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Published on: January 26, 2016
Computational design and experimental discovery of an antiestrogenic peptide derived from alpha-fetoprotein
Karl N Kirschner1, Katrina W Lexa, Amanda M Salisburg
1Hamilton College, Department of Chemistry, Center for Molecular Design, 198 College Hill Road, Clinton, New York 13323, USA.
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.
Insights
Researchers discovered smaller, highly active breast cancer peptides by predicting structures with molecular dynamics. These new peptides inhibit estrogen-dependent growth, offering a potential alternative to tamoxifen-resistant cancers.
Area of Science:
- Biochemistry
- Molecular Biology
- Drug Discovery
Background:
- Breast cancer is a leading cause of death in women, with tamoxifen being a primary treatment for estrogen receptor-positive cases.
- Intrinsic or acquired resistance to tamoxifen necessitates the development of novel breast cancer therapeutics targeting different molecular pathways.
- Previously identified 8-mer and 9-mer peptides showed efficacy against breast cancer in animal models, but their mechanism and smaller analogues were unknown.
Purpose of the Study:
- To investigate the structural dynamics of previously identified breast cancer-inhibiting peptides using computational methods.
- To discover smaller peptide analogues that retain the biological activity of larger peptides.
- To identify novel therapeutic candidates for tamoxifen-resistant breast cancer.
Main Methods:
- Replica exchange molecular dynamics simulations were employed to predict the structure and dynamics of active peptides.
- Computational analysis identified conserved structural motifs, specifically a reverse turn, in active larger peptides.
- Synthesized smaller peptide analogues were tested for biological activity in vitro and in vivo.
Main Results:
- Molecular dynamics simulations successfully predicted the structure and dynamics of active peptides.
- The simulations identified smaller peptide analogues that preserved the key reverse turn structure found in larger, active peptides.
- Synthesized smaller peptide analogues demonstrated significant inhibition of estrogen-dependent cell growth in a mouse uterine growth assay.
Conclusions:
- Computational modeling can effectively guide the discovery of smaller, potent peptide therapeutics.
- The identified smaller peptide analogues show promise as novel agents for treating estrogen-dependent breast cancer, including tamoxifen-resistant forms.
- These findings offer a new avenue for developing breast cancer drugs with distinct molecular targets.
