(574l) Challenges to Using Mechanisms of Action to Quantify Efficacy of Nucleoside-Analogue Reverse Transcriptase Inhibitors

Authors: 
Monaco, J. - Presenter, Undergraduate student
Khalili, S. - Presenter, The Pennsylvania State University
Armaou, A. - Presenter, Pennsylvania State University


In this work, the mechanisms by which nucleoside-analogue reverse transcriptase inhibitors (NRTIs), the most common class of drugs used in the treatment of HIV-1 exerts their antiviral effects are thoroughly analyzed. We subsequently seek to identify ways in which these known mechanisms could be employed to generate mathematical models for drug efficacy in terms of measurable physical values.

NRTIs are congeners of natural nucleotides that cannot form 3'-5'linkages, and function by competing with natural nucleotides for incorporation into the HIV genome during its reverse transcription. It is demonstrated that the probability of an RTI inclusion instead of its natural nucleotide can be expressed in terms of intracellular drug concentrations, natural nucleotide concentrations, and relevant rate constants derived from Reverse Transcriptase's mechanism of nucleotide addition. Unfortunately the probability of NTRI inclusion is only half of the puzzle. In order to determine the ultimate effect, the resistance of the NTRI to removal from the genome must be considered.

It is demonstrated that under certain idealized conditions, this mechanism is reducible to a simple mathematical expression: If each RTI incorporation might be assumed to carry with it some probability of permanently disabling the developing HIV genome, then efficacy and drug concentration can be shown to have a power relationship, while efficacy and natural nucleotide concentration have an inverse power relationship. However, detailed modeling of the entire process will require well informed in sillico simulations. While technically feasible, such simulation appears to require the collection of more physical data than is currently available. Under certain assumptions for the values of physical parameters, the use of stochastic simulations is demonstrated to quantify the relationship between NRTI efficacy and concentration