MATERIALS AND METHODS

31

The present study was focused on the evaluation of the neuroprotective effect

of Silk Protein, Sericin on Morphometric- and Behavioural Aspects, Cholinergic

system, Antioxidant system, Histological Aspects and Bioinformatics aspects.

Selection of Experimental Model:

The present study was carried out on the male albino rat, Rattus norvegicus,

weighing 160 ± 20 gm. Rat was chosen as experimental model for the present study

because of the following reasons.

1. Rat is considered as an excellent animal model for experimental studies

(McEwen and Stephenson, 1979).

2. Albino rats are relatively small, can be handled easily and require less feed.

3. The rats are preferred because of the plethora of Alzheimer’s Disease data that

exists for rodents (Bruce, 1985).

4. Extrapolation of the rats to the human being (man) is usually done for risk

assessment (Moser, 1990) for a wide variety of compounds (Grotenet al.,

1997).

5. It is worth full to develop animal model to understand the pathogenesis of AD

and to explore existing strategies for prevention and treatment of this

neurodegenerative disorder (Albensi, 2001).

Procurement and Maintenance of Experimental Animals:

Healthy Wistar strain Albino rats, Rattus norvegicus of the same age group of

3 months, weighing 160 ± 20 grams, obtained from Sri Venkateswara enterprises,

Bangalore were used as the experimental model in the present investigation. Prior to

experimentation, the rats were acclimatized according to the instructions given by

Behringer (1973). They were housed in polypropylene cages under the controlled

conditions of 28 ± 2°C temperature with photoperiod of 12 hours light and 12 hours

dark and 75% relative humidity maintained in the animal house of the Department

Zoology, according to the ethical guidelines for animal protection and welfare bearing

the Resolution No. 04/(i)/a/CPCSEA/ IAEC/ SVU/ KY- KPR / Dt. 28-03-2011. The

rats were fed with standard pellet diet supplied by Sri Venkateswara Enterprises,

Bangalore and water ad libitum throughout the period of experimentation.

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Biological effect of D-Gal:

Old Age can be induced by intraperitonial (IP) injection of D-Galactose, a

reducing sugar, which reacts readily with the free amines of amino acids in proteins

and peptides both in vivo and in vitro to form Advanced Glycation End-products

(AGE) through non-enzymatic glycation (Song et al., 1999; Bassi et al., 2002). The

Advanced Glycation End-product activates its receptors, which are coupled to

biochemical pathways that stimulate free radical production (Yan et al., 1996). D-

Galactose is a physiological nutrient, but over supply of D-Galactose will result in

abnormality of metabolism. The oxidative metabolism of D-Galactose produces

Reactive Oxygen Species(ROS), which surpass the ability of the cells to eliminate

them, consequently causing impairment of cellular membrane, structure and gene

expression (Wang, 1999; Zhang et al., 2006). In addition, the non-enzymatic

glycation is another pathway that can enhance oxidative lesions in ageing and age-

associated disease such as Alzheimer’s Disease (Baynes, 2001). Thus, long-term

intraperitoneal injection of D-Galactose induces AD in normal rat (Zhang et al., 2006;

Fang and Liu, 2007).

Collection of silk cocoons and extraction of Sericin:

Extraction of Sericin:

Raw Silk cocoons, purchased from local market of Chittoor were boiled in

water for 1hour and the resulting solution was cooled and filtered. After repeating this

process for 3 times, the filtrate was concentrated by using Hahnvapor Rotary

Evaporator (HS-2005V). 95% ethanol was added to the extract to precipitate Sericin,

collected by filtration, dried at 40oC, powdered and finally preserved in clean

container for further use. 8% SDS PAGE was done to confirm the presence of Sericin,

based on the molecular weight.

34

Picture -11: Sericin extraction from Silk Cocoons Flow chart

Induction of Alzheimer’s Disease:

D- Gal infection has been generally accepted to establish an aging model for

brain aging or anti-aging pharmacological research (Cui et al., 2006; Ho et al., 2003).

In the present study Memory impairment was induced to rats by IP injection of

D-Galactose (120mg/kg body weight) by dissolving in distilled water for one month

(Holden et al., 2003; Chen et al., 2006; Cui et al., 2006).

35

Administration of tested substance:

Silk Protein, Sericin (SP-P) extract (200 mg/kg body weight) was dissolved in

distilled water and given to the rat. A gavage tube was used to deliver the substance by

oral route, which is clinically expected route for administration. The volume of Sericin

administered was kept at 1 ml to the animal.

Experimental Design:

• Animal model : Male Albino Rat • Age : Three months old • Weight of : 160±20 grams • Chemical agents used for Induction of AD in Rat

: D-Galactose (D-Gal)

• Route of Administration : Intraperitoneal injection (IP) • Test substance : Sericin • Route of Administration : Oral

• Tissue selected • Brain regions selected

: :

Brain Cerebral Cortex (CC) and Hippocampus (HC)

• Isolation of tissues for Biochemical estimation

: 60th day and 90th day

Picture-12: Schematic representation of experimental design:

36

Grouping of Animals:

After the rats were acclimated to the laboratory conditions for 10 days before

the experimentation, they were randomly divided into four groups. Each main group

was again divided in to 2 sub groups of six each and were housed in separate cages.

These different groups of rats except control were treated with selected doses of

Sericin and D-Gal as given below. Keeping in view the altered activity of rats during

the nights compared to day time, all doses were given once in the morning hours in

between 8 A.M. to 9 A.M.

Group-I

(Control)

Control Rat

Group-II

(SP-S)

Rat, orally administered with Sericin (200 mg/kg body weight) up to 60

days (31st day to 90th day) continuously once in a day. (Joung et al.,

2011)

Group-III

(AD)

Rat, Intraperitoneally (IP) administered with D-Gal (120 mg/kg body

weight) up to end of the experiment (1st day to 90th day). (Zhang et al.,

2006; Hua et al., 2007)

Group-IV

(AD+SP-S)

Rat, Intraperitoneally injected with D-Gal (120 mg/kg body weight)

once daily for first 30 days. From 31stday onwards rats were

administered with Sericin (orally; 200 mg/kg body weight) along with

D-Gal (IP) up to 90th day.

In the present study the experimental duration selected was 90days. D-Gal was

given for first 30 days period to observe AD symptoms with the assessment of

cognitive skills in rats (AD group). Further AD induced rats were again treated with

D-Gal as well as Sericin simultaneously. To observe the cognitive skills, the rats were

subjected to behavioral studies on selected days (as per the experimental design).

37

Table-5: STANDARD METHODS APPLIED FOR VARIOUS PARAMETERS:

S.NO NAME OF THE PARAMETER

METHODS EMPLOYED

I Behavioural Aspects Morris water maze experiment(1984)

II Cholinergic System

Acetylcholine (ACh) Metcalf method (1957) as given by

Augustinsson (1957)

Acetylcholinesterase (AChE) Ellmanet al., (1961)

III Antioxidant System

Superoxide dismutase (SOD) Misra and Fridovich, (1971)

Catalase (CAT) Modified version of Aebi (1984)

Glutathione Reductase(GR) Carlberg and Mannervik (1985)

Lipid peroxidation (LPO) Ohkawaet al., (1979)

IV Histological Aspects Light Microscopy

V Bioinformatics Aspects

Modeling of 3D Structure MODBASE server

(http://salilab.org/modbase)

3D Structure Validation Ramachandran Plot

Energy Minimization Argus Lab

Protein-Protein Docking (Sericin and AChE)

Hex-6.0

Molecular Visualization PyMol

38

1. Behavioural Aspects:

Behavioral experiments were performed by using the water maze (Morris,

1984) which was originally designed to test the learning and memory ability in

rodents. A great deal of knowledge has been obtained on the neurochemical,

neuroanatomical and neurophysiological basis for the behavior associated with this

paradigm. The apparatus consisted of a circular tank, 100 cm in diameter and 50 cm in

depth painted with non-toxic white paint. The tank was filled with water (21-26oC) up

to a height of 30cm and the transparent escape platform made of plexiglass measuring

10cm in diameter and 29cm in height was hidden 1.5 cm below the surface of water in

a fixed location. Water was made opaque by mixing with powdered non-fat milk. The

platform was not visible from just above the water level and transfer trials have

indicated that escape on to the platform was not achieved by visual or other proximal

cues (Morris, 1981). The time spent by the animal to reach the hidden platform was

called as the Escape Latency and used as the index of memory.

Isolation of tissues:

For all biochemical estimations, the above mentioned four groups of rat were

sacrificed on selected days i.e., on 60thdayand 90thdayby cervical dislocation. The

brain was isolated immediately and placed on a chilled glass plate. Cerebral Cortex

and Hippocampus were separated by following standard anatomical marks (Glowinski

and Iverson, 1966) and they were frozen in liquid nitrogen and stored at -80oC until

further use. At the time of biochemical analysis, the tissues were thawed and used. The

results obtained were analyzed statistically.

Biochemical Assays:

Estimation of total proteins:

The total protein content was estimated by the method of Lowry et al., (1951).

2% homogenates were prepared in 10 % TCA and centrifuged at 1000xg for 15

minutes. The supernatant was discarded and the residue was dissolved in a known

amount of 1N sodium hydroxide. From this, 0.2ml was taken and 4 ml of alkaline

39

copper reagent and 0.4ml of folin phenol reagent (1:1 folin phenol and distilled water)

was added. The contents were allowed to stand for 30 minutes at room temperature

and the developed color was read at 600 nm in a spectrophotometer against a reagent

blank. The amount of total proteins present in the sample was calculated by using

bovine albumin standard and the values were expressed as mg/g wet weight of tissue.

Total proteins was calculated with the following formula

2. Cholinergic system:

i) Acetylcholine (ACh):

Acetylcholine (ACh) content was estimated by the method of Metcalf (1951)

as given by Augustinsson (1957). The rat brain regions such as Cerebral Cortex (CC)

and Hippocampus (HC) were weighed accurately, transferred to test tubes and placed

in a boiling water bath for 5 minutes to terminate the Acetylcholinesterase enzyme

activity and also to release the bound ACh. Then the tissues were homogenized in 1ml

of distilled water. To the homogenate, 1ml of alkaline hydroxylamine hydrochloride

was added followed by 1ml of 50 % hydrochloric acid solution. The contents were

mixed thoroughly and centrifuged. To the supernatant, 0.5ml of 0.37M ferric chloride

solution was added and the brown colour developed was read at 540nm against a

reagent blank (1ml of alkaline hydroxylamine hydrochloride+1ml of 50%

hydrochloride + 1ml of distilled water + 0.5ml of 0.37M ferric chloride solution) in a

spectrophotometer. The Acetylcholine content was expressed as μ moles of ACh/gm

wet weight of tissue.

ACh content was calculated with the following formula

∆ .

40

ii) Acetylcholinesterase (AChE):(E.C.: 3.1.1.7; Acetylcholine acetyl hydroxylase):

Acetylcholinesterase activity was estimated by the method of Ellman et al.,

(1961). 10% homogenates of different regions of rat brain were prepared in 0.25M ice

cold sucrose solution. The reaction was started with the addition of 100 μ liters of

homogenate to the reaction mixture containing 3.0ml of phosphate buffer (PH 8.0) +

20 μ moles of substrate (0.075M) + 100 μ moles of Dithiobis Trinitrobenzene

(DTNB,0.01M). The contents were incubated at 37°C for 15 minutes. The developed

colour was read at 412 nm in a spectrophotometer against a reagent blank containing

3.0ml of phosphate buffer (pH8.0) + 20 μ moles of substrate (0.075M) + 100 μ moles

of Dithiobis Trinitrobenzene (DTNB,0.01M).The enzyme activity was expressed as μ

moles of ACh hydrolyzed/mg protein/hour.

AChE activity was calculated with the following formula:

. .

3. Antioxidant System:

i) Superoxide Dismutase :(SOD EC: 1.15.1.6):

Superoxide dismutase activity was determined according to the method of

Misra and Fridovich, (1971) at room temperature. Different areas of rat brain such as

Cerebral Cortex (CC), and Hippocampus (HC) were homogenized in ice cold 50 mM

phosphate buffer (pH 7.0) containing 0.1 mM EDTA to give 5% homogenate (w/v).

The homogenates were centrifuged at 10,000 rpm for 10 mm at 4°C in ice cold

centrifuge. The supernatant was separated and used for enzyme assay. 100 µl of tissue

extract was added to 880 µl (0.05 M, PH 10.2, containing 0.1 mM EDTA) carbonate

buffer and 20 µl of 30 mM epinephrine (in 0.05% acetic acid) was added to the

mixture and measured the optical density values at 480 nm for 4 min in UV

Spectrophotometer.SOD activity was expressed as the amount of enzyme that inhibits

the oxidation of epinephrine by 50%, which is equal to 1 unit activity.

41

SOD activity was calculated with the following formula

Where,

ii) Catalase (CATEC 1.11.1.6):

Catalase activity was measured by a slightly modified version of Aebi, (1984)

at room temperature. Rat brain regions such as Cerebral Cortex (CC) and

Hippocampus (HC)were homogenized in ice cold 50 mM phosphate buffer (pH 7.0)

containing 0.1 mM EDTA to give 5% homogenate (w/v). The homogenates were

centrifuged at 10,000 rpm for 10 min. at 4°C in ice cold centrifuge. The resulting

supernatant was used as enzyme source. 10 µl of 100% ethyl alcohol was added to 100

µl of tissue extract and then placed in an ice bath for 30 min. After 30 minutes the

tubes were kept at room temperature followed by the addition of 10 µl of Triton X-100

RS. In a cuvette containing 200 µl of phosphate buffer and 50 µl of tissue extract, 250

µl of 0.066 M H202 (in phosphate buffer) was added and optical density was measured

at 240 nm for 60 s in a UV Spectrophotometer. The molar extinction coefficient of

43.6 M cm-1 was used to determine CAT activity. One unit activity is equal to the

moles of H202 degraded / mg protein /min.

Catalase activity was calculated with the following formula

∆ .

Where,

∆OD = Maximum OD difference between the 0” Sec to 60”sec.

42

iii) Glutathione Reductase (GR-EC: 1.6.4.2):

Glutathione Reductase activity was determined by a slightly modified method

of Carlberg and Mannervik, (1985) at 37°C. Selected rat brain regions such as

Cerebral Cortex (CC), and Hippocampus (HC)were homogenized (5%-w/v) in 50 mM

phosphate buffer (pH 7.0) containing 0.1 mM EDTA. The homogenates were

centrifuged at 10,000 rpm for at 4°C in ice cold centrifuge. The separated supernatant

part was used as enzyme source. NADPH (50 µl, 2mM) in 10mMTris buffer (pH 7.0)

was added to the cuvette containing 50 µl of GSSG (20mM) in phosphate buffer (0.5

M, pH 7.0 containing 0.1 mM EDTA) and 800 µl of phosphate buffer. The tissue

extract (100 µl) was added to the NADPH-GSSG buffered solution and measured at

340 nm for 3 mm. The molar coefficient of 6.22 X 103 cm-1 was used to determine GR

activity. One unit of activity is equal to the mM of NADPH oxidized I mg protein /

mim. The enzyme activity was expressed in μ moles of NADPH oxidized / mg protein

/min.

Glutathione Reductase activity was calculated with the following formula

∆ .

Where ,

∆OD = Maximum OD difference between the 0’ min to 4’min.

iv) Lipid Peroxidation (LPO):

The MDA levels were measured as described by Ohkawa et al., (1979).

Different areas of rat brain such as Cerebral Cortex (CC) and Hippocampus

(HC)tissue were homogenized (5%- W/V) in 50 mM phosphate buffer (pH 7.0)

containing 0.1 nM EDTA. The homogenates were centrifuged at 10,000 rpm for 10n

min at 40C in cold centrifuge. The separated supernatant part was used for estimation.

200 μl of the tissue extract was added to 50 μl of 8.1% Sodium Dodecyle Sulphate

(SDS), vortexed and incubated for 10 min at room temperature. 375 μl of twenty

percent acetic acid (pH 3.5) and 375 μl of thiobarbituric acid (0.6%) were added and

placed in a boiling water bath for 60 min. The samples were allowed cool at room

temperature. A mixture of 1.25 ml of Butanol:Phyridine(15:1) was added vortexed

43

and centrifuged at 1000 rpm for 5min. The colored layer (500 μl) was measured at

532 nm using 1,1,3,3-tetraethoxypropane as a standard. The values were expressed in

μ moles of Malondialdehyde formed/gram wet weight of the tissue.

MDA levels was calculated with the following formula:

4. Histopathology:

Histological examinations of the tissues Viz. Cerebral Cortex and

Hippocampus were carried out according to Humason (1972).

Light Microscopy

On selected days of experimentation viz. 60th and 90th day, the rats were

sacrificed by cervical dislocation and the selected brain regions such as CC and HC

were isolated. Isolated tissue of control and experimental rats were gently rinsed with

physiological saline (0.9% NaCl) to remove blood and debris adhering to the tissues.

They were fixed in 5% formalin for 24 hrs. The fixative was removed by washing

through running tap water overnight. After dehydrating through a graded series of

alcohols, the tissues were cleared in methyl benzoate, embedded in paraffin wax.

Sections were cut at 6μ thickness and stained with hematoxylin (Harris, 1900) and

counter stained with eosin (dissolved in 95% alcohol). After dehydration and clearing,

sections were mounted with DPX. The stained sections were observed under

microscope and the histological changes were recorded with the help of a pathologist.

5. Bioinformatics Aspects:

In order to understand the mechanisms of binding and the interaction between

Sericin and the Acetylcholinesterase, a three-dimensional (3D) structure of the rat

Acetylcholinesterase is generated based Homology modeling methods by using

MODBASE server. The initial models were improved by energy minimization

methods, the final refined models are further assessed by Ramachandran Plot. With

44

these models, the protein-protein docking studies were performed to check their

binding affinities.

The Present work was mainly concentrated on molecular interactions between

AChE and Sericin and the bioinformatics study was executed in various steps as given

below.

Homology modeling:

This, also known as comparative protein modeling or knowledge-based

modelingis used when there exists a clear structural relationship or functionally related

proteins with similar sequences, as measured by sequence identity and have similar

structures, in which the unknown sequence, called the target, bears a sufficiently

strong sequence similarity with another sequence, called the template, for which the

structure is already known. Broadly the modelling procedure can be divided intofour

steps: selecting the template, alignment of target with template, building the model

and evaluating the model (Ginalski, 2006).

The most basic step in structure prediction for selecting suitable template(s)

(sequence identity ≥ 30%) related to the target sequences were selected from the

Protein Data Bank (PDB) (Berman et al., 2000). This can be accomplished using

several tools that have been developed to carry out this step among which, BLAST

(Altschul et al., 1990) and PSI-BLAST (Altschul et al., 1997), FASTA (Pearson,

1988) are the most accepted ones.

The Coordinates of the three-dimensional model are built based on the

alignment and template structures. This step can be divided into two main trends. One

is to model the structure by copying the coordinates of the template in the aligned core

regions. The variable regions are modelled by taking fragments with similar sequences

from a database of previously observed loops. Then, the mutated side chains are

replaced with protamers that satisfy the stereo chemical criteria, together with limited

energy optimization. The sequence was submitted to database of protein structures like

MODEBASE server, a well-known program to build the Structures (Fiser et al.,

2000). The model building process consists of three main steps; in first step, the back

bone of the structure was build, then side chains were placed in second step and in

45

finally step, the entire structure was optimized. These steps were repeated until

acceptable results were obtained. Finally, the modeled structures were evaluated. It is

necessary to ensure that the model satisfies physical constraints and principles, such as

non-interpenetration of the atoms. Next in degree of importance, comes the

stereochemistry, such as bond lengths, angles, etc. The Ramachandran plot is a very

suitable method of checking the geometry of the model (Ginalski, 2006).

1. Collection of protein sequence from UniProt:

The sequences and the required information for the Proteins viz. AChE (Rattus

norvegicus) and Sericin (Bombyx mori) were retrieved from protein database UniPort

by using URL: http://www. uniprot.org.UniProt is a comprehensive, high-quality and

freely accessible database of protein sequence and functional information where many

entries were derived from genome sequencing projects. It contains a large amount of

information about the biological function of proteins derived from the research

literature. The UniProt consortium comprises the European Bioinformatics Institute

(EBI), the Swiss Institute of Bioinformatics (SIB), and the Protein Information

Resource (PIR). EBI located at the welcome trust genome campus in Hinxton, UK,

hosts a large resource of bioinformatics databases and services. SIB, located in

Geneva, Switzerland, maintains the ExPASy (Expert Protein Analysis System) servers

that are central resource for proteomics tools and databases. PIR is a successor to the

oldest protein sequence database hosted by the National Biomedical Research

Foundation (NBRF) at the Georgetown University Medical Center in Washington,

DC, USA. Margaret Dayhoff's prepared the Atlas of Protein Sequence and Structure

and published it in 1965. Finally, EBI, SIB, and PIR joined forces as the UniProt

consortium (2002).

II. BLAST (Basic Local Alignment Search Tool)

BLAST available at http://www.ncbi.nlm.nih.gov/BLAST was developed by

Altschul et al., (1997) for a rapid sequence comparison. Basic Local Alignment

Search Tool (BLAST) uses a heuristic to execute an approximate version of the Smith-

Waterman algorithm, which seeks directly approximates alignments that optimize a

measure of local similarity and the maximal segment pair scorelocal asopposed to

46

global alignments and is therefore able to detect relationshipsamong sequences which

share only isolated regions of similarity (Altschul et al., 1990). An early version of

BLAST, released in 1990 provided significance estimates for ungapped pair wise

alignments. More recent versions have provided two improvements: pairwise

alignments that are gapped and iterative searches derived from multiple alignments

(Altschul et al., 1997).

Once BLAST has found a similar sequence to the query in the database, it is

helpful to have some idea of whether the alignment is “good” and whether it portrays a

possible biological relationship or whether the similarity observed is attributable to

chance alone. BLAST uses statistical theory http://www.ncbi.nlm.nih.gov/

BLAST/tutorial/ Altschul-1. html to produce a bit score and expect value (E-value) for

each alignment pair (query to hit). A key element in this calculation is the

“substitution matrix”, which assigns a score for aligning any possible pair of residues.

The BLOSUM62 matrix is the default for most BLAST programmes. The E-value

gives an indication of the statistical significance of a given pairwise alignment and

reflects the size of the database and the scoring system used. Lower the E-value, more

significant is the hit.

As per Altschul et al., (1997), the BLAST family of programmes include:

BLASTP, which compares a protein sequence with a protein database; BLASTN,

which compares a nucleotide sequence with a nucleotide sequence; BLASTX, which

compares a nucleotide sequence (in all reading frames) with a protein database;

TBLASTN, which compares a protein sequence with a nucleotide sequence (in all

reading frames); and TBLASTX, which compares a nucleotide sequence (in all

reading frames) with a nucleotide database (in all reading frames); PSI–BLAST

Position Specific Iterated)and PHI-BLAST (Pattern-Hit Initiated BLAST).

Pearson and Lipman (1988) developed the programme, FASTA, for

comparing protein and DNA sequences. This program was developed with optimized

searches for local alignments using substitution matrices, and it has high level of

sensitivity for similarity searching. It has several features, including the similarity

search with several sequence and structure databases, genomics, and proteomics. In

addition, it has several features to get the pairwise alignment details, sequences of

47

aligned proteins, visual representation, and so on. The executable files and databases

for the sequence alignment program, FASTA, can be obtained from ftp://

ftp.ebi.ac.uk/pub/software/unix/fasta.

AChE (Rattus norvegicus) and Sericin (Bombyx mori) protein FASTA

sequences were retrieved from UniProt and submitted to BLAST-P against PDB to

retrieve the similar homology structures for query sequences by using the URL.

http://www.ncbi.nlm.nih.gov/BLASTP.

III. Modeling of 3D Structure for selected Proteins:

MODBASE is a queryable database of annotated protein structure models. The

models are derived by ModPipe, an automated modeling pipeline relying on the

programs PSI-BLAST and MODELLER. The database also includes fold assignments

and alignments on which the models were based. MODBASE contains theoretically

calculated models, and store the quality of the models. Additionally to the protein

structure models, MODBASE contains information about putative ligand binding

sites, SNP annotation, and protein-protein interactions. AChE (Rattus norvegicus) and

Sericin (Bombyx mori) protein sequences were submitted to MODBASE server to

build the 3D structures (http://modbase.compbio.ucsf.edu/modbase-cgi/).

IV. Validation of 3D structure:

MODEBASE-generated 3D structures were submitted to Ramachandran Plot

by using the URL http://dicsoft1.physics.iisc.ernet.in/rp/select.html.

V. Energy Minimization by using Argus Lab:

Energy minimization is also called energy optimization or geometry

optimization. This method is used to compute the equilibrium configuration of

molecules and solids. Stable states of molecular systems correspond to global and

local minima on their potential energy surface. Energy minimization is an efficient

tool for molecular structure optimization. It is necessary to reduce the net forces (the

gradients of potential energy) on the atoms until they become negligible.

Aurgus Lab, http://www.arguslab.com/arguslab.com/ArgusLab.html, is a

molecular modeling, graphics, and drug design program for Windows Operating

48

Systems. To date, there are > 20,000 downloads. Argus Lab is freely licensed.

Anyone can use it as many copies are needed for teaching where many students might

benefit from using Argus Lab. It is not allowed to redistribute Argus Lab from other

websites or sources. Aurgus lab is used for energy minimization of the lead molecules

which are taken mol format as input after minimization saved in PDB format.

In Aurgus lab software, the procedure is : go to File and open PDB file and

then remove hetero atoms and water molecules and then add hydrogen’s and then go

to optimize geometry.

VI. Protein-Protein Docking Studies by using Hex-version 6:

In the field of molecular modeling, docking is a method which predicts the

preferred orientation of one molecule to a second when bound to each other to form a

stable complex. Docking is frequently used to predict the binding orientation of small

molecule drug candidates to their protein targets in order to predict the affinity and

activity of the small molecule. Hex is an interactive molecular graphics program for

calculating and displaying feasible docking modes of pairs of protein and DNA

molecules. Hex can also calculate protein-ligand docking, assuming the ligand is rigid,

and it can superpose pairs of molecules using only knowledge of their 3D shapes.

Hex is freely available online docking software using Spherical Polar Fourier

(SPF) which correlates and accelerates the docking calculations. Hex is one of the few

docking programs having built-in graphics to view the docking results. It is the first

protein docking program to be able to use modern Graphics Processor Units (GPUs) to

accelerate the calculations.

In Hex's docking calculations, each molecule is modeled using 3D expansions

of real orthogonal spherical polar basis functions to encode both surface shape and

electrostatic charge and potential distributions. Essentially, this allows each property

to be represented by a vector of coefficients (which are the components of the basic

function). Overall docking score will be obtained from interaction energy in a pair of

3D structures. This docking approach is similar to conventional Fast Fourier

Transform (FFT) docking methods, which use Cartesian grid representations of

protein shape and other properties. However, the Cartesian grid approach only

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accelerates a docking search in three translational degrees of freedom. Whereas, the

SPF approach allows the effect of rotations and translations to be calculated directly

from the original expansion coefficients.

VII. Protein and Protien interaction and visualization by PyMol: PyMol is a

widely used open-source molecular visualization program maintained by DeLano

Scientific LLC as a user sponsored project. PyMol version 1.0 earned a reputation for

its ease of use and numerous features. A powerful set of scripts for calculating

physical properties of molecules is available among classical molecular models in

PyMol. The core of the program is a full featured Python interpreter, which is then

extended by an OpenGL 3D display, a Tcl/Tk based GUI and the PyMol API which

gives the possibility of creating plug-ins. Although, this later feature was mainly

intended for automatic coloring of atoms according to relevant properties, loading and

manipulating structures, it is also capable of inserting additional graphical primitives,

like spheres, cylinders, triangles and vertices called Compilsed Graphic Objects

(CGOs). PYMOL uses object-oriented code. In this software open pymol , goto file

and open PDB files of protein and ligand and go on interact to see the hydrogen bond

interactions, ionic interactions between the residues and atom.

Validity of experimental procedures:

General:

For all the enzyme studies in the present investigation, the assays were

standardized by conducting preliminary assay to determine the optimal PH,

temperature, enzyme and substrate concentration and these optimal conditions were

subsequently followed for each enzyme assay.

Aliquots for assay:

Aliquots were selected such that initial rates were approximated as nearly as

possible, yet proving sufficient product to fall in to a convenient range for

spectrophotometric measurement.

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Enzyme units:

The soluble protein content of the tissue homogenate was used as the enzyme

source and protein was estimated using Folin phenol reagent (Lowry et al., 1951).

This was used for the expression of enzyme units, i.e., μ moles of product formed or

substrate cleaved/mg protein/hour or minute.

Substrate requirements:

All the enzyme assays were made at saturating substrate concentrations, i.e.,

following zero order kinetics.

Lambert-Beer law:

For colorimetric procedures this law is applicable, which states that the optical

density of the resulting colored complex is proportional to the concentration of the

reaction products.

Enzyme nomenclature:

The nomenclature of the enzymes used in this thesis is according to the report

of the commission of enzymes of the International Union of Biochemistry.

Statistical Analysis:

Values of the measured in different parameters were expressed as Mean ±

SEM. One way ANOVA was used to test the significance of difference among the

four different groups with Dunnett’s post-hoc test for multiple comparisons using

standard statistical software, SPSS (Version -16). The results were presented with the

F-value and p-value. In all cases, F-value was found to be significant with p-value

less than 0.01. This indicates that the effects of factors are statistically significant.