Application General

8/8/2019 Application General

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Ravi Kapopara

Application of Bioinformatics in

various fields


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y General Application

y Application in Drug Discovery


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Molecular medicine

y The completion of the human genome means that we can

search for the genes directly associated with different

diseases and begin to understand the molecular basis of

these diseases more clearly.

y This new knowledge of the molecular mechanisms of

disease will enable better treatments, cures and even

preventative tests to be developed.


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Personalized medicine

y Today, doctors have to use trial and error to find the best

drug to treat a particular patient as those with the same

clinical symptoms can show a wide range of responses to the

same treatment.

y In the future, doctors will be able to analyse a patient's

genetic profile and prescribe the best available drug therapy

and dosage from the beginning.


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Preventative medicine

y With the specific details of the genetic mechanisms of

diseases being unravelled, the development of diagnostic tests

to measure a persons susceptibility to different diseases may

become a distinct reality.

y Preventative actions such as change of lifestyle or having

treatment at the earliest possible stages when they are more

likely to be successful, could result in huge advances in our

struggle to conquer disease.


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Gene therapy

y In the not too distant future, the potential for using genes

themselves to treat disease may become a reality.

y Gene therapy is the approach used to treat, cure or even

prevent disease by changing the expression of persons genes.y Currently, this field is in its infantile stage with clinical trials

for many different types of cancer and other diseases ongoing.


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Drug development

y At present all drugs on the market target only about 500

proteins.

y With an improved understanding of disease mechanisms and

using computational tools to identify and validate new drugtargets, more specific medicines that act on the cause, not

merely the symptoms, of the disease can be developed.

y These highly specific drugs promise to have fewer side effects

than many of today's medicines.


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Microbial genome applications

y By studying the genetic material of these organisms, scientists

can begin to understand these microbes at a very

fundamental level and isolate the genes that give them their

unique abilities to survive under extreme conditions.


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General Application

y Climate change Studies

y Alternative energy sources

y Biotechnology

y Antibiotic resistancey Forensic analysis of microbes

y Evolutionary studies

y Crop improvement

y Insect resistance


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y Improve nutritional quality

y Vetinary Science

y Comparative Studies


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APPLICATIONSOF BIOINFORMATICSINDRUG

DISCOVERY


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BioinformaticsTools

The processes of designing a new drug using bioinformatics tools have open a

new area of research. However, computational techniques assist one in

searching drug target and in designing drug in silco, but it takes long

time and money. In order to design a new drug one need to follow the

following path.

Identify target disease

Study Interesting Compounds

Detection the Molecular Bases for Disease

Rational Drug Design Techniques

Refinement of Compounds

Quantitative StructureActivity Relationships (QSAR)

Solubility of Molecule

Drug Testing


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Genomics

Database Description

GOLD (http://wit.integratedgenomics.com/GOLD/) Genomes online database, provides large and detailed

monitoring of genome sequencing project. According to it

there are about 110 completely sequenced genomes.

TIGR microbial Database(http://www.tigr.org/tdb/mdb/mdbcomplete.html)

Listing of published microbial genomes and chromosomesand those in progress.

EBI complete Genomes (http://www.ebi.ac.uk/genomes/) Gives the data on completed Genomes

NCBI Genomic Biology

(http://www.ncbi.nlm.nih.gov/Genomes/)

Keeps a wide range of data on genomes

National Human Genome Research Institute

(http://www.genome.gov)

Home of an international research effort to determine the

DNA sequence of entire Genome. Contributes to the

Human Genome Project include the National Institute of

Health (NIH).


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Bioinformatics tools for Genomics

analysis

y SLAM : Gene finding, alignment, annotation (human-mouse

homology identification)

y ACT (Artemis Comparison Tool) : comparative genomics

yGene Finder (Tool for finding out the gene from protein ornucleotide sequences)


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Proteomics

Systematic analysis of protein profiles of tissues

Bigger field than genomics.


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Types of Proteomics

y Structural Proteomics

y Functional Proteomics

y Cell map proteomics

y

Expression Proteomics


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y Structural Proteomics

y Goals to map out the 3-D structures of proteins and protein

complexes

y Provides Structural framework for understanding execution of

proteins function

y Different protein = different structure domains + different

function

y RasMol (A tool for Protein 3D structure prediction)


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y Functional Proteomics

y To find out the role of protein in cellular process

y Depending on their cellular location , cell types where they

are expressed , multimeric state and bound substartey Arraying functional proteins on a chip is the technique to find

out its function


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y Cell map proteomics

y Determination of subcellular location of proteins and PPI

(Protein -Protein Interaction) by purification of protein

complexes followed by MS (Mass Spectrometric)

identification.

y Yeast two-hybrid method is used to find PPI

y GRAMM is online server to find out PPI


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y Expression Proteomics

y Creation of quantitative maps of expressed proteins from cell

or tissue extracts

y

Protein Separation by 2-D Gel Electrophoresisy Identify by MS


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Function of Proteomics

Uses information determined by biochemical/crystal structure

methods

Visualization of protein structure (RasMol)

Make protein-protein comparisons (GRAMM)

Used to determine:

y conformation/folding

y antibody binding sites

y protein-protein interactions

y computer aided drug design


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Bioinformatics tools for Proteomics

analysis

y PepMAPPER, PeptideSearch = PMF tool

y ProFound =A tool for searching a protein sequence database

using information from mass spectra of peptide maps

y PAWS =A tool for analysis of protein sequence and posttranslation modification

y ExPasy is the main database which contain so many tools for

protein identification and charecterization


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Computer-Aided Drug Design (CADD)

y Computer-Aided Drug Design (CADD) is a specialized discipline

that uses computational methods to simulate drug-receptor

interactions.

y CADD methods are heavily dependent on bioinformatics tools,

applications and databases.As such, there is considerable overlap

in CADD research and bioinformatics.


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Bioinformatics Supports CADD

Researchy Virtual High-Throughput Screening (vHTS):-

1. Pharmaceutical companies are always searching for new leads todevelop into drug compounds.

2. One search method is virtual high-throughput screening. In vHTS,protein targets are screened against databases of small-moleculecompounds to see which molecules bind strongly to the target.


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Bioinformatics Supports CADD Research

y Virtual High-Throughput Screening (vHTS):-

3. If there is a hit with a particular compound, it can be extracted fromthe database for further testing.

4.With todays computational resources, several million compounds canbe screened in a few days on sufficiently large clustered computers.

5. Pursuing a handful of promising leads for further development cansave researchers considerable time and expense.

e.g.. ZINC is a good example of a vHTS compound library.


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Bioinformatics Supports CADD Researchy Sequence Analysis:-

1. In CADD research, one often knows the genetic sequence of multipleorganisms or the amino acid sequence of proteins from several species.

2. It is very useful to determine how similar or dissimilar the organismsare based on gene or protein sequences.

3.With this information one can infer the evolutionary relationships of the

organisms, search for similar sequences in bioinformatic databases andfind related species to those under investigation.

4. There are many bioinformatic sequence analysis tools that can be used

to determine the level of sequence similarity.


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Bioinformatics Supports CADD Researchy Homology Modeling:-

1.Another common challenge in CADD research is determining the 3-Dstructure of proteins.

2. Most drug targets are proteins, so its important to know their 3-D structurein detail. Its estimated that the human body has 500,000 to 1 millionproteins.

3. However, the 3-D structure is known for only a small fraction of these.Homology modeling is one method used to predict 3-D structure.


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Bioinformatics Supports CADD Researchy Homology Modeling:-

4. In homology modeling, the amino acid sequence of a specific protein(target) is known, and the 3-D structures of proteins related to the

target (templates) are known.

5. Bioinformatics software tools are then used to predict the 3-Dstructure of the target based on the known 3-D structures of thetemplates.

6. MODELLER is a well-known tool in homology modeling, and theSWISS-MODEL Repository is a database of protein structures createdwith homology modeling.


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Bioinformatics Supports CADD Researchy Similarity Searches:-

1. A common activity in biopharmaceutical companies is the search fordrug analogues.

2. Starting with a promising drug molecule, one can search for chemicalcompounds with similar structure or properties to a knowncompound.

3. There are a variety of methods used in these searches, includingsequence similarity, 2D and 3D shape similarity, substructuresimilarity, electrostatic similarity and others.

4. A variety of bioinformatic tools and search engines are available for thiswork


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y Drug Lead Optimization:-

1.When a promising lead candidate has been found in a drugdiscovery program, the next step (a very long and expensive step!)

is to optimize the structure and properties of the potential drug.

2. This usually involves a series of modifications to the primarystructure (scaffold) and secondary structure (moieties) of thecompound.


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y Drug Lead Optimization:-

3. This process can be enhanced using software tools thatexplore related compounds (bioisosteres) to the leadcandidate. OpenEyesWABE is one such tool.

4. Lead optimization tools such asWABE offer a rationalapproach to drug design that can reduce the time andexpense of searching for related compounds.


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y Physicochemical Modeling:-

1. Drug-receptor interactions occur on atomic scales.

2. To form a deep understanding of how and why drugcompounds bind to protein targets, we must consider

the biochemical and biophysical properties of both the

drug itself and its target at an atomic level.

3. Swiss-PDB is an excellent tool for doing this. Swiss-PDBcan predict key physicochemical properties, such as

hydrophobicity and polarity that have a profound

influence on how drugs bind to proteins.


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Bioinformatics Supports CADD Researchy Drug Bioavailability and Bioactivity:-

1. Most drug candidates fail in Phase III clinical trials after many years ofresearch and millions of dollars have been spent on them.And mostfail because of toxicity or problems with metabolism.

2. The key characteristics for drugs areAbsorption, Distribution,Metabolism, Excretion, Toxicity (ADMET) and efficacyin otherwords bioavailability and bioactivity.

3.Although these properties are usually measured in the lab, they canalso be predicted in advance with bioinformatics software.


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Benefits of CADD

y Cost Savings:-

1. The Tufts Report suggests that the cost of drug discoveryand development has reached $800 million for each drug

successfully brought to market.

2. Many biopharmaceutical companies now usecomputational methods and bioinformatics tools to

reduce this cost burden.


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Benefits of CADD

y Cost Savings:-

3. Virtual screening, lead optimization and predictions of

bioavailability and bioactivity can help guide experimentalresearch.

4. 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.


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Benefits of CADD

Time-to-Market:-

1. The predictive power of CADD can help drug research

programs choose only the most promising drugcandidates.

2. By focusing drug research on specific lead candidates

and avoiding potential dead-end compounds,biopharmaceutical companies can get drugs to marketmore quickly.


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Benefits of CADD

y Insight:-

1. One of the non-quantifiable benefits of CADD and theuse of bioinformatics tools is the deep insight that

researchers acquire about drug-receptor interactions.

2. Molecular models of drug compounds can revealintricate, atomic scale binding properties that are

difficult to envision in any other way.


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Benefits of CADD

y Insight:-

1.When we show researchers new molecular models of their

putative drug compounds, their protein targets and how thetwo bind together, they often come up with new ideas onhow to modify the drug compounds for improved fit.

2. This is an intangible benefit that can help design researchprograms.


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CADD

y CADD and bioinformatics together are a powerfulcombination in drug research and development.

y An important challenge for us going forward is finding

skilled, experienced people to manage all the bioinformaticstools available to us, which will be a topic for a future article.


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Research Achievements

y Software developed

y Bioinformatics data base developed


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Software developed

1. SVMProt: Protein function prediction software

http://jing.cz3.nus.edu.sg/cgi-bin/svmprot.cgi

2. INVDOCK: Drug target prediction software

3. MoViES: Molecular vibrations evaluation server

http://ang.cz3.nus.edu.sg/cgi-bin/prog/norm.pl


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Bioinformatics database developed

1. Therapeutic target database

http://xin.cz3.nus.edu.sg/group/cjttd/ttd.asp

2. Drug adverse reaction target database

http://xin.cz3.nus.edu.sg/group/drt/dart.asp3. DrugADME associated protein database

http://xin.cz3.nus.edu.sg/group/admeap/admeap.asp

4. Kinetic data of biomolecular interactions database

http://xin.cz3.nus.edu.sg/group/kdbi.asp5. Computed ligand binding energy database

http://xin.cz3.nus.edu.sg/group/CLiBE/CLiBE.asp


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Documents

Application General