An iterative approach to class II predictions.
An iterative approach to resolving protein-peptide binding motifs is appropriate when the length of the binding protein is variable and a variety of amino acid residues may successfully occupy multiple positions. This chapter describes an iterative algorithm that first aligns binding peptides of variable lengths and then extracts a quantitative motif from the resulting alignment. Numerous examples are presented to illustrate the utility of the iterative process.
Mallios
Ronna Reuben
RR
Grants and Research Office, Fresno, CA, USA.
D000465:Algorithms; D020816:Amino Acid Motifs; D000595:Amino Acid Sequence; D019295:Computational Biology; D003198:Computer Simulation; D030562:Databases, Protein; D015798:HLA-DR1 Antigen / Q000737:chemistry / Q000378:metabolism; D000949:Histocompatibility Antigens Class II / Q000737:chemistry* / Q000378:metabolism*; D006801:Humans; D007125:Immunogenetics; D008958:Models, Molecular; D010455:Peptides / Q000737:chemistry / Q000276:immunology / Q000378:metabolism; D011485:Protein Binding
D015798:HLA-DR1 Antigen; D000949:Histocompatibility Antigens Class II; D010455:Peptides