9 resultados para cyclic peptides

em Bucknell University Digital Commons - Pensilvania - USA


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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.

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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.

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Undergraduate research in chemistry provides not only a meaningful experience for the students, but is essential in getting research done. This talk will focus on an ongoing project in my lab: designing large molecules of specific shapes by studying the fundamental reactions. While results will be discussed, the talk will be tailored towards a general audience. I will attempt to highlight the outstanding contributions made by Bucknell students that have worked in my lab.

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Full geometry optimizations using the PM3, AM1, 3-21G∗/HF and 6-31G∗/HF levels of theory were conducted on the syn and anti conformations of cyclic3′,5′-adenosine monophosphate (cAMP). Comparison of the anti crystal structures with the semiempirical and ab initio results revealed that the ab initio results agree well with the experimental results. The results of semiempirical calculations are in qualitative agreement with experimental and ab initio values, with the exception of the glycosyl torsion angle for the anti conformer. Sugar puckering, which is not handled properly by semiempirical methods for unconstrained sugars, nucleosides, nucleotides and nucleotide base pairs, is modeled reasonably well by the semiempirical methods for cAMP. This improvement results from the constraints introduced by the cyclization of AMP to form the phosphodiester.

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The supermolecule approach has been used to model the hydration of cyclic 3‘,5‘-adenosine monophosphate, cAMP. Model building combined with PM3 optimizations predict that the anti conformer of cAMP is capable of hydrogen bonding to an additional solvent water molecule compared to the syn conformer. The addition of one water to the syn superstructure with concurrent rotation of the base about the glycosyl bond to form the anti superstructure leads to an additional enthalpy of stabilization of approximately −6 kcal/mol at the PM3 level. This specific solute−solvent interaction is an example of a large solvent effect, as the method predicts that cAMP has a conformational preference for the anti isomer in solution. This conformational preference results from a change in the number of specific solute−solvent interactions in this system. This prediction could be tested by NMR techniques. The number of waters predicted to be in the first hydration sphere around cAMP is in agreement with the results of hydration studies of nucleotides in DNA. In addition, the detailed picture of solvation about this cyclic nucleotide is in agreement with infrared experimental results.

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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.

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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.

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This study investigated the effect of cyclic wetting and drying on the backfill used in soil-bentonite (SB) cutoff walls. For this purpose, model SB vertical cutoff wall backfills were prepared comprising of a fine grained mortar sand and 2% bentonite (by total weight) and 4% bentonite (by total weight). Results of the study indicate that the volume change is influenced by the bentonite content, that is, the increase in volume change increased with increasing bentonite content.

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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.