Molecular modelling is a term used to describe the use of computers to construct and develop molecules and to perform a variety of calculations to predict their chemical characteristics and behaviour.1 Molecular modelling technique uses theoretical approaches to predict the conformational changes of proteins, DNAs and other macromolecular structures. These theoretical tools include quantum mechanics, empirical molecular mechanics, and statistical mechanics.2,3 Computer-assisted drug design or computer-aided drug design (CADD) is a branch of molecular modelling in which a detailed study on the molecular structure of target molecules is performed and the properties of the target-receptor binding site are evaluated.2,4,5 CADD technique is used in the design of novel drugs for many therapeutic uses. Molecular modeling technique reduces the vast use of time spent on the study of conformation of molecules and hence is indispensible in the field of pharmaceutical industry. They have their impact on building the molecule, visualisation and optimisation of the structure and comparison of similar molecules. Quantitative structure-activity relationship and quantitative structure-property relationship studies are performed using this technique. The immense knowledge based on molecular modeling paves way in determining the lead drug structures and molecules that bind to enzymes, developing derivatives of drug molecules, analyse the docking studies of family of ligands, and evaluating the physical parameters of macromolecules.6,7
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Use of computer-aided chemistry is vast and is indispensible in molecular modelling. It enables the user to create the models of molecular structures, to import experimental data from protein data banks available and to perform extensive calculation
using quantum and classical mechanical theories. These calculations are helpful in predicting the properties of the molecules such as electron distribution and to generate various conformations of the molecules to execute and evaluate their biological activities. Molecular modelling experiments use the mathematical derivations from computational chemistry to perform calculations based on molecular properties and geometries. The ligand binds to the protein by electrostatic, hydrogen-bonding and hydrophobic interactions. These interactions optimise the ligand to fit in to its active site. This optimization does not confirm the guaranteed desired activity of the drug.8,9
The computational chemistry implies two types of drug design8
Ligand-based drug design
Receptor-based drug design
These two approaches are chosen according to the availability of detailed knowledge on the structure of receptor site and the molecular modelling techniques used. Drug design is carried out based on the biological target and receptors. Drugs may be designed to inhibit a particular functioning of metabolic or signalling pathway that causes disease. Drugs are designed to bind to the active site, exert their action without affecting similar molecules. Drug should interact with the target protein and does not interfere in the normal metabolic processes. This could be achieved by testing a set of compounds often regarded as library of compounds. Prediction of interactions between the protein and the compound library would provide potentially active compounds that could be tested further for biological activity. These are termed the lead compounds, obtained by refining the molecular structures in the compounds library. Lead compounds are then examined for drug activity and side effects.8
AIM OF THE WORK
The work in this thesis mainly concerns about the computational molecular modelling techniques that are employed in the study of protein-substrate interactions. In this thesis the interaction of acetylcholinesterase (AChE) with potential set of inhibitors was studied using the software Scigress. Acetylcholinesterase is an enzyme that is mainly responsible for the degradation of the neurotransmitter acetylcholine which leads to cognitive disorders such as dementia and Alzheimer's disease. Hence the study of drug molecules that inhibit the enzyme acetylcholinesterase is more important. These AChE inhibitors were optimized and their docking studies were carried out in this work. Characterization of such interactions leads to thorough understanding of the mechanism of action of the drug molecules, functions of the protein, and therapeutic effect of drugs. Docking studies were also conducted to determine the best conformation of the drug molecule binded to the protein. These approaches carried out were influenced by the new ideas and reliable working hypotheses for molecular interactions in complexes of biological relevance. The application of these techniques is shown in the study of interaction of acetylcholinesterase with set of inhibitors. Binding energies of these inhibitors are calculated and evaluated for the efficiency of the drug molecules.
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Alzheimer's disease (AD) is one of the most common neurodegenerative disorders leading to dementia and memory loss. Clinical diagnosis of AD is based on the progressive impairment of memory, learning ability and other cognitive dysfunctions due to neurodegenerative disorder. Aging is generally considered to be the main factor in the impairment of memory and decrease in other mental functions. AD also decreases the ability of performing basic daily activities. Some common symptoms of this disease are apathy, verbal and physical agitation, anxiety, depression, delusions and hallucinations. Memory loss and other neuropsychological symptoms that include impairment of judgment, learning, abstract thinking, language, which are descriptive of AD, may be attributed to normal aging.10 The fact that AD increases with advancing the age, nowadays represents a major public health problem and it is probably becoming the most important pathology of the 21st century in the developed countries.10,12,13 The main cause of AD is decrease in the neurotransmitter acetylcholine (ACh). This decreased ACh level in elderly persons eventually leads to dementia. The effective method to prevent this is to inhibit the enzyme acetylcholinesterase (AChE) responsible for the cleavage of ACh and thereby enhance the amount of ACh.11
Biological Data of Acetylcholinesterase
Acetylcholinesterase (AChE, E.C 126.96.36.199) is an enzyme associated with the cholinergic signal system, which performs the role of removing acetylcholine from the receptors. In vertebrates, two types of cholinesterases can be distinguished on the basis of their substrate and inhibitor sensitivity. The AChE belongs to the "Î±/Î² hydrolase fold protein" superfamily comprising of serine hydrolases such as cholinesterases, carboxylesterases, and lipases.8,9,12
AChE, which is present in the central and peripheral nervous system and in skeletal muscles, plays a key role in terminating neurotransmission at cholinergic synapses by the hydrolysis of acetylcholine to choline and acetic acid. AChE may also participate in the development, differentiation, and pathogenic process such as AD and involve in the deterioration of the cholinergic innervations in the cortex region of the brain leading to AD. Thus the introduction of AChE inhibitors came into effect for the symptomatic treatment of AD.9,10
Cholinergic Synaptic Mechanism
Neurotransmitter ACh is found throughout the body, in which it regulates various vital functions. In the central nervous system (CNS), cholinergic neurotransmission is involved in a number of processes including memory and learning, cognitive functions, arousal, and motor control. ACh exerts its physiological effects via signalling through two distinct receptors namely muscarnic ACh receptors (mAChRs) and nicotinic ACh receptors (nAChRs). Once the ACh is released onto the synaptic cleft, acetylcholinesterase converts it into choline, which subsequently is taken up into the presynaptic terminal.6,7 A deeper understanding of this mechanism is clearly understood by exploring the enzyme AChE, its inhibiton and its biochemistry.
Figure 1: Mechanism of action of cholinergic neurotransmission (Adapted from R. Bullock).
Molecular Characteristics of Acetylcholinesterase
Sussman et al. first reported the three dimensional crystal structure of AChE from Torpedo californica (TcAChE) by X-ray analysis.15 At the molecular level TcAChE is a 537 amino acids long protein composed of a 12-stranded mixed Î²-sheet surrounded by 14 Î±-helices.14 Hhydrolysis of ACh in AChE takes place at the bottom of a long and narrow gorge lined with numerous aromatic amino acid residues that penetrate half into the enzyme.14
Active site is located ~20 Å from the surface of the enzyme and is composed of two sub-sites. A catalytic triad located at the base of the narrow gorge comprises of three components namely His440, Glu327, and Ser200 (Figure 3).15,16
A peripheral anionic site (PAS) is formed by the residues Tyr70 and Trp279. Two sets of residues that contribute to the peripheral anionic sub-site are located near the rim of the gorge.16,17 Hence, ligand association with the peripheral site may prevent access of substrate to the gorge by physical hindrance to restrict entry to the gorge by an allosteric mechanism, in which the active center conformation is altered. Recently, evidence was presented that AChE accelerates assembly of amyloid-Î²-peptides into the amyloid fibrils with involvement of PAS.18
Figure 2: Schematic representation of the 3D structure of Torpedo California AChE structure. 11 standard Î²-sheets (red) surrounded by 15 Î±-helices (yellow).
Figure 3: Binding site gorge of AChE with amino acids (Adapted from A. Khalid).
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Figure 4: Active binding site of Acetylcholinesterase. The catalytic triad is comprised of ser200, glu327, his440 and the peripheral anionic site is composed of tyr70 and trp279.
Physiological significance of AChE activity is reflected by the observation that it is targeted by number of natural and synthetic toxins. Based on the activity, acetyl cholinesterase inhibitors (AChEIs) are divided into two main classes: (1) irreversible organophosphorus inhibitors and (2) reversible inhibitors.19
Reversible AChEIs binds to the active binding site of the enzyme and inhibit the activity of acetylcholinesterase. Aminoacridines (tacrine), N-benzylpiperidines (donepezil), edrophonium and alkaloids (galanthamine) are the well known examples of reversible AChEIs.19,20
Tacrine hydrochloride (CognexÂ®) is a reversible cholinesterase inhibitor, known chemically as 1,2,3,4-tetrahydro-9-acridinamine monohydrochloride monohydrate. Tacrine hydrochloride is commonly referred to in the clinical and pharmacological literature as THA. It has an empirical formula of C13H14N2â€¢HClâ€¢H2O and a molecular weight of 252.74. Tacrine blocks the sodium and potassium channels and has a direct effect on muscarnic receptors.21,22,23
Figure 5: (A) 2D structure of tacrine (B) 3D representation of tacrine.
Galantamine (also called galanthamine) is an alkaloid containing tertiary amine isolated from several plants, including daffodil bulbs, but is now synthesized. Galantamine is a specific, competitive, and reversible inhibitor of AChE. It is also an allosteric modulator at nicotinic cholinergic receptor sites thereby potentiating and increasing the release of ACh neurotransmission. The IUPAC name is (4aS,6R,8aS)-4a,5,9,10,11,12-Hexahydro-3-methoxy-11-methyl- 6H-benzofuro[3a,3,2-ef] benzazepin-6-ol.24,25
Figure 6: (A) 2D structure of galantamine (B) 3D representation of galantamine.
Edrophonium is a rapid, short-acting reversible acetylcholinesterase inhibitor. It acts by inhibiting the action of acetylcholinesterase at sites of cholinergic transmission. IUPAC name of edrophonium is ethyl-(3-hydroxyphenyl)-dimethylazanium and its molecular formula is C10H16NO.26
Figure 7: (A) 2D structure of edrophonium (B) 3D representation of edrophonium.
Rivastigmine is a reversible acetylcholinesterase inhibitor that exerts its cholinergic effect by increasing the function of cholinergic receptors. Rivastigmine increases the concentration of acetylcholine through reversible inhibition of its hydrolysis by cholinesterase. IUPAC name of rivastigmine is (S)-N-Ethyl-N-methyl-3-[1-(dimethyl amino) ethyl] phenyl carbamate.27,28
Figure 8: (A) 2D structure of rivastigmine, (B) 3D representation of rivastigmine.
Huperzine A is a plant alkaloid derived from the Chinese club moss plant, Huperzia serrata. By reducing the activity of acetylcholinesterase, huperzine A reduces the breakdown of acetylcholine. Hence huperzine is a reversible acetylcholinesterase inhibitor. IUPAC name of huperzine is (1R,9S,13E)-1-Amino-13-ethylidene-11-methyl-6-azatricyclo [188.8.131.52] trideca-2(7),3,10-trien-5-one.29
Figure 9: (A) 2D structure of rivastigmine, (B) 3D representation of rivastigmine.
Organophosphorus compounds modulate their biological effects by inhibiting the action of acetylcholinesterase. This inhibition is due to the binding of the active oxygen analogue to the phosphorus triester. Some of the irreversible inhibitors are metrifonate, soman, sarin, cyclosarin, etc.
Molecular mechanics is a technique involving non-quantum mechanical methods used in the calculation of free energies of molecules. Potential energy of the molecule is described in the molecular mechanics that comes under laws of classical Newtonian physics. These equations of potential energy used for calculating the binding energy and the physical parameters used in these equations are known as force field. Energy generated using molecular mechanics can be used to compare the relative steric energy between the conformations generated by the same molecule. In a molecular system, total potential energy is the sum of individual potential components. Force field used in the molecular mechanics includes bond stretching, angle bonding, torsion, and van der Waals interactions.
Etot = Ebond + Ebend + Etors + Evdw + Eelec + Eother
Ebond = energy contribution due to bond stretching or compression
Ebend = energy contribution due to angle bending
Etor = energy contribution due to torsional alterations
Evdw = energy contribution due to van der Waals interactions
Eelec = energy contribution due to electrostatic interactions
Molecular geometry of a molecule is optimized by molecular mechanics in which the optimum geometry is predicted by moving the atoms present in the molecule until the net force acting on the atoms becomes zero. Primary goal of this optimization is to confirm the best molecular geometry.30
Molecular dynamics concerns with the detection of the potential energy of the molecule using empirical force fields. This molecular dynamics approximates real motions of the molecule in a molecular system by using the force field equations.31,32 Molecular dynamics give information regarding atomic positions and velocities of molecules. Binding free energy of protein molecule is calculated using molecular dynamics. Using molecular dynamics, thermodynamic properties and time dependent kinetic properties of molecules could be studied.33
Structure of receptor-ligand complexes is studied using the knowledge of molecular docking. Receptor usually is a protein and the ligand (inhibitor) is either a small molecule or another protein. Docking can be defined by placing the ligand in the most suitable conformation to interact with the protein. Amino acids can help stabilize protein structures due to their strong electrostatic interactions (e.g., hydrogen bonding) between their side chains. Concept of investigating the interactions between these amino acids as they approach their equilibrium geometry is studied using molecular docking.29,34 Hence the structure of intermolecular complex which is formed by two or more molecules to suggest binding modes of protein inhibitors can be predicted. Algorithms used in docking generate the possible structure conformations and thereby a mean score is calculated to identify the structure.35
General procedure of docking
Docking program is based on the algorithm used to perform the docking studies and the scoring function. Process of docking can be divided into five following stages36:
Generate possible conformations of the ligand
Docking all the available conformations
Scoring of the docked ligand (usually an assessment of binding interaction)
Selection of appropriate ligand molecules.
Docking is usually done by obtaining high-resolution X-ray crystallographic structures from protein database. Once the structure is obtained, active site of the protein must be located and structure of the potential ligand elucidated. Once the ligand is docked, possible conformation of that ligand and binding geometry of protein-ligand complex need to be analysed.37
The term genetic algorithm refers to general purpose optimization scheme that mimics the process of evolution.38,39 In molecular docking, genetic algorithm is used to solve problems occurring out of complex optimization. Theory behind this genetic algorithm is the evolution of a population of solutions possible using genetic operators such as migrations, mutations and crossovers to a final population which optimises a predefined function. In genetic algorithm, variables used are encoded into a genetic code and an initial population is created. Genetic operators mentioned above are applied to this and new population is created. Scoring is carried out for this new population and a set of iterations to be carried out depends on this scoring.40,41,42
REVIEW OF LITERATURE
Functions of acetylcholine in CNS was first envisaged by Dale (1935)43, and other experiments carried out further by Larrabee & Bronk (1938)44, Bronk (1939)45, Eccles (1944)46 suggested the role of acetylcholine which is responsible for the neuromuscular transmission in skeletal muscle and synaptic transmission in sympathetic ganglia. Research conducted by Coyle et al. (1983)47 emphasised the action of acetylcholine on cognitive and learning behaviour in humans and animals. This experimental conclusion was supported by works conducted by Hasselmo & Bower (1993)48, McIntyre (2002)49, and Hasselmo (2006)50. Hypothesis stating that cognitive disorders in AD is due to cholinergic degeneration of acetylcholine was investigated by Perry (1988)51 and the work done by Francis and his colleagues (1998)52 supported the fact that main cause of AD is due to the inhibition of acetylcholine by enzyme acetylcholinesterase. There are various research protocols and studies justifying the acetylcholinesterase inhibiting properties of drugs like tacrine, galantamine, decamethonium, donepezil, rivastigmine, edrophonium, and huperzine A. The 3D structure of TcAChE determined by X-ray analysis at a resolution of 2.8 Å was first investigated by Sussman et al. (1991).53 They confirmed that the enzyme contains 537 amino acids and is made up of Î±/Î² protein. The protein molecule is made up of 14 Î± helices and 12 strands of Î² sheets. This study confirmed the presence of active site lying near the bottom of a narrow gorge, comprising of a catalytic site made up of trp84 and phe330 and peripheral anionic site (PAS) made up of trp279 and tyr70 (see Figure 4). Rakonczay (2003)54 made a comparative study on eight inhibitors of AChE and evaluated IC50 values of these inhibitors. Binding of ligand or drug to protein molecule was illustrated by Ekholm (2001)55 using N-layered integrated molecular orbitalâ€‰and molecular mechanics (ONIOM) calculations at the active site consisting of catalytic triad. In a study conducted by Pilger et al. (2001)56, 3D structure of galantamine complexed with acetylcholinesterase showed an unusual protein-ligand interaction. Drug molecules bind at the base of the active site and thereby interact with both the acyl-binding pocket and ammonium binding site. Tertiary amino group of galantamine did not interact directly with the trp84 amino acid. This approach showed the possible interactions of galantamine with the catalytic triad and other amino acid moieties present in the protein molecule. Jung et al. (2007)57 made a comprehensive research of various approaches to the QSAR of tacrine derivatives against AChE activity using multiple linear regression (MLR), genetic algorithm (GA), and simulated annealing techniques. These models illustrated the role of hydrophobic and electrostatic interactions when the activity of AChE is increased. Inhibitors such as donepezil (Kawakami et al., 1996)58 and decamethonium which are unlike other inhibitors are gorge-sparing drugs in which the binding of these drugs occur outside the gorge as explained by Kryger et al. (1998)59 and hence the phe330 adopts an open access position running towards the wall of the gorge (Figure 10).
Figure 10: 3D structure of AChE-inhibitor complex showing the peripheral anionic site, gorge entry and catalytic triad.
Size of drug molecule is more concerned with their binding activity and it has direct effects on their reduced activity. Shen et al. (2002)60 made an extensive molecular dynamics study on AChE inhibitors. Results of molecular dynamics simulations of acetylcholinesterase were explained by Gilson et al. (2004)61 in which he states that cationic substrate acetylcholine is attracted towards the active site by strong electrostatic field generated by AChE. Simulation of AChE in water using molecular dynamics revealed the transient opening of a short channel near trp84. This is evident to explain the "back door" hypothesis that states the movement of substrates, inhibitors and solvents through the back door present at gorge of AChE. Kaur and Zhang (2000)62 proposed the fact that hydrophobicity and presence of ionisable nitrogen were the main requirements for inhibitors to react with acetylcholinesterase. They further concluded that water molecules present in acetylcholinesterase plays a very important role in defining the binding of the drug to the enzyme. Research carried out by Camps and his co-workers (1999)63 aimed at modelling derivatives of tacrine-huperzine A hybrids for the treatment of AD. The findings of this experiment suggested that derivatives occupied the same configuration as that of the hybrid molecule and are more potent. All these docking experiments and QSAR studies carried out were evident to prove the synthesis of new acetylcholinesterase inhibitors which are hybrid of two or more drug molecules and their derivatives thereby increasing potency and hence further findings may provide valuable drugs for treating AD in the future.
MATERIALS AND METHODS
Computational Modelling Methods and Protocols
Selection of protein and ligands
In this study, structure of protein and AChE inhibitors complex were taken from the Protein Data Bank (PDB) under 2ACE. The X-ray structures of TcAChE within a resolution of 2.5 Å were used for this study. Hydrogen molecules were added to the structure and charge of structure is brought to neutral. The PDB codes for set of inhibitors complexed with the protein molecules were as follows, 1acl (decamethonium), 1acj (tacrine), 1ax9 (edrophonium), 1dx6 (galantamine), 1eve (donepezil), 1gqr (rivastigmine), and 1vot (huperzine A).
X-ray crystallographic structures of AChE-inhibitor complexes were optimised using MM3 geometry in Scigress. Molecular mechanics parameters were determined and the orientation of the docked inhibitor is analysed.
Automated Docking procedure
Docking of following inhibitors, tacrine, edrophonium, rivastigmine, galantamine, donepezil, huperzine A, and decamethonium were performed using SCIGRESS. Automated docking was carried out using the Workspace application of SCIGRESS in which the ligand is automatically docked and scored in an active site. The docking procedure used scoring functions based on genetic algorithm with the potential of mean force64 (PMF) to perform the calculations. This docking models used, assumed that the docking is non-covalent.
Active site for acetylcholinesterase molecule was set by selecting neighbouring atoms of the ligand within a distance of 3 Å. Grid size was set at centre of active site with dimensions of 13 Ã- 13 Ã- 13 Å box and spacing of 0.375 Å. Docking procedure was made to run for a maximum of 3000 generations that had a population of 50 chromosomes and 300 iterations (conformations). Mutation rate for docking was fixed to be 0.3, crossover rate was 0.8 and convergence of 0.1 kcal was predefined. Scoring procedure was done by using PMF, which is a knowledge-based approach that extracts atomic potentials of pairwise protein-ligand complex structures in PDB. PMF showed a significant correlation between the experimental binding affinities and its computed score for protein-ligand complex.65-68
Copy of inhibitor was created in the chemical sample file and automated docking was set up to dock inhibitor in its active site. Ligand was kept flexible so that it prevents the molecule from breaking or bursting. Water molecules were excluded as they were not part of crystal structure. Root Mean Square (RMS) distance difference was calculated between the docked structure and original X-ray crystal structure. Docking runs for 3000 generations and for every 1000th generation, a pose of best fit is generated. At the end of 3000 generations, ligand was completely docked in its active site with the most favourable energy of binding.66,68
Docking Library of compounds
Library of inhibitors were made and docked to AChE using ProjectLeader tool in SCIGRESS. IC50 values of these inhibitors were collected from literature data and log IC50 values were calculated using ProjectLeader.
Results and Discussion
Detailed study of X-ray crystallographic structures of TcAChE-inhibitor complexes yielded some promising information concerning the orientation of inhibitors in their active site. Thorough knowledge on conformation of protein molecule to accommodate its inhibitor in its active site is critical in evaluating and predicting new inhibitors. Crystal structure of TcAChE was complexed individually with different inhibitors tacrine, edrophonium, decamethonium, huperzine A, donepezil, galantamine and rivastigmine.
MM-MM3 geometry analysis for these inhibitors complexed with TcAChE was carried out. Energy of final optimized structure was found out and tabulated under Table 1. Molecular mechanics parameters such as bond stretch (Ebond), bond angle (Ebend), improper torsion (EÏ‰), electrostatics (Eelec), torsion stretch (Etor), van der Waals forces (Evdw), and hydrogen bonding were calculated and tabulated in Table 2.
Table : Energy of the final optimized structure of set of inhibitors using MM-MM3 geometry
Energy of final optimized structure (kcal/mol)
Table : Molecular mechanics parameters of set of inhibitors
Interpretation of docking study
Automated docking was carried out for these inhibitors complexed with TcAChE. Crystal structures of previously docked inhibitor with TcAChE were taken to be the reference for docking approaches. Position of docked inhibitors is analysed with original crystal structure of inhibitors and it was predicted that binding pocket is different for these TcAChE -inhibitor complexes. This is evident from the orientation of these inhibitors. Inhibitors were binded according to the interaction with the amino acids present in the catalytic triad and formation of hydrogen bonds with neighbouring molecules.
Interaction of tacrine molecule built using Scigress with the AChE was investigated in the active site and docked tacrine molecule superimposed accurately on the crystal structure (Figure 11). In tacrine-TcAChE complex, acridine ring present in tacrine molecule is stacked with the protein molecule between the residues trp84 and phe330 at the catalytic triad. Root mean square (RMS) difference between the tacrine structures was found to be 0.281.
Figure 11: Docking of tacrine to the active site of TcAChE. Dark blue colour structure represents the structure of tacrine built using Scigress.
In decamethonium-TcAChE complex, orientation of the inhibitor is such that it aligns along the narrow gorge extending into active site. Quaternary group present at one end is aligned to indole ring of trp84 towards the active site and other quaternary group is aligned to trp279 present at top of narrow gorge (Figure 12). Orientation of the phenyl ring of phe330 lies parallel to the surface of gorge.69 Calculated RMS was found to be 1.798. Active site for decamethonium lies slightly outside the catalytic triad. This confirms the unique nature of decamethonium binding to the TcAChE.
Figure 12: Docking of decamethonium to active site of TcAChE. Dark blue colour structure represents the decamethonium structure built using Scigress.
Huperzine A-TcAChE complex showed that primary amino group of huperzine A interacts with aromatic rings of phe330 and trp84. A short hydrogen bond is formed between ethylidene methyl group and oxygen group of his440. Quaternary group present in huperzine A formed two aromatic-cation interactions. The work done by Saxena et al. (1994)69 proposed that carbonyl group present in huperzine-A pointed toward the oxyanion and primary amino group may interact with glu199 (Figure 13). Physical parameters of huperzine A-TcAChE complex were noted. Binding energy was found to be -98.245 kcal/mol. This value closely matched to the standard reference PMF score of Scigress application and hence validated the efficient binding of the inhibitor to protein molecule.
Figure 13: Docking of huperzine A to the active site of TcAChE. Dark blue colour structure represents the huperzine-A structure built using Scigress.
Donepezil-TcAChE complex showed a unique orientation of the drug along the gorge site, extending from the anionic active site to PAS. Major functional groups present in donepezil structure are a dimethoxyindanone moiety, a piperidine moiety, and a benzyl moiety. All these 3 groups interacted with the protein efficiently. Benzyl ring of the drug displayed a Ï€-Ï€ stacking with the indole ring of trp84 at the bottom of gorge.70,71 At the middle of gorge, piperidine moiety made a cationÂ-Ï€ interaction with phenyl ring of phe330. Indadone ring present in drug moiety interacted with indole ring of trp279 by classical Ï€-Ï€ interaction at the top of gorge (Figure 14). This clearly showed that donepezil had binded more efficiently with TcAChE and it is pharmacologically more efficient.71,72
Figure 14: Docking of donepezil to the active site of TcAChE. Dark blue colour structure represents the donepezil structure built using Scigress.
Binding of galantamine to the active site occurred at lower and upper end of the gorge. Comparison of crystal structure with docked structure made a good agreement for the orientation of inhibitor. Galantamine interacts with trp84, phe288 and phe290. Tertiary amino group present in galantamine interacted less likely with active site and strong hydrogen bonding is formed by the inhibitor with glu199 (Figure 15). It was also clearly evident from Figure 15, that oxygen moiety present in methoxy group on phenyl ring is in close vicinity to ser200 and his440.73
Figure 15: Docking of galantamine to the active site of TcAChE. Dark blue colour structure represents the galantamine structure built using Scigress.
It was observed that interaction of edrophonium with AChE is clearly evident from the stacking of edrophonium molecule between the aromatic rings of trp84 and phe330. It was also found that amino acids present in catalytic triad such as ser200, his440 and glu327 plays an important role in edrophonium-TcAChE complex (Figure 16). It was made clear that these binding interactions could lead to the discovery of edrophonium-like ammonium salts12 that are more potent inhibitors of AChE.74,75
Figure 16: Docking of edrophonium to the active site of TcAChE. Dark blue colour structure represents the edrophonium structure built using Scigress.
Rivastigmine complexed with AChE showed the linking of the carbamyl moiety to ser200 in the active site. It was observed that his440 had moved away slightly from glu327 and forms a hydrogen bond with glu199 (Figure 17). This caused a disruption to the active site. This eventually could be the reason for slower kinetics of reactivation.76,77
Figure 17: Docking of rivastigmine to the active site of TcAChE. Dark blue colour structure represents the rivastigmine structure built using Scigress.
Evaluation of Binding Energy
A set of inhibitors chosen for this study was made in to a library using the application ProjectLeader present in Scigress. ProjectLeader automatically docked the inhibitors to active site and binding energy for each inhibitor-protein complex was generated. Docking of library of inhibitors to the active site of TcAChE was performed using genetic algorithm. IC50 values of the inhibitors were taken from literature. IC50 values, log (IC50) and binding energy values were tabulated under Table 3.
Table 3: Calculated binding energy using PMF scoring and IC50 values of set of inhibitors