This document provides an introduction to the field of bioinformatics. It defines bioinformatics as a branch of science that uses computer technology to analyze and integrate biological information that can be applied to gene-based drug discoveries. It discusses the emergence of bioinformatics due to the desire to understand how genetic structure affects traits. It also outlines some common applications of bioinformatics like drug design, gene therapy, and microbial genomic analysis. Finally, it provides examples of some bioinformatics tools, databases, and centers in India.

1. INTRODUCTION TO BIOINFORMATICS
Department of Pharmaceutics, School of Pharmacy, Bharat Institute of Technology,
By-Pass road, Paratapur, Meerut
SUBMITTED TO- MS. NEHA GULATI SUBMITTED BY – PROMILA SHARAN
ASISTANT PROF. PHARMACEUTICS M.PHARMA 1 ST SEM

2. CONTENTS
 INTODUCTION TO BIOINFORMATICS.
 EMERGENCE OF BIOINFORMATICS .
 AIM OF BIOINFORMATICS.
 APPLICATION OF BIOINFORMATICS.
 TOOLS AND TECHNIQUES.
o IN DRUG DESIGN
o RATIONAL DRUG DELIVERY.
 BIOINFORMATICS CENTERS IN INDIA.
 DATABASE
o APPLICATIONS
o CLASSIFICATION

3. INTRODUCTION TO BIOINFORMATICS
It is a branch of science that deals with the study of biological information by using computer technology.
Computers are used to gather , store , analyze ,and integrate the biological information which can then be
applied to the gene based drugs discoveries and development.
Bioinformatics –
(Molecular) bio – informatics: bioinformatics is conceptualizing biology in
terms of molecules (in the sense of Physical chemistry) and applying “informatics
techniques” (derived from disciplines such as applied maths, computer
science and statistics) to understand and organize the information associated
with these molecules, on a large scale. In short, bioinformatics is a management
information system for molecular biology and has many practical applications.
As submitted to the Oxford English Dictionary.

4. The Emergence Of Bioinformatics.
Bioinformatics is a sub-field of the Biological Sciences
Bioinformatics is highly interdisciplinary and draws upon the following areas of study to solve biological
problems:
• Applied Mathematics
• Statistics
• Computer Science
• Also referred to as Computational Biology
The Emergence Of Bioinformatics
• With the discovery of DNA came a desire among biologists to understand how genetic structure affects the biological
traits of organisms
• Sequencing is not sufficient (95% of human genome is “junk” DNA)
• Genes must be identified and correlated with the functions of their corresponding proteins
• Biological phenomena must then be linked to protein identity, structure, and genomic origin
As a result, powerful new data management and analysis methods were developed
– These methods were precursors to current research in bioinformatics
– Recent progress in several sub-fields of biology is resulting in a boom in database size and complexity
– Consequently, there is a great need in many areas of biology for efficient database management and new computer-
based analytical techniques

5. GOAL:
To increasing the understanding of various biological techniques /processes like :
• Mapping of DNA
• Analyzing DNA
• To study /view / create 3D models of protein structures is being done.
• To organize data in a way that allows researchers to access existing information and to submit new
entries as they are produced, e.g. the Protein Data Bank for 3D macromolecular structures
APPPOACHES OF BOINFORMATICS.
STATIC DYANAMIC
Sequence Structure Interaction Reaction Multi agent Variable concentration
Data Fluxes based modeling of metabolite
• To develop tool sand resources that aid in the analysis of data. For example, having sequenced a
particular
protein, it is of interest to compare it with previously characterized sequences

6. APPLICATIONS OF BIOINFORMATICS
Bioinformatics is applicable in various fields including:
 More target drugs
 Personalized medicines
 Preventive medicines
 Gene therapy
Microbial genomic applications:
 Biotechnology
 Antibiotic resistance
 Forensic analysis of microbes
 Bio weapons creations
Agriculture :
 Crops management.
 Improvement in nutritional qualities

7.  Sequence analysis
 Genome annotation
 Computational evolutionary biology
 Analysis of gene expression
 Analysis of mutation in cancer
 Comparative genomics
 Modeling biological system Prediction of protein structures
 Drug design discovery
COMMONLY USED SOFTWARE TOOLS /TECHNIQUES ARE:
-In production and display of protein structure.
-Nucleic Acid Modeling Tool :Structure modification of single or double stranded DNA or RNA .
Identification of protein functions.
-Prediction of protein structures.
– Editing manipulation and analysis of Nucleic Acid and protein sequence .
- Analysis of protein structures.
- Structures and functions of genes and proteins.

8. Drug Design Software and Tools:
1.Sanjeevini
A complete drug design software.
2. Binding Affinity Prediction of Protein-Ligand Server(BAPPL)
Computes the binding free energy of a protein-ligand complex.
3. Binding Affinity Prediction of Protein-Ligand complex containing Zinc Server(BAPPL-Z)
Computes the binding free energy of a metalloprotein-ligand complex containing zinc.
4. Drug-DNA Interaction Energy (PreDDICTA) Calculates the Drug-DNA interaction energy.
5. ParDOCK - Automated Server for Rigid Docking Predicts the binding mode of the ligand in receptor
target site.
6. Active Site Prediction

9. How scientists can use bioinformatics to aid Rational Drug Discovery.

10. Sequence analysis:
DNA sequence of organisms are decoded & stored in databases. This sequence information is then analyzed to
determine that encoded protein. B.L.A.S.T. is used to search DNA sequence in the drugs.
Computational Evolutionary Biology:
Here the study of origin of species well as the changes they acquire over a large periods can be measured by
tracing the changes in their respective DNA rather studying there physical taxonomy or physiological changes.
Analysis of protein expression :
HTMS (High Through Mass Spectrometry) can provide a snapshot of the proteins present in biological samples
Peptool – used for identification of protein formations.
Analysis of Mutation in Cancer:
In cancer the genomes of affected cells are rearranged in complex ways , so various techniques are used to
identify unknown mutations in variety of genes in cancer-
 Oligonucleotides micro arrays – to identify the chromosomal gains & losses.
 Single nucleotides polymorphism arrays-- to detect mutations.
Image analysis :
Computational techniques are used for biomedical imagining is very important for both diagnostic & research:

11. BIOINFORMATICS CENTERS IN INDIA
1). Indian Institute of Technology, Hauz Khas, New Delhi.
2). Rice Genome Initiative Department of Plant Molecular Biology, South Campus B.J. Road, University of Delhi.
3). School of Biological Sciences, Madurai Kamraj University, Madurai.
4). Department of Physics, Indian Institute of Science Malleswaram, Bangalore.
5). National Institute of Immunology, Shahid Jeet Singh Marg JNU.
6). Institute of Microbial Technology, Sector 39A Chandigarh.
7). Department of Biotechnology, CGO Complex, Lodhi Road, New Delhi.
8). Bioinformatics Centre University of Pune, Ganeshkhind Pune.
9). Institute of Genomics & Integrative Biology, Delhi University Campus, Mall Road near Jubilee Hall Delhi.
10). National Brain Research Centre, Gurgaon, Haryana.
11). Centre for DNA Fingerprinting and Diagnostics, ECIL Road, Nacharam, Hyderabad.
12). JNU Bioinformatics Center, JNU New Mehrauli Road.

12. WHAT IS A DATABASE?
Data and databases are key to both bioinformatics and cheminformatics. Without large quantities of easily
accessible electronic data, most kinds of data searches would prove to be fruitless , and most kinds of
predictive or analytical software could never be developed or tested.
Application of Data Base Management in Pharmacy
24x7 best efforts support & basic database maintenance and patching
Perform daily export backup & operational monitoring
Setup a database account
Setup database& setup monitoring
Single instance database (Oracle, SQL, Mysql)
User does schema, tables, views and procedures
User has full responsibility to run the database
Assist with minor Data Migrations / Updates
Assist with releases twice per quarter
Assist with testing of scripts
Migration from test to production

13. Major freely
available
Public Domain
databases & data
Bioinformatics
mining tools
Facilities
National enter Of
Biotechnology European Genome NET
information Bioinformatics (KEGG & DDBI)
(NCBI)United Institutes (EBI) Japan
states
Database Analysis tools
BLASTA-sequence Recognition tools for Sequence alignment
searching sequence & structures tools

14. CONCLUSION
Bioinformatics have stretched its wings over the end less boundaries of
spectacular success , world wide recognition and remote communication at
every nook and corner in this world. There are certain sectors where
biotechnology is playing its vital role which we have previously discussed.
The advancements in the field of Bioinformatics are leading to more
focused area of study at Systems level. Taking note of this trend the center
has renamed it as “Centre for Computational Biology and Bioinformatics
(CCBB)”. The main objective should be of human resource development
activities and research in frontier areas of computational biology has taken a
shape and recognition within the country. We are also making back breaking
effort in inter–institutional collaboration in research projects. To keep
rhythm with the development in the field, importance is given to set up the
necessary infrastructure and resources for the academic community.

15. REFERENCE:
• N. M. Luscombe, D. Greenbaum, M. Gerstein,Department of Molecular Biophysics
and Biochemistry Yale University, New Haven, USA.
• Supercomputing Facility for Bioinformatics & Computational Biology, IIT Delhi.
• http://www.soe.ucsc.edu/programs/bioinformatics/graduate/.
• Kok K, Naylor SL, Buys CH. Deletions of the short arm of chromosome 3 in solid
tumors and the search for suppressor genes.Advances in Cancer Research 1997; 71:
27-92.
• Syngal S, et al. Sensitivity and specificity of clinical criteria for hereditary non-
polyposis colorectal cancer associated mutations in MSH2 and MLH1. Journal Med
Genet 2000; 37 (9): 641-5.