A comparative QSAR analysis of acetylcholinesterase inhibitors currently studied for the treatment of Alzheimer's disease

ABCpred: a webserver for the discovery of acetyl- and butyryl-cholinesterase inhibitors

Alzheimer's disease (AD) is one of the most common forms of dementia and is associated with a decline in cognitive function and language ability. The deficiency of the cholinergic neurotransmitter known as acetylcholine (ACh) is associated with AD. Acetylcholinesterase (AChE) hydrolyses ACh and inhibits the cholinergic transmission. Furthermore, both AChE and butyrylcholinesterase (BChE) plays important roles in early and late stages of AD. Therefore, the inhibition of either or both cholinesterase enzymes represent a promising therapeutic route for treating AD. In this study, a large-scale classification structure-activity relationship model was developed to predict cholinesterase inhibitory activities as well as revealing important substructures governing their activities. Herein, a non-redundant dataset constituting 985 and 1056 compounds for AChE and BChE, respectively, was obtained from the ChEMBL database. These inhibitors were described by 12 sets of molecular fingerprints and predictive models were developed using the random forest algorithm. Evaluation of the model performance by means of Matthews correlation coefficient and consideration of the model's interpretability indicated that the SubstructureCount fingerprint was the most robust with five-fold cross-validated MCC of [0.76, 0.82] for AChE and BChE, respectively, and test MCC of [0.73, 0.97]. Feature interpretation revealed that the aromatic ring system, heterocyclic nitrogen containing compounds and amines are important for cholinesterase inhibition. Finally, the model was deployed as a publicly available webserver called the ABCpred at http://codes.bio/abcpred/ .

Machine learning models for predicting the activity of AChE and BACE1 dual inhibitors for the treatment of Alzheimer's disease

Multi-target directed ligand-based 2D-QSAR models were developed using different N-benzyl piperidine derivatives showing inhibitory activity toward acetylcholinesterase (AChE) and β-Site amyloid precursor protein cleaving enzyme (BACE1). Five different classes of molecular descriptors belonging to spatial, structural, thermodynamics, electro-topological and E-state indices were used for machine learning by linear method, genetic function approximation (GFA) and nonlinear method, support vector machine (SVM) and artificial neural network (ANN). Dataset used for QSAR model development includes 57 AChE and 53 BACE1 inhibitors. Statistically significant models were developed for AChE (R² = 0.8688, q² = 0.8600) and BACE1 (R² = 0.8177, q² = 0.7888) enzyme inhibitors. Each model was generated with an optimum five significant molecular descriptors such as electro-topological (ES_Count_aaCH and ES_Count_dssC), structural (QED_HBD, Num_TerminalRotomers), spatial (JURS_FNSA_1) for AChE and structural (Cl_Count, Num_Terminal Rotomers), electro-topological (ES_Count_dO), electronic (Dipole_Z) and spatial (Shadow_nu) for BACE1 enzyme, determining the key role in its enzyme inhibitory activity. The predictive ability of the generated machine learning models was validated using the leave-one-out, Fischer (F) statistics and predictions based on the test set of 11 AChE (r² = 0.8469, r²_pred = 0.8138) and BACE1 (r² = 0.7805, r²_pred = 0.7128) inhibitors. Further, nonlinear machine learning methods such as ANN and SVM predicted better than the linear method GFA. These molecular descriptors are very important in describing the inhibitory activity of AChE and BACE1 enzymes and should be used further for the rational design of multi-targeted anti-Alzheimer's lead molecules.

4D-QSAR Molecular Modeling and Analysis of Flavonoid Derivatives as Acetylcholinesterase Inhibitors

Flavonoids are potential strikingly natural compounds with antioxidant activity and acetylcholinesterase (AChE) inhibitory activity for treating Alzheimer's disease (AD). In present study, in line with our interests in flavonoid derivatives as AChE inhibitors, a four-dimensional quantitative structure-activity relationship (4D-QSAR) molecular model was proposed. The data required to perform 4D-QSAR analysis includes 52 compounds reported in the literature, usually analogs, and their measured biological activities in a common assay. The model was generated by a complete set of 4D-QSAR program which was written by our group. The best model was found after trying multiple experiments. It had a good predictive ability with the cross-validation correlation coefficient Q² = 0.77, the internal validation correlation coefficient R² = 0.954, and the external validation correlation coefficient R²_pred = 0.715. The molecular docking analysis was also carried out to understand exceedingly the interactions between flavonoids and the AChE targets, which was in good agreement with the 4D-QSAR model. Based on the information provided by the 4D-QSAR model and molecular docking analysis, the idea for optimizing the structures of flavonoids as AChE inhibitors was put forward which maybe provide theoretical guidance for the research and development of new AChE inhibitors.

In Silico Studies in Drug Research Against Neurodegenerative Diseases

Background

Neurodegenerative diseases such as Alzheimer's disease (AD), amyotrophic lateral sclerosis, Parkinson's disease (PD), spinal cerebellar ataxias, and spinal and bulbar muscular atrophy are described by slow and selective degeneration of neurons and axons in the central nervous system (CNS) and constitute one of the major challenges of modern medicine. Computer-aided or in silico drug design methods have matured into powerful tools for reducing the number of ligands that should be screened in experimental assays.

Methods

In the present review, the authors provide a basic background about neurodegenerative diseases and in silico techniques in the drug research. Furthermore, they review the various in silico studies reported against various targets in neurodegenerative diseases, including homology modeling, molecular docking, virtual high-throughput screening, quantitative structure activity relationship (QSAR), hologram quantitative structure activity relationship (HQSAR), 3D pharmacophore mapping, proteochemometrics modeling (PCM), fingerprints, fragment-based drug discovery, Monte Carlo simulation, molecular dynamic (MD) simulation, quantum-mechanical methods for drug design, support vector machines, and machine learning approaches.

Results

Detailed analysis of the recently reported case studies revealed that the majority of them use a sequential combination of ligand and structure-based virtual screening techniques, with particular focus on pharmacophore models and the docking approach.

Conclusion

Neurodegenerative diseases have a multifactorial pathoetiological origin, so scientists have become persuaded that a multi-target therapeutic strategy aimed at the simultaneous targeting of multiple proteins (and therefore etiologies) involved in the development of a disease is recommended in future.

QSAR Models towards Cholinesterase Inhibitors for the Treatment of Alzheimer's Disease

Alzheimer's Disease (AD) is a multifactorial neurological syndrome with the combination of aging, genetic, and environmental factors triggering the pathological decline. Interestingly, the importance of the Acetylcholinesterase (AChE) enzyme has increased due to its involvement in the ß-amyloid peptide fibril formation during AD pathogenesis. In silico technique, QSAR has proven its usefulness in pharmaceutical research for the design/optimization of new chemical entities. Further, QSAR method advanced the scope of rational drug design and the search for the mechanism of drug action. It is a well-established fact that the chemical and pharmaceutical effects of a compound are closely related to its physico-chemical properties, which can be calculated by various methods from the compound structure. This chapter focuses on different Quantitative Structure-Activity Relationship (QSAR) studies carried out for a variety of cholinesterase inhibitors for the treatment of AD. These predictive models will be potentially used for further designing better and safer drugs against AD.

Design and synthesis of new piperidone grafted acetylcholinesterase inhibitors

Alzheimer's disease (AD) is a neurodegenerative disorder affecting 35million people worldwide. A common strategy to improve the well-being of AD patients consists on the inhibition of acetylcholinesterase with the concomitant increase of the neurotransmitter acetylcholine at cholinergic synapses. Two series of unreported N-benzylpiperidines 5(a-h) and thiazolopyrimidines 9(a-q) molecules were synthesized and evaluated in vitro for their acetylcholinesterase (AChE) inhibitory activities. Among the newly synthesized compounds, 5h, 9h, 9j, and 9p displayed higher AChE enzyme inhibitory activities than the standard drug, galantamine, with IC₅₀ values of 0.83, 0.98, and 0.73μM, respectively. Cytotoxicity studies of 5h, 9h, 9j, 9n and 9p on human neuroblastoma cells SH-SY5Y, showed no toxicity up to 40μM concentration. Molecular docking simulations of the active compounds 5h and 9p disclosed the crucial role of π-π-stacking in their binding interaction to the active site AChE enzyme. The presented compounds have potential as AChE inhibitors and potential AD drugs.

7-Methoxytacrine-p-Anisidine Hybrids as Novel Dual Binding Site Acetylcholinesterase Inhibitors for Alzheimer's Disease Treatment

Alzheimer's disease (AD) is a debilitating progressive neurodegenerative disorder that ultimately leads to the patient's death. Despite the fact that novel pharmacological approaches endeavoring to block the neurodegenerative process are still emerging, none of them have reached use in clinical practice yet. Thus, palliative treatment represented by acetylcholinesterase inhibitors (AChEIs) and memantine are still the only therapeutics used. Following the multi-target directed ligands (MTDLs) strategy, herein we describe the synthesis, biological evaluation and docking studies for novel 7-methoxytacrine-p-anisidine hybrids designed to purposely target both cholinesterases and the amyloid cascade. Indeed, the novel derivatives proved to be effective non-specific cholinesterase inhibitors showing non-competitive AChE inhibition patterns. This compounds' behavior was confirmed in the subsequent molecular modeling studies.

Synthesis, cholinesterase inhibition and molecular modelling studies of coumarin linked thiourea derivatives

Alzheimer's disease is among the most widespread neurodegenerative disorder. Cholinesterases (ChEs) play an indispensable role in the control of cholinergic transmission and thus the acetylcholine level in the brain is enhanced by inhibition of ChEs. Coumarin linked thiourea derivatives were designed, synthesized and evaluated biologically in order to determine their inhibitory activity against acetylcholinesterases (AChE) and butyrylcholinesterases (BChE). The synthesized derivatives of coumarin linked thiourea compounds showed potential inhibitory activity against AChE and BChE. Among all the synthesized compounds, 1-(2-Oxo-2H-chromene-3-carbonyl)-3-(3-chlorophenyl)thiourea (2e) was the most potent inhibitor against AChE with an IC50 value of 0.04±0.01μM, while 1-(2-Oxo-2H-chromene-3-carbonyl)-3-(2-methoxyphenyl)thiourea (2b) showed the most potent inhibitory activity with an IC50 value of 0.06±0.02μM against BChE. Molecular docking simulations were performed using the homology models of both cholinesterases in order to explore the probable binding modes of inhibitors. Results showed that the novel synthesized coumarin linked thiourea derivatives are potential candidates to develop for potent and efficacious acetylcholinesterase (AChE) and butyrylcholinesterase (BChE) inhibitors.

Benefits of statistical molecular design, covariance analysis, and reference models in QSAR: a case study on acetylcholinesterase

Scientific disciplines such as medicinal- and environmental chemistry, pharmacology, and toxicology deal with the questions related to the effects small organic compounds exhort on biological targets and the compounds' physicochemical properties responsible for these effects. A common strategy in this endeavor is to establish structure-activity relationships (SARs). The aim of this work was to illustrate benefits of performing a statistical molecular design (SMD) and proper statistical analysis of the molecules' properties before SAR and quantitative structure-activity relationship (QSAR) analysis. Our SMD followed by synthesis yielded a set of inhibitors of the enzyme acetylcholinesterase (AChE) that had very few inherent dependencies between the substructures in the molecules. If such dependencies exist, they cause severe errors in SAR interpretation and predictions by QSAR-models, and leave a set of molecules less suitable for future decision-making. In our study, SAR- and QSAR models could show which molecular sub-structures and physicochemical features that were advantageous for the AChE inhibition. Finally, the QSAR model was used for the prediction of the inhibition of AChE by an external prediction set of molecules. The accuracy of these predictions was asserted by statistical significance tests and by comparisons to simple but relevant reference models.

Molecular Docking Guided Comparative GFA, G/PLS, SVM and ANN Models of Structurally Diverse Dual Binding Site Acetylcholinesterase Inhibitors

Recently discovered 42 AChE inhibitors binding at the catalytic and peripheral anionic site were identified on the basis of molecular docking approach, and its comparative quantitative structure-activity relationship (QSAR) models were developed. These structurally diverse inhibitors were obtained by our previously reported high-throughput in vitro screening technique using 384-well plate's assay based on colorimetric method of Ellman. QSAR models were developed using (i) genetic function algorithm, (ii) genetic partial least squares, (iii) support vector machine and (iv) artificial neural network techniques. The QSAR model robustness and significance was critically assessed using different cross-validation techniques on test data set. The generated QSAR models using thermodynamic, electrotopological and electronic descriptors showed that nonlinear methods are more robust than linear methods, and provide insight into the structural features of compounds that are important for AChE inhibition.

QSAR studies on N-aryl derivative activity towards Alzheimer's disease

A Quantitative Structure Activity Relationship (QSAR) study has been an attempted on a series of 88 N-aryl derivatives which display varied inhibitory activity towards both acetylcholinesterase (AChE) and butyrylcholinesterase (BChE), targets in Alzheimer’s drug discovery. QSAR models were derived for 53 and 61 compounds for each target, respectively, with the aid of genetic function approximation (GFA) technique using topological, molecular shape, electronic and structural descriptors. The predictive ability of the QSAR model was evaluated using a test set of 26 compounds for AChE (r² _pred = 0.857), (q² = 0.803) and 20 compounds for BChE (r² _pred = 0.882), (q² = 0.857). The QSAR models point out that AlogP98, Wiener, Kappa-1-AM, Dipole-Mag, and CHI-1 are the important descriptors effectively describing the bioactivity of the compounds.

Modeling of acetylcholinesterase inhibition by tacrine analogues using Bayesian-regularized Genetic Neural Networks and ensemble averaging

Acetylcholinesterase inhibition was modeled for a set of 136 tacrine analogues using Bayesian-regularized Genetic Neural Networks (BRGNNs). In the BRGNN approach the Bayesian-regularization avoids overtraining/overfitting and the genetic algorithm (GA) allows exploring an ample pool of 3D-descriptors. The predictive capacity of our selected model was evaluated by averaging multiple validation sets generated as members of diverse-training set neural network ensembles (NNEs). The ensemble averaging provides reliable statistics. When 40 members are assembled, the NNE provides a reliable measure of training and test set R values of 0.921 and 0.851 respectively. In other respects, the ability of the nonlinear selected GA space for differentiating the data was evidenced when the total data set was well distributed in a Kohonen Self-Organizing Map (SOM). The location of the inhibitors in the map facilitates the analysis of the connection between compounds and serves as a useful tool for qualitative predictions.

Reversible and irreversible inhibitory activity of succinic and maleic acid derivatives on acetylcholinesterase

Aryl succinic and maleic acid derivatives are potent inhibitors of bovine acetylcholinesterase in vitro. Succinic acid aminophenol derivatives 1b-e and 2b-d act as reversible inhibitors of acetylcholinesterase, while maleic acid aminophenol derivatives 3b-d and 4c-e act as choline subsite-directed irreversible inhibitors, detected by dialysis in the presence of edrophonium. Linear relationships between the logarithm of the velocity of hydrolysis of acetylcholine plotted against the time of incubation at several different inhibitor concentrations were determined. The K(i) for reversible competitive inhibitors was determined. For irreversible inhibitors the K(i) for the dissociation constant of the enzyme-inhibitor complex at the beginning of the recognition process was also determined as well as the inactivation constant of the enzyme-inhibitor adduct formation k(+2) and the bimolecular inhibition constant k(i) for the inhibition of acetylcholinesterase by aminophenol derivatives 3b-d and 4c-e. The conclusions of this study can be summarized as follows for both families: (a) the aromatic moiety played a critical role in the recognition of the active site; (b) in case of the reversible inhibitor, when the ester function took the place of the hydroxyl fragment, there was an important increase in the affinity; and (c) the distance between phenolic hydroxyl and nitrogen was critical because the inhibition is ortho<<meta<para.

Hypochlorous acid is a potent inhibitor of acetylcholinesterase

The role of hydrogen peroxide and peroxynitrite in the induction of airway hyperreactivity has been well described. Another reactive species which is formed during airway inflammation is hypochlorous acid (HOCl). In the present investigation the effect of HOCl on cholinergic innervation of the airway was investigated. It was observed that HOCl was capable of increasing the basal tension of electrically stimulated tracheal smooth muscle. It was found that HOCl inhibits purified acetylcholinesterase with an IC50 value of 0.66 microM. Decreased acetylcholinesterase activity could allow accumulation of acetylcholine and increased airway muscle tension. The effects of HOCl on the isolated organ and the enzyme preparation could be precluded with thiol group-containing compounds such as reduced glutathione and N-acetylcysteine. The present findings indicate that HOCl can act as inhibitor of acetylcholinesterase. The implications of this finding for the induction of airway hyperreactivity are discussed.

Accurate prediction of the bound conformation of galanthamine in the active site of Torpedo californica acetylcholinesterase using molecular docking

The alkaloid (-)-galanthamine is known to produce significant improvement of cognitive performances in patients with the Alzheimer's disease. Its mechanism of action involves competitive and reversible inhibition of acetylcholinesterase (AChE). Herein, we correctly predict the orientation and conformation of the galanthamine molecule in the active site of AChE from Torpedo californica (TcAChE) using a combination of rigid docking and flexible geometry optimization with a molecular mechanics force field. The quality of the predicted model is remarkable, as indicated by the value of the RMS deviation of approximately 0.5A when compared with the crystal structure of the TcAChE-galanthamine complex. A molecular model of the complex between TcAChE and a galanthamine derivative, SPH1107, with a long chain substituent on the nitrogen has been generated as well. The side chain of this ligand is predicted to extend along the enzyme active site gorge from the anionic subsite, at the bottom, to the peripheral anionic site, at the top. The docking procedure described in this paper can be applied to produce models of ligand-receptor complexes for AChE and other macromolecular targets of drug design.

SAR of 9-amino-1,2,3,4-tetrahydroacridine-based acetylcholinesterase inhibitors: synthesis, enzyme inhibitory activity, QSAR, and structure-based CoMFA of tacrine analogues

In this study, we attempted to derive a comprehensive SAR picture for the class of acetylcholinesterase (AChE) inhibitors related to tacrine, a drug currently in use for the treatment of the Alzheimer's disease. To this aim, we synthesized and tested a series of 9-amino-1,2,3,4-tetrahydroacridine derivatives substituted in the positions 6 and 7 of the acridine nucleus and bearing selected groups on the 9-amino function. By means of the Hansch approach, QSAR equations were obtained, quantitatively accounting for both the detrimental steric effect of substituents in position 7 and the favorable electron-attracting effect exerted by substituents in positions 6 and 7 of the 9-amino-1,2,3,4-tetrahydroacridine derivatives. The three-dimensional (3D) properties of the inhibitors were taken into consideration by performing a CoMFA analysis on the series of AChE inhibitors made by 12 9-amino-1,2,3, 4-tetrahydroacridines and 13 11H-indeno[1,2-b]quinolin-10-ylamines previously developed in our laboratory. The alignment of the molecules to be submitted to the CoMFA procedure was carried out by taking advantage of docking models calculated for the interactions of both the unsubstituted 9-amino-1,2,3,4-tetrahydroacridine and 11H-indeno[1,2-b]quinolin-10-ylamine with the target enzyme. A highly significant CoMFA model was obtained using the steric field alone, and the features of such a 3D QSAR model were compared with the classical QSAR equations previously calculated. The two models appeared consistent, the main aspects they had in common being (a) the individuation of the strongly negative contribution of the substituents in position 7 of tacrine and (b) a tentative assignment of the hydrophobic character to the favorable effect exerted by the substituents in position 6. Finally, a new previously unreported tacrine derivative designed on the basis of both the classical and the 3D QSAR equations was synthesized and kinetically evaluated, to test the predictive ability of the QSAR models. The 6-bromo-9-amino-1,2,3,4-tetrahydroacridine was predicted to have a pIC(50) value of 7.31 by the classical QSAR model and 7.40 by the CoMFA model, while its experimental IC(50) value was equal to 0.066 (+/-0.009) microM, corresponding to a pIC(50) of 7.18, showing a reasonable agreement between predicted and observed AChE inhibition data.

Acetylcholinesterase inhibitors for potential use in Alzheimer's disease: molecular modeling, synthesis and kinetic evaluation of 11H-indeno-[1,2-b]-quinolin-10-ylamine derivatives

Continuing our work on tetracyclic tacrine analogues, we synthesized a series of acetylcholinesterase (AChE) inhibitors of 11H-indeno-[1,2-b]-quinolin-10-ylaminic structure. Selected substituents were placed in synthetically accessible positions of the tetracyclic nucleus, in order to explore the structure-activity relationships (SAR) and the mode of action of this class of anticholinesterases. A molecular modeling investigation of the binding interaction of the lead compound (1a) with the AChE active site was performed, from which it resulted that, despite the rather wide and rigid structure of 1a, there may still be the possibility to introduce some small substituent in some positions of the tetracycle. However, from the examination of the experimental IC50 values, it derived that the indenoquinoline nucleus probably represents the maximum allowable molecular size for rigid compounds binding to AChE. In fact, only a fluorine atom in position 2 maintains the AChE inhibitory potency of the parent compound, and, actually, increases the AChE-selectivity with respect to the butyrylcholinesterase inhibition. By studying the kinetics of AChE inhibition for two representative compounds of the series, it resulted that the lead compound (1a) shows an inhibition of mixed type, binding to both the active and the peripheral sites, while the more sterically hindered analogue 2n seems to interact only at the external binding site of the enzyme. This finding seems particularly important in the context of Alzheimer's disease research in the light of recent observations showing that peripheral AChE inhibitors might decrease the aggregating effects of the enzyme on the beta-amyloid peptide (betaA).

Acetylcholinesterase inhibitors: synthesis and structure-activity relationships of omega-[N-methyl-N-(3-alkylcarbamoyloxyphenyl)- methyl]aminoalkoxyheteroaryl derivatives

Acetylcholinesterase (AChE) inhibitors are one of the most actively investigated classes of compounds in the search for an effective treatment of Alzheimer's disease. This work describes the synthesis, AChE inhibitory activity, and structure-activity relationships of some compounds related to a recently discovered series of AChE inhibitors: the omega-[N-methyl-N-(3-alkylcarbamoyloxyphenyl)methyl]aminoalkoxy xanthen-9-ones. The influence of structural variations on the inhibitory potency was carefully investigated by modifying different parts of the parent molecule, and a theoretical model of the binding of one representative compound to the enzyme was developed. The biological properties of the series were investigated in some detail by considering not only the activity on isolated enzyme but the selectivity with respect to butyrylcholinesterase (BuChE) and the in vitro inhibitory activity on rat cerebral cortex as well. Some of the newly synthesized derivatives, when tested on isolated and/or AChE-enriched rat brain cortex fraction, displayed a selective inhibitory activity and were more active than physostigmine. In particular, compound 13, an azaxanthone derivative, displayed the best rat cortex AChE inhibition (190-fold higher than physostigmine), as well as a high degree of enzyme selectivity (over 60-fold more selective for AChE than for BuChE). When tested in the isolated enzyme, compound 13 was less active, suggesting some differences either in drug availability/biotransformation or in the inhibitor-sensitive residues of the enzyme when biologically positioned in rat brain membranes.

The 'aromatic patch' of three proximal residues in the human acetylcholinesterase active centre allows for versatile interaction modes with inhibitors

The role of the functional architecture of the human acetylcholinesterase (HuAChE) active centre in accommodating the non-covalent inhibitors tacrine and huperzine A, or the carbamates pyridostigmine and physostigmine, was analysed using 16 mutants of residues lining the active-centre gorge. Despite the structural diversity of the ligands, certain common properties of the complexes could be observed: (a) replacement of aromatic residues Tyr133, Tyr337 and especially Trp86, resulted in pronounced changes in stability of all the complexes examined; (b) effects due to replacements of the five other aromatic residues along the active-centre gorge, such as the acyl pocket (Phe295, Phe297) or at the peripheral anionic site (Tyr124, Trp286, Tyr341) were relatively small; (c) effects due to substitution of the carboxylic residues in the gorge (Glu202, Glu450) were moderate. These results and molecular modelling indicate that the aromatic side chains of residues Trp86, Tyr133 and Tyr337 form together a continuous 'aromatic patch' lining the wall of the active-centre gorge, allowing for the accommodation of the different ligands via multiple modes of interaction. Studies with HuAChE mutants carrying replacements at positions 86, 133 and 337 indicate that the orientations of huperzine A and tacrine in the HuAChE complexes in solution are significantly different from those observed in X-ray structures of the corresponding complexes with Torpedo californica AChE (TcAChE). These discrepancies may be explained in terms of structural differences between the complexes of HuAChE and TcAChE or, more likely, by the enhanced flexibility of the AChE active-centre gorge in solution as compared with the crystalline state.