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: October, 2010

End Date: October, 2016

Project 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.