Download Introduction to Proteomics by Daniel Liebler
Proteins themselves are macromolecules: long chains of amino acids. This amino acid chain is constructed when the cellular machinery of the ribosome translates RNA transcripts from DNA in the cell’s nucleus. The transfer of information within cells commonly follows this path, from DNA to RNA to protein.
Proteins can be organized in four structural levels:
- Primary (1°): The amino acid sequence, containing members of a (usually) twenty-unit alphabet
- Secondary (2°): Local folding of the amino acid sequence into α helices and β sheets
- Tertiary (3°): 3D conformation of the entire amino acid sequence
- Quaternary (4°): Interaction between multiple small peptides or protein subunits to create a large unit
Each level of protein structure is essential to the finished molecule’s function. The primary sequence of the amino acid chain determines where secondary structures will form, as well as the overall shape of the final 3D conformation. The 3D conformation of each small peptide or subunit determines the final structure and function of a protein conglomerate.
There are many different subdivisions of proteomics, including:
Proteomics has both a physical laboratory component and a computational component. These two parts are often linked together; at times data derived from laboratory work can be fed directly into sequence and structure prediction algorithms. Mass spectrometry of multiple types is used most frequently for this purpose.
Daniel C. Liebler masterfully introduces the science of proteomics by spelling out the basics of how one analyzes proteins and proteomes, and just how these approaches are then employed to investigate their roles in living systems. He explains the key concepts of proteomics, how the analytical instrumentation works, what data mining and other software tools do, and how these tools can be integrated to study proteomes. Also discussed are how protein and peptide separation techniques are applied in proteomics, how mass spectrometry is used to identify proteins, and how data analysis software enables protein identification and the mapping of modifications. In addition, there are proteomic approaches for analyzing differential protein expression, characterizing proteomic diversity, and dissecting protein-protein interactions and networks
Originally published: 4 December 2001
Author: Daniel Liebler
Editor: Daniel Liebler
Size: 4 Mb
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