Elwin Chappell posted an update 4 months ago
In RAW264.7 macrophages the ranking order of inhibition of P-gp activity was LOPV.RITV.AMPV. BBR accumulation was significantly increased in macrophages after acute and extended exposure to various HIV PIs. These findings suggest that the inhibitory effect of HIV PIs on P-gp activity was unidirectional, unlike atazanavir, which inhibits P-gp activity in short-term treatment and induces Pgp activity in long-term treatment. Similar to the findings in mouse macrophages, HIV PIs also increased intracellular concentration of BBR in human THP-1 macrophages wild type MDCK cells and P-gp-transfected MDCK cells, with a rank order of patency LOPV.RITV.AMPV. Moreover, a lower multiple of the increase in BBR concentration after individual HIV PIs or Verapamil treatment in MDCK cells was observed in wild type MDCK cells, which may due to the lower levels of endogenous P-gp expression. The P-gp expression level in wild type MDCK cells is about 4% of that in P-gp-transfected MDCK cells. The molecular docking studies further suggest that the inhibitory effect of individual HIV PIs on the P-gp transporter is as follows: LOPV.RITV.AMPV. These results also suggest that HIV PIs could competitively block the binding of BBR to its binding site in P-gp, while BBR has no reverse effect on the binding of HIV PIVs to their binding sites in P-gp. Taken together, our studies suggest that HIV PIs increase BBR concentrations mainly by inhibiting the activities of P-gp. It should be noted that it has recently been reported that HIV PIs are also inhibitors of breast cancer resistance protein and RuBi-4AP multidrug resistance-associated protein1. However, the expression of BCRP in murine macrophages has not been clearly identified and the role of MRPs and BCRP in the accumulation of BBR increased by HIV PIs remains to be established in our future study. It has been long realized that the bioavailability of BBR is very low in vivo. Several possible mechanisms have been identified for its poor bioavailability. P-gp-mediated efflux represents a major mechanism. Although inhibition of efflux of BBR by coadministration of HIV PIs may intuitively cause concern for use in clinic, this specific drug interaction may actually be beneficial to improve the biological activities of BBR. We will examine the effect of HIV PIs on bioavailability of BBR using an in vivo mouse model and further define the interaction between BBR and HIV PIs with other transporters in our future study. In summary, drug interactions of BBR with HIV PIs mediated by P-gp inhibition were suggested by in vitro studies using macrophages. Although further in vivo investigations of possible interactions are necessary, the current study provided valuable information for understanding the underlying cellular mechanism of BBR-HIV PIs interactions, which is critical to effectively applying this combinational therapy in the clinic. Tyrosine kinase inhibitors are nowadays frequently used for treatment of defined solid and hematological cancer entities. Although these drugs are typically developed for the targeting of single kinases which are specifically overexpressed in cancer cells, in reality they usually inhibit a multitude of kinases and nonkinase targets resulting in a heterogeneous activity profile which is poorly predictable. Based on this off-target activity most of the clinically used TKIs exert relevant side effects which can interfere with the efficacy of the treatment regime leading to unfavorable therapeutic windows. Therefore, the prediction of drug action profile as early as possible in the drug research and discovery process is of eminent importance to avoid clinical trials using compounds with unforeseen unfavorable efficacy – risk profiles. The realization of the ‘‘fail early principle’’, however, requires methods to extract drug action from drug response profiles based on high throughput testing in well defined cell culture systems. Moreover, identification of the full set of modes-of-action of drugs and the assessment of their respective impact on secondary drug action are of utmost importance both for optimal selection of targets or alternatively, combinations of targets for optimization of future drug discovery as well as for the optimal administration of already existing compounds. Due to the molecular complexity of the various cancer entities, network reconstruction of MoA from combinatorial drug experimentation will be of special relevance for cancer therapies. Several methods for identification of MoA, side effects and drug efficacy from cellular drug responses have been described. Prediction of drug efficacy as well as potential adverse side effects can be performed by chemical structures and experimental data from cell screening experiments of the compounds using appropriate similarity scores. An alternative approach uses established network information with respect to known MoA’s and predicts side effects identified by cooperative pathway analysis. Experimentally derived doseresponse surfaces from combinatorial drug experiments can be used to identify simplified or detailed models for the respective MoA’s and their interactions from analysis of the combinatorial drug response surfaces.