Synthesis and biological evaluation of selective tubulin inhibitors as anti-trypanosomal agents. Issue 12 (15th June 2017)

• Record Type: Journal Article
• Authors: Bobba, Viharika; Nanavaty, Vishal; Idippily, Nethrie D.; Zhao, Anran; Li, Bibo; Su, Bin
• Is Part Of: Bioorganic & medicinal chemistry. Volume 25:Issue 12(2017)
• Page Start: 3215
• Page End: 3222
• Publication Date: 2017-06-15
• Subjects: Trypanosomiasis -- Tubulin inhibitor -- Selective index -- Drug development; Bioorganic chemistry -- Periodicals; Pharmaceutical chemistry -- Periodicals; Biochemistry -- Periodicals; Chemistry, Clinical -- Periodicals; Chemistry, Organic -- Periodicals; Chimie bio-organique -- Périodiques; Chimie pharmaceutique -- Périodiques; 615.19
• DOI: 10.1016/j.bmc.2017.04.009
• Languages: English
• ISSNs: 0968-0896

Abstract

Graphical abstract: Highlights: A series of sulfonamide tubulin inhibitors were synthesized. The compounds were examined with mammalian cells and trypanosomal cells to identify selective drug candidates. A new analog showed high selectivity and potency against the growth of trypanosome cells. The compound decreased tubulin polymerization in trypanosome cells. Abstract: African trypanosomiasis is still a threat to human health due to the severe side-effects of current drugs. We identified selective tubulin inhibitors that showed the promise to the treatment of this disease, which was based on the tubulin protein structural difference between mammalian and trypanosome cells. Further lead optimization was performed in the current study to improve the efficiency of the drug candidates. We used Trypanosoma brucei brucei cells as the parasite model, and human normal kidney cells and mouse macrophage cells as the host model to evaluate the compounds. One new analog showed great potency with an IC50 of 70 nM to inhibit the growth of trypanosome cells and did not affect the viability of mammalian cells. Western blot analyses reveal that the compound decreased tubulin polymerization in T. brucei cells. A detailed structure activity relationship (SAR) was summarized that will be used to guide future lead optimization.