Insilico Design and Discovery of Some Novel Ache Inhibitors for Treatment of Alzheimer’s Disorder

 

Sandeep Reddy CH^1*, Sree Kumar Reddy G.², Manoj Kumar Mahto³, Pavan Kunala⁴, Chaitanya Kanth R.⁵

¹Dept. of Pharmacology, MLR institute of Pharmacy, Dundigal, Hyderabad, India.

²Dept. of Pharmaceutical Chemistry, JNTU-OTRI, Anantapur, India

³Dept. of Bioinformatics, Acharya Nagarjuna University, Guntur, AP, India.

⁴Dept. of Pharmaceutical Sciences, Rao’s college of Pharmacy, Nellore, AP, India.

⁵Dept. of Pharmaceutical Analysis, Vishnu College of Pharmacy, Bhimavaram, India.

*Corresponding author-Email: sandeep97@gmail.com

Enzyme Acetyl cholinesterase (AChE) catalyzes the neurotransmitter acetylcholine (ACh) at synaptic clefts of the neurons. Apart from its hydrolyzing activity it is also known to play an important role in amyloid formation thus causing Alzheimer’s disease (AD). AD is associated with significant loss of cholinergic neurons and reduced levels of ACh, which significantly impairs learning and memory processes. Acetyl cholinesterase inhibitors (ACIs) are one of the widely used drugsfor the treatment of mild to moderate Alzheimer’s dementia. Acetyl cholinesteraseinhibitors improve the neurological behavior by increasing availability of acetylcholine at synapse in the presence of intact cholinergic neurons. So identifying potent AChE inhibitors may declineneuro degeneration in AD patients. In this computational study, several novel AChE inhibitors were designed and optimized in the software Hyperchem. Also, these inhibitors were docked with the AChE in FLExX docking program and toxicity studies were conducted using OSIRIS property explorer. Here, the ligand 15 has shown better interaction and high binding affinity with AChE.

 

 

1. INTRODUCTION:

Alzheimer's disease (AD) is a brain disease that slowly destroys memory and thinking skills and, eventually, the ability to carry out the simplest tasks. Memory problems are one of the first signs of Alzheimer's. It is the most common cause of dementia among older people^[1]. Dementia is generally defined as the ‘loss of intellectual abilities (medically called cognitive function) like loss of thinking, remembering, and reasoning skills that interferes with a person's daily life and activities. Alzheimer's disease (AD) is neurodegenerative diseases of the central nervous system associated with progressive memory loss resulting in dementia. Two pathological characteristics are observed in AD patients at autopsy: extracellular plaques and intracellular tangles in the hippocampus, cerebral cortex, and other areas of the brain essential for cognitive function^[2].

 

•       Plaques are formed mostly from the deposition of amyloidal β (Aβ), a peptide derived from amyloidal precursor protein (APP).

•       Filamentous tangles are formed from paired helical filaments composed of neuron filament and hyperphosphorylated tau protein, a microtubule-associated protein.

A first sketch of the amyloidal cascade of events in AD would therefore be:

 

Acetyl cholinesterase (AChE) is an enzyme that degrades the neurotransmitter acetylcholinethrough its hydrolytic activity, producing choline and an acetate group. It is mainly found at neuromuscular junctions and cholinergic nervous system, where its activity serves to terminate synaptic transmission ^{[3, 4]}.

 

Drugs used to treat people with Alzheimer’s fall into two broad categories–drugs to treat cognitive symptoms, such as memory problems and other mental deficits of Alzheimer’s, and drugs to treat behavioral symptoms that do not respond to non-pharmacological behavioral-management approaches[5]. These drugs might include a variety of types of drugs broadly categorized as anti-agitation drugs.

 

Medications called cholinesterase inhibitors are prescribed for mild to moderate Alzheimer’s disease. These drugs may help delay or prevent symptoms from becoming worse for a limited time and may help control some behavioural symptoms. Scientists do not yet fully understand how cholinesterase inhibitors work to treat Alzheimer’s disease, but research indicates that they prevent the breakdown of acetylcholine, a brain chemical believed to be important for memory and thinking ^[6]. As Alzheimer’s progresses, the brain produces less and less acetylcholine; therefore, cholinesterase inhibitors may eventually lose their effect.

 

Application of information technology for the storage, retrieval and analysis of biological information, facilitated by the computers. Computer-assisted drug design (CADD), also called computer-assisted molecular design (CAMD), and represents more recent applications of computers as tools in the drug design process. In most current applications of CADD, attempts are made to find a ligand (the putative drug) that will interact favorably with a receptor that represents the target site^[7]. Binding of Ligand to the receptor may include hydrophobic, electrostatic, and hydrogen-bonding interactions. In addition, solvation energies of the Ligand and receptor site also are important because partial to complete Desolation must occur prior to binding. Ligand-based drug design is applicable when the structure of the receptor site is unknown, but when a series of compounds have been identified that exert the activity of interest^[8]. To be used most effectively, one should have structurally similar compounds with high activity, with no activity, and with a range of intermediate activities.

 

In the present study, we report few analogues of rivastigmine that show higher affinity and better interaction with the AChE. These results have been confirmed by the dock scores obtained from FlexX docking software.

 

MATERIALS AND METHODS:

Selection of target protein

Enzyme Acetyl cholinesterase was retrieved from the RCSB Protein Data Bank (http://www.rcsb.org/pdb/) with PDB Id –2HA3 ^[9]. Protein reports were obtained from RCSB Protein Data Bank (http://www.rcsb.org/pdb/). Active site identification is primarily done by using online tools like RCSB Ligand Explorer.

 

Fig: 1: positions for the modifications of rivastigmine class of AChE inhibitors (Lead)

Table: 1: newly designed rivastigmine analogs

Ligand	R1	R2	R3
Ligand 1	CH3	-CH=CH-CH3
Ligand 2	CH3
Ligand 3	CH3	-CH2CH2CH3
Ligand 4	CH3	CH2=CH-
Ligand 5	CH3
Ligand 6	CH3
Ligand 7	CH3
Ligand 8	CH3
Ligand 9	CH3
Ligand 10	CH3
Ligand 11	C2H5	-CH=CH-CH3
Ligand 12	C2H5
Ligand 13	C2H5
Ligand 14	C2H5
Ligand 15	CH3	-CH=CH-CH3
Ligamd 16	CH3
Ligand 17	CH3	-CH2CH2CH3
Ligand 18	CH3	CH2=CH-
Ligand 19	CH3
Ligand 20	CH3
Ligand 21	CH3
Ligand 22	CH3
Ligand 23	CH3
Ligand 24	CH3

 

These ligands are designed according to the SAR properties of the carbamate derivatives of AChEinhibitors. Modifications were given in the Table: 1

 

Selection of Lead moiety and designing of ligands

Its chemical structure is used as a starting point for chemical modifications in order to improve potency, selectivity, or pharmacokinetic parameters. Based on the literature review 3-[(dimethylamino)methyl]phenyl ethyl(methyl)carbamate have been selected as lead moiety^{[10, 11]}. Modification of the lead is visualized in Fig:1. 24 ligands are designed from the Lead compound by modifying the non pharmacophoric parts like R1, R2, R3.. All the ligands are designed by using Hyperchem.

 

Geometrical optimization of protein and ligands:

Geometrical optimization of protein is done by using HYPERCHEM 7.05 with parameters like force field CHARM ,rms gradient 0.01 ,maximum cycles 32000, invacuo and polakribere algorithm^[12].

 

Geometrical optimization of ligand is done by using HYPERCHEM 7.05 with parameters like force field OPLS, rms gradient 0.0001, maximum cycles 32000, invacuo and polakribere algorithm then we will get the energy for optimized value ^[13].

 

Toxicity studies

Toxicity profiles of ligands were studied by using an online tool, Osiris property explorer ^[14]. Toxicity parameters like mutagenicity, carcinogenicity, irritancy and teratogenicity of the ligands were predicted.

 

Docking studies

Protein Ligand Interactions were performed by using FlexX docking protocol. The FlexX docking can predict the interaction between the receptor-- ligand and protein interactions in biological systems. The consecutive steps in FlexX docking protocol is first the protein is loaded in to the FlexX docking software ^{[15, 16]}. Next choose receptor components like chains, cofactors, etc., chain A is selected. Reference ligand is selected it is PEG-905-A and include amino acids with 10Angstroms.and resolve chemical ambiguities next ligand in mol2 form is loaded in FlexXdocker and apply and dock. We get flex score for ligands, the ligand with less score shows better interaction and better action with fewer side effects.

 

RESULTS AND DISCUSSIONS:

Toxicity profile

Toxicity profiles of ligands are studied by using an online tool, Osiris property explorer. By employing the various toxicity problems like mutagenicity, carcinogenicity, irritancy and teratogenicity of the designed set of 24 ligands and the results are listed in the Table: 2

 

None of the ligands except ligand 3 and 17 are showing partial mutagenisity. Ligands 3, 11, 12,13,14 and 17 are showing partial carcinogenicity. Out of 24 ligands only ligands 1, 11 and 15 showing mild irritancy and none of theligands are having teratogenic effects. Prediction results are valued and color coded. Properties with high risks of undesired effects like mutagenicity or a poor intestinal absorption are shown in red. Whereas a green color indicates drug-conform behaviour. GREEN-NO; ORANGE-PARTIAL; RED-YES.

 

Table: 2: Toxicity profile of 24 ligands using Osiris property explorer

Ligand	Mutagenic	Tumourigenic	irritant	teratogenisity
Ligand 1	NO	NO	PARTIAL	NO
Ligand 2	NO	NO	NO	NO
Ligand 3	PARTIAL	PARTIAL	NO	NO
Ligand 4	NO	NO	NO	NO
Ligand 5	NO	NO	NO	NO
Ligand 6	NO	NO	NO	NO
Ligand 7	NO	NO	NO	NO
Ligand 8	NO	NO	NO	NO
Ligand 9	NO	NO	NO	NO
Ligand 10	NO	NO	NO	NO
Ligand 11	NO	PARTIAL	PARTIAL	NO
Ligand12	NO	PARTIAL	NO	NO
Ligand 13	NO	PARTIAL	NO	NO
Ligand 14	NO	PARTIAL	NO	NO
Ligand 15	NO	NO	PARTIAL	NO
Ligamd 16	NO	NO	NO	NO
Ligand 17	PARTIAL	PARTIAL	NO	NO
Ligand 18	NO	NO	NO	NO
Ligand 19	NO	NO	NO	NO
Ligand 20	NO	NO	NO	NO
Ligand 21	NO	NO	NO	NO
Ligand 22	NO	NO	NO	NO
Ligand 23	NO	NO	NO	NO
Ligand24	NO	NO	NO	NO

 

Table:3: FLEXx dock score of the ligands

LIGAND	SCORE
LIGAND-15	-5.145
LIGAND-18	-5.045
LIGAND-16	-4.718
LIGAND-19	-4.226
LIGAND-20	-4.131
LIGAND-21	-3.852
LIGAND-5	-2.431
LIGAND-2	-2.431
LIGAND-24	-2.392
LIGAND-22	-2.375
LIGAND-6	-2.348
LIGNAD-7	-2.327
LIGAND-23	-2.308
LIGAND-1	-2.232
LIGAND-4	-2.199
LIGAND-17	-2.046
LIGAND-11	-1.687
LIGAND-8	-0.512
LIGAND-10	-0.043
LIGAND-9	0.224
LIGAND-3	1.085
LIGAND-13	1.437
LIGAND-13	1.437
LIGAND-12	1.615

 

Docking Studies

Docking studies are performed by using FlexX docking protocol. The docking score for rivastigmine is -0.9661.The dock score of ligands 11, 17, 4, 1, 23,  7, 6, 22, 24, 2, 5, 21, 20, 19, 16, 18, 15 are higher when compare to rivastigmine and other designed ligands, this represents these  ligands have better drug  properties suitable for wet lab preparations. Dock sores of the analogs were tabulated in Table:3.

 

Fig:2: binding conformation of Ligand 15 at the active site of the AchE (2HA3)

 

Fig: 3: docked orientation of ligand 18 with AChE enzyme with 1 hydrogen bond at its active site.

 

The best among the 24 novel designed ligands , ligand 15 is having highest dock score (-5.145)which represents it has suitable properties for drugs. Due to naphthyl and allyl groups it is best suited in the poteinAChE by hydrophobic interactions, it is clearly visible in the following figure. In ligand oxygen is bonded through hydrogen bonding with Gln 185. Naphthalene ring interacts with the proline191 and phe186. Ligand interactions of ligand 15 are visualized in Fig:2

 

Ligands 18, 16, 19 and 20 are having better binding scores next to ligand 15. Docking interactions of these ligands can be visualized in fig: 3, 4, 5 and 6 respectively.

 

CONCLUSION:

Molecular modeling method has been used for modeling a new molecule for Alzheimer’s disease using AChE inhibitor ligands. This drug is drawn using Hyperchem, and its R 1, R-2,R-3 group is modified by replacing different functional groups. The binding free energy of the protein is calculated by performing docking process. The binding free energy of the designed ligands are obtained by eliminating the energy of the Lead moiety. The present study conclude that ligandno’s 11, 17, 4, 1, 23, 7, 6, 22, 24, 2, 5, 21, 20, 19, 16, 18, 15  have the maximum binding affinity toward AChE than rivastigmine.

 

The ADME studies show that these compounds have very good drug likeness and these compounds are recommended for the synthesis and in vivo evaluation under wet lab conditions.

 

REFERENCES:

1.     Berchtold NC, Cotman CW. Evolution in the conceptualization of dementia and Alzheimer's disease: Greco-Roman period to the 1960s. Neurobiology aging. 19(3); 1998:173-89.

2.     Ozelius L, Senthil G,  Lipton R, Soto-Valencia J, Risch N, Bressman S. LRRK2 G2019S as a cause of Parkinson's disease in Ashkenazi Jews. New England Journal Medicine. 354 (4);1985: 424-425.

3.     Sussman JL, Harel M, Frolow F, Oefner C, Goldman A, Toker L, Silman I. Atomic structure of acetylcholinesterase from Torpedo californica: a prototypic acetylcholine-binding protein. Science. 253 (5022); 1991: 872–879.

4.     Silman I, Futerman AH. Modes of attachment of acetylcholinesterase to the surface membrane. European journal of biochemistry. 30; 170(1-2); 1987:11-22.

5.     GleenonBM, Dynan KB,  PassmoreAP.Acetylcholinesterase inhibitors in Alzheimer’s disease. British Journal of Clinical Pharmacology. 48(4); 1999: 471–480.

6.     Corey-Bloom J, Anand R, Veach J. A randomized trial evaluating the efficacy and safety of ENA 713 (rivastigmine tartrate), a new acetylcholinesterase inhibitor, in patients with mild to moderately severe Alzheimer’s disease. International Journal Of Geriatric Psychopharmacology. 1;1998:55–65.

7.     Satyajit Dutta, Sovan Sutradhar, Kapil Sachan. Computer-Aided Drug Design - A New Approach In Drug Design And Discovery. International Journal of Pharmaceutical Sciences Review and Research. 3(4); 2010: 146-151.

8.     NutanPrakash, Dinta A G. Cheminformatics. Journal of proteomics  and bioinformatics.3(8); 2010 : 249-252.

9.     Yves Bourne, ZoranRadic, GerlindSulzenbacher, Esther Kim, Palmer Taylor, Pascale Marchot. Substrate and product trafficking through the active center gorge of acetylcholinesterase analyzed by crystallography and equilibrium binding. Journal of Biological Chemistry. 281(39), 2006: 29256-29267.

10.   A.A.N. de Paulal. Electronic structure calculations toward new potentially AChE inhibitors. Chemical Physics Letters. 446; 2007:304–308.

11.   Cyril Ronco. Synthesis and structure–activity relationship of Huprine derivatives as human acetylcholinesterase inhibitors. Bioorganic and medicinal chemistry. 17; 2009: 4523–4536.

12.   Daisy P, Sasikala R, Ambika A. Analysis of Binding properties of phosphoinositide 3-kinase through Insilico molecular docking. Journal of proteiomics and bioinformatics. 2(6); 2009: 274-284.

13.   Ghatol SP, Verma S, Agarwal K, Sharon A. Pharmacophore Distance Mapping and Docking Study of Some Benzimidazole Analogs as A2A Receptor Antagonists. International journal of pharmaceutical sciences and drug research. 2(1); 2010: 71-77.

14.   Lakshmi Vasavi Devi M, Deepak Reddy Gade, GopiRaju T, PavanKunala. Analogs of carbidopa: In silico design and development of novel DOPA decarboxylase inhibitors in the treatment of parkinson’s disease. Journal of pharmaceutical sciences and research. 3(4); 2011: 1176-1181.

15.   Simon  Cross. Improved FlexX Docking Using FlexS-Determined Base Fragment Placement. Journal of chemical information and modeling. 45 (4); 2005:993–1001.

16.   HolgerClaussen, Marcus Gastreich, Volker Apelt, Jonathan Greene, Sally A. Hindle, Christian Lemmen. The FlexX Database Docking Environment—Rational Extraction of Receptor Based Pharmacophores. Current Drug Discovery Technologies.1; 2004: 49-60.

 

 

 

Received on 07.02.2012          Modified on 02.03.2012

Accepted on 09.03.2012         © RJPT All right reserved