87560480 a-study-on-computer-aided-drug-design-for-m2-protein-in-h1 n1

A
PROJECT REPORT
ON
“A STUDY ON COMPUTER AIDED DRUG DESIGN FOR M2
PROTEIN IN H1N1”

CONTENTS
 Abstract
 Introduction
I. Proteins
II. Drug Designing
III. Active Site in Drug Designing
 Review OF
 Methodology
 Result and dissuasion
 Results
 Conclusion
 References

Today Information Technology is highly involved in all Biotechnology and
Pharmacology research and development sectors to understand biological
data, their properties, functions and individual role in the metabolites of a
living organism.
Computer Aided Drug Designing (CADD) is also an involvement of
information technology in pharmacology studies. This technology makes
easy to understand biomolecules and biochemical reactions. This method is
based on receptor and inhibitors interaction theory, in technical term it is
called Docking.
Virtual screening uses computer-based methods to discover new ligands on
the basis of biological structures. Large libraries are available, compounds
are docked into the structure of receptor targets by a docking computer
program.
Each compound is sampled in thousands to millions of possible
configurations and scored on the basis of its complementarity to the
receptor. Of the hundreds of thousands of molecules in the library, tens of
top-scoring predicted ligands (hits) are subsequently tested for activity in an
experimental assay.
This project aims to demonstrating Linux platform software based docking
dramatically into the process of discovery new drug that bind to biological
micro molecules with clear benefit for both the pharmaceutical industry and
whole social community .
Abstract

Initially I have focused on the M2protein of H1N1 which is an matrix
protein, enables hydrogen ions to enter the viral particle (virion) from the
endosome, thus lowering pH of the inside of the virus, which causes
dissociation of the viral partical and work on computational docking to study
the model ligands ‘amantadine and rimantadine’, and collected the library of
100 ligands; to inhibit the receptor “M2protein”, in the computational
methodology which is useful in Virtual Screening for finding the minimum
scored inhibitors from the ligands library.
However the results achieved demonstrate that high power computer
clustering software services technology (HPCCSN), networking technology
and Linux platform can be useful in applied drug design.

Chapter-1
Computer aided drug design CADD):
Computer aided drug design may be defined as the use of computational
techniques to design new drugs or drug molecule /to discovery new drugs.
1. Computer-Aided Drug Design (CADD) is a specialized discipline that
uses computational methods to simulate drug-receptor interactions.
CADD methods are heavily dependent on bioinformatics tools,
applications and databases. As such, there is considerable overlap in
CADD research and bioinformatics.
2. http://www.b-eye-network.com/view/852
BENIFITESOF CADD:
CADD methods and bioinformatics tools offer significant benefits for drug
discovery programs which are as follow.
 Costsaving
The tuff report suggests that the cost of drug discovery and development
has reached $800 million for each drug successfully brought to market.
Many biopharmaceutical companies now use computational methods and
bioinformatics tools to reduce this cost burden. Virtual screening, lead
optimization and predictions of bioavailability and bioactivity can help
guide experimental research. Only the most promising experimental lines
of inquiry can be followed and experimental dead-ends can be avoided
early based on the results of CADD simulations.

 Time-to-Market:
The predictive power of CADD can help drug research programs choose
only the most promising drug candidates. By focusing drug research on
specific lead candidates and avoiding potential “dead-end” compounds,
biopharmaceutical companies can get drugs to market more quickly.
 Insight:
One of the non-quantifiable benefits of CADD and the use of
bioinformatics tools is the deep insight that researchers acquire about
drug-receptor interactions. Molecular models of drug compounds can
reveal intricate, atomic scale binding properties that are difficult to
envision in any other way. When we show researchers new molecular
models of their putative drug compounds, their protein targets and how
the two bind together, they often come up with new ideas on how to
modify the drug compounds for improved fit. This is an intangible
benefit that can help design research programs. .
RECEPETOR
such binding occurs, the receptor goes into a conformational change which
ordinarily initiates a cellular response. However, some ligands merely block
receptors without inducing any response (e.g. antagonists). Ligand-induced
activity of the ligands changes in receptors result in physiological changes
which constitute the biological. In biochemistry, a receptor is a protein
molecule, embedded in either the plasma membrane or cytoplasm of a cell,
to which a mobile signaling (or "signal") molecule may attach. A molecule

which binds to a receptor is called a "ligand," and may be a peptide (such as
a neurotransmitter), a hormone, a pharmaceutical drug, or a toxin, and when
http://en.wikipedia.org/wiki/Receptor_(biochemistry)
http://upload.wikimedia.org/wikipedia/commons/0/07/Transmembrane_
receptor.png
DRUG:
Drugs are chemical subestances thet specifically interact with specific
biological recepeter and increase or decrease its activity.
A drug, broadly speaking, is any substance that, when absorbed into the
body of a living organism, alters normal bodily function.
Pharmacology,defines a drug as "a chemical substance used in the
treatment, cure, prevention, or diagnosis of disease or used to otherwise
enhance physical or mental well-being.

Drugs are usually distinguished from endogenous biochemicals by being
introduced from outside the organism. For example, insulin is a hormone
that is synthesized in the body; it is called a hormone when it is synthesized
by the pancreas inside the body, but if it is introduced into the body from
outside, it is called a drug.
http://en.wikipedia.org/wiki/Drug
http://www.scleroderma.org/images/medicalimages/research_advances/
Figure-3_Receptor-Ligand.jpg
Virtual Screening:
Virtual screening (VS) is a computational technique used in drug discovery
research. It involves the rapid in silico assessment of large libraries of
chemical structures in order to identify those structures most likely to bind to
a drug target, typically a protein receptor or enzyme.
Virtual screening has become an integral part of the drug discovery process.
Related to the more general and long pursued concept of database searching,
the term "virtual screening" is relatively new. Walters, et al. define virtual

screening as "automatically evaluating very large libraries of compounds"
using computer programs.[
The purpose of virtual screening to come up with hits of novel chemical
structure that bind to the macromolecular target of interest. Thus, success of
a virtual screen is defined in terms of finding interesting new scaffolds rather
than many hits. Interpretations of VS accuracy should therefore be
considered with caution. Low hit rates of interesting scaffolds are clearly
preferable over high hit rates of already known scaffolds.
Method:
There are two broad categories of screening techniques: ligand-based and
structure-based.
1. Ligand-based method
Given a set of structurally diverse ligands that binds to a receptor, a model of
the receptor can be built based on what binds to it. These are known as
pharmacophore models. A candidate ligand can then be compared to the
pharmacophore model to determine whether it is compatible with it and
therefore likely to bin
Another approach to ligand-based virtual screening is to use chemical
similarity analysis methods to scan a database of molecules against one
active ligand structure.

2. Structure-based
Structure-based virtual screening involves docking of candidate ligands into
a protein target followed by applying a scoring function to estimate the
likelihood that the ligand will bind to the protein with high affinity.
Applications:
Virtuale screening useful in folloing situations.
 The number avilable compounds in a library greatly exceeds the
experimentally based "wet" screen capacity to evaluate these
compounds. Virtual screening can then be used to prioritize
compounds for screening thereby identifying a greater number of hits
than could be identified by screening a random subset of compounds
selected from the same library.
 The number of compounds that could be synthesized using
combinatorial chemistry methods greatly exceeds the synthetic
capacity. Virtual screening can be used to screen a virtual library of
compounds that could be synthesized to identify those most likely to
bind. Then synthetic capacity can be focused on those compounds.
http://en.wikipedia.org/wiki/Virtual_screening

Chapter-2
H1N1:
Influenza A(H1N1) virus is a subtype of influenzavirus A and the most
common cause of influenza (flu) in humans. Some strains of H1N1 are
endemic in humans and cause a small fraction of all influenza-like illness
and a large fraction of all seasonal influenza. H1N1 strains caused roughly
half of all human flu infections in 2006. Other strains of H1N1 are endemic
in pigs (swine influenza) and in birds (avian influenza).
In June 2009, WHO declared that flu due to a new strain of swine-origin
H1N1 was responsible for the 2009 flu pandemic. This strain is commonly
called "swine flu" by the public media.
http://en.wikipedia.org/wiki/Influenza_A_virus_subtype_H1N1

Fig: This image showing structure of H1N1.

NOMENCULTURE:
Influenza A virus strains are categorized according to two proteins found on
the surface of the virus: hemagglutinin (H) and neuraminidase (N). All
influenza A viruses contain hemagglutinin and neuraminidase, but the
structures of these proteins differ from strain to strain, due to rapid genetic
mutation in the viral genome.
Influenza A virus strains are assigned an H number and an N number based
on which forms of these two proteins the strain contains. There are 16 H and
9 N subtypes known in birds, but only H 1, 2 and 3, and N 1 and 2 are
commonly found in humans.
Classification
Of the three genera of influenza viruses that cause human flu, two also cause
influenza in pigs, with influenza A being common in pigs and influenza C
being rare. Influenza B has not been reported in pigs. Within influenza A
and influenza C, the strains found in pigs and humans are largely distinct,
although due to reassortment there have been transfers of genes among
strains crossing swine, avian, and human species boundaries.
Influenza C
Influenza C viruses infect both humans and pigs, but do not infect birds.
Transmission between pigs and humans have occurred in the past.For
example, influenza C caused small outbreaks of a mild form of influenza
amongst children in Japan and California. Due to its limited host range and
the lack of genetic diversity in influenza C, this form of influenza does not
cause pandemics in humans.

Influenza A
Swine influenza is known to be caused by influenza A subtypes H1N1,
H1N2, H3N1, H3N2, and H2N3. In pigs, three influenza A virus subtypes
(H1N1, H3N2, and H1N2) are the most common strains worldwide. In the
United States, the H1N1 subtype was exclusively prevalent among swine
populations before 1998; however, since late August 1998, H3N2 subtypes
have been isolated from pigs. As of 2004, H3N2 virus isolates in US swine
and turkey stocks were triple reassortants, containing genes from human
(HA, NA, and PB1), swine (NS, NP, and M), and avian (PB2 and PA)
lineages.
http://en.wikipedia.org/wiki/Influenza_A_virus_subtype_H1N1
(H1N1) pandemic:
In the 2009 flu pandemic, the virus isolated from patients in the United
States was found to be made up of genetic elements from four different flu
viruses – North American Mexican influenza, North American avian
influenza, human influenza, and swine influenza virus typically found in
Asia and Europe – "an unusually mongrelised mix of genetic sequences”.
This new strain appears to be a result of reassortment of human influenza
and swine influenza viruses, in all four different strains of subtype H1N1.
Preliminary genetic characterization found that the hemagglutinin (HA) gene
was similar to that of swine flu viruses present in U.S. pigs since 1999, but
the neuraminidase (NA) and matrix protein (M) genes resembled versions
present in European swine flu isolates. The six genes from American swine
flu are themselves mixtures of swine flu, bird flu, and human flu viruses.

While viruses with this genetic makeup had not previously been found to be
circulating in humans or pigs, there is no formal national surveillance system
to determine what viruses are circulating in pigs in the U.S. On June 11,
2009, the WHO declared an H1N1 pandemic, moving the alert level to phase
6, marking the first global pandemic since the 1968 Hong Kong flu.
http://upload.wikimedia.org/wikipedia/commons/d/d0/AntigenicShift_H
iRes.png

How H1N1 causes flu(Mechanismof pathogenesis):
Flu is caused by a virus called Influenza virus and mainly affects the
respiratory tract.
Mode of transmission - Droplet borne, or air borne i.e., when a person
sneezes or coughs, large number of infectious droplets gets dispersed in air
and when these are inhaled they infect others. Hence it spreads very fast
from person to person and has a potential to cause pandemic
Mechanism or Pathogenesis - the virus has 2 important antigens
1)Neuraminidase(N)
2)Hemaglutinin(H)
Depending on these only H1N1 is classified.. It has the tendency to change
its serotype, like previously it was caused by H5N1 so on.
When person inhales a virus partical, it gets to the respiratory epithelial cells
with the help of hem agglutinin and enters the cells with the help of
neuraminidase. It replicates inside the cells and spreads the neighbouring
cells. Remember it does not enter blood usually its infection is only confine
to respiratory epithelium.
The epithelium gets damaged, which invites secondary bacterial infections.
The person suffers from a bacterial pneumonia. Person dies of secondary
bacterial infection. Not because of flu as such. Many a times or most of the
times the flu is just confined to respiratory system without any secondary
infection and hence most of the people just suffer from a just a short
duration of cold or cough. But they transmit the infection.
Once infected, the person starts infecting others with the release of the
infectious particles into the air.

http://in.answers.yahoo.com/question/index?qid=20090625044628AAa7nD
u
M2 protein:
Introduction
The M2 protein is a proton-selective ion channel protein, integral in the viral
envelope of the influenza A virus. The channel itself is a homotetramer
(consists of four identical M2 units), where the units are helices stabilized by
two disulfide bonds. It is activated by low pH.
Structure
Fig: M2 Protein of H1N1
The M2 protein unit consists of three protein domains: the 24 amino acids on
the N-terminal end, exposed to the outside environment, the 19 hydrophobic
amino acids on the transmembrane region, and the 54 amino acids on the C-
terminal end, oriented towards the inside of the viral particle. Two different
high-resolution structures of truncated forms of M2 have been reported: the
structure of a mutated form of the M2 transmembrane region by itself , as
well as a longer version of the protein containing only naturally-occurring
sequence in the transmembrane region. The two structures also suggest
different binding sites for the adamantane class of anti-influenza drugs.

Function
The M2 protein has an important role in the life cycle of the influenza A
virus. It is located in the viral envelope. It enables hydrogen ions to enter the
viral particle (virion) from the endosome, thus lowering pH of the inside of
the virus, which causes dissociation of the viral matrix protein M1 from the
ribonucleoprotein RNP. This is a crucial step in uncoating of the virus and
exposing its content to the cytoplasm of the host cell.
Inhibition and resistance
The function of the M2 channel can be inhibited by antiviral drugs
amantadine and rimantadine, which then blocks the virus from taking over
the host cell. The molecule of the drug binds to the transmembrane region,
sterically blocking the channel. This stops the protons from entering the
virion, which then does not disintegrate.
These drugs are sometimes effective against influenza A if given early in
the infection but are always ineffective against influenza B because B
viruses do not possess M2 molecules
However, the M2 gene is susceptible to mutations. When one of five amino
acids in the transmembrane region gets suitably substituted, the virus gains
resistance to the existing M2 inhibitors. As the mutations are relatively
frequent, presence of the selection factors (eg. using amantadine for
treatment of sick poultry) can lead to emergence of a resistant strain ontent
to the cytoplasm of the host cell.

http://en.wikipedia.org/wiki/M2_protein
TREATMENTOF SWINE FLU (PIGS AND HUMAN):
In swine
As swine influenza is rarely fatal to pigs, little treatment beyond rest and
supportive care is required. Instead veterinary efforts are focused on
preventing the spread of the virus throughout the farm, or to other
farms.Vaccination and animal management techniques are most important in
these efforts. Antibiotics are also used to treat this disease, which although
they have no effect against the influenza virus, do help prevent bacterial
pneumonia and other secondary infections in influenza-weakened herds.
In humans
If a person becomes sick with swine flu, antiviral drugs can make the illness
milder and make the patient feel better faster. They may also prevent serious
flu complications. For treatment, antiviral drugs work best if started soon
after getting sick (within 2 days of symptoms). Beside antivirals, supportive
care at home or in hospital, focuses on controlling fevers, relieving pain and
maintaining fluid balance, as well as identifying and treating any secondary
infections or other medical problems. The U.S. Centers for Disease Control
and Prevention recommends the use of Tamiflu (oseltamivir) or Relenza
(zanamivir) for the treatment and/or prevention of infection with swine
influenza viruses; however, the majority of people infected with the virus
make a full recovery without requiring medical attention or antiviral drugs.
The virus isolates in the 2009 outbreak have been found resistant to
amantadine and rimantadine.

http://en.wikipedia.org/wiki/Swine_influenza#Treatment
INHABITOR:
Antiviral drugs Amantadine and Rimantadine are the principle inhibitor of
M2 protein of H1N1.
These antiviral medicines prevent the spread of type influenza A by
interfering with the production of the virus inside the body. They do not treat
or protect you against influenza B. These antiviral drugs inhibits the M2
protein by blocking its ion chanel.
These antiviral medicines reduce the severity of influenza (flu) symptoms
and shorten the course of the illness of influenza A. They need to be started
within 48 hours of the first symptoms and continued, usually, for 7 days.
For the past few years, the U.S. Centers for Disease Control and Prevention
(CDC) have advised doctors not to use amantadine (Symadine or
Symmetrel) or rimantadine (Flumadine) to treat or prevent the flu. These
medicines have not worked against most types of the flu virus.
When used to protect people during a flu outbreak, antiviral medicines
usually are used for 7 days but may be continued for 5 to 7 weeks.
In healthy young adults and children, antiviral medicines can be very
effective in preventing influenza A during an outbreak. But these antiviral
medicines do not always treat or prevent the flu.

When given within 48 hours after symptoms begin, they may reduce
symptoms, shorten the length of influenza A illness by 1 or 2 days, and
allow for a faster return to usual activities.
Side Effects:
Side effects have been reported with both amantadine and rimantadine:
 Amantadine can cause sleeplessness (insomnia), hallucinations, and
agitation in a small number of people (2%).
 Rimantadine often causes side effects that affect the digestive system,
such as an upset stomach, nausea, and loss of appetite.
More serious but less frequent side effects (seizures, confusion) have been
reported in older adults and, most commonly, in adults who have seizure
disorders. Lowering the dose reduces these side effects without reducing the
effectiveness of the medication.
Side effects decrease after about 1 week of use and reverse as soon as
treatment stops.

Mark S.P. Sansomand Ian D. Kerr . : a molecularmodelling study of
the ion channel , Received September3, 1992; revised October 22, 1992;
accepted October 28, 1991.
 The influenza A M2 protein forms cation-selective ion channels which
are blocked by the anti-influenza drug amantadine. A molecular model
of the M2 channel is presented in which a bundle of four parallel M2
transbilayer helices surrounds a central ion-permeable pore. Analysis
of helix amphipathicity was used to aid determination of the
orientation of the helices about their long axes. The helices are tilted
such that the N-terminal mouth of the pore is wider than the C-
terminal mouth. The channel is lined by residues V27, S31 and I42.
Residues D24 and D44 are located at opposite mouths of the pore,
which is narrowest in the vicinity of I42. Energy profiles for
interaction of the channel with Na+, amantadine-H+ and
cyclopentylamine-H+ are evaluated. The interaction profile for Na+
exhibits three minima, one at each mouth of the pore, and one in the
region of residue S31. The amantadine-H+ profile exhibits a minimum
close to S31 and a barrier near residue I42. This provides a molecular
model for amantadine-H+ block of M2 channels. The profile for
cyclopentylamine-H+ does not exhibit such a barrier. It is predicted
that cyclopentyl-amine-H+ will not act as an M2 channel blocker
(Mark S.P. Sansom et.al 1992).

Takeda M, Pekosz A, Shuck K, Pinto LH, Lamb RA. Influenza a virus
M2 ion channel activity is essential for efficient replication in tissue
culture. J Virol. 2002 Feb;76(3):1391-9.
 The amantadine-sensitive ion channel activity of influenza A virus
M2 protein was discovered through understanding the two steps in the
virus life cycle that are inhibited by the antiviral drug amantadine:
virus uncoating in endosomes and M2 protein-mediated equilibration
of the intralumenal pH of the trans Golgi network. Recently it was
reported that influenza virus can undergo multiple cycles of
replication without M2 ion channel activity (T. Watanabe, S.
Watanabe, H. Ito, H. Kida, and Y. Kawaoka, J. Virol. 75:5656-5662,
2001). An M2 protein containing a deletion in the transmembrane
(TM) domain (M2-del(29-31)) has no detectable ion channel activity,
yet a mutant virus was obtained containing this deletion. Watanabe
and colleagues reported that the M2-del(29-31) virus replicated as
efficiently as wild-type (wt) virus. We have investigated the effect of
amantadine on the growth of four influenza viruses: A/WSN/33;
N31S-M2WSN, a mutant in which an asparagine residue at position
31 in the M2 TM domain was replaced with a serine residue;
MUd/WSN, which possesses seven RNA segments from WSN plus
the RNA segment 7 derived from A/Udorn/72; and A/Udorn/72.
N31S-M2WSN was amantadine sensitive, whereas A/WSN/33 was
amantadine resistant, indicating that the M2 residue N31 is the sole
determinant of resistance of A/WSN/33 to amantadine. The growth of
influenza viruses inhibited by amantadine was compared to the
growth of an M2-del (29-31) virus. We found that the M2-del (29-31)

virus was debilitated in growth to an extent similar to that of influenza
virus grown in the presence of amantadine. Furthermore, in a test of
biological fitness, it was found that wt virus almost completely
outgrew M2-del(29-31) virus in 4 days after co-cultivation of a 100:1
ratio of M2-del (29-31) virus to wt virus, respectively. We conclude
that the M2 ion channel protein, which is conserved in all known
strains of influenza virus, evolved its function because it contributes
to the efficient replication of the virus in a single cycle (Takeda M
et.al 2002)
Thanyada Rungrotmongkol, Pathumwadee Intharathep a, Maturos
Malaisree a, Nadtanet Nunthaboot c, Nopphorn Kaiyawet a, Pornthep
Sompornpisut a, Sanchai Payungporn d, Yong Poovorawan d, Supot
Hannongbua a,Susceptibility of antiviral drugs against2009 influenza A
(H1N1) virus Biochemical and Biophysical Research Communications
 Due to antigenic differences amongst influenza A strains, the current
seasonal influenza vaccines cannot provide protection against this new
strain of A (H1N1) influenza virus. Up to date, there are two classes
of anti-influenza agents:
(i) NA inhibitors, oseltamivir and zanamivir, protecting the release and
spread of progeny virions
(ii) (ii) adamantane derivatives, amantadine and rimantadine, preventing
the proton transfer in the M2 ion-channel. The A (H1N1) viruses
isolated from patients in USA and Mexicoare sensitive to NA
inhibitors but show resistance to adamantane derivatives. To gain

the fundamental knowledge on the structure and the drug–target
interactions of the new strain of influenza A (H1N1) virus,
homology modeling and molecular dynamics (MD) simulations
were carried out on the three inhibitor–enzyme complexes: OTV-
NA, AMT-M2 and RMT-M2. The present study is an extension
from, and is compared to, our previous works on avian
influenzaH5N1 virus were focused to understand the structural
properties, intermolecular interactions and predictive inhibitory
potencies of both wild- and mutant-type viruses at the NA and HA
(Thanyada Rungrotmongkol et.al 2009).
Kanta Subbarao & Tomy Joseph. Scientific barriers to developing
vaccines againstavianinfluenza viruses. Nature Reviews Immunology 7,
267-278 (April 2007)
 The influenza A virus particle has a lipid envelope that is derived
from the host cell membrane. Three envelope proteins haemagglutinin
(HA), neuraminidase (NA) and an ion channel protein (matrix protein
2, M2) are embedded in the lipid bilayer of the viral envelope. HA
(rod shaped) and NA (mushroom shaped) are the main surface
glycoproteins of influenza A viruses. The ratio of HA to NA
molecules in the viral envelope usually ranges from 4:1 to 5:1. b | The
HA glycoprotein is synthesized as an HA0 molecule that is post-
translationally cleaved into HA1 and HA2 subunits; this cleavage is
essential for virus infectivity. The HA glycoprotein is responsible for
binding of the virus to sialic-acid residues on the host cell surface and

for fusion of the viral envelope with the endosomal membrane during
virus uncoating. The NA glycoprotein cleaves sialic-acid receptors
from the cell membrane and thereby releases new virions from the cell
surface. M2 functions as a pH-activated ion channel that enables
acidification of the interior of the virion, leading to uncoating of the
virion. Matrix protein 1 (M1), which is the most abundant protein in
the virion, underlies the viral envelope and associates with the
ribonucleoprotein (RNP) complex. Inside the M1 inner layer are eight
single-stranded RNA molecules of negative sense that are
encapsidated with nucleoprotein (NP) and associated with three RNA
polymerase proteins , polymerase basic protein 1 (PB1), PB2 and
polymerase acidic protein (PA) , to form the RNP complex. The PB1,
PB2 and PA proteins are responsible for the transcription and
replication of viral RNA. The virus also encodes a non-structural
protein (NS) that is expressed in infected cells and a nuclear export
protein (NEP). The location of NEP in the virion is not known (Kanta
Subbarao et. al. 2007).
.
.

Tools and techniques:
I used a variety of tools and a large number of techniques in completion of
this project. These all tools and techniques were unknown to me before and I
have used these for the first time.
HARDWARE CONFIGURATION:
Processor - Intel® Pentium® P4 2.8GHz D2
RAM - 1 GB
Hard disk – 160 GB
Server computer platform:
 LINUX:
We did our search for the best operating system for our life science and we
use LINUX operating system. Nowadays, Linux is one of the most flexible
and popular operating systems for biological purposes. Linux is used
because of the following reasons:
 Cost: For desktop or home use, Linux is very cheap or free,
 Windows is expensive: Forserver use, Linux is very cheap compared
to Windows.
 Running from CD: Linux can run from a CD. But for Windows, it
has to first be installed to hard disk.
 Viruses: Compared to Windows, Linux is virus-free.
 Security: You have to log on to Linux with a user id and password.
This is not true of Windows.
 Bugs: Linux has a reputation for fewer bugs than Windows,
 Hardware the OS runs on: Linux runs on many different hardware
platforms, not so with Windows.

 Multiple Users: Linux is a multi- user system; Windows is not.
Traditional comparative genomics process is a time consuming as well as
money. The introduction of HighPerformanceComputing andNetworking
(HPCN) techniques in this process would decrease the costs and the time
necessary to compare the genomes. The current project focuses on the
Computer Assisted motifs finding using High Performance Computing &
Networking (HPCN) as a tool to improve the process of comparing
genomes. Computational power is now available in the form of Linux
Cluster Technologies.
Client computer platform:
 WINDOW’S Operating System
OPERATING SYSTEM: PCQ LINUX version – 2004, WINDOWS -XP
and LIVE CDs.
TOOLS AND SOFTWARES:
ON LINE SOFTWARES: PDB, KEGG, NCBI, and
UNIPROT.
OFFLINE SOFTWARES: PYMOL, GHEMICAL, OPEN
BABEL, FRED, VIDA.
SOFTWARES:
 Supercomputing in Linux:
A step-by-step guide on how to set up a cluster of PCQ Linux machines for
supercomputing .To keep it simple, we start with a cluster of three machines.
One will be the server and the other two will be the nodes. However,
plugging in additional nodes is easy and will tell the modification to

accommodate additional nodes. Instead of two nodes, we can have a single
node. So, even if we have two PCs, we can build a cluster.
Set up server hardware:
We should have at least a 2 GB or bigger hard disk on the server. It should
have a graphics card that is supported by PCQ Linux 7.1 and a floppy drive.
We also need to plug in two network cards, preferably the faster PCI cards
instead of ISA, supported by PCQ Linux. Why two network cards? Adhering
to the standards for cluster setups, if the server node needs to be connected
to the outside (external) network, Internet or your private network the nodes
in the cluster must be on a separate network. This is needed if we want to
remotely execute programs on the server. If not, we can do away with a
second network card for the external network. . Hence, on the server, one
network card (called external interface) will be connected to the Labs
network and the other network card (internal interface) will be connected to
a switch. We used a 100/10 Mbps switch. A 100 Mbps switch is
recommended because the faster the speed of the network, the faster is the
message passing. All cluster nodes will also be connected to the switch.
PYMOL:
PYMOL is a molecular graphics system with an embedded Python
interpreter designed for real-time visualization and rapid generation of high-
quality molecular graphics images and animations. It can also perform many
other valuable tasks (such as editing PDB files) to assist you in your
research. The extensible core PyMOL module (hosted here at Source Forge)
is available free to everyone via the "Python" license (a simple BSD-like
permission statement), but we ask all users to purchase a license and
maintenance agreement in order to cover our development and supportcosts.

In order to motivate such sponsorship, we offer support and other incentives
to PyMOL’s licensees with current maintenance subscriptions. In this way,
we seek to insure the viability of the Open-Source project by providing a
specific incentive (or reward) for outside support. However, our hope is that
only a small subset of PyMOL's total value will need to be restricted to
Incentive packages just enough to justify regular contributions and keep the
project self-sustaining.
Fig: PYMOL software home page.

FRED RECEPTOR
Fred receptor is a wizard like graphical utility that prepares an active site for
docking with FRED, Open- Eye’s docking program. fred receptor was
created to make preparing an active site a more intuitive process by allowing
the user to visualize the active site and how it is setup, however FRED does
not require that the active site be prepared with fred receptor. Input to fred
receptor is the structure of the target protein, generally from an X-ray
crystallography experiment. Output is a receptor file, which is a specialized
OEB (Open Eye’s molecule format) file, used by FRED.
Fig: FRED RECEPTOR home page.

F.R.E.D
F.R.E.D. (Fast Rigid Exhaustive Docking) is a protein-ligand docking
program, which takes a multiconformer library/database and receptor file as
input and outputs molecules of the input database most likely to bind to the
receptor. FRED is a command line program, although a GUI is available to
setup and create receptor files prior to docking. Typical docking time for
FRED is a few seconds per ligand. FRED jobs can also be easily distributed
over multiple computers/processors using PVM to further reduce docking
time.
The following structure-based scoring functions are available in FRED.
These scoring functions also have MASC variant.
1. SHAPEGAUSS: A shape-based scoring function that uses smooth
Gaussian functions to represent the shapes of molecules.
2. PLP: or Piecewise Linear Potential
3. CHEMGAUSS2: Version 2 of the Chemgauss scoring function, which
uses smooth Gaussian functions to represent the shape and chemistry of
molecules.
4. CHEMGAUSS3: Version 3 of the Chemgauss scoring function, which
uses smooth Gaussian functions to represent the shape and chemistry of
molecules.
Fred receptor is a wizard like graphical utility that prepares an active site for
docking with FRED, Open-Eye’s docking program. fred receptor was
created to make preparing an active site a more intuitive process by allowing
the user to visualize the active site and how it is setup, however FRED does
not require that the active site be prepared with fred receptor. Input to Fred
receptor is the structure of the target protein, generally from an X-ray

crystallography experiment. Output is a receptor file, which is a specialized
OEB (Open Eye’s molecule format) file, used by FRED.
PROTOTYPESOFTWARE:
The Fred receptor program is prototype software, which means the overall
design of this program may be changed in future versions. This is the first
time a GUI has been created to assist Fred, or any OpenEye computational
program, and as such is somewhat experimental. We expect and hope to get
feedback from users regarding the Fred receptor program. Based on that
feedback and other considerations future versions of Fred receptor may have
a substantially different look and feel as well as somewhat modified
functionality. For example the next version of Fred may have a completely
graphical interface that the Fred receptor programs functionality is merged
into.
Prototype software does not mean beta software. The Fred receptor is a
complete stable utility to assist Fred users in preparing their active site for
docking.
OPEN BABEL:
Open babel is free software, a chemical expert system mainly used for
converting chemical file formats. Due to the strong relationship to
informatics this program belongs more to the category cheminformatics than
to molecular modeling. It is available for Windows, UNIX, and Mac OS. It
is distributed under the GNU GPL. The project's stated goal is: "Open Babel
is a community-driven scientific project assisting both users and developers
as a cross-platform program and library designed to support molecular
modeling, chemistry, and many related areas, including interconversion of

file formats and data. Open Babel is a full chemical software toolbox. In
addition to converting file formats, it offers a complete programming library
for developing chemistry software. The library is written primarily in C++
and also offers interfaces to other languages (e.g., Perl, Python, Ruby, and
Java) using essentially the same API. This documentation outlines the Open
Babel programming interface, providing information on all public classes,
methods, and data. In particular, strives to provide as much (or as little)
detail as needed. More information can also be found on the main website
and through the Open babel-discuss mailing list. Open babel is a
community-driven scientific project including both cross-platform programs
and a developer library designed to support molecular modeling, chemistry,
and many related areas, including interconversion of file formats and data.
OPEN BABEL GUI:
A graphical user interface to babel's functionality. You can start Open Babel
GUI using the shortcut in the Start Menu. You can copy this onto your
desktop to make it easier to access it. This graphical interface is an
alternative to a command line and has the same capabilities. It is written
using wxWidgets and has the capability to be compiled on most platforms.
Currently it is available only on Windows and is available in the compiled
download. At present the interface is entirely text with no graphical display
of molecular structure. It does however provide an environment likely to be
familiar to Windows users and displays the options available rather than the
user having to remember them.

Fig: This figure shows home page of open babel GUI.

OMEGA:
Omega builds initial models of structures by assembling fragment templates
along sigma bonds. Input molecules graphs are fragmented at exocyclic
sigma and carbon to heteroatom acyclic (but not exocyclic) sigma bonds.
Fig: OMEGA software

VIDA:
VIDA is Open Eye’s main visualization application designed to intuitively
and effortlessly handle very large data sets while still generating extremely
high quality images. VIDA provides multiple modes of display including
1D, 2D, and 3D displays. Furthermore, VIDA is an excellent interface for
data analysis as it contains a chemically-aware spreadsheet and a powerful
list-based architecture.
Fig: VIDA home page.

List of online and off line tools:
S.No.
Tools / Servers /
Databases Used
Used for
1. NCBI Sequence Database
2. PDB Protein structure
3. PYMOL Protein structure visualization
4. FRED RECEPTOR Active site finding
5. PUBCHEM Ligand libraroy
6. OPEN BABEL Converting chemical files
7. OMEGA Fragment of Chemical Compounds
9. FRED Docking
10 VIDA Docking visualization

Proteinsearching:
In first step I retrieved target protein (M2 Protein) sequence by
usingNCBI,provides scientific community.
Fig: This image showing some information on NCBI.

Fig:This image showing information about M2 Protein on NCBI .

Fig : Protein sequence of M2 protein by using FASTA format.

Protein structure:
After taking the M2 protein sequence, I download the struture from PDB.
Fig: This image showing some information of various M2 protein on PDB.

Fig: This image showing some information on PDB.

Protein Study by Pymol:
After downloading the M2 protein sequence we use the Pymol visualization
software to study the 3-D structure of M2protein.
Fig: Image showing 3-D structure of M2 protein on Pymol.

Protein study: For further study (Helix, loops, chains etc) of M2 protein
we use the Pymol visualization software.
1. Load the PDB file
File -> Open -> 1w2i.pdb
2. Hide everything and then show protein cartton
PyMOL> hide everything, all
PyMOL> show cartoon, all
Fig :Visualization of target M2 protein structure on pymol.In this image
pymol shows four chains.

3. Color the helix, sheet, and loop
PyMOL> color purple, ss h
PyMOL> color yellow, ss s
PyMOL> color green, ss ""
Fig: Image showing the helix in purpel color of M2 protein on Pymol.

Fig : This image showing helix of M2 protein on Pymol.

4. Color chain A and B
PyMOL> color red, chain A
PyMOL> color blue, chain B
Fig : Image showing the four chains of M2 protein by four different colour
on Pymol.

Fig: This image showing the surface structure of M2 protein on PYMOL.
The four colours showing the four chains of M2 protein.

Active site finding :
In next step to find active site of target protein we used the software FRED
RECEPTOR.
Fig : This image showing active site of M2 protein whitch is kept in box.

Ligand libraroy:
The next step is to creat ligand liberary based on model inhabitor
amantadine and rimantadine.
Fig : This image showing some information for modal ligand on
PUBCHEM.

Fig : This image showing some information about amantadine ligand on
PUBAHEM .

Fig : This image showing some information about rimantadine ligand on
PUBCHEM.

After that I collectedthe 100 inhibitors library for next docking step.
Fig : This image showing the ligand library.

Running process of docking:
1) Prepare the receptor and find active sites via FRED receptor and save
file in “.oeb” format.
2) Library preparation: collect SDF file from PUBCHEM, NCBI.
a) Open the “OPEN BABEL” software and convert all SDF files
into MOL2 format.
3) Merge all the converted SDF files into a single file by the below given
command in linux operating system.
4) For the preparation of fragments of all chemical compounds as a
merged file by OMEGA.
C) Save the target protein file and omega fragment file in the
directory of FRED.
5) For the final step of docking proceed with the FRED software
a) Run the FRED software in LINUX and give the following
command:

Fig: fragment and conformation of files through OMEGA
software

Fig: Showing monitors performance during docking.

Fig: This image is showing the files formed during docking process.

RESULTS & DISCUSSION
CADD is a technique to perform the initial results of any pharmaceutical
products. This is fully based on computer and computing power and I have
used this in my project and entitled as “A STUDY ON COMPUTER
AIDED DRUG DESIGN FOR M2 PROTEIN OF H1N1 “which deals with a
real life problem for human health.
M2 protein (matrix protein) is involved in causing swine flu disease. It
enables hydrogen ions to enter the viral particl from the endosome, thus
lowering pH inside the viral partical, which causes dissociation of the viral
partical. This is a crucial step in uncoating of the virus and exposing its
content to the cytoplasm of the host cell.
I have used M2 protein as target and collected the possible 100 ligands
library from the PUBCHEM and through virtual screening I found out the
minimum energy inhibitor CID_44918, IUPAC name-: 1-(1-aminopentyl)
adamantane hydrochloride.

Fig: This image is showing shapegauss file having the shapegauss scores of
all the ligands used in the docking.

Fig: This image is showing some information of finally selected ligand on
PUBCHEM.

Fig: This image is showing some information of finally selected adamantane
hydrochloride adamantane hydrochloride ligand on PUBCHEM.

Docking visualization:
After the docking process we study the result by using docking visualization
software, VIDA.
Fig: This image is showing the binding of selected ligand with target protein
on VIDA.

with different angle.

Fig: This image is showing the binding of selected ligand with target protein,
kept in net.

helix.

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