Title |
Structural and functional studies of S-adenosyl-L-methionine binding proteins: a ligand-centric approach
|
---|---|
Published in |
BMC Molecular and Cell Biology, April 2013
|
DOI | 10.1186/1472-6807-13-6 |
Pubmed ID | |
Authors |
Rajaram Gana, Shruti Rao, Hongzhan Huang, Cathy Wu, Sona Vasudevan |
Abstract |
The post-genomic era poses several challenges. The biggest is the identification of biochemical function for protein sequences and structures resulting from genomic initiatives. Most sequences lack a characterized function and are annotated as hypothetical or uncharacterized. While homology-based methods are useful, and work well for sequences with sequence identities above 50%, they fail for sequences in the twilight zone (<30%) of sequence identity. For cases where sequence methods fail, structural approaches are often used, based on the premise that structure preserves function for longer evolutionary time-frames than sequence alone. It is now clear that no single method can be used successfully for functional inference. Given the growing need for functional assignments, we describe here a systematic new approach, designated ligand-centric, which is primarily based on analysis of ligand-bound/unbound structures in the PDB. Results of applying our approach to S-adenosyl-L-methionine (SAM) binding proteins are presented. |
X Demographics
Geographical breakdown
Country | Count | As % |
---|---|---|
United States | 1 | 50% |
Unknown | 1 | 50% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Practitioners (doctors, other healthcare professionals) | 1 | 50% |
Scientists | 1 | 50% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
---|---|---|
Unknown | 73 | 100% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Student > Ph. D. Student | 20 | 27% |
Researcher | 10 | 14% |
Student > Master | 9 | 12% |
Student > Bachelor | 7 | 10% |
Student > Doctoral Student | 4 | 5% |
Other | 7 | 10% |
Unknown | 16 | 22% |
Readers by discipline | Count | As % |
---|---|---|
Biochemistry, Genetics and Molecular Biology | 17 | 23% |
Agricultural and Biological Sciences | 16 | 22% |
Chemistry | 11 | 15% |
Computer Science | 3 | 4% |
Medicine and Dentistry | 2 | 3% |
Other | 6 | 8% |
Unknown | 18 | 25% |