There are several ways, in which chemical stability of a molecule can be calculated. The simplest one involves difference in energy between highest occupied molecular orbital (HOMO) and lowest unoccupied molecular orbitals (LUMO) of a system. It is also a key parameter to determine the molecular properties of a molecule . Energy of HOMO and LUMO are computed theoretically by DFT-RB3LYP/6-31G(d,p) method and the contour diagrams of best molecules are shown in Fig. 3, where positive and negative lobes are noted as red and green color, respectively. HOMO has ability to donate electron and behave as nucleophile and on the other hand, LUMO has electron accepting tendency from nucleophile, behave like electrophile .
The chemical reactivity, kinetic stability, optical polarizability and chemical hardness-softness of a molecule depend on the band gap energy (∆EHL) of HOMO and LUMO. Molecule possessing small ∆EHL, has higher chemical reactivity as well as highly polarizable and behaves as soft molecule [24, 25]. On the other hand, relatively higher ∆EHL value indicates high chemical stability as well as least chemical reactivity for a molecule. Besides, the molecules with higher dipole moment have a tendency to participate in strong intermolecular interaction. The chemical softness of the molecules depends on the degree of chemical reactivity and the reverse is in the case of hardness .
In this study, we have found 34 derived molecules with higher ∆EHL value (> 5.65eV) and the remaining 19 compounds with low or slightly small ∆EHL value (< 5.65eV). Among them, R9 has the highest value (8.5eV) and therefore it is highly unreactive species. On the other hand, R41 is the compound possessing the lowest ∆EHL of 3.7eV and is considered as highly polarizable, reactive species i.e. soft compound. From dipole moment parameters, it is found that 7 compounds such as R8, R9, R15, R27, R35, R43 and R50 have larger tendency, to participate in strong intermolecular interaction (dipole moment > 6 Debye).
Global reactivity descriptors
In order to understand various aspects of pharmacological properties and eco-toxicological character of drug molecules, several new chemical descriptor parameters have been developed. Conceptual DFT based parameters were used to understand the structure, reactivity of molecules by calculating various useful parameters like chemical potential, global hardness, softness and electrophilicity index. Using HOMO and LUMO energy, the ionization potential (I) and electron affinity (A) can expressed as
Using these values, other descriptor properties such as chemical potential (µ), global hardness (η), global softness (S), electronegativity (σ) and electrophilicity index (ω) were calculated.
Chemical stability of a system is represented by global hardness . This property predicts the measure of resistance to change the distribution of electronic charge in a molecule . According to Parr, electrophilicity index (ω) has determine the capacity of a species to accept electron . The lower chemical hardness value (ƞ≤2.83eV) with low chemical potential (µ<-2.74eV) of R13, R15, R27, R35, R36, R41, R44 and R45 may lead to act these compounds as soft with higher polarizablility, compared to others in this series. On the other hand, higher value of electronegativity (σ>3eV) and elecrophilicity index (ω>1.5eV) of R12, R15, R27,R28, R29, R35, R36, R41, R43, R44, R45, R46, R50 and R52 have indicated higher electron withdrawing tendency, act like electrophiles.
Molecular descriptor properties
In silico drug like properties and bioactive score were used to select best drug candidates, using OSIRIS suite and Molinspiration online property toolkit. Mutagonic, tumorigenic, irritant, reproductive index and drug-like, drug score values were visualized from OSIRIS and similarly, Molinspiration web server has predicted such valuable parameters like miLogP, TPSA, number of rotatable bonds (nrotb), number of hydrogen bond acceptors (nON) and donors (nOHNH). Good permeability across cell membrane is based on miLogP parameter. The tendency of generating hydrogen bonds is based on TPSA parameter. Number of rotatable bonds denotes the flexibility of a molecule. Molecular properties and structural features, irrespective of known drugs were checked on the basis of drug-likeness data of molecules . The excellent results (Table 3, S3, S4) have shown the probability of these compounds as future drugs.
According to Lipinski’s rule of five, all compounds having zero violation have shown good bioavailability and here all the derived compounds may act as good bioavailable drug. Molecules having nOHNH≤5, have indicated higher probability of solubility in cellular membranes and here all of these derived compounds have followed this rule . Besides, all the molecules having molecular weight, MW<450, nON≤10, nrotb<10 and TPSA<160Å, are qualified oral route of newly designed molecules [29, 30].
Table 4 illustrates the in silico ADME properties. Most important parameters, used for pharmacokinetic study of a drug are absorption, distribution, metabolism and excretion . In silico ADME properties of most of these derived compounds have shown satisfactory result. In this present work, 34 derived compounds have better result for intestinal absorption (HIA>90%), closed to 100. Out of these, R19 containing highest value of HIA (100%), has shown maximum absorption. Most of the derived compounds have followed moderate permeability in vitro Caco2 cell ranges, 19-22 nm/sec and few of them were failed, showing very unsatisfactory results. Also they have low or moderate permeability for in vitro MDCK cells. Results having, in vivo blood brain barrier (BBB) penetration indicate that most of the compounds (except R3, R20 and R44) have low absorption into central nervous system (CNS), less capability to cross CNS. 23 compounds, containing plasma protein binding data (PPB) indicate higher bound capacity, higher skin permeability than standard rivastigmine. Thus from overall results, we may concluded that most of these derived compounds have capability of good drug likeness and ADME properties.
Molecular docking studies
Molecular docking is becoming an increasingly significant method to realize the foundation of protein-ligand visualization .This present study was done to determine the binding affinity of the ligands with the active sites of bovine serum albumin (PDB: 4F5S) (Table S5). Binding energy of a protein-ligand complex gives the idea of strength and affinity of the interaction between the ligand and the protein. Binding energy of rivastigmine has shown the value of -6.6Kcal/mol when docked with receptor. The docking results indicated that 23 derived compounds have better results of binding energy than standard rivastigmine as shown in Fig. 4. These best 23 compounds are named as R1, R2, R3, R4, R5, R6, R8, R10, R13, R22, R24, R27, R28, R30, R32, R36, R40, R42, R45, R47, R49, R50 and R53. Among them, binding energies of the compounds R36 and R47 were come out as highest (-7.6 Kcal/mol and -7.5 Kcal/mol respectively). The active site residues of the receptor was represented as ASP323, ARG208, LEU326, LYS350, ALA212, ALA349, GLU353, ALA209, LEU346, LEU480, PHE205, VAL481, LEU330, GLY327, LYS211. Introduction of two acid groups (-COOH) in R36 compound (Fig. 5) and one amide group (–CONH2) in R47 compound (Fig. 6) have given the highest value of negative binding energy. From the docking result we found one conventional hydrogen bond for compounds R2, R1,R12,R18, R20,R26, R32, R28, R36 R37, R45, R52 ; two conventional hydrogen bonds for compounds R7, R9, R13,R19, R21, R23, R30, R43, R50, R53; three conventional hydrogen bonds for R3, R8, R10, R29, R34, R35, R37, R38, R40, R47.
MD simulation analysis
The best protein-ligand complexes of the receptor (PDB ID: 4F5S) docked with two best designed inhibitors (R36 and R47) along with standard rivastigmine were simulated for understanding structural deviations in dynamic environment for the time scale of 10 ns. Each inhibitor along with its complex was recorded for root mean square deviation (RMSD) from its initial position and the calculated values were plotted in Fig. 7a. It has been found that the RMSD of these compounds shows satisfactory stability in dynamic conditions.
In this case, RMSD lines for all the two docked complexes have follow the similar pattern and are almost coincide with the standard protein-rivastigmine complex line. All these three lines are parallel to x-axis after 2 ns. In case of ligands cases, these best designed docked compounds (R36 and R47) have lower RMSD pattern, compared to standard rivastigmine after approximately 4 ns In conclusion, all these two ligands have satisfied the validation of protein-ligand interactions in terms of RMSD values. In Fig. 7b, we have shown the root mean square fluctuation (RMSF), which measures the deviation of each amino acid of the used protein over a time interval of 10 ns. The overall result shows that the RMSF values of all the amino acids of the proteins docked with these two best inhibitors along with standard one do not change considerably as compared to their receptors.
On the other hand, Fig. S1 illustrates the radius of gyration (Rg) and solvent accessible surface area (SASA) plots for these two best ligands along with standard rivastigmine, docked with studying receptors. Rg has determined the compactness of the system. Both these complexes correspond similar Rg pattern of about 2.78 nm as compared to standard complex after 10 ns, revealing similar compact behaviour for these two complexes (Fig. S1a). In Fig. S1b, it has been found that the docked structures (protein-R36 and protein-R47) have almost similar SASA pattern of around 303 nm2, compared with protein-rivastigmine complex.
Furthermore, we have performed g_mmpbsa binding free energy analysis and we have measured the contribution energy of each residues as shown in Fig. S2. Different free energy parameters that contribute to the binding energy are plotted in Fig. 8. Here, the docked complex of R47-4F5S has the highest contribution towards van der Waal interaction, electrostatic, polar and non-polar solvation as well as binding free energy (Table S5).