Student Protein Analysis System), SIB (Swiss Institute of Bioinformatics),

Student Name—-Muhammad Ramzan

VU ID mc160402117

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and use of tools in it.

BIF 501




       The scientific knowledge has multiplied very rapidly and is shared
in a vast manner as was never been in the past. The scientific knowledge was
divided into many disciplines due to its vastness but with new discoveries has
increased this knowledge so much that these disciplines are coming closer and closer
in such a way that new fields are emerging. This vast scientific is needed
again and again and is retrieved and analyzed for obtaining data.
Bioinformatics is the one of such disciplines of science that provides the
facility of retrieval and analysis of biological data to carry out further
investigations in order to get more biological information. This branch of
science helps the biologists to get important information from already
preserved biological data saved on different web sites or computer programs
which are also called bioinformatics tools without any cost. The present review
provides a detailed summary of some of the tools used in bioinformatics available
for biologist for the retrieval and analysis of biological data. Particularly
this review focuses on those fields of life researches in which these
biological tools provide great information as analysis of DNA structure and
sequence, protein structure and sequence for the identification of different
characteristics as the finding of 3D structure of their molecules to find
molecular interactions. It also discusses about life phenomenon to get
important information from the already preserved data on various biological


Key words:-

Life sciences; Sequence analysis; Phylogeny; Structure prediction; Molecular
interaction; biological data, biomolecules, sequencing profiling


ADMET (absorption, distribution, metabolism, excretion and
BLAST (Basic Local Alignment Search Tool), I-TASSER
(Iterative threading assembly refinement), DNA (Deoxyribo Nucleic Acid), cDNA (complementary
DNA), ORF (Open Reading Frame), PDB (Protein Data
Bank), ExPASy (the Expert Protein Analysis System), SIB (Swiss Institute of
Bioinformatics), HMM (Hidden
Markov Model), CADD(Computer Aided Drug Design)  


       Bioinformatics is
very important and useful interdisciplinary science of the present age. It is
derived from the combination of many other branches of science as biology,
computer science, mathematics, statistics etc. It is developed for the storage
of biological data, its retrieval and analysis 1.
The scientist who used the term “bioinformatics” for the first time in 1970 was
Paulien Hodgeweg who was a Dutch system-biologist. He used of the information
technology for the study of the life 2,3.
The introduction of this useful mechanized modeling and the production of SWISS
MODEL about 18 years ago 4 caused a great deal of progress of the bioinformatics.
Then to onward the field of bioinformatics has become an integral part of
biological informational data with a faster speed.

       Mathematical and
other computing tools are used for the determination of structure and
properties of proteins, genes and genetic analysis. It also helps in the study
of biomolecules and their interaction in the cell. Although the information
generated by these tool are not as reliable as obtained by experimentation. The
process of experimentation is costly and time consuming. However in sillico
analysis can still make it easy to reach a known decision for performing an
expensive experiment. For example a druggable material contains ADMET
(absorption, distribution, metabolism, excretion and toxicity) characteristics to
get through medical tests. If the a material does not contain necessary
ADMET’s, then most probably it is not accepted. In order to overcome such
deficit, several bioinformatics tools are being developed to find ADMET’
characteristics that permit the scientists and researchers to evaluate a large
quantity of compounds to find most druggable substance before starting of
medical tests 5.

        Many reviews on particular conditions
of bioinformatics have written 6-8. But no one proves to be equitable for scientific
researcher who does not work according to computational biology. In this review
we are taking chance to introduce some tools of bioinformatics. In this review
only those tools are selected which are advantageous to get information from
biological data to a large extent. These tools include analysis of DNA and
protein sequences and structure including 3D structure of proteins,
phylogenetic studies as well as the interaction of different molecules in the

Gene Identification and Sequence Analysis:

     Sequence analysis means to understand
various characteristics of a biomolecule as proteins or nucleic acid. For this
purpose first step is to retrieve relative sequences from public database.
After refining if necessary these are introduced to different tools that forecast
their features. These tools as BLAST (Basic Local Alignment Search Tool) 10,
ClustalW 11
help us to find gene and protein sequences find their evolutionary history and basis.
These tools use latest mathematical and statistical methods to analyze the
sequences. Some tools especially helpful in finding promoter regions (the
regions of genes which start transcription process) and terminator (that mark
the end of the gene, introns, exons. For this purpose
ORF (Open Reading Frame) is used. Mostly predictions rely on
complementary DNA (cDNA) and Expressed Sequence Tags (ESTs). However, the
cDNA/ESTs information is often limited and deficient, therefore makes the work
of finding new genes enormously difficult. Computational scientists have developed
another technique known as an ab initio geneidentification. The prospective of
this technique was established in a study, which was able to forecast 88% of
already confirmed exons and 90% of the coding nucleotides from Drosophila
melanogaster with very low rate of false-positive recognition 12.
Keeping in view the accuracy (~90%) delivered by this approach, it could be a trustworthy
tool for annotating lengthy genomic sequences and calculation of new genes

 Following in the table are some tools used for
gene identification and sequence analysis of proteins in bioinformatics.






This search
tool is used for DNA sequences, amino acid sequences and protein sequence
analysis. BLAST tool helps to find the order comparing with library or
database of sequences. 



This search
tool is used for homologous protein sequences. Its common use is to find homologous protein or nucleotide sequences, and to perform sequence


Clustal Omega

is the most recent form of Clustal alignment program. It is online and
command-line based. The distinctive trait of Clustal-omega is its
scalability, as thousands of medium to large sized sequences can be
associated at the same time. It will also make use of multiple processors,
where present. In addition, the quality of alignments is better to the
previous versions. The algorithm uses seeded guide trees and HMM
profile-profile progressive alignments.



It is used
for sequence profiling.


ORF Finder

This tool is
used to find Open Reading Frame when an accepted gene sequence is subjected
to this tool. This tool is especially helpful in finding promoter regions
(the regions of genes which start transcription process) and terminator (that
mark the end of the gene, introns, exons,



A sector of
the UniProt data base containing the physically annotated protein sequences


Clustal W

A very popular site
for pairwise and multiple sequence alignment. . It runs in Windows,
Linux/Unix and Mac operating systems



GENSCAN is freely
accessible software used for “recognition of whole gene structures in
genomic DNA”. Genscan can be used “for predicting the locations and
exon-intron structures of genes in genomic sequences from a diversity of




Predicting Protein Structure and Function

 In the
beginning protein molecules have no shape of amino acid strings, which finally
fold to form a three-dimensional (3D) structure to become biologically active.
The folding of the protein into a correct way is a precondition for any protein
to perform its biological functions. Therefore, information of 3D structure of
a protein is essential to gain an impending into the function of a definite
protein. Frequently, 3D structures are found by X-ray crystallography or correlated
techniques. Though, these techniques are costly, difficult and intense and are
often vulnerable by the bad heterologous expression, and attempts to get good
crystals 14. Therefore, a few structures (~250) using XRD and NMR(Nuclear Magnetic Resonance) spectroscopy are submitted compared to nearly
a million monthly submissions to NCBI. Information of tertiary structures on
genome scale level for many proteins is consequently missing. Instead, a
protein’s 3D structure can be found using different bioinformatics tools, and as
a result has become important in the field of bioinformatics 14. i-TASSER:
It is a tool used for finding protein 3D structure. It can also describe the
functions of proteins that are based on sequence. This server gives 3D
structure of selected protein through numerous threading using templates from
PDB 16. One of the most important tools for
finding protein structure is ExPASy (the Expert Protein Analysis System powered
by the Swiss Institute of Bioinformatics (SIB). The Expasy tool also
provides many supplementary tools to determine resemblance, outline
recognition, and studying post-translational modifications 15.   

Here are given in the table some important tool
used for finding protein structure in bioinformatics.





Iterative Threading ASSEmbly Refinementis
a bioinformatics tool for finding three-dimensional structure model of
protein molecules from amino acid sequences



Predicts 3D structure of protein
based on comparative modeling



The Expert Protein
Analysis System powered by the Swiss Institute of Bioinformatics (SIB). The
Expasy tool also provides many supplementary tools to determine resemblance,
outline recognition, and studying post-translational modifications


Protein Data Bank

This is
another major resource of proteins containing information of
experimentally-determined structures of nucleic acids, proteins, and other
complex assemblies.



Drug Designing

       Discovery of drugs is a process by which
new drug molecules are discovered or designed to treat different diseases.
Before the arrival of bioinformatics tools, scientists used chemistry,
pharmacology and clinical and medical sciences to find out new compounds.
However, the conventional procedure is quite slow and costly as well.
Bioinformatics has greatly helped in this difficult process and is playing a
crucial role in advancing the process of drug discovery/designing.  In fact, a totally new and devoted field
known as Computer Aided Drug Design (CADD) has come into reality to discover
new drug molecules 19. The whole
process of discovering and designing new drug molecules is quite complex and
difficult. The whole process can be divided into four steps: recognition of
drug aim and validation of target 20.
In this section, we will briefly discuss how bioinformatics is useful in
discovering new drugs.

. A number of databases have been
developed to make easy the look for of new drug targets. Here are given some
bioinformatics tools to describe drug designing.





This tool provides the information present in protein database
related to the drug and their latest based version targets,thomton-srv/database/drugport/


This is a collection of drug like molecules along with their 2-D
structure, calculated and abstracted properties such as; logP, molecular
mass, binding constants, pharmaco-kinetics etc.


Conclusion and
Future Prospects

       Bioinformatics is a relatively new
discipline and is progressing very rapidly in the last few years. It has made
it promising to test our hypothesis practically and therefore allows to take a
better and an informed conclusion before initiation expensive experimentations.
Although, more and more tools for analyzing genomes, proteomes, predicting
structures, normal drug designing and molecular simulations are being
developed; none of them is ‘perfect’. Therefore, pursue for finding a better
method for solving the given problems will persist. One thing is clear that the
future research will be guided largely by the accessibility of databases, which
could be either generic or specific. It can also be assumed that developments in
the field of bioinformatics and bioinformatics tools and software packages
would be able to give results that are more correct and thus more trustworthy
interpretations. prediction in the field of bioinformatics include its future that
it will contribute to practical perceptive of the human genome, leading to better
discovery of drug targets and individualized treatment. Thus, bioinformatics
and other scientific disciplines have to be improved for the benefit of human


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