In Silico drug evaluation by molecular docking, ADME studies and DFT calculations of 2-(6-chloro-2-(4-chlorophenyl)imidazo[1,2-a]pyridin-3-yl)-N, N-dipropylacetamide

Abstract

In this study, the structural, electronic, pharmacokinetic, and biological properties of molecule 2-(6-kloro-2-(4-klorofenil)imidazo[1,2-a]piridin-3-il)-N, N-dipropilasetamid (Alpidem), an imidazopyridine derivative anxiolytic known for its high BZ₁ (benzodiazepine-1) receptor affinity and low adverse effect profile, were comprehensively investigated by density functional theory (DFT) and in-silico methods. The alpidem molecule was optimized using the 6-311G(d, p) basis set with the B3LYP and B3PW91 methods; information on the stability and chemical reactivity of the structure was obtained via the highest occupied molecular orbital (HOMO), lowest unoccupied molecular orbital (LUMO), molecular electrostatic potential (MEP) maps, natural bonding orbital (NBO) analysis, non-linear optical (NLO) properties, and Mulliken charge distributions. Comparative analysis of two different methods has shown that the results are consistent with each other and provide reliable data. In addition, the drug similarity, bioavailability score, bioactivity values, absorption, distribution, metabolism, and excretion (ADME) profiles of the Alpidem molecule were calculated, and it was determined that the Alpidem molecule has pharmacologically favorable properties. Within the scope of molecular docking analyses, its interactions with two different enzymes (PDB ID: 2Z5X and 4BDT) associated with Alzheimer’s disease were evaluated. The binding energy values obtained were − 8.00 kcal/mol (2Z5X) and − 9.60 kcal/mol (4BDT), respectively, and the strong binding affinity, especially with the 4BDT protein, suggests that Alpidem may be a potential inhibitor candidate in Alzheimer’s disease. This multi-level theoretical study demonstrates that Alpidem is a drug repurposing molecule not only as an anxiolytic but also in neurodegenerative diseases and provides important data that will shed light on experimental studies. The results of this multi-level theoretical study show that Alpidem is a drug repurposing molecule not only as an anxiolytic but also in neurodegenerative diseases and provides important data that will shed light on experimental studies.

Introduction

Since nitrogen heterocycles are used in organic chemistry, materials science, optics, and organometallic chemistry, they are of great significance in agricultural chemistry and contemporary medicines [1]. Twelve of the top 25 medications were categorized as small molecule therapies and contained heterocyclic moieties, according to an analysis of their sales. Together, these moieties, which were usually composed of nitrogen atoms, brought in more than US$50 billion a year [2]. In this context, a range of pharmaceutical compounds with a variety of biological functions comprise bicyclic systems with a fused imidazole ring and a bridgehead nitrogen, such as imidazo[1,2-a]pyrimidine, imidazo[1,2-a]pyrazine, and imidazo[1,2-a]pyridine [3]. Analgesic, antituberculosis, antibacterial, antifungal, antiprotozoal, anti-inflammatory, antiulcer, antiviral, anticancer, anticonvulsant, antitumor, anthelmintic, antiepileptic, and antipyretic properties are just a few of the many activities that have resulted from the synthesis of imidazo[1,2-a]pyridine in medicinal chemistry in recent years [4]. Alpidem, Zolimidine, Olprinone, and Zolpidem are a few examples of pharmaceuticals. Numerous bioactive chemicals and natural products contain these main types of heterocyclic compounds [5]. Condition-based differentiation in organic synthesis has been emphasized in the field as a useful and efficient technique for finding new organic reactions [6]. This has led to the creation of intriguing molecules from the same initial reactants by merely altering the conditions, such as by regulating the reaction time [7].

DFT calculations provide thermodynamic parameters and electronic properties of molecules. Gaussian 09 is widely accepted and researched or used by scientists and researchers, most commonly chemists, physicists, biochemists, and chemical engineers [8]. From energy profiles and geometric structures to electrical properties and optical qualities, DFT is becoming a dependable and affordable method for exposing basic information about material properties. From the tiny realm of atoms and molecules to larger unit cells, this adaptable method is proving crucial for understanding data at different dimensions [9]. For this purpose, in this study, “Density Functional Theory” (DFT) methods, which form the basis of quantum chemistry calculations, were used. Perdew and Wang (PW91), which is a three-parameter exchange-correlation function, and the Lee-Yang-Parr correlation function (B3LYP) are the functions of the DFT method that aims to calculate electron density [10–12]. Calculations were made with basis sets such as 6-311G(d, p), which provide more detailed and reliable results. Since it is possible to determine the structural properties, geometry, internal energy, spectroscopic properties, electronic and thermodynamic properties of a molecule with the selected methods and sets, these methods and basis sets were chosen.

A progressive neurological illness, Alzheimer’s disease (AD) is becoming a significant worldwide public health issue. The main cognitive impairments caused by AD are memory loss, trouble with thinking, and behavioral abnormalities [13]. Families, caregivers, and healthcare institutions are all heavily burdened by this illness in addition to the patients themselves. The World Health Organization (WHO) estimates that 55 million people worldwide suffer from dementia, with AD accounting for 60–72% of cases [14]. By 2050, this number is predicted to rise to 152 million. There are very few viable therapies available despite much study [15]. But with two developments in molecular biology and neurology, we now have a better knowledge of the fundamental processes driving AD, which opens up new treatment options [16]. Enzymes like acetylcholinesterase (AChE) and monoamine oxidases (MAOs) in particular are crucial in interfering with cholinergic and monoaminergic transmission, which intensifies the cognitive loss associated with AD [17]. A promising strategy to slow neurodegeneration and enhance patient outcomes is to target these enzymes. Because of its role in cholinergic neurotransmission, AChE is crucial in the treatment of AD [18]. In AD, acetylcholine (ACh) levels are lowered, which affects cognition and memory. In the synaptic cleft, AChE quickly breaks down ACh, aggravating cognitive impairments. Restoring cholinergic neurotransmission is facilitated by targeting AChE [19]. Because of their possible role in neurodegenerative processes and neurotransmitter imbalances linked to AD, monoamine oxidases (MAOs) have garnered interest [20]. One possible explanation for the pathophysiology of AD is the dysregulation of neurotransmitters like serotonin and dopamine. By oxidatively deaminating certain neurotransmitters, MAOs decrease neurotransmission. Inhibiting MAO activity can improve neuronal function and cognition by increasing synaptic dopamine and serotonin levels [21].

In this study, theoretical calculations of the Alpidem compound synthesized by Iranfar et al. [22] were performed using density functional theory (DFT) B3PW91, B3LYP methods and 6-311G(d, p) basis set. In addition, biological activity analyses were performed to evaluate the potential therapeutic effects of the compound for Alzheimer’s disease. In this context, the therapeutic potential, safety, and selectivity profile of Alpidem were examined, and its suitability for Alzheimer’s treatment was investigated. In order to better understand the factors determining the dual inhibitory properties of the compound, molecular docking analyses were performed against monoamine oxidase (MAO, PDB ID: 2Z5X) and acetylcholinesterase (AChE, PDB ID: 4BDT) enzymes. With these analyses, it was aimed to provide rational explanations for compound-enzyme interactions, establish relationships with biological results, and understand the inhibitory activity at the molecular level. In addition, in order to evaluate the potential of the Alpidem compound in the drug development process, in silico ADME (absorption, distribution, metabolism, and excretion) studies were carried out to examine its drug-like properties.

Materials and methods

The alpidem molecule was first drawn in ChemBioDraw for DFT calculations in the gas phase with the Gaussian 09 program [23] and minimized by the SYBL2 (mol2) method with the Chem3D program. Similarly, the drawn molecules were converted to 3D MOL2 files in Chem3D and transferred to GaussView 6.0. DFT study was calculated on the 6-311G (d, p) basis set in the B3PW91 and B3LYP methods, and images of each calculation (geometry optimization (bond length, bond angles, planar bond angles), HOMO and LUMO analysis, Mulliken atomic charges, MEP, NLO, and NBO analysis) were taken. A molecular docking study for ligand-enzyme interactions and the compound’s potential to bind to protein as an inhibitor was performed with Schrödinger’s Maestro Molecular Modeling platform (version 11.8) (the ligand-protein docking approach was realized with the glide docking module) [24]. The crystal structures of enzyme codes (PDB ID: 2Z5X and PDB ID: 4BDT) were downloaded from the PDB database [25]. Preparation and ligand docking placement studies were carried out using the LigPrep module, protein prep, and receptor grid box modules. Inhibition performance, docking score, and binding conformations were determined. Docking study results were visualized with the Discovery Studio 2016 client (Visualizer 2005) [26]. The physicochemical properties of the Alpidem molecule, drug similarity model score, bioactivity scores, absorption, distribution, metabolism, excretion (ADME), and toxicity properties were predicted in silico using online tools such as Admetlab 2.0 [27].

Results and discussion

Structure analysis

Table 1 lists the optimal parameters, which were determined by calculating the molecule’s dihedral angles as well as the lengths and angles between atoms. The bond length determines the atom’s size, bond energy, and electronegativity. On the other hand, bond length equals both electronegativity and bond energy [28]. From the table it has been found that the distance between C-C atoms varies between 1.36870Å and 1.54618Å. We observed that the distance between C-Cl atoms was 1.74444Å-1.75906Å, the distance between C-N atoms was 1.35931Å-1.40343Å, the distance between C-O atoms was 1.22422Å-1.22598Å (high) and the angle between C19-N20-C24 atoms had the highest bond angle. We observed that the bond lengths and bond angles, calculated by two different methods, are compatible with each other and are compatible with the bond lengths in the literatüre [29]. The Alpidem molecule’s optimized geometry has been given in Fig. 1 utilizing the B3LYP method.

Table 1.

The alpidem molecule’s theoretically calculated some bond angles (^o) and bond lengths (Å)

Bond lengths	B3PW91	B3LYP	Bond lengths	B3PW91	B3LYP
C1-C2 C3-C4	1.38706 1.36870	1.38886 1.36932	C25-C26 C14-CI17	1.52540 1.74460	1.53143 1.75893
C1-C6	1.38157	1.38217	C6-N5	1.39675	1.40343
C9-C11	1.44132	1.44552	C4-N8	1.37063	1.37629
C11-C12	1.41298	1.41542	C1-C17	1.74444	1.75906
C13-C14	1.39134	1.39262	C19-N20	1.35931	1.36385
C14-C15	1.39292	1.39421	C19-O27	1.22422	1.22598
C15-C16	1.38415	1.38656	N8-H31	1.00676	1.00773
C18-C19	1.53982	1.54618	C16-H35	1.08340	1.08224
C22-C23	1.52535	1.53124	C23-H42	1.09296	1.09260
Bond Angles B3PW91 B3LYP Bond Angles B3PW91 B3LYP
C1-C2-C3	118.11237	118.00813	C10-C18-C19	116.06336	115.86412
C4-N5-C6	120.25542	120.08099	C18-C19-O27	118.86073	118.68656
C4-N8-C9	110.07633	109.89616	C19-N20-C24	125.70257	125.79009
C9-C11-C16	122.63654	122.73302	C6-C1-CI7	117.07073	116.98971
C12-C13-C14	119.67658	119.61403	H36-C18-H37	107.18416	107.19153
Planar Bond Angles B3PW91 B3LYP Planar Bond Angles B3PW91 B3LYP
C3-C4-N5-C10	178.10051	177.79358	N20-C21-C22-C23	179.08316	179.21558
C9-C10-C18-C19	123.18999	122.41355	N20-C24-C25-C26	176.04554	176.15925
C9-C11-C16-C15 C10-C18-C19-O27	179.50359 109.37400	179.45719 107.08274	C13-C14-C15-H34 N5-C4-N8-H31	177.97921 156.59414	178.08569 155.19605

Fig. 1.

Optimized geometry display using the B3LYP method and 6-311G(d, p) basis set of the Alpidem molecule

Mulliken atomic charges

The oldest and most widely utilized technique for population study is the Mulliken charge distribution. The fact that it is found in many programs is an effective factor in its widespread use [30]. This method is dependent on the method of obtaining molecular orbitals by linear combination of atomic orbitals and is based on the distribution of wave functions to atoms while distributing the places where two orbitals overlap equally. Mulliken charges of the optimized crystal structure were carried out using the methods of studying the gas phase. The Mulliken charge’s distribution has been given in Table 2. Carbon atoms’ Mulliken charges were either positive or negative. Every hydrogen atom had a net positive charge; however, because of the electronegative atom (N8), H31 received the most positive charge from other hydrogen atoms. They serve as atoms that receive. Also, it was proved that the optimized compound has a negative charge because the oxygen atom acts as a donor atom. We observed that the Mulliken atomic charges determined by two different methods are close to each other.

Table 2.

The alpidem molecule’s mulliken atomic charges

Atoms	B3PW91	B3LYP	Atoms	B3PW91	B3LYP
C1	-0.419	-0.375	N5	-0.540	-0.484
C3	-0.267	-0.236	N8	-0.524	-0.481
C6	0.218	0.198	CI7	-0.058	-0.070
C9	0.136	0.124	N20	-0.406	-0.393
C11	-0.164	-0.138	CI17	-0.065	-0.386
C13	0.024	0.026	O27	-0.365	-0.352
C14	-0.268	-0.245	H31	0.246	0.237
C15	0.023	0.024	H33	0.127	0.117
C16	-0.103	-0.091	H35	0.123	0.109
C18	-0.354	-0.285	H39	0.156	0.136
C19	0.436	0.409	H40	0.159	0.139
C21	-0.129	-0.084	H43	0.126	0.112
C22	-0.250	-0.213	H45	0.164	0.142
C23	-0.344	-0.306	H47	0.136	0.117
C25	-0.261	-0.218	H49	0.126	0.111
C26	-0.347	-0.309	H51	0.141	0.124

HOMO and LUMO analysis

Frontier orbitals, or HOMO and LUMO, give information on a molecule’s electrical, optical, and reactive characteristics. They are employed to forecast the energy, stability, and reactivity of a compound’s orbitals. The softness, hardness, chemical activity, intramolecular charge transfer, and relative stability of the molecule are all significantly influenced by the energy differential between the LUMO and HOMO orbitals [31]. More instability, greater softness, more chemical reactivity, and simpler electron excitation are all indicated by lower HOMO and LUMO energy gaps. Greater stability, higher chemical hardness, less chemical reactivity, and less easy electron excitation are all indicated by larger energy gaps [32]. The B3PW91 method gave HOMO and LUMO orbital energy values of -0.8346 eV and − 6.8662 eV, respectively. The HOMO and LUMO orbitals’ computed energies in the B3LYP method gave − 1.6065 eV and − 6.4016 eV, respectively. The energy gap ((ΔE)|E_HOMO-E_LUMO) of the mentioned organic molecule for both basis sets was found to be 6.0316 eV and 4.7951 eV. The low value of this energy gap indicated that the Alpidem molecule exhibited high chemical reactivity, biological activity, and polarizability. In Figs. 2 and 3 and D HOMO-LUMO diagrams have been given according to the energy values of the Alpidem molecule calculated using the B3LYP, B3PW91 methods and 6-311G(d, p) basis set. Table 3 shows the chemical reactivity parameters of the Alpidem molecule calculated using the B3LYP, B3PW91 methods and the /6-311G(d, p) basis set. Furthermore, the energies of the HOMO and LUMO orbitals were utilized to compute the chemical reactivity parameters of the examined molecule, including chemical softness (s), chemical potential (µ), chemical hardness (η), and electrophilicity index (ω). The compute chemical potential, chemical hardness, electrophilicity index, and chemical softness values for the B3PW91 and B3LYP methods for the studied molecule were found to be (-3.8504, -40041) eV, (3.0158, 2.3975) eV, (1.5079, 1.1987) eV, and (2.4580, 3.3436) eV, respectively. Information on a compound’s capacity to bind with biomolecules may be found in its electrophilicity index. Furthermore, the HOMO orbitals were partially situated on the benzene ring that was bound to the atom (C1 and N5) and focused on the carbon atom (C6).

Fig. 2.

The alpidem molecule’s boundary molecular orbitals calculated with the B3PW91 method

Fig. 3.

The alpidem molecule’s boundary molecular orbitals calculated with the B3LYP method

Table 3.

Calculated the alpidem molecule’s quantum chemical parameters using the B3PW91 and B3LYP methods

Molecules energy		B3PW91	B3LYP
ELUMO		-0.8346	-1.6065
EHOMO		-6.8662	-6.4016
ELUMO+1		0.2155	0.2248
EHOMO−1		-6.9173	-6.8645
Energy Gap	(ΔE)|EHOMO-ELUMO|	6.0316	4.7951
Ionization Potential	(I = − EHOMO)	6.8662	6.4016
Electron Affinity	(A = − ELUMO)	0.8346	1.6065
Electronegativity	(χ=(1 + A)/2)	0.9173	1.3032
Chemical Potential	(µ=−(I + A)/2)	-3.8504	-4.0041
Chemical hardness	(η=(I − A)/2)	3.0158	2.3975
Chemical softness	(s = 1/2η)	1.5079	1.1987
Electrophilicity index	(ω = µ2/2η)	2.4580	3.3436

Molecular electrostatic potential (MEP)

MEP is a highly helpful descriptor for hydrogen bonding interactions and is correlated with electron density. MEP is also an excellent tool for examining the mechanisms behind interactions between enzymes and substrates as well as between drugs and receptors [33]. The relative reactivity regions for electrophilic and nucleophilic attacks on a molecule are predicted using molecular electrostatic potential, or MEP [34]. MEP surface analysis of the Alpidem molecule was determined using B3PW91 and B3LYP methods. The map of the investigated compound’s electrostatic potential surface has been given in Fig. 4. For the B3PW91 approach, the compound’s color code falls between − 6.632 eV and + 6.632 eV, whereas for the B3LYP method, it falls between − 6.355 eV and + 6.355 eV. The red and blue colors represented the more electron-rich and electron-poor regions of the MEP structure, respectively. In MEP, hydrogen atoms had the positive potential areas, whereas electronegative atoms (such as oxygen and nitrogen) had the negative potential regions.

Fig. 4.

The alpidem molecule’s MEP surface calculated B3PW91 and B3LYP methods

Non-linear optical properties (NLO)

Applications in data storage, laser technology, telecommunications, image processing, optical signaling, nanofabrication, and biological imaging are all potential uses for nonlinear optical (NLO) materials. The total statistical dipole moment (µ), average polarizability (α), anisotropy of polarizability (Δα), and average first-order hyperpolarizability (β) were computed using the DFT method in order to examine the NLO characteristics of the title chemical [35]. The computed outcomes have been given in Table 4. Numerous research have documented utilizing urea as a positive control material for comparison, making it one of the first NLO materials to be acknowledged.

Table 4.

Alpidem molecule’s NLO parameters of calculated using B3PW91 and B3LYP methods

Parameters	B3PW91	B3LYP	Parameters	B3PW91	B3LYP-
βXXX	20.4327	-8.5343	µx	-4.4312	4.6782
βYYY	14.8251	2.7136	µy	3.2468	2.5021
βZZZ	3.0527	-0.4164	µz	1.9304	-1.5944
βXYY	-31.8937	34.8689	µ(D)	5.8227	5.5397
βXXY	7.9131	1.4277	αxx	-197.5805	-200.8606
βXXZ	30.5951	-26.9186	αYY	-159.6822	-160.7123
βXZZ	-11.8831	8.9182	αzz	-179.0743	-180.3828
βYZZ	9.4273	9.9184	αXY	21.0014	-21.1221
βYYZ	38.2456	-35.7831	αXZ	1.6502	1.6816
βXYZ	25.2626	24.0736	αYZ	-11.2735	10.4550
β(esu)	3.55 × 10− 30	3.60 × 10− 30	α(au)	5.9649	5.6790

Urea (Reference)= µ_(D)=1.3197, β(esu) = 0.1947 × 10^− 30

Equations (1–3) calculated the average values of the total first static hyperpolarizability (β), static dipole moment (µ) and polarizability (α) of the x, y, and z components. According to calculations, the query molecule’s primary hyperpolarizability parameters were 5.8227, 5.5397 µ(D), 5.9649, 5.6790 α(au), and 2.77 × 10^− 30, 2.70 × 10^− 30 β(esu) in the B3PW91 and B3LYP techniques, respectively. According to reports, the reference compound’s first-order hyperpolarizability value was 0.1947 × 10^− 30 esu (β). Compared to urea, the query chemical exhibited almost seven times greater hyperpolarizability activity. In the relevant part, we specified the compound’s hyperpolarizability, and the resulting outcome is likewise compatible with the energy gap value. The compound could be a good NLO material candidate because the computed results were better than the control material.

1

2

3

NBO analysis

Information about conjugative and hyperconjugative interactions in a compound, as well as intramolecular and intermolecular hydrogen bonding, can be obtained from NBO [36]. Natural bond orbital calculation was carried out under the Gaussian 09 W program package using the B3PW91 method. The donor-acceptor stabilization energy E(2) related to the i→j delocalization is computed as follows for each donor NBO (i) and acceptor NBO (j): E(2) = qi.F(i, j)² / (ɛ_i-ɛ_j)

where qi is the donor orbital occupancy (2 for closed shell, 1 for open shell), ʛi, ɛj are diagonal elements (orbital energies), and F(i, j) is the off-diagonal NBO Fock matrix element. The whole chemical system gains from a higher degree of conjugation because of the bigger stabilizing energy value E2 [37]. The donor-acceptor connection can therefore be maintained by electron delocalization between occupied Lewis and unoccupied non-Lewis-type native bonding orbitals. Additional delocalization inside the molecular system is demonstrated by the electron density of the conjugated single and double bonds of the conjugated system [38]. According to the findings of the NBO analysis, the examined compound’s non-Lewis structure is 2.65% (valence non-Lewis, 2.48%, and Rydberg non-Lewis, 0.20%) and overall Lewis structure is 97.31% (core, 99.96%, and valence Lewis, 99.64%). The theoretical conclusion revealed several kinds of interactions, including π → π*, σ → σ*, σ* → σ*, and π* → π* (Table 5). The two transitions computed above are therefore in good agreement with the measured electronic spectra, according to the NBO findings. π(C-C) interactions and antibonding π*C-C) interactions are the main mechanisms by which the equivalent π* bonds in aromatic rings are conjugated. The interactions of πC11-C12 with π*C13-C14 and πC11-C12 with π*C15-C16 and πC13-C14 with π*C11-C12 and πC13-C14 with π*C15-C16 and πC15-C16 with π*C11-C12 and πC15-C16 with π*C13-C14 were observed in the C11/C16 benzene ring with the stabilization energies of 10.03, 10.74, 11.16, 8.83, 8.59, and 11.24 kcal/mol, respectively. The interactions of πC1-C2 with π*N5-C5 and σC3-H29 with σ*C4-N5 and σ*C13-C14 with σ*C15-C16 and π*C3-C4 with π*C1-C2 were observed to have high stabilization energies of 23.63, 3.43, 122.34, and 152.96 kcal/mol, respectively (Table 5). The aforementioned energies demonstrated that heteroatoms and the aromatic ring had a resonance relationship and stabilized the structure of the molecule under study. As a result, the compound’s whole system has more conjugations. Furthermore, the molecule underwent intramolecular charge transfer and electron redistribution in different orbitals, as demonstrated by NBO and simulated electronic spectrum analysis.

Table 5.

Alpidem molecule’s selected NBO results of calculated using B3PW91 method

NBO(i)	Type	Occupancies	NBO(j)	Type	Occupancies	E(2)a (Kcal/mol)	E (j)-E(i)b (a.u.)	F (i, j)c (a.u)
C1-C2	π	0.80006	C3-C4	π*	0.19469	6.17	0.28	0.053
C1-C2	π	0.80006	N5-C6	π*	0.27886	23.63	0.23	0.097
C2-C3	σ	0.98166	C4-N8	σ*	0.01261	3.24	1.11	0.076
C3-C4	π	0.81932	C1-C2	π*	0.18937	11.98	0.31	0.077
C3-C4	π	0.81932	N5-C6	π*	0.27886	4.50	0.25	0.044
C3-H29	σ	0.98634	C4-N5	σ*	0.02052	3.43	0.93	0.072
N5-C6	π	0.87292	C3-C4	π*	0.19469	10.80	0.36	0.082
N5-C6	π	0.87292	C9-C10	π*	0.15229	8.74	0.36	0.072
C9-C10	σ	0.98227	C9-C11	σ*	0.01479	3.19	1.23	0.079
C9-C10	π	0.89932	N5-C6	π*	0.27886	6.30	0.26	0.056
C9-C10	π	0.89932	C11-C12	π*	0.19471	4.58	0.30	0.049
C11-C12	π	0.81640	C9-C10	π*	0.15229	8.87	0.29	0.065
C11-C12	π	0.81640	C13-C14	π*	0.19382	10.03	0.27	0.066
C11-C12	π	0.81640	C15-C16	π*	0.15373	10.74	0.28	0.071
C13-C14	π	0.82650	C11-C12	π*	0.19471	11.16	0.29	0.073
C13-C14	π	0.82650	C15-C16	π*	0.15373	8.83	0.30	0.065
C15-C16	π	0.83806	C11-C12	π*	0.19471	8.59	0.29	0.064
C15-C16	π	0.83806	C13-C14	π*	0.19382	11.24	0.28	0.072
C3-C4	π*	0.19469	C1-C2	π*	0.18937	152.96	0.01	0.085
N5-C6	π*	0.27886	C1-C2	π*	0.01351	37.27	0.06	0.088
N5-C6	π*	0.27886	C3-C4	π*	0.00951	19.35	0.05	0.057
N5-C6 C13-C14	π* σ*	0.27886 0.01534	C9-C10 C15-C16	π* σ*	0.01383 0.00824	11.63 122.34	0.05 0.01	0.047 0.082

In silico studies

ADME analysis

Predicting Absorbed, Distributed, Metabolized, and Excreted (ADME) boundaries from subatomic structure is one of its shared objectives [39]. In contrast to traditional approaches, computational approaches used to calculate drug similarity, pharmacokinetics guide the selection, and physicochemical properties of compounds with favorable properties, increasing the potential to discover new lead drug candidates in importantly reduced time frames [40]. This raises the possibility of finding novel lead medication candidates in a lot less time. Consequently, ADME investigations and in-silico molecular property predictions were carried out [40]. Admetlab 2.0 [27], a free online tool for evaluating drug similarity, was used to evaluate the study done on ADME. Drug molecular similarity has been assessed using a number of criteria, such as Lipinski’s rule of five and the Pfizer rule for oral bioavailability evaluation. Alpidem Lipinski conformed with all of the requirements when we looked at Lipinski’s rule of five, lipophilicity (LogP), molecular weight (MW), number of H-bond acceptors (HBA), and number of H-bond donors (HBD) factors. Color regions and physicochemical parameter maps of the studied compound have been given in Fig. 5. In Tables 6, 7, 8, 9, 10 and 11, the general results and comments of the in silico drug analysis of the Alpidem compound have been given. Table 6 shows the physicochemical and lipophilicity values of the Alpidem molecule and control ligands. When we examine the values, we see that the Alpidem molecule complies with the rules of 4BDT (Control Ligand) Lipinski, while 2Z5X (Control Ligand) does not comply with the rules of Lipinski.

Fig. 5.

Color regions and physicochemical parameters of alpidem molecule

Table 6.

Physicochemical properties and lipophilicity parameters of alpidem molecule

Property	ALPİDEM	2Z5X (C.Ligand)	4BDT (C.Ligand)	Comment
Molecular Weight	403.12	785.160	314.120	Molecular Weight < 600
nHA	4	24	3	Hydrogen bond acceptors < 12
nHD	0	13	3	Hydrogen bond donors < 7
nRot	8	10	2	Rotatable bonds < 11
nRing	3	6	2	nRing:0–6
MaxRing	9	14	16	Atoms in the biggest ring: 0–18
nHet	6	26	4	Heteroatoms:1–15
nRig	17	6	20	Rigid bonds:0–30
TPSA	37.61	362.930	59.140	Topological Polar Surface Area:0-140
logS	-5.352	-4.135	-5.570	Log of the aqueous solubility: -4-0.5 log mol/L
logP	5.107	-3.606	4.099	Log of the octanol/water partition coefficien: 0–5

Table 7.

Medicinal chemical properties of alpidem molecule

Property	Value	Decision	Comment
QED	0.522	●	• A drug-likeness measure based on the desirability notion; • Attractive > 0.67; unattractive 0.49–0.67; too complex < 0.34
SAscore	2.398	●	• The purpose of the synthetic accessibility score is to gauge how simple it is to synthesize drug-like compounds. • SAscore ≥ 6, difficult to synthesize; SAscore.
MCE-18	18.0	●	• MCE-1845 is considered a suitable value.
Lipinski Rule	Accepted	●	• MW ≤ 500; logP ≤ 5; Hacc ≤ 10; Hdon ≤ 5 • One property is acceptable if the other two are out of range, which might result in inadequate permeability or absorption.
Pfizer Rule	Rejected	●	• logP > 3; TPSA < 75 • Compounds that have a low TPSA (< 75) and a high log P (> 3) are probably toxic.
Golden Triangle	Accepted	●	• 200 ≤ MW ≤ 50; -2 ≤ logD ≤ 5 • The ADMET profile may be better for compounds that meet the Golden Triangle criteria.
PAINS	0 alerts	-	• Reactive compounds, frequent hits, alpha-screen artifacts, and pan assay interference compounds.

Accepted: ● Color, Rejected: ● Color

Table 8.

Absorption evaluation of pharmaceutical and pharmacokinetic properties of alpidem molecule in terms of chemical parameters

Property	Value	Decision	Comment
Caco-2 Permeability	-4.832	●	• higher than − 5.15 Log unit
MDCK Permeability	1.4e-05	●	• low permeability: <2 × 10− 6 cm/s • medium permeability: 2–20 × 10− 6 cm/s • high passive permeability: >20 × 10− 6 cm/s
Pgp-inhibitor	0.999	●	• The chance of being a Pgp-substrate is the output value.
Pgp-substrate	0.011	●	• MW ≤ 500; logP ≤ 5; Hacc ≤ 10; Hdon ≤ 5 • One property is acceptable if the other two are out of range, which might result in inadequate permeability or absorption.
HIA	0.002	●	• Category 1: HIA+(HIA < 30%); Category 0: HIA-( HIA < 30%); The output value is the probability of being HIA+
F20%	0.002	●	• 20% Bioavailability • Category 1: F20%+ (bioavailability < 20%); Category 0: F20%-(bioavailability ≥ 20%); The output value is the probability of being F20% +
F30%	0.002	●	• 30% Bioavailability • Category 1:F30%+(bioavailability < 30%); Category 0:F30%-(bioavailability ≥ 30%);The output value is the probability of being F30%+

Table 9.

Distribution evaluation of pharmaceutical and pharmacokinetic properties of alpidem molecule in terms of chemical parameters

Property	Value	Decision	Comment
PPB	97.98%	●	• Plasma Protein Binding • Optimal:< 90%. Drugs with a low therapeutic index may be highly protein-bound.
VD	0.89	●	• Volume Distribution, Optimal:0.04–20 L/kg
BBB Penetration	0.994	●	• Blood-Brain Barrier Penetration • Category 1:BBB+; Category 0: BBB-; The likelihood of being BBB is the output value.
Fu	1.861%	●	• The fraction unbound in plasms, Low: 20%

Table 10.

Metabolism evaluation of pharmaceutical and pharmacokinetic properties of alpidem molecule in terms of chemical parameters

Property	Value	Comment
CYP1A2 inhibitor	0.801	• Category 1: Inhibitor; Category 0: Non-inhibitor; • • The output value represents the likelihood of being an inhibitor.
CYP1A2 substrate	0.72	• Category 1: Substrate; Category 0: Non-substrate; • The output value represents the likelihood of being an inhibitor.
CYP2C19 substrate	0.818	• Category 1: Substrate; Category 0: Non-inhibitor; • • The likelihood of becoming an inhibitor is the output value.
CYP2C9 inhibitor	0.861	• Category 1: Category 0: Non-inhibitor; • The likelihood of becoming an inhibitor is the output value.
CYP2C9 substrate	0.256	• Category 1: Substrate; Category 0: Non-substrate; • The likelihood of being substrate is the output value.
CYP2D6 inhibitor	0.698	• Category 1: Inhibitor; Category 0: Non-inhibitor; • The likelihood of becoming an inhibitor is the output value.
CYP3A4 substrate	0.661	• Category 1: Substrate; Category 0: Non-substrate; • The likelihood of being substrate is the output value.

Table 11.

Excretion evaluation of pharmaceutical and pharmacokinetic properties of alpidem molecule in terms of chemical parameters

Property	Value	Decision	Comment
CL	8.879	●	• Clearance • High: >15 mL/min/kg; moderate: 5–15 mL/min/kg; low:<5 mL/min/kg
T1/2	0.201	●	• Category 1: long half-life; Category 0: short half-life; • long half-life:>3 h; short half-life:<3 h • The output value represents the likelihood of a lengthy half-life.

When drugs are taken orally, the gut is usually the primary site of absorption. The goal of human intestinal absorption (HIA) is to calculate the percentage of substances (> 30%) absorbed via the small intestine. The alpidem molecule demonstrated high intestinal membrane absorption. The Alpidem chemical demonstrated the capacity to pass the blood-brain barrier (BBB) in terms of distribution characteristics, which is essential for lowering toxicity and side effects or boosting the effectiveness of medications that target the brain. The nonspecific binding of a drug to plasma proteins, which influences the body’s availability of free drug, is assessed by plasma protein binding (PPB). More than 60% of plasma proteins bound alpidem compound 97.98, suggesting a longer half-life and less excretion. All of the substances were shown to be inhibitors of cytochrome P450 enzymes, namely CYP2D6 and CYP3A4 isoforms, when considering metabolic characteristics. In order to enhance interactions with liver enzymes like P450s, this step is essential. Drug clearance, renal organic cation transporter 2 (OCT2) inhibition, and half-life (T1/2) were taken into account while determining excretion values. Hepatic clearance (liver metabolism and biliary clearance) and renal clearance (excretion via the kidneys) are the two main components of the proportionality constant, which is used to evaluate drug clearance from plasma or serum. This parameter is essential for determining how long a medication will remain in the circulation and for influencing dosing rates in order to reach steady-state concentrations. The Alpidem molecule displayed clearance values between 8.879 and 0.201 milliliters per minute per kilogram of body weight.

Molecular docking studies

Drug development can be facilitated and accelerated with the use of molecular docking, a crucial tool in structure-based drug design. By using molecular docking, researchers may virtually screen the ligand-target protein interaction and forecast the binding affinities and conformations of any species to the target protein [41]. Alzheimer’s illness has recently become a global public health threat. However, specific drug therapy against Alzheimer’s disease has not yet been discovered [42]. Therefore, so as to research for a new drug, we investigated how the compound interacts with Alzheimer’s disease by performing in silico evaluation of the active site of the compound [43]. Since in silico molecular docking studies can be carried out with a large variety of ligands, take less time, and make it simple to compare ligand scores, they encourage creativity in the synthesis of novel medications [44].

The enzymes monoamine oxidases (MAOs) (PDB: 2Z5X) and acetylcholinesterase (AChE) (PDB: 4BDT) required for molecular docking were retrieved from the online resource RSCB protein database [25] and subjected to the protein preprocessing module of Schrödinger Maestro version 11.8 [24]. The protein preparation wizard was utilized to prepare the proteins that were utilized for docking. As part of the preparation, hydrogen bonds were assigned, bond sequences were added, hydrogens were added, proteins were optimized, and waters more than five from the het group were minimized and deleted. The Maestro’s Sitemap tool [24] analysis was used to identify the high-potential binding locations of ligands on proteins. The Maestro’s Glide program [24] was used to create the protein receptor grid. In the molecular docking analysis, the enzymes’ docking scores (PDB: 2Z5X) and (PDB: 4BDT) [25] were obtained as -8.00 kcal/mol and − 9.60 kcal/mol, respectively, and these values have been given in Table 12. Considering the high binding affinity of the Alpidem compound, we believe that the chemical we examined will be an important drug candidate in the creation of structure-based drugs to treat Alzheimer’s disease. The Alpidem compound 4BDT enzyme had a higher docking score than 2Z5X enzyme, and it was also shown that it has the power to inhibit the biological process of the protein at a higher rate than the 2Z5X. Using the Discovery Studio 2016 client (Visualizer 2005) [26] program, good docking positions were selected for docking analysis and protein-ligand interaction, and molecular docking images have been given in Figs. 6, 7, 8 and 9. Important interactions, amino acids, and bond lengths of the Alpidem compound in docking analysis have been given in Tables 13 and 14.

Table 12.

Molecular Docking interactions scores with PDB: 2Z5X, PDB: 4BDT enzymes of alpidem compound and control ligands

Compound		Docking Score
	(PDB: 2Z5X)	Control Ligand	(PDB: 4BDT)	Control Ligand
Alpidem	-8.00	-8.30	-9.60	-9.90

Fig. 6.

2D Mode view of alpidem Compound-PDBID:2Z5X and control ligand-PDBID:2Z5X

Fig. 7.

Molecular docking visual results of alpidem compound with 2Z5X enzyme

Fig. 8.

2D mode view of alpidem compound-PDBID:4BDT and control ligand-PDBID:4BDT

Fig. 9.

Molecular docking visual results of alpidem compound with 4BDT enzyme

Table 13.

Parameters of the interaction between alpidem compound and 2Z5X enzym

	Alpidem compound			Control ligand
Important Interactions	Full Name	Type	Bond Length (Å)	Full Name	Type	Bond Length (Å)
Van der Waals	ILE23 THR52 VAL65 GLY67 ALA448	Isoleucine Threonine Valine Glycine Alanine	- - - - -	GLY202 ALA111 TYR124 VAL115 ARG493	Glycine Alanine Tyrosine Valine Arginine	- - - - -
Conventional Hydrogen Bond	CYS406	Cysteine	4.65	TYR121 LYS136 ASN125 THR205	Tyrosine Lysine Asparagine Threonine	5.57 6.14 3.68 3.65
Halogen (Cl, Br, I)	GLN215	Glutamine	5.27	-	-	-
Unfavorable Donor-Donor	MET445	Methionine	6.05	-	-	-
Pİ-Pi T-Shaped	TYR404 TYR444	Tyrosine Tyrosine	5.63 6.07	TYR12 -	Tyrosine -	5.76
Alkyl	PRO446 VAL303 LYS305	Arginine Valine Lysine	3.24 4.81 5.03	-	-	-
Pi-Alkyl	ARG51 TYR69 TRP397 TYR444 MET445	Arginine Tyrosine Tryptophan Tyrosine Methionine	5.04 4.93 4.87 6.07 4.26			4.65
Attractive Charge	-	-	-	ASP132 GLU492	AsparticAcid GlutamicAcid	5.38 5.68
Carbon Hydrogen Bond	-	-	-	TRP128 ARG129	Tryptophan Arginine	4.80 4.91
Unfavorable Positive-Positive	-	-	-	LYS136	Lysine	7.82
Pi-Cation	-	-	-	HIS488	Histidine	5.09

Table 14.

Parameters of the interaction between alpidem compound and 4BDT enzym

	Alpidem Compound			Control Ligand
Important Interactions	Full Name	Type	Bond Length (Å)	Full Name	Type	Bond Length (Å)
Van der Waals	GLN71 VAL73 THR83 GLY120 GLU202 TYR341	Glutamine Valine Threonine Glycine GlutamicAcid Tyrosine	- - - - - -	GLY448 HIS447 PHE338 ALA204 SER125 ASP74	Glycine Histidine Phenylalanine Alanine Serine AsparticAcid	- - - - - -
Conventional Hydrogen Bond	TYR124 TYR337	Tyrosine Tyrosine	6.21 6.79	SER203 -	Serine -	4.37 -
Carbon Hydrogen Bond	SER125	Serine	4.60	-	-	-
Halogen (Cl, Br, I)	TYR72	Tyrosine	5.38	-	-	-
Pi-Cation	TRP86	Tryptophan	4.48	-	-	-
Pi-Anion	ASP74	AsparticAcid	4.60	-	-	-
Pi-Donor Hydrogen Bond	SER125	Serine	6.51	TYR337	Tyrosine	5.90
Pİ-Pi Stacked	TRP86	Tryptophan	5.65	TRP86	Tryptophan	4.63
Alkyl	PRO446 ASP74	Proline AsparticAcid	4.58 5.70	TRP439 PRO446	Tryptophan Proline	4.10 4.73
Pi-Alkyl	TYR449 HIS447 PHE338	Tyrosine Histidine Phenylalanine	5.15 5.51 6.10	MET443 TYR449 -	Methionine Tyrosine -	5.93 5.90 -
Unfavorable Donor-Donor	-	-	-	GLY	Glycine	3.56

Table 12 shows the docking scores obtained in the molecular docking analysis of the Alpidem compound (calculated docking score − 8.00) and control ligand (Flavin-Adenine Dinucleotide) (Calculated Docking Score − 8.30) with 2Z5X protein. When we look at the docking scores in Table 12, it is seen that the binding scores for the Alpidem compound are close to the binding scores of the natural ligand. Figure 6 shows the 2D mode image of the Alpidem compound and control ligand with 2Z5X protein. When we examine Fig. 6, we observed that the targets in question carry different amino acids other than the amino acids found in the receptor binding sites and the compound classes that interact with the targets, namely Pi-Alkyl, Conventional hydrogen bond, Pi-Pi T-shaped, Van der Waals.

Table 12 shows the docking scores obtained in the molecular docking analysis of Alpidem compound (Calculated Docking Score − 9.60) and control ligand (Huprine W) (Calculated Docking Score − 9.90) with 4BDT protein. When we look at the docking scores in Table 12, it is seen that the binding scores for the Alpidem compound are close to the binding scores of the natural ligand. Figure 8 shows the 2D mode image of the Alpidem compound and control ligand with 4BDT protein. When we examine Fig. 8, we observed that the targets in question carry similar amino acids except for the amino acids found in the receptor binding sites and the compound classes that interact with the targets, Carbon Hydrogen Bond, Halogen, Pi-Cation, Pi-Anion, unfavorable Hydrogen Bond.

Conclusion

In this study, the potential molecular docking, ADME properties, and density functional theory (DFT) methods of the Alpidem molecule for Alzheimer’s disease were investigated in detail. As a result of the calculations performed using B3LYP and B3PW91 methods and the 6-311G(d, p) basis set, the optimized geometry, electronic properties (HOMO-LUMO), electrostatic potential maps (MEP), natural bond orbital analysis (NBO), and nonlinear optical (NLO) behaviors of the molecule were revealed. (MAOs) (PDB: 2Z5X) and (AChE) (PDB: 4BDT) enzymes were used for molecular docking analysis. The optimized geometry of Alpidem exhibits conformational flexibility to be compatible with target proteins in the active sites. The imidazo[1,2-a]pyridine core in the structure of the molecule has the capacity to establish hydrogen bonds and hydrophobic interactions with the binding sites of both AChE and MAO enzymes. In addition, the presence of aromatic rings enables π–π stacking interactions with aromatic amino acids such as tryptophan and phenylalanine, especially in the active site of AChE, thus increasing the stability of the inhibitor–enzyme complex. In terms of electronic properties, the HOMO and LUMO energy levels of the molecule for the B3PW91 method were calculated as -6.86 eV and − 0.83 eV, respectively, and the obtained energy range of 6.03 eV indicates that the molecule is sufficiently chemically reactive. Likewise, the HOMO and LUMO energy levels of the molecule for the B3LYP method were calculated as -6.40 eV and − 1.60 eV, respectively, and the obtained energy range of 4.79 eV indicates that the molecule is chemically sufficiently reactive. This supports the potential to establish strong electronic interactions with the active sites of enzymes. Electrostatic potential (MEP) maps show that electrophilic and nucleophilic regions are evident on the surface of Alpidem, and it is thought that these regions may play a role in enzyme binding. The Alpidem molecule is a good NLO material as it has significantly higher first order hyperpolarizability values ​​than the two different method urea. In addition, the dipole moment of the molecule was calculated as B3PW91: 5.82 Debye and B3LYP: 5.5397 Debye, indicating that the compound may be advantageous in terms of appropriate solubility and cell membrane permeation capacity in biological media. Significant changes were observed in TPSA and logPow values ​​from the ADME analysis results. ADME analysis yielded positive results by following Lipinski rules. From ADME analysis results, the pharmacokinetic profile of Alpidem molecule provides important data in terms of systemic bioavailability and potential drug-drug interactions, especially considering its lipophilic structure, high intestinal membrane absorption, and its capacity to cross the blood-brain barrier (BBB) ​​in terms of distribution properties required to reduce toxicity and side effects or increase the efficacy of brain-targeting drugs. These properties indicate the pharmacokinetic limitations that Alpidem may encounter in clinical use, but they also demonstrate the potential to overcome these limitations with appropriate formulation development strategies. Future studies should focus particularly on the pharmacological activity of Alpidem’s metabolites, their effects on elimination half-life, and tissue distribution properties. In addition, we believe that confirming in vitro ADME findings with in vivo models and determining pharmacokinetic parameters associated with the safety profile will be of great importance for the clinical candidacy process of the drug. The molecular binding affinity of Alpidem compound was found to be -8.00 kcal/mol and − 9.60 kcal/mol as a result of docking analyses with 2Z5X and 4BDT protein targets, respectively. These findings indicate that Alpidem exhibits a strong interaction with target proteins. Especially the high binding affinity reveals that this compound is a potential candidate in structure-based drug design for the treatment of Alzheimer’s disease. In future studies, the therapeutic effects and clinical applications of Alpidem can be evaluated in more detail. Future molecular docking, in vitro enzymatic analyses and pharmacokinetic evaluations are important to demonstrate the biological validity of these theoretical findings.

Author contributions

VT, KG, MB designed and coordinated the study, VT, KG, MB made analyzes. VT, KG. – performed the literature review and drafted the manuscript. All authors have read and agreed to the published version of the manuscript.

Funding

The authors declare that they received no financial support.

Data availability

No datasets were generated or analysed during the current study.

Declarations

Ethics and consent to participate

Not applicable.

Competing interests

The authors declare no competing interests.