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

ACS Citation

Shields, G. C. Computational Approaches for the Design of Peptides with Anti-Breast Cancer Properties. Future Med. Chem. 2009, 1 (1), 201-€“212.

Abstract

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.

Source Name

Future Medicinal Chemistry

Publication Date

2009

Volume

1

Issue

1

Page(s)

201-212

Document Type

Citation

Citation Type

Article

Share

COinS