Structural genomics
Structural genomics is a field of genomics that involves the characterization of genome structures. This is in contrast to functional genomics, which is concerned with characterizing gene functions and interactions. The primary goal of structural genomics is to build a 3D model of every protein encoded by a given genome. This field of study has been greatly facilitated by the development of high-throughput methods for protein structure determination.
Overview[edit | edit source]
Structural genomics seeks to describe the 3D structure of every protein encoded by a given genome. This genome-based approach allows for a high-throughput method of structure determination by a combination of experimental and modeling approaches. The principal difference between structural genomics and traditional structural prediction is that structural genomics attempts to determine the structure of every protein encoded by the genome, rather than focusing on one particular protein.
With full-genome sequences available, it is now possible to apply the techniques of structural genomics to understand the function and interaction of proteins on a genome-wide scale. Structural genomics involves taking a large number of approaches to structure determination, including experimental methods using genomic sequences or modeling-based approaches based on sequence or structural homology to a protein of known structure or based on chemical and physical principles for a protein with no homology to any known structure.
Techniques[edit | edit source]
Structural genomics involves a number of techniques, with the main ones being X-ray crystallography and NMR spectroscopy. Cryo-electron microscopy is also emerging as a popular technique for structure determination. These techniques are used in a high-throughput fashion to solve many structures quickly.
Applications[edit | edit source]
The knowledge gained from structural genomics can be applied in a number of ways. It can be used to predict the structure of many unknown proteins, to identify novel protein folds and to explore the protein function space. It can also be used to understand the evolution of proteins and to design new proteins with desired functions.
See also[edit | edit source]
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