Molecular Docking and Pharmacological Investigations of Rivastigmine-Fluoxetine and Coumarin–Tacrine hybrids against Acetyl Choline Esterase

The present AChE inhibitors have been successful in the treatment of Alzheimer׳s Diseases however suffers serious side effects. Therefore in this view, the present study was sought to identify compounds with appreciable pharmacological profile targeting AChE. Analogue of Rivastigmine and Fluoxetine hybrid synthesized by Toda et al, 2003 (dataset1), and Coumarin−Tacrine hybrids synthesized by Qi Sun et al (dataset2) formed the test compounds for the present pharmacological evaluation. p-cholorophenyl substituted Rivastigmine and Fluoxetine hybrid compound (26d) from dataset 1 and −OCH3 substitute Coumarin−Tacrine hybrids (1h) from dataset 2 demonstrated superior pharmacological profile. 26 d showed superior pharmacological profile comparison to the entire compounds in either dataset owing to its better electrostatic interactions and hydrogen bonding patterns. In order to identify still better compound with pharmacological profile than 26 d and 1h, virtual screening was performed. The best docked compound (PubCId: PubCid: 68874404) showed better affinity than its parent 26 d, however showed poor ADME profile and AMES toxicity. CHEMBL2391475 (PubCid: 71699632) similar to 1h had reduced affinity in comparison to its parent compound 1h. From, our extensive analysis involving binding affinity analysis, ADMET properties predictions and pharmacophoric mappings, we report p-cholorophenyl substituted rivastigmine and fluoxetine hybrid (26d) to be a potential candidate for AcHE inhibition which in addition can overcome narrow therapeutic window of present AChE inhibitors in clinical treatment of Alzheimer׳s disease. Abbreviations AD - Alzheimer׳s Disease, AChE - Acetyl Choline Estarase, OPLS - Optimized Potentials for Liquid Simulations, PDB - Protein Data Bank.

reported with impairment in memory, decision making, orientation to physical surroundings and language.
Cholinergic hypothesis of the pathogenesis now shows dysregulation of cholinergic system forms the major pathological feature of AD [4]. Biopsies of the cerebral cortex has shown that these cholinergic neurons which provide extensive innervations in the cerebral cortex selectively degenerate which affects the cognitive functions, especially memory [5]. With the immense role of cholinergic system in AD, several pharmacological strategies have been aimed at correcting the cognitive deficits by manipulating cholinergic neurotransmission. The most powerful strategy developed was development of Acetyl Choline Esterase (ChEI) inhibitors that selectively blocks Acetyl Choline Esterase (AChE)-an enzyme which is involved in termination of synaptic transmission by hydrolysis of acetyl choline and finally making it unavailable for neural transmission in coxtex which otherwise is manifested as cognitive dysfunction observed in AD. Since the introduction of the first cholinesterase inhibitor in 1997, most clinicians would consider treatment by the cholinergic drugs like donepezil, galantamine and rivastigmine that forms first line pharmacotherapy for mild to moderate Alzheimer's disease [6,7].
Various clinical trials of inhibitors have shown that, on the whole their effects were modest however were associated with frequent adverse reactions and lack of the drug's substrate specificity [8]. In addition, some drugs like donepezil delays the disease worsening but nevertheless offers acute symptoms like headache, constipation, confusion and dizziness. In some patients, the regular dose of donepezil, galantamine and rivastigmine have been positively associated with acute insomnia and anorexia [9]. Considering the side effects of the present compounds, the treatment strategy of AD thus shifted to ethnopharmacological approach which promises high activity bestowed with minimal side effects. In traditional practices of medicine, numerous plants have been used to treat cognitive disorders, including neurodegenerative diseases such as Alzheimer's disease (AD). There are numerous drugs available in Western medicine that have been directly isolated from plants, or are derived from templates of compounds from plant sources. Therefore, In the view of above, the present study focuses computer based pharmacological profiling, evaluation and identification high affinity plant compounds from the dataset of rivastigmine and fluoxetine hybrid compound synthesized by N. Toda

Preparation of protein and compounds
The crystal structure of AChE receptor was retrieved from Protein Data Bank (PDB) with PDB ID: 1ACJ [12] (Figure 2). The X-Ray diffraction structure of AChE receptor had a resolution of 2.80 Å and R value of 0.195. Unit cell parameters were as Length [Å] a = 113.70, b = 113.70, c = 138.10, Angles [°] α = 90.00, β = 90.00, γ = 120.00. The structure was downloaded in pdb format and was further prepared for docking process. The protein was prepared using the PrepWiz module of Schrodinger suite. In the preparation procedure, the protein was first preprocessed by assigning the bond orders and hydrogens, creating zero order bonds to metals and adding disulphide bonds. The missing side chains and loops were filled using Prime Module of Schrodinger. Further all the water molecules were deleted beyond 5 Å from hetero groups. Once the protein structure was preprocessed, H bonds were assigned which was followed by energy minimization by OPLS 2005 force field [13]. The final structure obtained was saved in.pdb format for further studies. All the ligands were optimized through OPLS 2005 force field algorithm embedded in the LigPrep module of Schrödinger suite, 2013 (Schrodinger. LLC, New York, NY) [14]. The ionizations of the ligand were retained at the original state and were further desalted. The structures thus optimized were saved in sdf format for docking procedures.

Structure Similarity search
The compound with superior pharmacological profile amongst the two datasets was further used as query molecule in pursuit to identify still better druglike compound than any molecules mentioned in the dataset. Similarity search was supervised by Binary Finger Print Based Tanimoto similarity equation to retrieve compounds with similarity threshold of 95 % against NCBI's Pubchem compound database [15].

Molecular docking of compounds
Molecular docking program-Molegro Virtual Docker (MVD) which incorporates highly efficient PLP (Piece wise Linear potential) and MolDock scoring function provided a flexible docking platform [16,17]. All the ligands were docked at the active site of AChE. Docking parameters were set to 0.20Å as grid resolution, maximum iteration of 1500 and maximum population size of 50. Energy minimization and hydrogen bonds were optimized after the docking. Simplex evolution was set at maximum steps of 300 with neighborhood distance factor of 1. Binding affinity and interactions of ligands with protein were evaluated on the basis of the internal ES (Internal electrostatic Interaction), internal hydrogen bond interactions and sp2-sp2 torsions. Post dock energy of the ligand-receptor complex was minimized using Nelder Mead Simplex Minimization (using non-grid force field and H bond directionality) [18]. On the basis of rerank score best interacting compound was selected from each dataset.

Bioactivity and ADMET profiling of compounds.
All the compounds were screened for its drug ability by lipinksi filters. Biological activity of the ligands was predicted using Molinspiration webserver (© Molinspiration Cheminformatics 2014). The complete ADMET properties was calculated using admetSAR [19,20].

Pharmacophoric Mapping
Pharmacophoric mapping which involves ligand interaction patterns, hydrogen bond interaction, hydrophobic interactions was evaluated using Accelrys Discovery Studio 3.5 DS Visualizer [21].  1h (Figure 1b) from dataset 2 demonstrated highest binding affinity. In particular, compound 26 d a hybrid molecule with the motifs of Rivastigmine and Fluoxetine with functional modification with p-chlorophenyl showed highest affinity than compounds in either groups. From keen perusal of the structural details of 26d, it may be assumed that large substituent (R= pchlorophenyl) may attributed to its better activity (IC50 >1000) and highest affinity (Rerank Score=-168.933).
From dataset 2, compound 1h-a Coumarin-Tacrine hybrid demonstrated highest binding affinity against AChE. However, our observations of binding affinity did not correlate with the estimated activity by authors, 1q as described by authors shows highest activity (Ki= 91.1), while adhering to our observation it is 1h which showed highest binding affinity (rerank score=-166.33). The discrepancies observed is an important subject for further investigation. However, taking into consideration all the compounds from dataset1 and 2, unarguably 26d (from dataset) (Figure 2) demonstrated highest binding affinity and in addition showed optimal in vitro activity. In further approach, in pursuit to identify even better molecule endowed with superior pharmacological profile than compound 26 d from dataset 1 and compound 1h from dataset 2, virtual screening was performed against Pubchem database (taking compound 61 as query). A total of 14 compounds structurally similar to compound 26d were retrieved while 18 structural similar were retrieved against its parent compound 1h. All the similar compounds those akin to 26 d and 1h retrieved hitherto were docked against AChE structure. Compound with Pubchem Id: 68874404 (Figure 1c) showed superior binding affinity out of all the similar 14 compounds retrieved against its parent compound 26 d, while, compound CHEMBL2391475 (PubCid: 71699632) (Figure 1d) demonstrated superior affinity among all the 18 compounds retrived with respect to its parent compound1h Table 3 (see  supplementary material).
It worthy to note that though PubCid: 68874404 showed slightly higher affinity to AChE than its parent compound 26d , however, quite apparent from predicted activity scores, Table 4 (see supplementary material) it shows abruptly less activity for enzyme inhibition. In addition the ADMET profiles were comparatively poor when compared to its parent compound 26d Table 5 (see supplementary material). However, the important drawback of compound PubCid: 68874404 was that it was predicted to be Ames toxic. Therefore, it can be presumed that, though it has good affinity profile, however, it should not form candidate drug owing to its toxicity.
While in the case of CHEMBL2391475 the affinity score was 1.09 folds declined than its parent compound 1h Table 3 (see supplementary material) in addition the predicted enzyme inhibition activity was considerably lower In the further perusal, our pursuit was to reveal the rationale behind superior pharmacological profile of 26 d. In terms of binding affinity, the appreciable binding can be attributed to its excellent interaction profile especially in terms of electrostatic and H-bonding interactions Table 3  As show in Table 6 (see supplementary material), the interaction profile of 26 d was quite appreciable than compound 1h from dataset 2 and its respective similar CHEMBL2391475 (PubCid: 71699632). An obvious thing which can be noted is, although 26 d similar compound PubCid: 68874404 shows good interaction profile, nevertheless, as mentioned above suffer with poor ADME properties and AMES toxicity.
Owing to optimal affinity, high enzyme inhibition activity and non-toxicity, 26 d was further analyzed for pharmacophoric mappings. Comprehensively shown in Figure 3  Supplementary material: * Compound with highest binding affinity, + Activity tested in mouse brain.