title: Identification of non-random sequence properties in groups of signature peptides obtained in random sequence peptide microarray experiments.
abstract: Immunosignaturing is an emerging experimental technique that uses random sequence peptide microarrays to detect antibodies produced by the immune system in response to a particular disease. Two important questions regarding immunosignaturing are "Do microarray peptides that exhibit a strong affinity to a given type of antibodies share common sequence properties?" and "If so, what are those properties?" In this work, three statistical tests designed to detect non-random patterns in the amino acid makeup of a group of microarray peptides are presented. One test detects patterns of significantly biased amino acid usage, whereas the other two detect patterns of significant bias in the biochemical properties. These tests do not require a large number of peptides per group. The tests were applied to analyze 19 groups of peptides identified in immunosignaturing experiments as being specific for antibodies produced in response to various types of cancer and other diseases. The positional distribution of the biochemical properties of the amino acids in these 19 peptide groups was also studied. Remarkably, despite the random nature of the sequence libraries used to design the microarrays, a unique group-specific non-random pattern was identified in the majority of the peptide groups studied. © 2016 Wiley Periodicals, Inc. Biopolymers (Pept Sci) 106: 318-329, 2016.
authors.affiliation: Cancer Research Center and Department of Epidemiology and Biostatistics, University at Albany, State University of New York, One Discovery Drive, Rensselaer, NY, 12144.
authors.forename: Igor B
authors.initials: IB
authors.lastname: Kuznetsov
mesh_terms: D020816:Amino Acid Motifs; D000906:Antibodies / Q000032:analysis*; D000915:Antibody Affinity; D006801:Humans; D007118:Immunoassay / Q000295:instrumentation / Q000706:statistics & numerical data; D015233:Models, Statistical; D009369:Neoplasms / Q000145:classification / Q000175:diagnosis* / Q000235:genetics / Q000276:immunology*; D019151:Peptide Library; D040081:Protein Array Analysis; D011485:Protein Binding
chemical_list: D000906:Antibodies; D019151:Peptide Library
keywords: amino acid property scales; antibody binding; background distribution; biased amino acid composition; biochemical properties; compositional bias; immunosignatures; sequence patterns; statistical analysis