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

被引:2
|
作者
Shields, George C. [1 ,2 ]
机构
[1] Armstrong Atlantic State Univ, Deans Off, Savannah, GA 31419 USA
[2] Armstrong Atlantic State Univ, Dept Chem & Phys, Coll Sci & Technol, Savannah, GA 31419 USA
基金
美国国家科学基金会;
关键词
MOLECULAR-DYNAMICS SIMULATION; FREE-ENERGY LANDSCAPE; REPLICA EXCHANGE SIMULATIONS; GROWTH-INHIBITORY PEPTIDE; HUMAN ALPHA-FETOPROTEIN; BETA-HAIRPIN; FORCE-FIELD; FOLDING MECHANISM; ACTIVE-SITE; CENTER-DOT;
D O I
10.4155/FMC.09.13
中图分类号
R914 [药物化学];
学科分类号
100701 ;
摘要
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.
引用
收藏
页码:201 / 212
页数:12
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