Design of novel inhibitors of DNA topoisomerases using computer-aided methods

Abstract

Humans possess two main types of topoisomerase (Top) enzymes, Top1 and Top2, which have different structures and mechanisms of action. Both Top1 and Top2 are over-expressed in tumour cells and therefore important targets in anticancer therapy. Several topoisomerase inhibitors are used clinically. However, their use is limited due to side effects and drug resistance. Hence, the search for novel Top inhibitors is ongoing. In particular, the development of dual Top1/Top2 inhibitors is believed to be associated with advantageous drugs displaying improved anticancer activity and reduced drug resistance problems. This study reports the use of computer-aided drug design methods to discover novel Top1, Top2 and dual inhibitors. In particular, available ligand and crystal structure information was analysed and used to develop ligand- and complex-based pharmacophores which were applied in database screening of the National Cancer Institute (NCI, USA) database. To filter the hits obtained, docking, 2D-similarity methods, druglikeness filters and expert selection were used. Structurally novel potential Top1 and Top2 inhibitors were identified by the study and, in case of Top1, the activity of the hits was confirmed in in vitro enzyme inhibition and cytotoxicity assays performed at the National Cancer Institute (USA). Furthermore, the performance of the developed pharmacophores and the docking protocols used was evaluated in a retrospective analysis based on selected test set compounds. As an alternative approach, pharmacophore models for Top1 were also generated in a purely structure-based manner, based on binding pocket interaction maps. Different approaches to cluster and select pharmacophore features were investigated, including hierarchical clustering methods, energy calculations and the use of pharmacophore subsets. In addition, the performance of structure-based pharmacophores was investigated in prospective and retrospective analyses. In the final part of the study, all methods developed for Top1 and Top2 were combined to suggest novel dual topoisomerase inhibitors. In conclusion, this study presents the application of computer-aided drug design techniques which led to the identification of structurally novel Top1, Top2 and dual inhibitors worthy of further investigation as potential anticancer agents.