Genome wide recognition of tumor necrosis factor (TNF) like ligands in human and Arabidopsis genomes: a structural genomics approach

Tumor necrosis factors (TNFs) play a crucial role in mammalian signal transduction pathways for cell proliferation, survival, and differentiation. Genome sequencing projects provide a unique opportunity for genome-wide recognition of TNF-related ligand proteins. Genome-wide screening for TNF-related proteins in human and Arabidopsis was carried out using protein fold recognition scheme. In the protein-structure threading scheme, sequence-structure models are evaluated using contact energy score based on Miyazawa-Jernigan and Li-Tang-Wingreen models. Prescreening potential TNF structures on the basis of secondary structure composition reduces the search space and shifts the score distribution of the selected candidates to a higher score region. To investigate the influence of sequence length on threading results, protein fold recognition was conducted on human and Arabidopsis complete protein sequences of different lengths. The test on known TNFs from diverse species indicates that about 83% of TNFs can be identified; the test on human genome sequences shows that about 80% of known TNFs can be recognized. Integration of secondary structure profiling into the scheme improves performance by adjusting local sequence-structure relationship. However, this improvement largely depends on the accuracy of the secondary-structure prediction. Average scoring performs better than maximal scoring in model evaluation and selection. This genome-wide search scheme was also used to search potential TNF-like signal proteins in Arabidopsis genome. Possible candidates in human and Arabidopsis genomes are discussed. These results demonstrate that structure based methods can contribute to functional prediction on a genome-wide scale