Telomeres are DNA-protein structures at the ends of linear chromosomes essential for the maintenance of genomic stability. Telomerase activity is non-existent in the majority of normal cells but is activated in 80-85% of tumour cell lines in essentially all types of cancer1. This enzyme functions in cancer cells by maintaining the integrity of the telomeric ends rendering the cells ‘immortal’. The recognition of telomerase as a possible target for the treatment of cancer 20 years ago has stimulated a tremendous amount of research in this area. However, the binding modes and inhibitory mechanism of most classes of telomerase inhibitors are currently unknown. This study was conducted to predict the binding mode of existing telomerase inhibitors and to use the information obtained through ligand based pharmacophore generation in discovering novel telomerase inhibitors. The three main steps used are: selection of training sets based on published data; pharmacophore model generation, screening of virtual databases for novel compounds. Discovery Studio 3.1 software was used to generate pharmacophore models2. In this study, three types of datasets of inhibitors were studied: non-nucleoside, nucleoside and G-quadruplex inhibitors. From the pharmacophore models I have hypothesised the binding modes of nucleoside and non-nucleoside inhibitors. These pharmacophore models provide clues to the different binding modes employed by different classes of telomerase inhibitors. The models developed are being used to search databases for more promising telomerase inhibitors.