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Genomics:
Studying Genome
(total DNA sequence of an Organism). Commonly used gene finding
programmes from the sequenced DNA are GRAIL, GeneID, GeneParser,
GeneLang, FGELEH, Genie, and EcoPhrase are neural nets and other AI
or statistical method.
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Pharmacogenomics:
Using genomics
technology to study the genetic differences in how people respond to
medical treatment.
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Phamacokinetics:
It’s related to
pharmacogenomics, which is the study of known genes that are
responsible for variations in drug metabolism. Thus medicine in
general will become much more specific to the individual
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Proteomics:
High throughput
analysis of all the proteins in cell, tissue or organism. Proteins
are separated through 2Dgel electrophoresis, and sequence determined
using peptide fingerprinting that is – the separated protein is
digested into short peptides using protease: the pattern of sizes of
the peptides is characteristics of the protein, then you can search
all the proteins in the genomic database and work out which protein
they must have come forth, without having to do any protein
sequencing.
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Cheminformatics:
It is the fusion of IT with Chemistry. During chemical research lots
of new compounds are synthesized and a huge information and data is
generated. Cheminformatics deals with the collection, storage,
organization and application of this vast chemical information in a
systematic manner, which is frequently used in drug discovery.
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Cheminformatics and Drug Discovery:
Since a large number of molecules have to be processed for drug
synthesis; the methods used must be very fast. To speed up the drug
discovery two techniques of Cheminformatics commonly used
Combinatorial Chemistry and High Throughput Screening (HTS).
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Combinatorial Chemistry (Combichem):
It’s the production of a
collection of variants on a known chemical in parallel: such related
variants that are all members of a chemical family are called
congeners.
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High Throughput Screening:
A
method of drug discovery where a molecule (drug) (that can react
with a target molecule) is searched out from a large chemical
libraries (chemi-informatics.
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Applications of Bioinformatics
are –
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Searching Evolutionary links:
Searching
Similarities And Diversities Among The Organisms within or among the
species
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Isolating Novel Genes for Gene Therapy:
HIV resistant gene
from Some African tribe, Cancer resistant gene from closely linked
Primates
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Drug Designing:
Designing and Production of New, Desired Novel Drugs. It requires
Three Steps –
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Acquire knowledge about the 3D structure of the
target site:
It
is done upto the level of atomic resolution. This is done through
NMR (Nuclear Magnetic Resonance) and X-Ray diffraction patterns
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Designing of Ligand:
Design a ligand
(molecule) that is complementary to and will fit the binding site,
using computer graphics and computer simulation (Virtual reality
simulations)
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Ligand modification:
Ligand modified to
a have Pharmacological and toxicological properties
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Protein Engineering:
It’s the design,
Production, analysis and use of altered, non-natural proteins. It
usually involves modifying natural protein through -
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Site directed mutagenesis: It is deliberate
point mutation created at desired site on DNA.
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Chemical Synthesis of Desired DNA and Later on Its
Translation:
Successfully academically produced short peptides but
to date no practical product launched.
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Applications:
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Broadening substrate specificity of Enzymes:
Protease
(breaks protein)
like Subtilisin is engineered for use in detergents
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Improve enzyme stability - So that it can be
used at harsh environment. Its done by increasing the no of
disulfide bonds
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Improving Storage Protein nutritive quality:
generally they lack certain essential amino acids
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Altering Pharmacological action like affecting
Protein drug delivery:
like- Therapeutic insulin tends to form multi-molecule
complexes thus slowing its absorption rate in the cells, but
Replacing Proline 28 in B chain of insulin by aspartate stops
insulin aggregation allowing its rapid absorption.
