Galactose as Broad Ligand for Multiple Tumor Imaging and Therapy.

Galactose residues could be specifically recognized by the asialoglycoprotein receptor (ASGPR) which is highly exhibited on liver tissues. However, ASGPR has not been widely investigated on different tumor cell lines except for hepatoma carcinoma cells, which motivates us to investigate the possibility of galactose serving as a board tumor ligand. In this study, a galactose (Gal)-based probe conjugated with fluorescence dye MPA (Gal-MPA) was constructed for the evaluation of tumor affinities/targeted ability on different tumor cell lines. In the vitro cell study, it was indicated that the fluorescence probe Gal-MPA displayed higher cell affinity to tumor cells (HepG2, MCF-7 and A549) than that of the normal liver cells l02. In the vivo dynamic study of Gal-MPA in tumor-bearing mice (HepG2, MCF-7, A549, HCT116, U87, MDA-MB-231 and S180), it was shown that its high tumor targeted ability with the maximal tumor/normal tissue ratio reached up to 6.8. Meanwhile, the fast tumor-targeted ability within 2 hours and long retention on tumor site up to 120 hours were observed. Our results demonstrated that galactose should be a promising broad ligand for multiple tumor imaging and targeted therapy. Subsequently, Gal was covalently conjugated to doxorubicin (DOX) to form prodrug Gal-DOX for tumor targeted therapy. The therapeutic results of Gal-DOX than DOX being better suggested that galactosylated prodrugs might have the prospective potential in tumor targeted therapy.

Small sized EGFR1 and HER2 specific bifunctional antibody for targeted cancer therapy.

Targeting tumors using miniature antibodies is a novel and attractive therapeutic approach, as these biomolecules exhibit low immunogenicity, rapid clearance, and high targeting specificity. However, most of the small-sized antibodies in existence do not exhibit marked anti-tumor effects, which limit their use in targeted cancer immunotherapy. To overcome this difficulty in targeting multiple biomarkers by combination therapies, we designed a new bifunctional antibody, named MaAbNA (multivalent antibody comprised of nanobody and affibody moieties), capable of targeting EGFR1 and HER2, which are widely overexpressed in a variety of tumor types. The small-sized (29 kDa) MaAbNA, which was expressed in E.coli, consists of one anti-EGFR1 nanobody and two anti-HER2 affibodies, and possesses high affinity (KD) for EGFR1 (~4.1 nM) and HER2 (~4.7 nM). In order to enhance its anti-tumor activity, MaAbNA was conjugated with adriamycin (ADM) using a PEG2000 linker, forming a new complex anticancer drug, MaAbNA-PEG2000-ADM. MaAbNA exhibited high inhibitory effects on tumor cells over-expressing both EGFR1 and HER2, but displayed minimal cytotoxicity in cells expressing low levels of EGFR1 and HER2. Moreover, MaAbNA-PEG2000-ADM displayed increased tumoricidal effects than ADM or MaAbNA alone, as well exhibited greater antitumor efficacy than EGFR1 (Cetuximab) and HER2 (Herceptin) antibody drugs. The ability of MaAbNA to regulate expression of downstream oncogenes c-jun, c-fos, c-myc, as well as AEG-1 for therapeutic potential was evaluated by qPCR and western-blot analyses. The antitumor efficacy of MaAbNA and its derivative MaAbNA-PEG2000-ADM were validated in vivo, highlighting the potential for use of MaAbNA as a highly tumor-specific dual molecular imaging probe and targeted cancer therapeutic.

A combination of 2D similarity search, pharmacophore, and molecular docking techniques for the identification of vascular endothelial growth factor receptor-2 inhibitors.

The human vascular endothelial growth factor receptor-2 (VEGFR-2) has been an attractive target for the inhibition of angiogenesis. In the current study, we used a hybrid protocol of virtual screening methods to retrieve new VEGFR-2 inhibitors from the Zinc-Specs Database (441 574 compounds). The hybrid protocol included the initial screening of candidates by comparing the 2D similarity to five reported top active inhibitors of 13 VEGFR-2 X-ray crystallography structures, followed by the pharmacophore modeling of virtual screening on the basis of receptor-ligand interactions and further narrowing by LibDOCK to obtain the final hits. Two compounds (AN-919/41439526 and AK-968/40939851) with a high libscore were selected as the final hits for a subsequent cell cytotoxicity study. The two compounds screened exerted significant inhibitory effects on the proliferation of cancer cells (U87 and MCF-7). The results indicated that the hybrid procedure is an effective approach for screening specific receptor inhibitors.

The targeting mechanism of DHA ligand and its conjugate with Gemcitabine for the enhanced tumor therapy.

Docosahexaenoic acid (DHA), an omega-3 C22 natural fatty acid serving as a precursor for metabolic and biochemical pathways, was reported as a targeting ligand of anticancer drugs. However, its tumor targeting ability and mechanism has not been claimed. Here we hypothesized that the uptake of DHA by tumor cells is related to the phosphatidylethanolamine (PE) contents in cell membranes. Thus, in this manuscript, the tumor-targeting ability of DHA was initially demonstrated in vitro and in vivo on different tumor cell lines by labeling DHA with fluorescence dyes. Subsequently, the tumor targeting ability was then correlated with the contents of PE in cell membranes to study the uptake mechanism. Further, DHA was conjugated with anticancer drug gemcitabine (DHA-GEM) for targeted tumor therapy. Our results demonstrated that DHA exhibited high tumor targeting ability and PE is the main mediator, which confirmed our hypothesis. The DHA-GEM displayed enhanced therapeutic efficacy than that of GEM itself, indicating that DHA is a promising ligand for tumor targeted therapy.

Tubulin inhibitors: pharmacophore modeling, virtual screening and molecular docking.

AIM: To construct a quantitative pharmacophore model of tubulin inhibitors and to discovery new leads with potent antitumor activities. METHODS: Ligand-based pharmacophore modeling was used to identify the chemical features responsible for inhibiting tubulin polymerization. A set of 26 training compounds was used to generate hypothetical pharmacophores using the HypoGen algorithm. The structures were further validated using the test set, Fischer randomization method, leave-one-out method and a decoy set, and the best model was chosen to screen the Specs database. Hit compounds were subjected to molecular docking study using a Molecular Operating Environment (MOE) software and to biological evaluation in vitro. RESULTS: Hypo1 was demonstrated to be the best pharmacophore model that exhibited the highest correlation coefficient (0.9582), largest cost difference (70.905) and lowest RMSD value (0.6977). Hypo1 consisted of one hydrogen-bond acceptor, a hydrogen-bond donor, a hydrophobic feature, a ring aromatic feature and three excluded volumes. Hypo1 was validated with four different methods and had a goodness-of-hit score of 0.81. When Hypo1 was used in virtual screening of the Specs database, 952 drug-like compounds were revealed. After docking into the colchicine-binding site of tubulin, 5 drug-like compounds with the required interaction with the critical amino acid residues and the binding free energies < -4 kcal/mol were selected as representative leads. Compounds 1 and 3 exhibited inhibitory activity against MCF-7 human breast cancer cells in vitro. CONCLUSION: Hypo1 is a quantitative pharmacophore model for tubulin inhibitors, which not only provides a better understanding of their interaction with tubulin, but also assists in discovering new potential leads with antitumor activities.

Pharmacophore modeling and virtual screening for the discovery of new type 4 cAMP phosphodiesterase (PDE4) inhibitors.

Type 4 cAMP phosphodiesterase (PDE4) inhibitors show a broad spectrum of anti-inflammatory effects in almost all kinds of inflamed cells, by an increase in cAMP levels which is a pivotal second messenger responsible for various biological processes. These inhibitors are now considered as the potential drugs for treatment of chronic inflammatory diseases. However, some recently marketed inhibitors e.g., roflumilast, have shown adverse effects such as nausea and emesis, thus restricting its use. In order to identify novel PDE4 inhibitors with improved therapeutic indexes, a highly correlating (r = 0.963930) pharmacophore model (Hypo1) was established on the basis of known PDE4 inhibitors. Validated Hypo1 was used in database screening to identify chemical with required pharmacophoric features. These compounds are further screened by using the rule of five, ADMET and molecular docking. Finally, twelve hits which showed good results with respect to following properties such as estimated activity, calculated drug-like properties and scores were proposed as potential leads to inhibit the PDE4 activity. Therefore, this study will not only assist in the development of new potent hits for PDE4 inhibitors, but also give a better understanding of their interaction with PDE4. On a wider scope, this will be helpful for the rational design of novel potent enzyme inhibitors.