3.1 Molecular docking of A, D ang G
Molecular docking is technique used to characterize the protein-ligand interaction using computational tools like autodock, paradock, iGEMDOCK method. Docked poses were given in the two and three-dimensional view to visualize the molecular interaction. 3D views mainly focused on the conventional Hydrogen bonding while the 2D view focused on the all-possible interactions like non-conventional hydrogen bonding, hydrophobic interaction, electrostatic, etc. Docking analysis shows that A forms five classical hydrogen bonding with PHE-140 (2.76), GLU-166 (3.19, 2.10, 2.86) and with CYS-145 (2.90), D forms eight conventional hydrogen bonds with GLY-143, (2.05) SER-144 (2.99), CYS-145 (2.37), HIS-163 (2.87), HIS-164 (2.90), ASP-187 (3.25), TYR-54 (2.88, 2,76), G forms six hydrogen bonds with HIS-164 2.58, HIS-163 (2.84), GLY-143 (2.32), SER-144 (2.65), CYS-145 (2.23, 3.12). Analysis of non-conventional hydrogen bonding A form bonds with HIS-163 (2.45), D form bonds with GLY-143 (2.89) and G form bonds with ARG-188 (2.41), MET-165 (2.21), HIS-41 (3.3), ASP-187 (3.02). Hydrophobic interactions were also analyzed for ligand because it helps to stabilize the ligands into the active binding cavity of protein. A shows hydrophobic interaction with MET-165 (2.54), D with CYS-145 (4.10) and G with MET-49 (4.25, 5.46) and MET-165 (5.10).
Table 1
shows the binding energy of different dock poses of acyclovir, ganciclovir and hydroxymethyl-ganciclovir.
S.No
|
Ligand
|
Total Energy
|
Ligand
|
Total Energy
|
Ligand
|
Total Energy
|
1
|
A-0
|
-104.785
|
G-0
|
-109.324
|
D-0
|
-118.124
|
2
|
A -1
|
-103.521
|
G-1
|
-110.567
|
D-1
|
-118
|
3
|
A -2
|
-104.53
|
G-2
|
-107.279
|
D-2
|
-112.417
|
4
|
A-3
|
-103.388
|
G-3
|
-110.605
|
D-3
|
-113.368
|
5
|
A-4
|
-103.05
|
G-4
|
-109.548
|
D-4
|
-119.226
|
6
|
A-5
|
-103.917
|
G-5
|
-109.292
|
D-5
|
-113.106
|
7
|
A-6
|
-105.054
|
G-6
|
-109.132
|
D-6
|
-114.796
|
8
|
A-7
|
-105.068
|
G-7
|
-108.602
|
D-7
|
-116.265
|
9
|
A-8
|
-104.73
|
G-8
|
-107.609
|
D-8
|
-114.076
|
10
|
A-9
|
-103.084
|
G-9
|
-107.915
|
D-9
|
-109.424
|
Table 2
Different types of interaction of A, G and D with Mpro of nCoV.
Ligand
|
H-Bond
|
Hydrophobic
|
Classical
|
Non-classical
|
Amino Acid
|
Distance
|
Amino Acid
|
Distance
|
Amino Acid
|
Distance
|
A
|
PHE-140
|
2.60
|
HIS-163
|
2.37
|
MET-165
|
2.50
|
GLU-166
|
2.05, 2.70, 3.22
|
|
|
|
|
CYS-145
|
2.96
|
|
|
|
|
G
|
ASN-142
|
3.10, 3.32
|
HIS-172
|
1.76
|
|
|
SER-144
|
2.67
|
MET-165
|
2.91
|
|
|
CYS-145
|
1.79
|
HIS-41
|
2.74
|
|
|
D
|
SER-144
|
2.43
|
GLY-143
|
2.54
|
|
|
ASN-142
|
3.18
|
HIS-172
|
1.62
|
|
|
HIS-41
|
2.80
|
ASN-142
|
3.68
|
|
|
|
|
HIS-163
|
2.99
|
|
|
|
|
HIS-41
|
3.05
|
|
|
3.2 DFT calculations
Different thermodynamic parameters such as enthalpy, free energy, optimization energy, thermal energy and zero-point energy were calculated. HOMO can serve as an electron donor [28] and LUMO is the first can act as an electron acceptor [29]. Higher the energy of HOMO indicate more the ability to donate electron density. HUMO, LUMO and optimized geometry of A, G and D are given in Figure 3.
Further, different thermodynamics parameter such as zero-point Energy, thermal energy, Optimization energy and thermal enthalpy are calculated and no significant changes is found as in Table 3. Free energies are an important parameter for deciding the stability of compound. It is considered that lesser the free energy of molecule indicates higher stability. Among A, G and D, D has the least free energy -1039.7090 (Hartree per particle) and considered to more stable. Dipole moment is also an important parameter for predicting the solubility in aqueous medium. Table 3 shows that G has the highest dipole moment of 10.4241a.u. in all.
Table 3
Thermodynamic parameters of A, G and D.
Compound
|
Sum of electronic and zero-point Energies (Hartree per particle)
|
Sum of electronic and thermal Energies (Hartree per particle)
|
Sum of electronic and thermal Enthalpies (Hartree per particle)
|
Sum of electronic and thermal Free Energies (Hartree per particle)
|
Optimization energy (Hartree per particle)
|
Dipole moment
(a.u.)
|
A
|
-810.66964
|
-810.65477
|
-810.65382
|
-810.65382
|
-810.880213
|
9.7791
|
G
|
-925.16575
|
-925.14840
|
-925.14746
|
-925.21332
|
-925.40877
|
10.4241
|
D
|
-1039.66047
|
-1039.6412
|
-1039.64026
|
-1039.7090
|
-1039.93684
|
8.9611
|
Various physiochemical descriptors were also determined for above reported three molecules by DFT calculation as given Table in 4. ELUMO and EHOMO are significant chemical factors for determining a molecules reactivity and are also applied to derive a range of important chemical reactivity descriptors such as chemical hardness (ɳ), chemical potential (µ), softness(S), electronegativity (χ) are reported in Table 4. Energy gap of HOMO and LUMO is a useful parameter for determining the reactivity of compound. The HOMO and LUMO energy are directly proportional to the ionization potential and electron affinity.
Table 4
Physio-chemical descriptors of acyclovir, ganciclovir and hydroxymethyl-ganciclovir
S.No.
|
Compound
|
ELUMO
|
EHOMO
|
EHOMO−LUMO
|
ELUMO+ HOMO
|
ɳ
|
χ
|
S
|
µ
|
Ω
|
1
|
A
|
-0.0297
|
-0.2252
|
-0.1955
|
-0.2549
|
-0.0978
|
0.12745
|
-5.1154
|
-0.1275
|
-0.0831
|
2
|
D
|
-0.0297
|
-0.2251
|
-0.1953
|
-0.2548
|
-0.0977
|
0.12740
|
-5.1201
|
-0.127
|
-0.0831
|
3
|
G
|
-0.0294
|
-0.2245
|
-0.1951
|
-0.2538
|
-0.0975
|
0.12692
|
-5.1264
|
-0.1269
|
-0.0826
|
3.3 Molecular dynamics simulations
Molecular dynamics simulations is used to analyze the dynamic of macromolecular system. It uses the trajectories obtained from MD simulations and gives useful information to investigate the protein-ligand interactions [30, 31]. MD simulations main protease of nCoV with of A, G and D were performed for 100 ns at different temperature. Root mean square deviation is the measure of the average of square root of deviation from the mean distance [32, 33]. It provides the conformational stability of macromolecular system due to binding of ligand into binding cavity. RMSD values ranges between the 0.2 nm to 0.5 nm. It was also found that on increasing temperature the RMSD value increases. Lower temperature favors stabilization of protein-ligand complex. During simulations, no loop was seen which indicates less deviation due to binding of the ligands Figure 4.
Root mean square fluctuation is used to study the fluctuation values of the atomic coordinates of the atoms of amino acids [34]. Fluctuations values were used to analyze the configurational changes in the presences of ligand at different temperature. RMSF graphs for the protein with A, G and D were analyzed and given the Figure 5. From the analysis, fluctuations were recorded in range of 140-160, 40-60, 160-180, 240-260 amino acids. Most of the fluctuations were occur in the range of amino acid comes in molecular docking range.
Radius of gyration is the measure of the distance between center of mass and axis of rotation. It is used to study the stability of protein in presence of small molecules. Lesser the value of radius of gyration indicates higher the stability [35, 36]. Radius of gyration values were analyzed for the main protease of nCoV in presence of A, G and D at different temperature (Figure 6). At low temperature, radius of gyration is less meaning more stability. But an increasing temperature value of Rg increases and thus the stability decreases. Results of molecular docking corroborate the results obtained by MD simulations.
Molecular dynamic simulation analysis used to examine their of Mpro of nCoV in presence of A, G and D over time span at various temperature. Conventional hydrogen bonding is more significant and formed between fluorine, oxygen and nitrogen with hydrogen. The anchoring is tighter as the number of hydrogen bond increases and the length of hydrogen bond decreases [37, 38]. The number of hydrogen bonds and their persistency were analyzed during simulation at different temperatures as given in Figure 7. Maximum number of hydrogen bonds were found 6 in case of acyclovir while in case of derivative and ganciclovir maximum hydrogen bonds are five.
3.4 Absorption, Distribution, Metabolism and Excretion (ADME) of A, G and D
ADME characteristics is as important in the drug development process [39]. ADME drug characteristics such as absorption, distribution, metabolism and elimination are critical to a drug candidate’s clinical success. It is estimated that about 50% of the drugs fails due to insufficient effectiveness which includes low bioavailability due to inadequate intestinal absorption and poor metabolic stability [40–43]. Lipophilicity is one of the most important criteria to predict the molecule as a drug and it is a partition coefficient of n-octanol and water (log PO/W). It determines the amount of solute dissolves in the water v/s organic solvent in a solution [44]. The partition coefficient is a significant indicator of a substance physical constitution and determines its behavior in various situation. For effective drug, the value of log PO/W is less than or equal to 5 [45]. Solubility is an important criterion for deciding a molecule to be drug, therefore, log S should be less than 6. According to Lipinski’s rule of five an orally active drug must have: (i) hydrogen bond donor less than or equal to five (ii) hydrogen bond acceptor less than or equal to ten (iii) molecular mass less than 500g/mol (iv) log P values less than 5 [46–48]. Table 5 shows the physiochemical properties of A, G and D. All the studied molecules obey the Lipinski rule of 5.
Table 5
Physiochemical properties of acyclovir, ganciclovir and hydroxymethyl-ganciclovir
Physiochemical properties
|
Acyclovir
|
Ganciclovir
|
Derivative of acyclovir
|
Log S
|
-0.41
|
-0.42
|
0.37
|
Solubility
|
Very soluble
|
Very soluble
|
Highly soluble
|
Heavy atoms
|
16
|
18
|
20
|
Molecular weight (g/mol)
|
225.20
|
255.23
|
285.26
|
No. of rotational bonds
|
4
|
5
|
6
|
No. H-bond acceptors
|
5
|
6
|
7
|
Num. H-bond donors
|
3
|
4
|
5
|
Log Po/w (WLOGP)
|
-1.48
|
-2.11
|
-2.75
|
Physiochemical space for oral bioavailability
|
|
|
|
Drug likeness is an important criterion for evaluating behavior of molecule during early stage of drug development. This factor may be regarded as a way to link physicochemical properties of a compound to its biopharmaceutical properties in the human body for oral delivery. Despite the fact that there are several methods for delivery of oral dosages is favored for patient comfort and compliance. At various stages of the discovery process, early assessment of oral bioavailability i.e. the percentage of the dosage that reaches the blood following oral administration, is a significant decision- making factor. Bioavailability is influenced by a number of factors but gastrointestinal absorption is most important. The BBB may be regarded as a shield that protects the brain through a “physical” barrier and a “biochemical” barrier (e.g. P glycoprotein pumping out substrate from CNS tissues). Blood-brain barrier is a system that ensure the consistency of central nervous system environment by allowing brain tissues to interchange nutrient with the outside world. Effective BBB penetration is important for targeting CNS illness, but non-CNS drugs should have restricted BBB penetration due to side effect [49]. Despite the importance of active transport, passive diffusion is the primary route for drug to reach the brain from the blood. The method for assessing active efflux through biological membrane such as from the gastrointestinal wall to the lumen or from the brain, requires knowledge of compounds that are substrate or non- substrate of the permeability glycoprotein. P-gp has a number of functions, one of which is to protect the central nervous system from xenobiotics. TPSA is a key characteristic for drug likeness and its value must be smaller than 130 Å. TPSA is considered to be a useful indicator of a compounds ability to transport drug. In Table 6 bioactivity and drug likeness score of A, G and D are given. A shows high GI absorption, TPSA value 119.06 Å and following Lipinski rule with zero violation [50, 51]. G and D have TPSA value more than 130 Å but they followed the Lipinski rule with zero violation.
Table 6
Bioactivity and Drug likeness score of acyclovir, ganciclovir and hydroxymethyl-ganciclovir
C. No.
|
GI absorption
|
BBB permeant
|
Lipinski rule
|
Log Kp (skin permeation)
(cm/s)
|
TPSA (Å)
|
P-gp substrate
|
A
|
High
|
No
|
Yes; 0 violation
|
-8.78
|
119.06
|
No
|
G
|
Low
|
No
|
Yes; 0 violation
|
-9.04
|
139.29
|
No
|
D
|
Low
|
No
|
Yes; 0 violation
|
-10.20
|
159.52
|
No
|