Molecular Docking and Toxicity Analysis of Novel Atorvastatin Structural Analogues with HMG-CoA Reductase

 

Jaya Tripathi^1*, Manoj Kumar Mahto², Divya R.³, Prof. M. Bhaskar⁴, Sajad Shahbazi⁵

¹Aravinda Biosolutions Pvt. Ltd., Hyderabad, A P, India

²Dept. of Bioinformatics (Biotechnology), Acharya Nagarjuna University, Guntur, AP, India

³Dept. of Bioinformatics, Gulbarga University, Karnataka, India

⁴Dept. of Zoology, Sri Venkateswara University, Tirupati, AP, India

⁵Dept. of Biotechnology, Kakatiya University, Warangal, AP, India

*Corresponding Author E-mail: bioinfo.250887@gmail.com

 

This study aims to design a potent drug for cardiovascular disorders in which HMG-CoA is the main target. Analogue based Drug Design (ABDD) approach was used and six Atorvastatin analogues have been designed on the basis of their drugability, observed by an online tool ‘Osiris’. All analogues have been minimized with a commercial software Hyperchem 8.0 and then been docked against the target i.e.  enzyme HMG-CoA reductase, with Gold 3.01 docking tool. Docking studies of designed analogues shows that the -CH2CH2CH3 and -Cl substituents of Atorvastatin that were designed by modification at Fluorine atom of drug molecule are showing maximum binding affinity with target. Toxicity studies results for these analogues have also been found favorable.

 

 

INTRODUCTION:

Cardiovascular diseases are one of the biggest causes of death worldwide. Arteries and veins are the transporters of oxygenated blood throughout the body. Disfunction of these blood vessels usually results in cardiovascular diseases.^[1] The most common reason of their disfunction is the deposition of cholesterol and fatty compounds, which clogs the vessels thus hindering blood supply in different organs of the body and causing strokes, angina attack, hypertension and other cardiovascular disorders.^[2] Researches shows that smoking, alcohol consumption, excessive coffee intake, obesity, prolonged stress state, lack of exercise, diabetic condition are some of the risk factors that increase the chances of different cardiovascular disorders, however are curable and can be controlled.^[3,4]

 

Most circulatory cholesterol is synthesized internally rather than by dietary intake during the steroid biosynthesis through Hydroxymethylglutaryl-coenzyme A (HMG-CoA).^[5] This HMG-CoA is a key molecule for cholesterol biosynthesis.

 

Here HMG-CoA reductase is an enzyme which catalyses the conversion of HMG-CoA into mevalonate, which further get converted to isopentenyl pyrophosphate, farnesyl pyrophosphate, squalene, lanosterol and finally to cholesterol, through decarboxylation and condensation reactions in different steps involving actions of few enzymes such as geranyl transferase, squalene synthase and Oxidosqualene cyclase.^[6] Thus HMG-CoA reductase is identified as the initial rate determining factor of cholesterol biosynthesis thus considered as a target widely accepted for drug development studies of cardiovascular disease.

 

This insilico approach for predicting the structure of novel molecules that can inhibit the activity of the disease causing molecule is called as computer added drug design. This prediction can be done either by keeping in consideration the structure of the disease causing molecule which is often a protein i.e. called the structure based approach of drug design or by structural analysis of previously known drug molecules i.e. called analogue based approach of drug design.

 

Atorvastatin inhibitor has been taken for study where statin is a class of drugs used for cholesterol biosynthesis inhibition by inhibiting the activity of HMG-CoA reductase.^[7]  Atorvastatin has firstly been synthesized in Pfizer’s laboratory and has been marketed by trade name Lipitor, though in some countries it is also being sold under the trade names Sortis, Torvast, Torvacard, Totalip, Tulip, Xarator, Atorpic, Liprimar, and Atorlip.^[8]

Fig 1: Showing ligplot of Atorvastatin with 1HWK

 

Focus of our study is to optimize the activity of drug Atorvastatin against HMG-CoA protein. For that six Atorvastatin structural analogues were designed by changing the functional group at Fluorine atom of Atorvastatin and checked for their binding affinity in target site. Molecule showing highest binding affinity with target was considered as probable potent drug which further needs to be evaluated in laboratory. 

 

MATERIAL AND METHODS:

Target identification and optimization

A molecule of HMG-CoA reductase with known crystal structure of 4 chains and 2.22 Å resolutions has been identified and downloaded from http://www.rcsb.org/pdb server with PDB ID 1HWK. From analysis of Ligplot obtained from PDBsum, which informs about interactions between ligand and target molecule, it has been found that Chain A of the target is participating in interactions more than B, C or D with ligand thus been chosen for the study with active site residues Ser 661, Arg 590, Asp 690, Ser 684, Lys 691.  Binding site residues can be visualized from Fig:1.Molecule 1HWK was loaded in Hyperchem 8.0, Chain B, C and D, heteroatoms, ligands and water molecules were removed from the structure. Molecule was typed with CHARMm forcefield and energy minimization was performed with Steepest Descent and Polak Ribiere algorithm, RMS gradient 0.1 and Max Steps 2000 parameter values.^[9]

 

Design of Atorvastatin Structural Analogues

Structure of Atorvastatin molecule was retrieved from Drugbank and sketched and minimized in Hyperchem 8.0 software. Structural analogues were developed by modifications at Fluorine atom of Atorvastatin by replacing with Br, Cl, CCl3, CF3, CH2OH and CH2CH2CH3 respectively which can be seen in Fig: 2, on the basis of their drugability observed in Osiris online tool. All the analogues were then sketched in Hyperchem 8.0 software with CHARMm forcefield and energy minimization was performed with Polak Ribiere algorithm, RMS gradient 0.1 and Max Steps 2000 parameter values.^[10]

Fig 2: Atorvastatin showing –F group where modification done

 

Toxicity Analysis

All analogues were then subjected to toxicity prediction through Osiris online tool for all toxicity profiles like mutagenicity, carcinogenicity, irritant effect and reproductive effect. Toxicity analysis was done to know about the probable undesired effects of drug in the body. ^[11]

 

Docking

Gold 3.01 version software has been used for docking. Docking is the study for prediction of protein-ligand interactions. The Hydrogen bonds and Vanderwaals interactions between target and ligand make the complex stable, and this stability is measured by fitness score/Gold score.^[12] Gold fitness score are defined by hydrophilic and hydrophobic constraints which can be formulated as below

GOLD fitness = Shb_ext + 1.375(Svdw_ext) + Shb_int + Svdw_int

 

Where Shb_ext and Shb_int are the external and internal hydrogen bond energies and Svdw_ext and svdw_int are external and internal vanderwaals energies respectively. Gold tool works on the basis of genetic algorithm and provides full ligand and partial protein flexibility.^[13] Optimized structures of target and analogues were given as input for docking.^[14]

 

Table 1: Single point calculation and Geometry optimization calculations

Analogue	Single Point Calculation Energy (kcal/mol)	Energy after Geometry Optimization (kcal/mol)
Atorvastatin	35543	2261.04
Br	35514	2262.05
Cl	35553	2260.90
CF3	35521	2264.57
CCl3	35542	2265.49
CH2OH	35533	2263.49
CH2CH2CH3	35541	2261.021

 

RESULTS AND DISCUSSION:

In order to design a new drug for HMG-CoA reductase, six analogues were designed by modification at Fluorine atom of Atorvastatin inhibitor, which were then subjected to single point calculation and geometry optimization with Hyperchem 8.0 software and optimized energies were listed in table:1. In table 2 the energy potential of the optimized protein was listed.

 

Target was then subjected to geometry optimization with Hyperchem 8.0 software using Steepest Descent and Polak Ribiere algorithms.

 

Table 2: Geometry Optimization values for 1HWK

Steepest Descent                                                  Polak Ribiere

Gradient (kcal/mol- Å)	Geometry optimization (kcal/mol)	Gradient (kcal/mol- Å)	Geometry optimization (kcal/mol)
0.164557	- 687993.875	0.000004	-687571.4375

 

From toxicity analysis of Atorvastatin and all analogues, no mutagenicity, carcinogenicity, irritant effectivity or reproductive effectivity was found. Following table is representing the toxicity analysis results. Reults obtained from OSIRIS property explorer were tabulated in table:3.

 

Table 3: Osiris toxicity properties analysis

Analo-gues	Mutagenic	Carcino-genic	Irri-tant	Re-productive Effective
Atorvastatin	No	No	No	No
Br	No	No	No	No
Cl	No	No	No	No
CF3	No	No	No	No
CCl3	No	No	No	No
CH2OH	No	No	No	No
CH2CH2CH3	No	No	No	No

 

Docking was then performed using Gold 3.01 software and following fitness scores were obtained after analysis of results:

Table 4: GOLD docking results

S.No.	Analogues	Gold  fitness  Scores	S(hb_ext)	S(vdw_ext)	S(hb_int)	S(vdw_int)
1	Atorvastatin	45.87	0.00	33.07	0.00	0.40
2	Br	35.30	1.59	33.97	0.00	-12.99
3	CL	48.61	0.00	35.35	0.00	0.00
4	CF3	46.57	0.00	33.87	0.00	0.00
5	CCl3	47.95	0.40	34.91	0.00	-0.46
6	CH2OH	47.22	5.27	31.55	0.00	-1.44
7	CH2CH2CH3	53.67	3.94	37.62	0.00	-1.99

 

Atorvastatin’s Fitness Score was found 45.87, where all the analogues other than Br are showing higher fitness score than Atorvastatin, on which –CH₂CH₂CH₃ and –Cl substituents are showing highest fitness scores, i.e. 53.67  and 48.61 respectively thus having highest binding affinity with target. Here analysis shows that the values of external vanderwaals energies are higher than that of Atorvastatin (33.07) for –CH₂CH₂CH₃ analogue (37.62) and external hydrogen bonds energies are also high, which are the important components determining the fitness of complex. Dock scores and their variables were tabulated in table: 4.

 

CONCLUSION:

Computer Aided Drug Design is an excellent approach of Drug discovery saving time and cost of experiments in vitro. Binding affinity optimization was done Insilico by designing structural analogues of Atorvastatin and predicting their interactions with HMG-CoA target by docking studies. As –CH₂CH₂CH₃ substituent of Atorvastatin analogue has shown positive results in Toxicity profile analysis and has shown the best binding affinity with target, there are chances for this analogue to show better activity than Atorvastatin in vitro.

 

ACKNOWLEDGEMENTS:

I gratefully acknowledge Mr. Deepak Reddy Gade, Dept. of Pharmaceutical Chemistry, JNTUA-OTRI, Anantpur, Andhra Pradesh, India for his support in carrying out this research.

 

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Received on 23.01.2012         Modified on 13.02.2012

Accepted on 09.03.2012         © AJRC All right reserved