A highly soluble, non-phototoxic, non-fluorescent blebbistatin derivative.

Blebbistatin is a commonly used molecular tool for the specific inhibition of various myosin II isoforms both in vitro and in vivo. Despite its popularity, the use of blebbistatin is hindered by its poor water-solubility (below 10 micromolar in aqueous buffer) and blue-light sensitivity, resulting in the photoconversion of the molecule, causing severe cellular phototoxicity in addition to its cytotoxicity. Furthermore, blebbistatin forms insoluble aggregates in water-based media above 10 micromolar with extremely high fluorescence and also high adherence to different types of surfaces, which biases its experimental usage. Here, we report a highly soluble (440 micromolar in aqueous buffer), non-fluorescent and photostable C15 amino-substituted derivative of blebbistatin, called para-aminoblebbistatin. Importantly, it is neither photo- nor cytotoxic, as demonstrated on HeLa cells and zebrafish embryos. Additionally, para-aminoblebbistatin bears similar myosin II inhibitory properties to blebbistatin or para-nitroblebbistatin (not to be confused with the C7 substituted nitroblebbistatin), tested on rabbit skeletal muscle myosin S1 and on M2 and HeLa cells. Due to its drastically improved solubility and photochemical feature, as well as lack of photo- or cytotoxicity, para-aminoblebbistatin may become a feasible replacement for blebbistatin, especially at applications when high concentrations of the inhibitor or blue light irradiation is required.

para-Nitroblebbistatin, the non-cytotoxic and photostable myosin†II inhibitor.

Blebbistatin, the best characterized myosin II-inhibitor, is commonly used to study the biological roles of various myosin II isoforms. Despite its popularity, the use of blebbistatin is greatly hindered by its blue-light sensitivity, resulting in phototoxicity and photoconversion of the molecule. Additionally, blebbistatin has serious cytotoxic side effects even in the absence of irradiation, which may easily lead to the misinterpretation of experimental results since the cytotoxicity-derived phenotype could be attributed to the inhibition of the myosin II function. Here we report the synthesis as well as the in vitro and in vivo characterization of a photostable, C15 nitro derivative of blebbistatin with unaffected myosin II inhibitory properties. Importantly, para-nitroblebbistatin is neither phototoxic nor cytotoxic, as shown by cellular and animal tests; therefore it can serve as an unrestricted and complete replacement of blebbistatin both in vitro and in vivo.

Experimental confirmation of new drug-target interactions predicted by Drug Profile Matching.

We recently introduced Drug Profile Matching (DPM), a novel affinity fingerprinting-based in silico drug repositioning approach. DPM is able to quantitatively predict the complete effect profiles of compounds via probability scores. In the present work, in order to investigate the predictive power of DPM, three effect categories, namely, angiotensin-converting enzyme inhibitor, cyclooxygenase inhibitor, and dopamine agent, were selected and predictions were verified by literature analysis as well as experimentally. A total of 72% of the newly predicted and tested dopaminergic compounds were confirmed by tests on D1 and D2 expressing cell cultures. 33% and 23% of the ACE and COX inhibitory predictions were confirmed by in vitro tests, respectively. Dose-dependent inhibition curves were measured for seven drugs, and their inhibitory constants (Ki) were determined. Our study overall demonstrates that DPM is an effective approach to reveal novel drug-target pairs that may result in repositioning these drugs.

Drug effect prediction by polypharmacology-based interaction profiling.

Most drugs exert their effects via multitarget interactions, as hypothesized by polypharmacology. While these multitarget interactions are responsible for the clinical effect profiles of drugs, current methods have failed to uncover the complex relationships between them. Here, we introduce an approach which is able to relate complex drug-protein interaction profiles with effect profiles. Structural data and registered effect profiles of all small-molecule drugs were collected, and interactions to a series of nontarget protein binding sites of each drug were calculated. Statistical analyses confirmed a close relationship between the studied 177 major effect categories and interaction profiles of ca. 1200 FDA-approved small-molecule drugs. On the basis of this relationship, the effect profiles of drugs were revealed in their entirety, and hitherto uncovered effects could be predicted in a systematic manner. Our results show that the prediction power is independent of the composition of the protein set used for interaction profile generation.