Activity modeling and simulation of bacterial efflux pump inhibitors based on advanced laser methods
Project code: PN-II-PT-PCCA-2011-3.1-1350
Ctr. No: 85/2012
Funded by: MEN-CD, UEFISCDI
Program: PCCA
Contractor: National Institute of Lasers, Plasma and Radiation Physics
Project Leader: Dr. George Viorel POPESCU
Start Date: July, 2012
End Date: December 2016
Project Executive Summary
Medical research has progressed greatly based on recent advances in genomics and systems biology. New concepts, such as personalized medicine (drug selection based on
individual genomics profile), have emerged while large improvements in drug efficiency is expected from knowledge of organisms' systems biology. We aim at developing a
comprehensive approach that will pave a rational path from genes to drugs using computational (drug-pathogen modeling and simulation) and biophysical (spectral characterization
of drug molecules, analysis of laser-irradiated drugs, testing of drug-pathogen interaction) investigation methods. Starting from initial observations (obtained as part of drug stability
studies) on the interaction of laser-irradiated drugs with pathogens, we have performed molecular docking simulations for screening efflux pump inhibitors. We are proposing here to
further explore the effect of laser radiation on efflux pump inhibitors (EPI) in order to develop predictive methods that use spectral information for computational selection of drugs,
and to develop comprehensive models of drug-pathogen interaction. Such methods can be used for designing new classes of drugs with better target affinity, stability and enhanced
tissue targeting. We propose an implementation of our approach using a large library of available chemical compounds that will include the quinazoline derivatives class. Our work
will include: analysis of laser-irradiated drug reaction pathways, analysis and prediction of drug stability, modeling drug-EPI interaction dynamics and development of drug activity
prediction models based on pharmacophore analysis and spectral information. Testing the predictive power of our method will be done on bacterial strains that overexpress MDR
bacterial pumps, as well as on animal models, using the selected drugs with predicted EPI activity. Finally, we will use our computational method to recommend new chemical compounds with desired EPI activity.
