Poly-glutamic dendrimer-based conjugates for cancer vaccination - a computational design for targeted delivery of antigens.

Computational techniques are useful to predict interaction models and molecular properties for the design of drug delivery systems, such as dendrimers. This work evaluated the impact of surface modifications of mannosamine-conjugated multifunctional poly(glutamic acid) (PG)-dendrimers as nanocarriers of the tumour associated antigens (TAA) MART-1, gp100:44 and gp100:209. Molecular dynamics simulations and docking studies were performed. Nitrobenzoxadiazole (NBD)-PG-G4-dendrimer displayed 64 carboxylic groups, however, the Frontier Molecular Orbital Theory study evidenced that only 32 of those were available to form covalent bonds. When the number of mannosamines conjugated to dendrimer was increased from 16 to 32, the dendrimer interacted with the receptor with higher affinity. However, 16 mannosamines-NBD-PG-G4-dendrimer was chosen to conjugate TAA for added functionality as no carboxylic end groups were available for further conjugation in the 32 mannosamines-dendrimer. Docking results showed that the majority of TAA-conjugated NBD-PG-G4-dendrimer demonstrated a favourable interaction with mannosamine binding site on mannose receptor, thus constituting a promising tool for TAA targeted delivery. Our in silico approach effectively narrows down the selection of the best candidates for the synthesis of functionalised PG-dendrimers with desired functionalities. These results will significantly reduce the time and efforts required to experimentally synthesise modified dendrimers for optimal antigen delivery.

Computational classification models for predicting the interaction of drugs with P-glycoprotein and breast cancer resistance protein.

P-glycoprotein (P-gp/ABCB1) and breast cancer resistance protein (BCRP/ABCG2) are two members of the adenosine triphosphate (ATP) binding cassette (ABC) family of transporters which function as membrane efflux transporters and display considerable substrate promiscuity. Both are known to significantly influence the absorption, distribution and elimination of drugs, mediate drug-drug interactions and contribute to multiple drug resistance (MDR) of cancer cells. Correspondingly, timely characterization of the interaction of novel leads and drug candidates with these two transporters is of great importance. In this study, several computational classification models for prediction of transport and inhibition of P-gp and BCRP, respectively, were developed based on newly compiled and critically evaluated experimental data. Artificial neural network (ANN) and support vector machine (SVM) ensemble based models were explored, as well as knowledge-based approaches to descriptor selection. The average overall classification accuracy of best performing models was 82% for P-gp transport, 88% for BCRP transport, 89% for P-gp inhibition and 87% for BCRP inhibition, determined across an array of different test sets. An analysis of substrate overlap between P-gp and BCRP was also performed. The accuracy, simplicity and interpretability of the proposed models suggest that they could be of significant utility in the drug discovery and development settings.

Natural chalcones as dual inhibitors of HDACs and NF-κB.

Histone deacetylase enzymes (HDACs) are emerging as a promising biological target for cancer and inflammation. Using a fluorescence assay, we tested the in vitro HDAC inhibitory activity of twenty-one natural chalcones, a widespread group of natural products with well-known anti-inflammatory and antitumor effects. Since HDACs regulate the expression of the transcription factor NF-κB, we also evaluated the inhibitory potential of the compounds on NF-κB activation. Only four chalcones, isoliquiritigenin (no. 10), butein (no. 12), homobutein (no. 15) and the glycoside marein (no. 21) showed HDAC inhibitory activity with IC50 values of 60-190 µM, whereas a number of compounds inhibited TNFα-induced NF-κB activation with IC50 values in the range of 8-41 µM. Interestingly, three chalcones (nos. 10, 12 and 15) inhibited both TNFα-induced NF-κB activity and total HDAC activity of classes I, II and IV. Molecular modeling and docking studies were performed to shed light into dual activity and to draw structure-activity relationships among chalcones (nos. 1-21). To the best of our knowledge this is the first study that provides evidence for HDACs as potential drug targets for natural chalcones. The dual inhibitory potential of the selected chalcones on NF-κB and HDACs was investigated for the first time. This study demonstrates that chalcones can serve as lead compounds in the development of dual inhibitors against both targets in the treatment of inflammation and cancer.

Advanced microscopy solutions for monitoring the kinetics and dynamics of drug-DNA targeting in living cells.

Many anticancer drugs require interaction with DNA or chromatin components of tumor cells to achieve therapeutic activity. Quantification and exploration of drug targeting dynamics can be highly informative in the rational development of new therapies and in the drug discovery pipeline. The problems faced include the potential infrequency and transient nature of critical events, the influence of micropharmacokinetics on the drug-target equilibria, the dependence on preserving cell function to demonstrate dynamic processes in situ, the need to map events in functional cells and the confounding effects of cell-to-cell heterogeneity. We demonstrate technological solutions in which we have integrated two-photon laser scanning microscopy (TPLSM) to track drug delivery in subcellular compartments, with the mapping of sites of critical molecular interactions. We address key design concepts for the development of modular tools used to uncover the complexity of drug targeting in single cells. First, we describe the combination of two-photon excitation with fluorescence lifetime imaging microscopy (FLIM) to map the nuclear docking of the anticancer drug topotecan (TPT) at a subset of DNA sites in nuclear structures of live breast tumor cells. Secondly, we demonstrate how we incorporate the smart design of a two-photon 'dark' DNA binding probe, such as DRAQ5, as a well-defined quenching probe to uncover sites of drug interaction. Finally, we discuss the future perspectives on introducing these modular kinetic assays in the high-content screening arena and the interlinking of the consequences of drug-target interactions with cellular stress responses.