Improvement of domain linker prediction by incorporating loop-length-dependent characteristics

Protein dissection into structural domains that can fold in isolation is an important issue in both functional and structural proteomics. Here, we analyzed inter- and intradomain loop sequences (respectively named domain linker and nonlinker loops) and computed a domain linker likelihood score, which was used for developing a domain boundary prediction protocol. The analysis confirmed our previous results indicating that the amino acid composition in terms of glycine, proline, aspartic acid, asparagine, lysine, and histidine significantly differs between linker and nonlinker loops. However, a detailed examination revealed that the amino acid composition bias actually depends on the loop length. Indeed, significant frequency deviations were observed for glycine, proline, and aspartic acid in short linker and nonlinker loops, whereas deviations were observed for aspartic acid, proline, asparagine, and lysine in long linker and nonlinker loops. Finally, we incorporated this loop-length-dependent amino acid composition bias in a simple linker prediction protocol, which predicted linkers with a 40.6% specificity and a 36.1% sensitivity. These figures are 4.4 and 2.4% higher than those obtained with our former prediction protocol that does not incorporate loop-length-dependent characteristics. This result should have practical significance for experimental protein dissection, since the probability of obtaining a stably folding structural domain by randomly dissecting a protein sequence is estimated to be 12.6%.