD simulation that showed the formation of up to 09 H-Bonds with the permanence of 4 to 6 H-Bonds until the end of the simulation as can be seen in Figure 15.

The same analysis were performed to the other seven systems simulated and the results confirmed the docking results obtained to compounds 3 and 6, showing that all the ligants are stable inside the BaNH active site along the simulations time. Interactions observed to compounds 3 and 6 confirmed them as the most promising as lead compounds for the design of BaNH inhibitors.

Conclusions

In the present work we performed docking and MD studies of BaNH with 6 known NH inhibitors. The docking results have shown that there is a good correlation

Figure 14: Potential hydrophobic interaction of compound 6 with Trp238.

Figure 13: Frames of compound 6 inside the active site of BaNH along the MD simulation.

13

New Chemotherapeutics Against the Deadly

Anthrax Disease

between theoretical and experimental data. Compounds 3 and 6 showed to be the most promising as BaNH inhibitors since they showed the best averaged energies and total intermolecular H-Bond compared to the other compounds and the natural substrates. The results of MD simulations confirms the docking results showing that the proposed inhibitors remain well anchored and stable in the site for the sim-ulated time in all systems. These results combined suggest that compounds 3 and 6 are promising as leads for the design of potential inhibitors for BaNH. They also suggest the design of derivatives of these compounds in order to establish the best pharmacophore groups and to optimize interactions with key amino acid residues of the active site. These derivatives must have as substituents, preferably aromatic groups in order to explore potential hydrophobic interactions with the tryptophan residues belonging to the active site. It is also desirable that the substituents have a larger volume containing amine and carbonyl groups, in order to occupy the whole cavity, increasing this way, the potential to make interactions with residues Val12, Asp38, His80 and Tyr243.

Acknowledgments

The Authors wish to thank the Brazilian financial agencies CNPq, FAPEMIG, FAPERJ and CAPES/MD (Edital PRODEFESA 2008) for financial support and the Military Institute of Engineering and University Federal of Lavras for the physical infrastructure and working space.

References

T. C. C. França, A. T. Castro, M. N. Rennó, and J. D. F Villar. 1. Revista Militar de Ciência e Tecnologia XXVII, 56-67 (2008).D. L. Goldman and C. Arturo. 2. Front Biosci 13, 4009-4014 (2008).L. E. Lindler, F. J. Lebeda, and G. W. Korch. 3. Biological weapons defense: infectious dis-eases and counter bioterrorism. New Jersey, Human, (2005).D. J. Hammond and W. E. Gutteridge. 4. Mol Biochem Parasitol 13, 243-261 (1984).W. Versées and J. Steyaert. 5. Curr Opin Struct Biol 13, 731-738 (2003).E. D. Akten, S. Cansu, and P. Doruker. 6. J Biomol Struct Dyn 27, 13-25 (2009).A. M. Andrianov. 7. J Biomol Struct Dyn 26, 445-454 (2009).A. M. Andrianov and I. V. Anishchenko. 8. J Biomol Struct Dyn 27, 179-193 (2009).G. Ompraba, D. Velmurugan, P. A. Louis, Z. A. Rafi.9. J Biomol Struct Dyn 27, 489-500 (2010).M. T. Cambria, D. Di Marino, M. Falconi, S. Garavaglia, and A. Cambria. 10. J Biomol Struct Dyn 27, 501-509 (2010).E. F. F. da Cunha, E. F. Barbosa, A. A. Oliveira, and T. C. Ramalho. 11. J Biomol Struct Dyn 27, 619-625 (2010).C. Meynier, F. Guerlesquin, and P. Roche. 12. J Biomol Struct Dyn 27, 49-57 (2009).S. Mohan, J. J. P. Perry, N. Poulose, B. G. Nair, and G. Anilkumar. 13. J Biomol Struct Dyn 26, 455-464 (2009).

Figure 15: Number of H-Bonds between compound 6 and BaNH along the MD simultaion.

14

Guimarães et al.

T. C. Ramalho, M. S. Caetano, E. F. F. da Cunha, T. C. S. Souza, and M. V. J. Rocha. 14. J Biomol Struct Dyn 27, 195-207 (2009).J. Sille and M. Remko. 15. J Biomol Struct Dyn 26, 431-444 (2009).H. R. Bairagya, B. P. Mukhopadhyay, and K. Sekar. 16. J Biomol Struct Dyn 27, 149-158 (2009).B. Jin, H. M. Lee, and S. K. Kim. 17. J Biomol Struct Dyn 27, 457-464 (2010).C. Koshy, M. Parthiban, and R. Sowdhamini. 18. J Biomol Struct Dyn 28, 71-83 (2010).F. Mehrnejad and M. Zarei.19. J Biomol Struct Dyn 27, 551-559 (2010).S. Roy and A. R. Thakur. 20. J Biomol Struct Dyn 27, 443-455 (2010).A. Sharadadevi and R. Nagaraj. 21. J Biomol Struct Dyn 27, 541-550 (2010).S. Sharma, U. B. Sonavane, and R. R. Joshi. 22. J Biomol Struct Dyn 27, 663-676 (2010).Y. Tao, Z. H. Rao, and S. Q. Liu. 23. J Biomol Struct Dyn 28, 143-158 (2010).M. J. Aman, H. Karauzum, M. G. Bowden, and T. L. Nguyen. 24. J Biomol Struct Dyn 28, 1-12 (2010).J. F. Varughese, J. M. Chalovich, and Y. Li. 25. J Biomol Struct Dyn 28, 159-174 (2010).J. Zhang. 26. J Biomol Struct Dyn 27, 159-162 (2009).L. Zhong, and J. M. Xie. 27. J Biomol Struct Dyn 26, 525-533 (2009).A. Cordomi and J. J. Perez. 28. J Biomol Struct Dyn 27, 127-147 (2009).Y. Yuan, M. H. Knaggs, L. B. Poole, J. S. Fetrow, and F. R. Salsbury, Jr. 29. J Biomol Struct Dyn 28, 51-70 (2010).J. Wiesner, Z. Kriz, K. Kuca, D. Jun, and J. Koca. 30. J Biomol Struct Dyn 28, 393-403 (2010).C. Y. C. Chen. 31. J Biomol Struct Dyn 27, 271-282 (2009).C. Y. C. Chen. 32. J Biomol Struct Dyn 27, 627-640 (2010).C. Y. Chen, Y. H. Chang, D. T. Bau, H. J. Huang, F. J. Tsai, C. H. Tsai, and C. Y. C. Chen. 33. J Biomol Struct Dyn 27, 171-178 (2009).H. J. Huang, K. J. Lee, H. W. Yu, C. Y. Chen, C. H. Hsu, H. Y. Chen, F. J. Tsai, and 34. C. Y. C. Chen. J Biomol Struct Dyn 28, 23-37 (2010).H. J. Huang, K. J. Lee, H. W. Yu, H. Y. Chen, F. J. Tsai, and C. Y. Chen. 35. J Biomol Struct Dyn 28, 187-200 (2010).T. C. C. França, P. G. Pascutti, T. C. Ramalho, and J. D. Figueroa-Villar. 36. Biophys Chem 115, 1-10 (2005).T. C. C. França, A. Wilter, P. G. Pascutti, T. C. Ramalho, and J. D. Figueroa-Villar. 37. J Braz Chem Soc 17, 1383-1392 (2006).A. S. Gonçalves, T. C. C. França, A. Wilter, and J. D. F. Villar. 38. J Braz Chem Soc 17, 968-975 (2006). T. C. C. França, M. R. M. Rocha, M. N. Rennó, L. W. Tinoco, and J. D. Figueroa-Villar. 39. J Braz Chem Soc 19, 64-73 (2008).M. L. da Silva, A. S. Gonçalves, P. R. Batista, J. D. Figueroa-Villar, P. G. Pascutti, and T. 40. C. C. França. Mol Sim 36 (1), 5-14 (2010).T. C. Ramalho, T. C. C. França, M. N. Rennó, A. P. Guimarães, E. F. F. Cunha, and K. Kuc41. ˇa, Chem-Biol Interact 185, 73-77 (2010).T. C. Ramalho, T. C. C. França, M. N. Rennó, A. P. Guimarães, E. F. F. Cunha, and K. Kuc42. ˇa, Chem-Biol Interact 187, 436-440 (2010).A. S. Gonçalves, T. C. C. França, J. D. F. Villar, and P. G. Pascutti, 43. J Braz Chem Soc 21, 179-184 (2010).A. Goeminne, M. McNaughton, G. Bal, G. Surpateanu. P. Van Der Veken, S. De Prol, 44. W. Versées, J. Steyaert, A. Haemers, and K. Augustyns. Eur J Med Chem 43, 315-326 (2008).A. Goeminne, M. McNaughton, G. Bal, G. Surpateanu, P. Van Der Veken, S. De Prol, 45. W. Versées, J. Steyaert, A. Haemers, and K. Augustyns. Bioorg Med Chem 16, 6752-6763 (2008).M. Boutellier, B. A. Horenstein, A. Semenyaka, V. L. Schramm, and B. Ganem. 46. Bio-chemistry 33, 3994-4000 (1994).W. Versées, K. Decanniere, R. Pellé, E. Van Holsbeve, and J. Steyaert. 47. J Biol Chem 277, 15938-15946 (2002).W. Versées, J. Barlow, and J. Steyaert. 48. J Mol Biol 359, 331-346 (2006).N. Guex and M. C. Peitsch. 49. Electrophoresis 18, 2714-2723 (1997).R. Thomsen and M. H. Christensen. 50. J Med Chem 49, 3315-3321 (2006).H. M. Berman, J. Westbrook, Z. Feng, G. Gilliland, T. N. Bhat, H. Weissig, I. N. Shindyalov, 51. and P. E. Bourne. Nucleic Acids Res 28, 235-242 (2000).W. J. Hehre, B. J. Deppmeier, and P. E. Klunzinger. 52. PC SPARTAN Pro. Irvine, CA: Wave-function, (1999).D. Josa, E. F. F. da Cunha, T. C. Ramalho, T. C. S. Souza, and M. S. Caetano. 31. J Biomol 53. Struct Dyn 25, 373-376 (2008).D. Van der Spoel, A. R. Van Buuren, E. Apol, P. J. Meulenhoff, D. P. Tieleman, A. L. T. 54. M. Sijbers, B. Hess, A. K. Feentra, E. Lindahl, R. Van Drunen and H. J. C. Berendsen. GROMACS user manual version 3.0. Groningen: University of Groningen, Department of Biophysical Chemistry, (2001).

15

New Chemotherapeutics Against the Deadly

Anthrax Disease

A. W. Schuettelkopf and D. M. F. Van Aalten. 55. Acta Crystallogr, Sect D: Biol Crystallogr, 1355 (2004).M. J. Frisch, G. W. Trucks, H. B. Schlegel, E. S. Scuseria, and J. A. Pople. 56. Gaussian 98, revision A.11. Pittsburg: Gaussian, (2001).W. Humphrey, A. Dalke, and K. Schulte. 57. J Mol Graph 14, 33-38 (1996).P. M. Edwards. 58. J Chem Inf Comput Sci 42, 1270-1271 (2002).R. Koradi, M. Billeter, and K. Wüthrich. 59. J Mol Graph 14, 51-55 (1996).D. Warren. 60. The PyMOL molecular graphics system, DeLano Scientific, San Carlos, CA (2002).

Date Received: September 20, 2010

Communicated by the Editor Ramaswamy H. sarma

All in-text references underlined in blue are linked to publications on ResearchGate, letting you access and read them immediately.