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Molecular docking studies have been carried out for a better understanding of the drug-receptor interactions. All the synthesized compounds have been subjected to molecular docking against targets that have been chosen based on the specific mechanism of action of the quinolones used in the antibacterial activity screening. A study of the characteristics and molecular properties of the small molecule known as ligand has been realized. In the first stage of the study, the 2D and 3D structures have been generated. The most stable conformer for each structure was obtained by geometry optimization and energy minimization. A series of topological, conformational characteristics and QSAR properties, important to assess the flexibility and the ability of the studied conformer to bind to the protein receptor, were determined and analyzed. These properties were discussed in order to assess the flexibility and the binding ability of studied conformers to bind to the receptor protein. The docking studies have been carried out. The score and hydrogen bonds formed with the amino acids from group interaction atoms are used to predict the binding modes, the binding affinities and the orientation of the docked quinolones in the active site of the protein receptor.
National Institute of Chemical-Pharmaceutical Research and Development, Bucharest, Romania
Amalia Stefaniu
National Institute of Chemical-Pharmaceutical Research and Development, Bucharest, Romania
*Address all correspondence to: lucia.pintilie@gmail.com
1. Introduction
An important parameter in the development of a new drug is the drug’s affinity to the identified target (protein/enzyme). Predicting the ligand binding to the target (protein/enzyme) by molecular simulation would allow the synthesis to be restricted to the most promising compounds [1, 2, 3, 4, 5, 6, 7, 8, 9]. Molecular docking can be accomplished by two interdependent steps [7, 8, 9]. The first step consists in sampling the ligand conformations in the active site of the protein receptor. The second step is to classify these conformations by a scoring function. The sampling algorithms should be able to reproduce experimental binding mode. Various algorithms used for docking analysis are molecular dynamics, Monte Carlo methods, genetic algorithms, fragment-based methods, point complementary methods and distance geometry methods, systematic searches. The scoring function should classify the highest among all the generated conformations. These mathematical models are used to predict the strength of binding affinity called noncovalent interaction between two molecules after they have been docked. They have also developed scoring function to predict the strength of other types of intermolecular interactions, for example, between two proteins or between proteins and DNA or protein and drug. These configurations are evaluated using the scoring functions to distinguish experimental binding modes of all other ways explored by the search algorithm. The goal of molecular docking is to predict the ligand-receptor complex structure by computation method to identify new active molecules that bind to a biological target [10, 11, 12, 13, 14]. The main methods used for docking are Lock and Key/Rigid Docking and Induced Fit/Flexible Docking. In rigid docking, the internal geometry of the receptor and ligand is kept fixed and docking is performed. In flexible docking, enumeration on the rotations of one of the molecules (usually smaller one) is performed. Every rotation, the surface cell occupancy and energy are calculated; later, the most optimum pose is selected.
This chapter presents design and molecular docking studies about 8-chloro-quinolone compounds. The influence of the presence of chlorine atom in the eighth position of the quinolone ring (Figure 1, where R8 = Cl) on the antimicrobial activity against Staphylococcus aureus has been studied. The predicted activity has been correlated with the experimental activity who has been determined by agar dilution method [15, 16].
Figure 1.
The structure of the quinolone compounds.
Drugs belonging to the quinolone compound are characterized by a quicker biological activity and a larger antibacterial spectrum. They are active on both gram-positive and gram-negative bacteria, as well as on recently discovered bacteria with intercellular development (Legionella, Mycoplasma, etc.), or even on acid-resistant bacteria (M. tuberculosis and M. leprae). The area of use of quinolones has expanded from urinary infections to systemic acute and chronic infections (lung and bronchus infections, osteitis, septicemia and endocarditis, chronic infections [chronic bronchitis, purulent osteoarthritis, chronic prostatite, cystitis and chronic sinusitis]) [15, 16].
Molecular docking studies have been performed with CLC Drug Discovery Workbench Software in order to achieve accurate predictions on optimized conformation for both the quinolone (as ligand) and their target receptor protein to form a stable complex. Molecular docking studies have been performed on topoisomerase II DNA gyrase with 32 quinolone compounds to understand the binding affinity of all quinolones with DNA gyrase. The crystal structure of topoisomerase II was downloaded from Protein Data Bank (PDB ID: 2XCT) [17]. The quinolone compounds have been synthesized in our laboratory [16], and their structures are shown in Figure 1 and Table 1.
The ligands have been prepared using SPARTAN’14 software package [18]. In this study, the DFT/B3LYP/6–31G* level of basis set has been used for the computation of molecular structure, vibrational frequencies and energies of optimized structures (Figure 2). In order to perform structure–activity relationship (SAR) studies, some electronic properties (Table 2) such as highest occupied molecular orbital (HOMO) and lowest unoccupied molecular orbital (LUMO) energy values, HOMO and LUMO orbital coefficient distribution, molecular dipole moment, polar surface area (PSA), the ovality, polarizability, the octanol water partition coefficient (logP), the number of hydrogen-bond donors (HBDs) and ad acceptors (HBAs) and acceptor sites (HBAs) and positive and negative ionizable sites are derived from CFD assignments. HBA/HBD and ±Centers, Hydrophobe Centers including aromatic centers, can be viewed in Figure 2, for the quinolones FPQ 28 and 6ClPQ 28 (compounds that showed good activity against MRSA [19]). The polarizability is useful to predict the interactions between nonpolar atoms or groups and other electrically charged species, such as ions and polar molecules having a strong dipole moment.
Figure 2.
Optimized geometry of quinolone compounds.
Compounds
Molecular properties
Dipole moment (debye)
E HOMO (eV)
E LUMO (eV)
HOMO-LUMO GAP
Polarizability (10−30 m3)
PSA(Å2)
Ovality
Log P
HBA count
HBD count
NF
12.76
−5.76
−1.41
4.35
65.09
56.587
1.45
1.37
5
1
FPQ50
8.71
−6.00
−2.02
3.98
66.33
57.344
1.46
1.92
5
1
PF
12.36
−5.77
−1.43
4.34
66.65
46.369
1.48
1.74
5
1
FPQ51
8.91
−5.79
−1.97
3.82
67.92
46.808
1.49
2.30
5
1
FPQ27
12.86
−5.76
−1.40
4.36
66.57
56.053
1.48
1.68
5
1
FPQ29
9.10
−6.01
−1.96
4.05
67.80
56.717
1.49
2.24
5
1
FPQ35
12.50
−5.77
−1.39
4.38
64.18
44.034
1.43
2.30
4
1
FPQ36
8.83
−6.14
−1.97
4.17
65.44
44.405
1.45
2.86
4
1
FPQ32
9.49
−6.63
−1.82
−4.81
65.58
45.402
1.46
2.72
4
1
FPQ33
8.28
−6.33
−2.05
4.28
66.75
44.781
1.47
3.28
4
1
Q83
9.49
−6.36
−1.82
4.54
67.06
45.389
1.49
3.05
4
1
Q85
8.29
−6.33
−2.05
4.58
68.23
44.785
1.50
3.61
4
1
FPQ24
9.48
−6.34
−1.82
4.52
67.07
45.295
1.48
3.12
4
1
FPQ30
8.23
−6.33
−2.06
4.27
68.24
44.768
1.50
3.68
4
1
FPQ25
10.15
−6.02
−1.58
4.44
64.87
51.758
1.44
1.59
5
1
FPQ28
8.26
−6.24
−1.97
4.97
66.00
51.859
1.45
2.15
5
1
NClX
8.80
−6.08
−1.93
4.15
65.98
57.537
1.47
1.77
5
1
6ClPQ50
7.81
−6.06
−2.11
3.95
67.11
56.756
1.48
2.32
5
1
PClX
11.84
−5.84
−1.59
4.25
67.42
46.688
1.49
2.14
5
1
6ClPQ51
8.69
−5.77
−2.07
3.07
68.72
46.277
1.51
2.70
5
1
6ClPQ27
8.56
−6.13
−1.93
4.20
67.46
57.339
1.59
2.08
5
1
6ClPQ29
8.00
−6.04
−2.10
3.94
68.60
56.469
1.51
2.64
5
1
6ClPQ35
12.16
−5.92
−1.54
4.38
64.92
44.303
1.44
2.70
4
1
6ClPQ36
8.51
−6.05
−2.09
3.96
66.27
43.934
1.47
3.26
4
1
6ClPQ32
9.48
−6.25
−1.89
4.36
66.39
44.937
1.47
3.12
4
1
6ClPQ33
8.26
−6.19
−2.11
4.08
67.57
44.194
1.49
3.68
4
1
Q80
9.47
−6.26
−1.89
5.07
67.86
44.979
1.50
3.45
4
1
Q87
8.26
−6.19
−2.12
4.07
69.04
44.205
1.51
4.01
4
1
6ClPQ24
9.47
−6.24
−1.89
4.35
67.88
44.863
1.50
3.52
4
1
6ClPQ30
8.27
−6.19
−2.12
4.07
69.05
44.304
1.51
4.08
4
1
6ClPQ25
7.85
−6.26
−1.97
4.29
65.69
52.427
1.46
1.99
5
1
6ClPQ28
6.68
−6.20
−2.20
−4.00
66.86
51.596
1.48
2.55
5
1
Table 2.
Molecular properties for CPK model computations for quinolone compounds using Spartan’14 V1.1.4 software.
2.1.1. Molecular polar surface area (PSA)
Molecular polar surface area (PSA) [20] is a descriptor that has been shown to correlate well with passive molecular transport through membranes and therefore allows the prediction of transport properties of the drugs. Log P is estimated according to the method of Ghose, Pritchett and Crippen [21]. A number of important graphical quantities resulted from quantum chemical calculations were displayed, manipulated and interrogated. Another indicator of electrophilic addition local map is provided by the ionization potential, an overlapping of the energy of electron removal (ionization) on the electron density. In addition, the electrostatic potential map, an overlay of the electrostatic potential (the attraction or repulsion of a positive charge for a molecule) on the electron density, is valuable for describing the overall distribution of molecular charge, as well as to predict the sites of electrophilic addition. Another indicator of the electrophilic addition is supplied by the local ionization potential map, an overlapping of the energy of electron removal (ionization) on the electron density. In the end, an indicator of nucleophilic addition is offered by the |LUMO| map, an overlap of the absolute value of the lowest unoccupied molecular orbital (LUMO).
2.1.2. Frontier molecular orbital analysis
The molecular orbital analysis of the Frontier molecular orbitals (FMOs) plays an essential role in the chemical stability of a molecule and in the interactions between atoms. They provide information that can be used to predict the characteristics of molecules such as optical properties and biological activities. Between them, the most important are the highest occupied molecular orbital (HOMO) and the lowest unoccupied molecular orbital (LUMO). The HOMO represents the ability of a molecule to donate an electron, while the LUMO represents the ability to accept an electron [22, 23]. The HOMO and LUMO, calculated at the B3LYP/6-31G* level, can be seen in Figure 3 for the gas phase, for the quinolones FPQ 28 and 6ClPQ 28 (compounds that showed good activity against MRSA [19]). The graphic has ‘blue and red’ regions. These correspond to positive and negative values of the orbital.
Figure 3.
HBA/HBD and ±Centers, Hydrophobe centers of 8-chloro-quinolone compounds: (a) FQ28 (b) 6ClPQ28.
For the HOMO of 7-piperazinyl-8-unsubstituted-quinolones, electron density of NF, PF and FPQ27 is localized on piperazine heterocyclic, on aromatic ring and on 4-oxo group. For the HOMO of 7-piperazinyl-8-chloro-quinolones, electron density of FPQ 50 and FPQ 51 is localized on piperazine heterocyclic; for FPQ29 compound, electron density is localized on piperazine heterocyclic and C6, C8 and C10 atoms from aromatic ring. For the HOMO of 7-piperidinyl-8-unsubstituted-quinolones, electron density of Q 83, FPQ 24 and FPQ 32is localized on piperidine heterocyclic, and on C6, C7 and C8 atoms from aromatic ring. For the HOMO of 7-piperidinyl-8-chloro-quinolones, electron density of Q 85, FPQ 30 and FPQ 33is localized on piperidine heterocyclic, on C6, C7 and C8 atoms from aromatic ring and on chlorine atom. For the HOMO of 7-morpholinyl-8-unsubstituted-quinolone, FPQ 25 electron density is localized on morpholine heterocyclic, on aromatic ring and on 4-oxo group. For the HOMO of 7-morpholinyl-8-chloro-quinolone, FPQ 28 electron density is localized on morpholine heterocyclic, on aromatic ring, on 4-oxo group and on chlorine atom. For the HOMO of 7-pyrrolidinyl-8-unsubstituted-quinolone, FPQ 35 electron density is localized on pyrrolidine heterocyclic, on aromatic ring and on 4-oxo group. For the HOMO of 7-pyrrolidinyl-8-chloro-quinolone, FPQ 36 electron density is localized on pyrrolidine heterocyclic, on aromatic ring, on 4-oxo group and on chlorine atom. For the LUMO of 7-substituted-8-unsubstituted-quinolones, NF, PF, FPQ27, O 83, FPQ 24, FPQ 32, electron density of FPQ 25 and FPQ 35 is localized on 4-piridinona ring and on aromatic ring. For the LUMO of 7-substituted-8-chloro-quinolones, electron density of FPQ 50, FPQ 51, FPQ29, O 85, FPQ 30, FPQ 33, FPQ 28 and FPQ 36 is localized on 4-piridinona ring, on aromatic ring B and on chlorine atom. For the 6-cloroqinolones, the electron density is located in the same manner as the corresponding fluoroquinolones.
The frontier orbital gap helps to characterize chemical reactivity of the molecule (Table 2). HOMO and LUMOs determine the way in which it interacts with other species. The introduction of the electron-withdrawing substituent (chlorine) at position C 8 in quinolone compounds decreases the HOMO-LUMO gap as compared to their corresponding 8-unsubstituted quinolone compounds (Figure 4).
Figure 4.
HOMO, LUMO surfaces of 8-chloro-quinolone compounds: (a) FQ28 (b) 6ClPQ28.
2.1.3. Molecular electrostatic potential (MEP)
Molecular electrostatic potential (MEP) has been evaluated using B3LYP method with the basis set 6-31G* to investigate the chemical reactivity of a molecule. The MEP is especially important for the identification of the reactive sites of nucleophilic or electrophilic attack in hydrogen-bonding interactions and for the understanding of the process of biological recognition [21, 22]. An electrostatic potential map for quinolone compounds shows hydrophilic regions in red (negative potential) and blue (positive potential) and hydrophobic regions in green. In Figure 5 can be viewed the MEP of the quinolones FPQ28 and 6ClPQ28.
Figure 5.
The optimized geometry and electrostatic potential pattern of the surface of (a) FPQ 28 and (b) 6ClPQ 28 (red—negative, high electron density, blue—positive area, low electron density).
The local ionization potential map provides another indicator of electrophilic addition; the local ionization map is an overlay of the energy of electron removal (ionization) on the electron density (Figure 6). |LUMO| map, map that represents a superposition of the absolute value of the lowest unoccupied molecular orbital (the LUMO) on the electron density, provides another indicator of the nucleophilic addition (Figure 7).
Figure 6.
The optimized geometry and local ionization potential map of (a) FPQ 28 and (b) 6ClPQ 28.
Figure 7.
The optimized geometry and ILUMOI map of (a) FPQ 28 and (b) 6ClPQ 28.
2.2. Molecular docking
The steps to go through to explore protein-ligand interaction using docking are as follows: set up the binding site in a Molecule Project, import the dock ligands to a Molecule Table and inspect the docking results. The docking studies have been carried out using CLC Drug Discovery Workbench Software. The score and hydrogen bonds formed with the amino acids from group interaction atoms are used to predict the binding modes, the binding affinities and the orientation of the docked quinolone compounds (Figure 8a–c, e, f, h) in the active site of the protein receptor (Table 3). The docking score used in the Drug Discovery Workbench is the PLANTSPLP score [24]. The protein-ligand complex has been realized based on the X-ray structure of S. aureus DNA GYRASE, who was downloaded from the Protein Data Bank (PDB ID: 2XCT) [17].
Figure 8.
Molecular docking studies with 2XCT receptor. (a) Docking pose of the co-crystallized ligand CP. (b) Docking pose of the co-crystallized ligand CP interacting with residues in the binding site. (c) Docking pose of FPQ 28. (d) Docking validation of FPQ 28. (e) Docking pose of the FPQ 28 interacting with residues in the binding site. (f) Docking pose of Q 83. (g) Docking validation of Q 83. (h) Docking pose of the Q 83 interacting with residues in the binding site.
–O sp2 from COOH(CO)–N sp2 from HIS 1081 –O sp3 from COOH(OH)–O sp2 from ASP 510
2.759 2.830
Table 3.
The list of intermolecular interactions between the ligand molecules docked with 2XCT using CLC drug discovery workbench software.
2.2.1. Docking method validation
It ensures that the ligand orientations and position obtained from the molecular docking studies are valid and reasonable potential binding modes of ligands; the docking methods and parameters used have been validated by redocking (Figure 8d, f).
2.2.2. Determining molecular properties
Using the “Calculate Molecular Properties” tool it have been calculated important molecular properties such as logP, number of hydrogen bond donors, number of hydrogen bond acceptors and molecular weight, parameters that can be used to evaluate if a molecule has properties that would make it a likely orally active drug, according to the Lipinski’s rule of five [25].
Number of hydrogen bond donors less than 5 (the total number of nitrogen-hydrogen and oxygen-hydrogen bonds);
Number of hydrogen bond acceptors less than 10 (the total number of nitrogen and oxygen atoms);
The molecular weight less than 500 Daltons;
Log P (octanol–water partition coefficient) less than 5. The calculation of the log P is based on the XLOGP3-AA method [26].
The number of violations of the Lipinski rules gives an indication of how drug-likeness for a molecule is. In general, orally active drugs have fewer than two violations.
These properties can be useful for identifying potential drug-like molecules, or for removing nondrug-like molecules from a compound library before starting a large virtual screening experiment (Table 4).
Molecular docking study has been performed relating to some quinolone compounds known in medical therapeutics: ciprofloxacin, norfloxacin and pefloxacin. For a correct interpretation of the data has been used in the study the corresponding compound of ciprofloxacin, ClCp. ClCp is the compound having a chlorine atom in 6-position of quinolone ring in place of fluorine atom.
The result of molecular docking study for quinolone FPQ 28, compound with a good activity ‘in vitro’ against Staphylococcus aureus ATCC 6538 (MIC = 0.32 μg/ml) and with a good activity against MRSA [19], reveals docking score −39.63 (RMSD 0.17) and shows the occurrence of two hydrogen bonds with HIS 1081 (2.863 Å) and ASP 510 (2.671 Å) (Figure 8c). The orientation of the FPQ 28 is the same of NF (norfloxacin). Same orientation shows also the compounds: FPQ 32, FPQ 33, Q 83, Q 85, FPQ 27, FPQ 29, FPQ24 and FPQ 25 (Figure 9c). Docking score of NF compound is −39.79 (RMSD 0.11). NF shows the occurrence of two hydrogen bonds with HIS 1081 (2.863 Å) and ASP 510 (2.671 Å). The better score docking has been obtained from quinolone Q83: −42.73 (RMSD 0.07). Q83 shows the occurrence of two hydrogen bonds with HIS 1081 (2.761 Å) and ASP 510 (2.855 Å), and its orientation is the same of NF. Compound Q83 shows also a good activity ‘in vitro’ against Staphylococcus aureus ATCC 6538 (MIC <0.125 μg/ml).
Figure 9.
Docking pose of quinolone compounds in the binding site. (a) The quinolones with the similar binding mode of the co-crystallized ligand Cp. (b) The quinolones with the similar binding mode of the ClCp. (c) The quinolones with the similar binding mode of the ligand NF. (d) The quinolones with the similar binding mode of the ligand PF. (e) The quinolones with the similar binding mode of the ligand FPQ 35.
Results of the docking showed that quinolones have adopted various orientations. The same orientation with the co-crystallized ligand Cp (ciprofloxacin) shows the compound 6 ClPQ 27, 6ClPQ 28, 6ClPQ35 and Q 87. Co-crystallized Cp shows the occurrence of three hydrogen bonds with SER 438 (3.065 Å), SER 438 (2.816 Å) and ASP 437 (2.872 Å) (Figure 9a). The quinolones with the similar binding mode of the ClCp are 6ClPQ 51 and 6ClPQ 24 (Figure 9b). The quinolones with the similar binding mode of the ligand PF (pefloxacin) are 6ClPQ50, NClX, 6ClPQ 25, Q 80, FPQ 30, 6 ClPQ 33, PClX, FPQ 51, 6 ClPQ 36 and 6ClPQ 30.Docking score of PF is −39.89 (RMSD 0.65).PF shows the occurrence of three hydrogen bonds with LYS 460 (2.732 Å), LYS 460 (2.934 Å) and ASP 512 (2.948 Å) (Figure 9d). Same orientation shows the compounds FPQ 35, FPQ 24 and FPQ 50 (Figure 9e).
3.1. Drug-likeness of the quinolone compounds
According to the data presented in Table 4, four quinolones (Q 85, Q 87, FPQ 30 and 6ClPQ30) failed to respect one parameter (Log P > 5) of the Lipinski rules (Lipinski violation is 1). It was observed that 30 compounds of the study have zero violation of all the parameters involved in Lipinski’s rule of five.
In silico molecular docking, simulation was performed to position all quinolone compounds into the preferred binding site of the protein receptor S. aureus DNA GYRASE, to predict the binding modes, the binding affinities and the orientation. The docking studies revealed that the all compounds showed good docking score. The docking score is a measure of the antimicrobial activity of the studied compounds. A correlation of the predicted data was observed which is obtained by molecular docking study (score docking) with the experimental data obtained from the evaluation of the antimicrobial activity against Staphylococcus aureus ATCC 6538 [16] of the quinolone compounds (Figure 10a, b, and 11a, b).
Figure 10.
(a) MIC histogram of 6-fluoro-quinolone compounds. Minimum inhibitory concentration (MIC) of quinolone compounds against St. aur. ATCC 6538 (8-H-fluoroquinolones-blue, 8-Cl-fluoroquinolones-red). (b) Score docking of 6-fluoro-quinolone compounds (8-H-fluoroquinolones-blue, 8-Cl-fluoroquinolones-red).
Figure 11.
(a) MIC histogram of 6-chloro-quinolone compounds. Minimum inhibitory concentration (MIC) of quinolone compounds against St. aur. ATCC 6538 (8-H-chloroquinolones-blue, 8-Cl-chloroquinolones-red). (b). Score docking of 6-chloro-quinolone compounds (8-H-chloroquinolones-blue, 8-Cl-chloroquinolones-red).
The studies presented in this chapter show the importance of the design and the molecular docking in the discovery of new compounds with biological activity. The prediction of the binding affinity of a new compound (ligand) to an identified target (protein/enzyme) is a significant parameter in the development of a new drug. The prediction of the binding mode of a ligand (a new compound) to the target (protein/enzyme) by molecular simulation would allow restricting the synthesis to the most promising compounds.
This chapter has been financed through the NUCLEU Program, which is implemented with the support of ANCSI (project no. PN 09-11 01 01 and PN 09-11 01 09).
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Written By
Lucia Pintilie and Amalia Stefaniu
Submitted: 09 June 2017Reviewed: 07 December 2017Published: 11 July 2018
Open access peer-reviewed chapter
