Synthesis,Biological Evaluation of 1,1‐Diarylethylenes as a Novel Class of Antimitotic Agents

The cytotoxic activities of 23 new isocombretastatin A derivatives with modifications on the B‐ring were investigated. Several compounds exhibited excellent antiproliferative activity at nanomolar concentrations against a panel of human cancer cell lines. Compounds isoFCA‐4 ( 2 e ), isoCA‐4 ( 2 k ) and isoNH₂CA‐4 ( 2 s ) were the most cytotoxic, and strongly inhibited tubulin polymerization with IC₅₀ values of 4, 2 and 1.5 μM , respectively. These derivatives were found to be 10‐fold more active than phenstatin and colchicine with respect to growth inhibition but displayed similar activities as tubulin polymerization inhibitors. In addition, cell cycle arrest in the G₂/M phase and subsequent apoptosis was observed in three cancer cell lines when treated with these compounds. The disruptive effect of 2 e , 2 k and 2 s on the vessel‐like structures formed by human umbilical vein endothelial cells (HUVEC) suggest that these compounds may act as vascular disrupting agents. Both compounds 2 k and 2 s have the potential for further prodrug modification and development as vascular disrupting agents for treatment of solid tumors.     

Synthesis and Biological Evaluation of Chromium Bioorganometallics Based on the Antibiotic Platensimycin Lead Structure

The recent discovery of the natural product platensimycin as a new antibiotic lead structure has triggered the synthesis of numerous organic derivatives for structure–activity relationship studies. Herein, we describe the synthesis, characterization and biological evaluation of the first organometallic antibiotic inspired by platensimycin. Two bioorganometallic compounds containing (η⁶‐pentamethylbenzene)Cr(CO)₃ ( 2 ) and (η⁶‐benzene)Cr(CO)₃ ( 3 ), linked by an amide bond to the aromatic part of platensimycin, were synthesized. Their antibiotic activities were tested against B. subtilis 168 (Gram positive) and E. coli W3110 (Gram negative) bacterial strains. Both compounds were found to be inactive against E. coli but derivative 2 inhibits B. subtilis growth at a moderate MIC value of 0.15 mM . To test the intrinsic toxicity of chromium, several chromium salts along with {η⁶‐(3‐pentamethylphenyl propionic acid)}Cr(CO)₃ ( 5 ) and {η⁶‐(3‐phenyl propionic acid)}Cr(CO)₃ ( 6 ) were tested against both bacterial strains. No activity was observed against E. coli for any of the compounds; B. subtilis growth was not inhibited by Cr(NO₃)₃ and only very weakly by 5 , K₂Cr₂O₇ and Na₂CrO₄ at MIC values of 0.5, 0.68 and 1.24 mM , respectively. Compounds 2 , 3 , 5 and 4 (the pure organic analogue of 2 ) show similar cytotoxicity against HeLa, HepG2 and HT‐29 mammalian cell lines. Furthermore, the cellular uptake and the intracellular distribution of compounds 2 , 3 and Cr(NO₃)₃ in B. subtilis were studied using atomic absorption spectroscopy to gain insight in to the possible cellular targets. Compound 2 was found to be readily taken up and distributed almost equally among cytosol, cell debris and cell membrane in B. subtilis.     

From Structure–Activity to Structure–Selectivity Relationships: Quantitative Assessment,Selectivity Cliffs,and Key Compounds

The exploration of structure–activity relationships (SARs) in chemical lead optimization is mostly focused on activity against single targets. Because many active compounds have the potential to act against multiple targets, achieving a sufficient degree of target selectivity often becomes a major issue during optimization. Herein we report a data analysis approach to explore compound selectivity in a systematic and quantitative manner. Sets of compounds that are active against multiple targets provide a basis for exploring structure–selectivity relationships (SSRs). Compound similarity and selectivity data are analyzed with the aid of network‐like similarity graphs (NSGs), which organize molecular networks on the basis of similarity relationships and SAR index (SARI) values. For this purpose, the SARI framework has been adapted to quantify SSRs. Using sets of compounds with differential activity against four cathepsin thiol proteases, we show that SSRs can be quantitatively described and categorized. Furthermore, local SSR environments are identified, the analysis of which provides insight into compound selectivity determinants at the molecular level. These environments often contain “selectivity cliffs” formed by pairs or groups of similar compounds with significantly different selectivity. Moreover, key compounds are identified that determine characteristic features of single‐target SARs and dual‐target SSRs. The comparison of compounds involved in the formation of selectivity cliffs often reveals chemical modifications that render compounds target selective.