April 3, 2013
Structural genomics (SG) programs were formed by development of structure biology in large scale. Targets were selected from a speciﬁc genome, topologically similar types of proteins or protein families. (REF: Maksymilian) SG programs have developed more accurate and eﬃcient methodologies on structure determination over the last decade (REF: Maksymilian), where many are used for the determination of protein structures. The programs aim to describe 3-dimensional structure of every protein encoded by a given genome, as opposed to traditional structural prediction in focussing on only one particular protein. Structural genomics allows for a high-throughput method of structure determination by a combination of experimental and modelling approaches. (REF: National) Genomics can be divided into three branches: structural, comparative and functional genomics. There have been new discover models used for candidate genes that rely on functional and comparative genomics, where these models were advance through entrepreneurial companies such as Paradigm Genetics, Ceres, Crop Design and Mendel Biotechnology. (REF: Gutterson). This essay will focus on structural genomics, highlighting its strengths and challenges as well as its application on the following: protein structure determination, homology modelling, drug discovery, and brieﬂy on the agricultural biotechnology industry. Future prospects for structural genomics will also be discussed.
The understanding of many biological processes at molecular levels leads to the generation of enormous amounts of experimental data. The fact that the number of known protein sequences is growing rapidly results in a gap between genomic and structural information that eventually the tradition methods of structural biology would not be able to provide structure determination and understanding of their functions at a molecular level. SG programs, on the other hand, was created to aim to limit such disparities. Diﬀerent SG centres use diﬀerent methods for structure determination. The quality of X-ray structures solved by SG, on average, is reported to be better than that of structures determined by traditional structure biology. (REF: Bhattacharya) MOLPROBITY is a recent developed program that has made an impact on quality of structures. By using this program, the overall quality of structures in the Protein Database (PDB) has been improved signiﬁcantly. By making diﬀraction images publicly available, as done by some SG centres such as JCSG and CSGID can provide the opportunity to fully examine data quality. It also allows the data to be used for new developments on crystallographic protocols, and in training purposes. Also, Figure 1(Fig 4 p 592)(REF: Maksymilian) shows that SG delivers structures at a much faster rate than traditional structural biology. The cost of determining a single structure using SG programs is not much higher than the cost of the hardware to store raw data from all PDB structures (REF: Joachimiak), and this makes structural genomics more advantageous over the use of traditional structural biology. A signiﬁcant aspect that SG focuses on is the production of pure and soluble proteins. It was reported that SG programs have improved processes such as surface entropy reduction (REF: Derewenda), large-scale reductive methylation of lysine residues (REF: Kim), in situ proteolysis (REF: Dong + Wernimont), and nanolitre volume crystallisation (REF: Gerdts + Hazes + Li L). Technically, the fact that many technologies were available to allow development in terms of parallelisation, miniaturisation and automation made structural genomics possible. These technologies have been successful in implementing ways to determine protein structures eﬃciently. The contributions to improved technology for structural biology include: protein production, crystallisation,...