Dr Jamie Platts Project Titles
1. Computational Screening of Metal-Based Telomerase Inhibitors.
Abstract: Telomeric DNA and the associated enzyme telomerase are attractive targets for selective anti-cancer drugs, having been described as "a therapeutic target for the third millennium". Human telomeres consist of multiple repeats of the sequence 5'-[TTAGGG]-3', attached to the end of each chromosome, that are designed to protect the chromosome and its genetic data from degradation by environmental effects. In healthy cells, cell division is accompanied by loss of telomeres, such that these have a pre-programmed life span of 20 to 50 divisions. In cancerous cells, however, the ribonucleoprotein telomerase can re-attach the sequence to the chromosome, thus bestowing effective immortality. Transition metal complexes are one class of molecule that show promise as telomerase inhibitors, with metals including platinum, nickel, ruthenium, copper and zinc demonstrating selective inhibition of telomerase at low concentrations. We propose to develop and test molecular modelling approaches that will shed new light onto the mechanism of telomerase inhibition by transition metal complexes. Accurate quantum mechanical methods will be used for detailed study of potential binding modes of transition metal complexes to models of telomeric DNA and telomerase RNA, allowing us to probe the effects of varying complex structure on binding. Data from these studies will also allow us to test and refine parameters for faster empirical methods to treat transition metals, such that much larger systems and their dynamical behaviour can be modelled. By monitoring structural properties over multiple snapshots of thermal motion, we will obtain comprehensive detail on the effect of metallation on telomere structures and hence illuminate a number of important but unanswered questions regarding metal complexes as telomerase inhibitors. Models of activity will also be sought by quantitative structure-activity relation (QSAR) methods, relating calculated properties to activities from in vivo and in vitro assays using appropriate statistical techniques.