The Search for Low Energy Conformational Families of Small Peptides: Searching for Active Conformations of Small Peptides in the Absence of a Known Receptor

Breast cancer is the most common cancer among women. Tamoxifen is the preferred drug for estrogen receptor-positive breast cancer treatment, yet many of these cancers are intrinsically resistant to tamoxifen or acquire resistance during treatment. Therefore, scientists are searching for breast cancer drugs that have different molecular targets. Previous work revealed that 8-mer and cyclic 9-mer peptides inhibit breast cancer in mouse and rat model systems, interacting with an unknown receptor, while peptides smaller than eight amino acids did not inhibit breast cancer. We have shown that the use of replica exchange molecular dynamics predicts structure and dynamics of active peptides, leading to the discovery of smaller peptides with full biological activity. These simulations identified smaller peptide analogs with a conserved turn, a β-turn formed in the larger peptides. These analogs inhibit estrogen-dependent cell growth in a mouse uterine growth assay, a test showing reliable correlation with human breast cancer inhibition. We outline the computational methods that were tried and used with the experimental information that led to the successful completion of this research.

Antiestrogenic and anticancer activities of peptides derived from the active site of alpha-fetoprotein

Cyclo[EKTOVNOGN] (AFPep), a cyclic 9-amino acid peptide derived from the active site of alpha-fetoprotein, has been shown to prevent carcinogen-induced mammary cancer in rats and inhibit the growth of ER+ human breast cancer xenografts in mice. Recently, studies using replica exchange molecular dynamics predicted that the TOVN region of AFPep might form a dynamically stable putative Type I beta-turn, and thus be biologically active without additional amino acids. The studies presented in this paper were performed to determine whether TOVN and other small analogs of AFPep would inhibit estrogen-stimulated cancer growth and exhibit a broad effective-dose range. These peptides contained nine or fewer amino acids, and were designed to bracket or include the putative pharmacophoric region (TOVN) of AFPep. Biological activities of these peptides were evaluated using an immature mouse uterine growth inhibition assay, a T47D breast cancer cell proliferation assay, and an MCF-7 breast cancer xenograft assay. TOVN had very weak antiestrogenic activity in comparison to AFPep's activity, whereas TOVNO had antiestrogenic and anticancer activities similar to AFPep. OVNO, which does not form a putative Type I beta-turn, had virtually no antiestrogenic and anticancer activities. A putative proteolytic cleavage product of AFPep, TOVNOGNEK, significantly inhibited E2-stimulated growth in vivo and in vitro over a wider dose range than AFPep or TOVNO. We conclude that TOVNO has anticancer potential, that TOVNOGNEK is as effective as AFPep in suppressing growth of human breast cancer cells, and that it does so over a broader effective-dose range.

Computational approaches for the design of peptides with anti-breast cancer properties

Background: Breast cancer is the most common cancer among women. Tamoxifen is the preferred drug for estrogen receptor-positive breast cancer treatment, yet many of these cancers are intrinsically resistant to tamoxifen or acquire resistance during treatment. Therefore, scientists are searching for breast cancer drugs that have different molecular targets. Methodology: Recently, a computational approach was used to successfully design peptides that are new lead compounds against breast cancer. We used replica exchange molecular dynamics to predict the structure and dynamics of active peptides, leading to the discovery of smaller bioactive peptides. Conclusions: These analogs inhibit estrogen-dependent cell growth in a mouse uterine growth assay, a test showing reliable correlation with human breast cancer inhibition. We outline the computational methods that were tried and used along with the experimental information that led to the successful completion of this research.

Structural Analysis of alpha-Fetoprotein (AFP)-like Peptides with Anti-Breast-Cancer Properties

The abundance of alpha-fetoprotein (AFP), a natural protein produced by the fetal yolk sac during pregnancy, correlates with lower incidence of estrogen receptor positive (ER+) breast cancer. The pharmacophore region of AFP has been narrowed down to a four amino acid (AA) region in the third domain of the 591 AA peptide. Our computational study focuses on a 4-mer segment consisting of the amino acids threonine-proline-valine-asparagine (TPVN). We have run replica exchange molecular dynamics (REMD) simulations and used 120 configurational snapshots from the total trajectory as starting configurations for quantum chemical calculations. We optimized structures using semiempirical (PM3, PM6, PM6-D2, PM6-H2, PM6-DH+, PM6-DH2) and density functional methods (TPSS, PBE0, M06-2X). By comparing the accuracy of these methods against RI-MP2 benchmarks, we devised a protocol for calculating the lowest energy conformers of these peptides accurately and efficiently. This protocol screens out high-energy conformers using lower levels of theory and outlines a general method for predicting small peptide structures.