Bradford A. Jameson

In this paper, we introduce a computer algorithm which can be used to predict the topological features of a protein directly from its primary amino acid sequence. The computer program generates values for surface accessibility parameters and combines these values with those obtained for regional backbone flexibility and predicted secondary structure. The output of this algorithm, the antigenic index, is used to create a linear surface contour profile of the protein. Because most, if not all, antigenic sites are located within surface exposed regions of a protein, the program offers a reliable means of predicting potential antigenic determinants. We have tested the ability of this program to generate accurate surface contour profiles and predict antigenic sites from the linear amino acid sequences of well-characterized proteins and found a strong correlation between the predictions of the antigenic index and known structural and biological data.

We have investigated three prostatic cancer cell lines, PC-3, DU-145, and LNCa.FGC, and found that all three cell lines can grow in serum-free medium without the addition of exogenous growth factors. All three cell lines produce substantial amounts of insulin-like growth factor 1 (IGF-1) that is secreted in the medium and they all display constitutively autophosphorylated IGF-1 receptors; two of the cell lines overexpress IGF-1 receptor RNA. The growth of all three cell lines is inhibited by an antisense oligodeoxynucleotide to IGF-1 receptor RNA or by peptide analogues of IGF-1 that compete with IGF-1 binding to its receptor. Our results indicate that these three cell lines grow by an autocrine loop in which the overproduced IGF-1 activates its receptor. Interference with the activation of the receptor leads to cessation of growth.

The activation of the insulin-like growth factor 1 (IGF-1) receptor by its ligand plays a central role in the growth of most cell types. We have used the techniques of computational chemistry in order to design and synthesize several novel analogues of IGF-1. These analogues were able to inhibit the autophosphorylation of the IGF-1 receptor as well as the growth of several different cell types, including prostate carcinoma cells and SV40-transformed cells. Additionally, we have found that D-amino acid analogues of these peptides are apparently resistant to the proteolytic degradation that occurs in the presence of whole sera. Consequently, these analogues seem to show great potential both as probes of the structure/function activities of the IGF-1 signalling pathway and as novel clinical strategies in controlling abnormal cellular growth.