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-- ThorChristianHobaek - 09 Sep 2009

Homework assignment 1

Table of Contents

1 Biographical text

Please see my home page for information about me.

2 Links added using plugins

The following link to the Wikipedia page about the Polio vaccine has been auto-added to this site using the Interwiki Plugin: Wikipedia:Polio_vaccine

Another link was added using the E Fetch Plugin:

3 Interesting Pubmed paper about the polio virus

This interesting article has some recorded findings that central nervous system (CNS) injury related to the polio virus is caused by apoptosis.

4 Relation between computational and synthetic biology

4.1 Computer models of cellular process networks

Computational biology is relevant for synthetic biology because it can be used to develop algorithms and computer simulations to build knowledge about connections between cellular processes. For example, computational models can be used to predict metabolism, gene regulatory networks and signal transduction pathways, which gives the synthetic biologist a lot of useful information prior to fabrication.

4.2 Protein structure prediction

Computational models are used to predict the three-dimensional protein structure from its amino acid sequence. One of these methods is the de novo or ab into methods, which uses physical principles (for example using a suitable energy function and finding its global minimum configuration) instead of referring to already known structures. Tertiary protein structures are important for synthesizing enzymes or drugs.

5 Differences between viruses and transposons

Viruses Transposons
Has the ability to survive outside the cell because of the gag gene Lacks the gag gene, so it only stays inside it hosts cell
Can penetrate the cell membrane because of the env gene and therefore infect other cells or organisms Lacks the env gene and therefore cannot spread beyond it's host cell
Have a protein coat to protect the viral gene The gene moves around in the cell without any protection
Viral gene consists of either DNA or RNA The transposon is a DNA sequence

The ability of a virus to intrude a cell and transfer and incorporate DNA sequences into a cell's genome, can be used for treatment of disease. By extracting an existing viral gene from the protein coat and replacing it by a desired gene, this gene can be incorporated into the cell by using the virus as a way for cellular entrance. The desired gene can then replace the mutant gene in the chromosomes and thereby treat the disease. The method is called gene therapy.

Transposon can be inserted into a host chromosome to induce a mutation, called mutagenesis.

A possible physical limitation of gene therapy may be the size of the modified viral RNA or DNA. The size of the gene and the encapsulating protein cap must be low enough to allow cellular entrance.

6 Bioinformatic tools

6.1 Protein structure prediction tools

  Ab initio protein structure prediction Comparative protein structure modeling
Description Estimates the tertiary protein structure from only the amino acid sequence. The technique is based on energetic principles that governs protein folding Use a set of tertiary structure motif as templates for solving the protein structure, thereby basing itself on previously solved structures or threading
Examples Rosetta@home, ROBETTA, Abalone, Bhageerath, CABS, Selvita Protein Modeling Platform WHAT IF, TIP-STRUCTFAST, SWISS-MODEL, ROBETTA, EasyModeller, MODELLER, LIBRA I, HHpred, Geno3D, GeneSilico, ESyPred3D, CPHModel, CABS, Biskit, 3D-JIGSAW
Accuracy 5 A root mean square deviation (RMSD) of ~1
Run-time Slow Fast
Memory usage Vast Low

6.2 Gene function tools

  Controlled vocabularies for gene/enzyme function Biochemical pathway databases
Description Gene ontology and EC numbers. Gene ontology is a formal representation of concepts and terms related to genetic properties. EC numbers specify a enzyme-catalyzed reaction. Each EC number is associated with a recommended name of the involved enzymes. Databases of networks of biochemical pathways in cells down to molecular interactions.
Examples AmiGo, Obo-Edit, ENZYME and BRENDA KEGG, GeneDB, EcoCyc, BioCyc and MetaCyc

6.3 Structure analysis tools

  Protein/protein docking software Protein/small-molecule docking software
Description Predicts whether two or more selected proteins will bind, what kind of spatial conformation the complex will have and how strong the binding between proteins are. Based on purely physical principles. Predicts the position and orientation of a small molecule, ligand, when it binds to a protein (enzyme or receptor).
Application Make it easier to design proteins to perform designated biological functions by knowing how it interacts. Can also be used to help understand why misfolded protein complexes cause genetic disease. Can help pharmaceutical researchers to find suitable drug candidates by making it possible to search through a database of target proteins.
Examples RosettaDock and AutoDock EADock, Autodock and Molecular Docking Server
Memory usage Huge Huge, but less than protein/protein docking software

6.4 Sequence analysis tools

  Sequence assembly software Gene-finding software
Description Align and merges short fragments of a longer DNA sequence to reconstruct the original sequence. Identifies fragments of genomic DNA that are biologically important. The extrinsic approach and the ab initio approach are the two main methods. Extrinsic approach uses known mRNA or protein sequences and searches the genome for similar sequences. If a genome has a high degree of similarity of the known mRNA, it is a strong evidence that this region is a protein-coding gene. In ab initio approach a target genome is searched for protein-coded sequences without any knowledge about the mRNA structure. It is therefore a predictive tool.
Examples ABySS, AMOS, Arachne WGA, CAP3, PCAP Ensembl, RefSeq, BLAST, GLIMMER, GeneMark, GENSCAN

6.5 RNA-structure tools

  RNA folding software RNA design software
Description Predicts the tertiary RNA structure from a known nucleic acid sequence, by first predicting the secondary structure, the base pairing within the RNA. Use RNA folding predictions to characterize RNA structures by their function, thus making it possible to design RNA molecules for therapeutic treatments.
Examples CentroidFold, CONTRAfold, KineFold, Mfold, Pknots, PknotsRG, RNAfold, RNAshapes, RNAstructure, Sfold, UNAFold RNAsoft, Sfold
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