title: Data mining of supersecondary structure homology between light chains of immunogloblins and MHC molecules: absence of the common conformational fragment in the human IgM rheumatoid factor.
abstract: It is shown that fuzzy search and data mining techniques of supersecondary structure homology for subunits of proteins using conformational code patterns of α-helix-type (3β5α4β) and β-sheet-type (6α4β4β) fragments can be used to extract correlations between fragments of MHC class I molecules and the light chain of immunoglobulins. The new method of conformational pattern analysis with fuzzy search of structural code homology reflects well the shape of main chain rather than secondary structure in comparison with the DSSP method. Further, the data mining technique using the combination of h- and s-fragment patterns can quantify the supersecondary structure homology between any subunits of proteins with different amino acid sequences. Characteristic fragment patterns (string "shhshss"), which were sandwiched between two identical amino acid sequences His and Pro, were found in light chains of various types of immunogloblins, α-chain and β-2 microglobulin of MHC class I and α-chain and β-chain of MHC class II, but not in heavy chains of Fab immunoglobulin fragments and T cell receptors (TCR). Leukocyte immunoglobulin-like receptors (LILR) are related by the conformational fragment (string "shhshss") to β-2 microglobulins as a type of pair forms (string "sohsss"). Further, human IgM rheumatoid factor, one of the immunogloblins, did not strongly exhibit the conformational fragment pattern. Nonclassic MHC class I molecules CD1D, MIC-A, and MIC-B, which have functions to activate NKT, NK, and T cells, did not also clearly show the patterns. These code-driven mining techniques can be utilized as a metadata-generating tool for systems biology to elucidate the biological function of such conformational fragments of MHC I and II molecules, which come in contact with various signal ligands on the surface of T cells and natural killer cells.
authors: National Institute of Advanced Industrial Science and Technology (AIST) , AIST Tsukuba West, 16-1 Onogawa, Tsukuba, Ibaraki 305-8569, Japan.
authors: Hiroshi
authors: H
authors: Izumi
authors: Akihiro
authors: A
authors: Wakisaka
authors: Laurence A
authors: LA
authors: Nafie
authors: Rina K
authors: RK
authors: Dukor
mesh_terms: D000595:Amino Acid Sequence; D000818:Animals; D018360:Crystallography, X-Ray; D057225:Data Mining / Q000379:methods*; D017143:Fuzzy Logic; D006801:Humans; D007074:Immunoglobulin G / Q000737:chemistry; D007147:Immunoglobulin Light Chains / Q000737:chemistry; D007075:Immunoglobulin M / Q000737:chemistry*; D007136:Immunoglobulins / Q000737:chemistry*; D008285:Major Histocompatibility Complex; D051379:Mice; D008958:Models, Molecular; D010446:Peptide Fragments / Q000737:chemistry; D011487:Protein Conformation; D011948:Receptors, Antigen, T-Cell / Q000737:chemistry / Q000187:drug effects; D012217:Rheumatoid Factor / Q000737:chemistry*
chemical_list: D007074:Immunoglobulin G; D007147:Immunoglobulin Light Chains; D007075:Immunoglobulin M; D007136:Immunoglobulins; D010446:Peptide Fragments; D011948:Receptors, Antigen, T-Cell; D012217:Rheumatoid Factor