Computational design and experimental discovery of an antiestrogenic peptide derived from alpha-fetoprotein

Elucidating Solution Structures of Cyclic Peptides Using Molecular Dynamics Simulations

Protein-protein interactions are vital to biological processes, but the shape and size of their interfaces make them hard to target using small molecules. Cyclic peptides have shown promise as protein-protein interaction modulators, as they can bind protein surfaces with high affinity and specificity. Dozens of cyclic peptides are already FDA approved, and many more are in various stages of development as immunosuppressants, antibiotics, antivirals, or anticancer drugs. However, most cyclic peptide drugs so far have been natural products or derivatives thereof, with de novo design having proven challenging. A key obstacle is structural characterization: cyclic peptides frequently adopt multiple conformations in solution, which are difficult to resolve using techniques like NMR spectroscopy. The lack of solution structural information prevents a thorough understanding of cyclic peptides' sequence-structure-function relationship. Here we review recent development and application of molecular dynamics simulations with enhanced sampling to studying the solution structures of cyclic peptides. We describe novel computational methods capable of sampling cyclic peptides' conformational space and provide examples of computational studies that relate peptides' sequence and structure to biological activity. We demonstrate that molecular dynamics simulations have grown from an explanatory technique to a full-fledged tool for systematic studies at the forefront of cyclic peptide therapeutic design.

Temperature Replica Exchange Molecular Dynamics Simulations of Cyclic Peptide Conformation

Collapse

Design and synthesis of biologically active peptides: a 'tail' of amino acids can modulate activity of synthetic cyclic peptides

In earlier work, we synthesized a cyclic 9-amino acid peptide (AFPep, cyclo[EKTOVNOGN]) and showed it to be useful for prevention and therapy of breast cancer. In an effort to explore the structure-function relationships of AFPep, we have designed analogs that bear a short 'tail' (one or two amino acids) attached to the cyclic peptide distal to its pharmacophore. Analogs that bore a tail of either one or two amino acids, either of which had a hydrophilic moiety in the side chain (e.g., cyclo[EKTOVNOGN]FS) exhibited greatly diminished biological activity (inhibition of estrogen-stimulated uterine growth) relative to AFPep. Analogs that bore a tail of either one or two amino acids which had hydrophobic (aliphatic or aromatic) side chains (e.g., cyclo[EKTOVNOGN]FI) retained (or had enhanced) growth inhibition activity. Combining in the same biological assay a hydrophilic-tailed analog with either AFPep or a hydrophobic-tailed analog resulted in decreased activity relative to that for AFPep or for the hydrophobic-tailed analog alone, suggesting that hydrophilic-tailed analogs are binding to a biologically active receptor. An analog with a disrupted pharmacophore (cyclo[EKTOVGOGN]) exhibited little or no growth inhibition activity. An analog with a hydrophilic tail and a disrupted pharmacophore (cyclo[EKTOVGOGN]FS) exhibited no growth inhibition activity of its own and did not affect the activity of a hydrophobic-tailed analog, but enhanced the growth inhibition activity of AFPep. These results are discussed in the context of a two-receptor model for binding of AFPep and ring-and-tail analogs. We suggest that tails on cyclic peptides may comprise a useful method to enhance diversity of peptide design and specificity of ligand-receptor interactions.

Mechanism of Cancer Growth Suppression of Alpha-Fetoprotein Derived Growth Inhibitory Peptides (GIP): Comparison of GIP-34 versus GIP-8 (AFPep). Updates and Prospects

The Alpha-fetoprotein (AFP) derived Growth Inhibitory Peptide (GIP) is a 34-amino acid segment of the full-length human AFP molecule that inhibits tumor growth and metastasis. The GIP-34 and its carboxy-terminal 8-mer segment, termed GIP-8, were found to be effective as anti-cancer therapeutic peptides against nine different human cancer types. Following the uptake of GIP-34 and GIP-8 into the cell cytoplasm, each follows slightly different signal transduction cascades en route to inhibitory pathways of tumor cell growth and proliferation. The parallel mechanisms of action of GIP-34 versus GIP-8 are demonstrated to involve interference of signaling transduction cascades that ultimately result in: (1) cell cycle S-phase/G2-phase arrest; (2) prevention of cyclin inhibitor degradation; (3) protection of p53 from inactivation by phosphorylation; and (4) blockage of K+ ion channels opened by estradiol and epidermal growth factor (EGF). The overall mechanisms of action of both peptides are discussed in light of their differing modes of cell attachment and uptake fortified by RNA microarray analysis and electrophysiologic measurements of cell membrane conductance and resistance. As a chemotherapeutic adjunct, the GIPs could potentially aid in alleviating the negative side effects of: (1) tamoxifen resistance, uterine hyperplasia/cancer, and blood clotting; (2) Herceptin antibody resistance and cardiac (arrest) arrhythmias; and (3) doxorubicin's bystander cell toxicity.

Discovery of a competitive apelin receptor (APJ) antagonist

The apelin receptor (APJ) is a class A G-protein-coupled receptor (GPCR) and is a putative target for the treatment of cardiovascular and metabolic diseases. Apelin-13 (NH₂-QRPRLSHKGPMPF-COOH) is a vasoactive peptide and one of the most potent endogenous inotropic agents identified to date. We report the design and discovery of a novel APJ antagonist. By using a bivalent ligand approach, we have designed compounds with two 'affinity' motifs and a short series of linker groups with different conformational and non-bonded interaction properties. One of these, cyclo(1-6)CRPRLC-KH-cyclo(9-14)CRPRLC is a competitive antagonist at APJ. Radioligand binding in CHO cells transfected with human APJ gave a K(i) value of 82 nM, competition binding in human left ventricle gave a K(D) value of 3.2 μM, and cAMP accumulation assays in CHO-K1-APJ cells gave a K(D) value of 1.32 μM.

Enantiomeric separation of chiral dipeptides by CE-ESI-MS employing a partial filling technique with chiral crown ether

Enantiomer of chiral dipeptides were separated by CE-ESI-MS in a bare fused-silica capillary using (+)-(18-crown-6)-2,3,11,12-tetracarboxylic acid (18C6H4) as the chiral selector. As 18C6H4 is a kind of nonvolatile chiral selector, in order to prevent from 18C6H4 into the ion-source of CE-ESI-MS, a partial filling technique was employed in this study. Some dipeptides with one chiral center or two chiral centers, such as DL-Leu-DL-Leu, D-Ala-D-Ala and L-Ala-L-Ala, Gly-D-Phe and Gly-L-Phe were used to evaluate this CE-ESI-MS system. Optimized conditions were achivevd with 2.0 mol/L acetic acid (pH 2.15) as the running electrolyte, 5 mM 18C6H4 in 3.0 mol/L acetic acid (pH 2.00) was injected hydrodynamically (50 mbar for 960 s) before sample injection. In total 7.5 mM acetic acid in 80% v/v methanol-water was used as the sheath liquid, and 20 kV applied voltage was used. Under the optimum conditions, these dipeptides were separated and detected. LODs (defined as S/N=3) of this method were 0.20, 0.10, 0.05 and 0.10 micromol/L for D-Ala-D-Ala, L-Ala-L-Ala, DL-Leu-DL-Leu, Gly-L-Phe and Gly-D-Phe, respectively. The RSDs (n=7) of the method were 0.68-2.08% for migration times and 2.32-5.24% for peak areas. The proposed method was also successfully applied to the enantioselective analysis of these dipeptides in the spiked serum samples with satisfactory results.

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

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.