Word Decoding of Protein Amino Acid Sequences with Availability Analysis: A Linguistic Approach

The amino acid sequences of proteins determine their three-dimensional structures and functions. However, how sequence information is related to structures and functions is still enigmatic. In this study, we show that at least a part of the sequence information can be extracted by treating amino acid sequences of proteins as a collection of English words, based on a working hypothesis that amino acid sequences of proteins are composed of short constituent amino acid sequences (SCSs) or “words”. We first confirmed that the English language highly likely follows Zipf''s law, a special case of power law. We found that the rank-frequency plot of SCSs in proteins exhibits a similar distribution when low-rank tails are excluded. In comparison with natural English and “compressed” English without spaces between words, amino acid sequences of proteins show larger linear ranges and smaller exponents with heavier low-rank tails, demonstrating that the SCS distribution in proteins is largely scale-free. A distribution pattern of SCSs in proteins is similar among species, but species-specific features are also present. Based on the availability scores of SCSs, we found that sequence motifs are enriched in high-availability sites (i.e., “key words”) and vice versa. In fact, the highest availability peak within a given protein sequence often directly corresponds to a sequence motif. The amino acid composition of high-availability sites within motifs is different from that of entire motifs and all protein sequences, suggesting the possible functional importance of specific SCSs and their compositional amino acids within motifs. We anticipate that our availability-based word decoding approach is complementary to sequence alignment approaches in predicting functionally important sites of unknown proteins from their amino acid sequences.     

Discoidin Domain Receptors Promote α1β1- and α2β1-Integrin Mediated Cell Adhesion to Collagen by Enhancing Integrin Activation

The discoidin domain receptors, DDR1 and DDR2, are receptor tyrosine kinases that bind to and are activated by collagens. Similar to collagen-binding β1 integrins, the DDRs bind to specific motifs within the collagen triple helix. However, these two types of collagen receptors recognize distinct collagen sequences. While GVMGFO (O is hydroxyproline) functions as a major DDR binding motif in fibrillar collagens, integrins bind to sequences containing Gxx’GEx”. The DDRs are thought to regulate cell adhesion, but their roles have hitherto only been studied indirectly. In this study we used synthetic triple-helical collagen-derived peptides that incorporate either the DDR-selective GVMGFO motif or integrin-selective motifs, such as GxOGER and GLOGEN, in order to selectively target either type of receptor and resolve their contributions to cell adhesion. Our data using HEK293 cells show that while cell adhesion to collagen I was completely inhibited by anti-integrin blocking antibodies, the DDRs could mediate cell attachment to the GVMGFO motif in an integrin-independent manner. Cell binding to GVMGFO was independent of DDR receptor signalling and occurred with limited cell spreading, indicating that the DDRs do not mediate firm adhesion. However, blocking the interaction of DDR-expressing cells with collagen I via the GVMGFO site diminished cell adhesion, suggesting that the DDRs positively modulate integrin-mediated cell adhesion. Indeed, overexpression of the DDRs or activation of the DDRs by the GVMGFO ligand promoted α1β1 and α2β1 integrin-mediated cell adhesion to medium- and low-affinity integrin ligands without regulating the cell surface expression levels of α1β1 or α2β1. Our data thus demonstrate an adhesion-promoting role of the DDRs, whereby overexpression and/or activation of the DDRs leads to enhanced integrin-mediated cell adhesion as a result of higher integrin activation state.