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Bioinformatics: Working Areas

After human genome project (in which human genome was sequenced), gene and protein sequencing work of human tribes and economically important plant, animal and microbes throughout the world was carried out in 100s and 1000s of laboratories. Understanding the importance of outcome of such sequencing work an urgent need was felt to develop tools (softwares and hardware) to better interpret these huge accumulated data. This led to origin of a term- Bioinformatics. Bioinformatics is the collection, storage and organization of information of biological interest (Biological data like- gene/genome sequences, protein sequences) so as to get useful information out of such databases, such as what protein the sequenced gene will code or what will be the 3D structure and function of the protein from the given amino acid sequence. Major working areas under bioinformatics are:

  • 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.

  • Pharmacogenomics: Using genomics technology to study the genetic differences in how people respond to medical treatment.

  • 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  

  • 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.

  • 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.

  • 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).

  • 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.  

  • 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.

  • Applications of Bioinformatics are –

  • Searching Evolutionary links: Searching Similarities And Diversities Among The Organisms within or among the species

  • Isolating Novel Genes for Gene Therapy: HIV resistant gene from Some African tribe, Cancer resistant gene from closely linked Primates

  • Drug Designing: Designing and Production of New, Desired Novel Drugs. It requires Three Steps

  • 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

  • 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)

  • Ligand modification: Ligand modified to a have Pharmacological and toxicological properties

  • Protein Engineering: It’s the design, Production, analysis and use of altered, non-natural proteins. It usually involves modifying natural protein through -

  • Site directed mutagenesis: It is deliberate point mutation created at desired site on DNA.

  • Chemical Synthesis of Desired DNA and Later on Its Translation: Successfully academically produced short peptides but to date no practical product launched.

  • Applications:

  • Broadening substrate specificity of Enzymes:  Protease (breaks protein) like Subtilisin is engineered for use in detergents

  • Improve enzyme stability - So that it can be used at harsh environment. Its done by increasing the no of disulfide bonds  

  • Improving Storage Protein nutritive quality: generally they lack certain essential amino acids

  • 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.

 

 

 

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