Lipophilic guanylhydrazone analogues as promising trypanocidal agents: An extended SAR study

Sleeping sickness and Chagas disease, caused by the tropical parasites Trypanosoma brucei and Trypanosoma cruzi, constitute a significant socioeconomic burden in low-income countries of sub-Saharan Africa and Latin America, respectively. Drug development for treating these diseases is underfunded. Moreover, current treatments are outdated and difficult to administer, while drug resistance is an emerging concern. In this report, a team of researchers lead by Dr. Grigoris Zoidis at the National and Kapodistrian University of Athens (Athens, Greece), in collaboration with researchers at the Ruder Boskovic Institute (Zagreb (Croatia), and the London School of Hygiene and Tropical Medicine (London, United Kingdom) have attempted to extend the structure-activity relationship (SAR) analysis of a number of lipophilic guanylhydrazone analogues with respect to in vitro growth inhibition of T. brucei and T. cruzi. The synthesis of adamantane-based compounds that have potential as antitrypanosomal agents has been extensively reviewed by the team. The researchers also investigated the critical role of the adamantane ring by synthesizing and testing a number of novel lipophilic guanylhydrazones. The introduction of hydrophobic bulky substituents onto the adamantane ring generated the most active analogues, illustrating the synergistic effect of the lipophilic character of the C1 side chain and guanylhydrazone moiety on trypanocidal activity. In their study, the n-decyl C1-substituted compound G8 proved to be the most potent adamantane derivative against T. brucei with activity in the nanomolar range (EC50=90 nM). Molecular simulations were also performed to better understand the structure-activity relationships between the studied guanylhydrazone analogues and their potential enzyme target.

Keywords: Adamantane, S-adenosylmethionine decarboxylase (AdoMetDC), guanylhydrazones, structure-activity relationships, trypanocidal agents, kernel-based partial least squares regression, szmap, hydration analysis, docking-scoring calculations.

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