Computational design and experimental discovery of an antiestrogenic peptide derived from alpha-fetoprotein

Abstract

Breast cancer is the most common cancer among women, and tamoxifen is the preferred drug for estrogen receptor-positive breast cancer treatment. Many of these cancers are intrinsically resistant to tamoxifen or acquire resistance during treatment. Consequently, there is an ongoing need for breast cancer drugs that have different molecular targets. Previous work has shown that 8-mer and cyclic 9-mer peptides inhibit breast cancer in mouse and rat models, interacting with an unsolved receptor, while peptides smaller than eight amino acids did not. We show that the use of replica exchange molecular dynamics predicts the structure and dynamics of active peptides, leading to the discovery of smaller peptides with full biological activity. Simulations identified smaller peptide analogues with the same conserved reverse turn demonstrated in the larger peptides. These analogues were synthesized and shown to inhibit estrogen-dependent cell growth in a mouse uterine growth assay, a test showing reliable correlation with human breast cancer inhibition.

Figure 1

Overlay of the cyclic-[EKTPVNPGN] (red), cyclic-[EKTPVN-PGQ] (blue), cyclic-[EMTPVNPGQ] (orange), and the EMTPVNPG (green) and EMTPTNPG (purple) peptides from REMD simulations. Each structure represents the β-turn motif sampled during the dynamics.

Figure 2

The top graphs depict the distances between the conserved threonine and asparagine C_α atoms as a function of simulation time for the TPVN (left), TPVNP (middle), and cyclic-[EMTPVNPGQ] (right) peptides. The bottom graphs depict their corresponding φ (x-axis) and ψ (y-axis) angles as a function of simulation time for the conserved proline (red) and valine (green) amino acids.