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.

Computational Design and Experimental Discovery of an Anti-estrogenic Peptide Derived from Alpha-Fetoprotein

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.

Ramachandran-type Plots for Glycosidic Linkages: Examples from Molecular Dynamics Simulations using the Glycam06 Force Field

The goals of this article are to (1) provide further validation of the Glycam06 force field, specifically for its use in implicit solvent molecular dynamic (MD) simulations, and (2) to present the extension of G.N. Ramachandran's idea of plotting amino acid phi and psi angles to the glycosidic phi, psi, and omega angles formed between carbohydrates. As in traditional Ramachandran plots, these carbohydrate Ramachandran-type (carb-Rama) plots reveal the coupling between the glycosidic angles by displaying the allowed and disallowed conformational space. Considering two-bond glycosidic linkages, there are 18 possible conformational regions that can be defined by (α, ϕ, ψ) and (β, ϕ, ψ), whereas for three-bond linkages, there are 54 possible regions that can be defined by (α, ϕ, ψ, ω) and (β, ϕ, ψ, ω). Illustrating these ideas are molecular dynamic simulations on an implicitly hydrated oligosaccharide (700 ns) and its eight constituent disaccharides (50 ns/disaccharide). For each linkage, we compare and contrast the oligosaccharide and respective disaccharide carb-Rama plots, validate the simulations and the Glycam06 force field through comparison to experimental data, and discuss the general trends observed in the plots.