Exploration of novel antimicrobial drug targets is required for building a new defense against threats posed by pathogens with natural or engineered antibiotic-resistance. In our previous work, we used comparative and functional genomics to identify, prioritize, and validate candidate drug targets among the key enzymes in the biosynthesis of indispensable adenylate-containing cofactors. Nicotinate Mononucleotide Adenylyltransferase (NMNAT), a key enzyme in NAD biosynthesis, highly conserved in a broad range of bacterial pathogens, was chosen as the most promising target. The major goal of the proposed project is to develop efficient inhibitors targeting this enzyme in bacterial pathogens, potential agents of biological warfare, as prototypes for new antibiotics. To address this goal, we will use an integrated approach based on comparative structural, functional, and computational analysis techniques. A choice of NMNAT family is supported by our preliminary results, which include kinetic and structural analysis of bacterial orthologs and analogous human enzymes (counter-targets), and the first verified inhibitors predicted by in silico screening of compound libraries. Recently, one of these inhibitors was shown to strongly suppress the growth of gram-positive bacteria in culture. Our research work will be structured around the following Specific Aims: (I) Functional analysis of representative target enzymes. Cloning, overexpression, purification and kinetic analysis of 10 representative NMNAT target enzymes tentatively identified by genomic searches in NIAID priority bacterial pathogens of categories A and B. (II) 3D structural analysis of selected target enzymes and structure-based inhibitor design. An in silico screening of 3,000,000 known chemical compounds will be performed using structural templates derived from the comparative analysis of representative bacterial targets and human counter-targets. (Ill) Experimental testing, kinetic and structural analysis of enzyme-inhibitor interactions. A combination of computer-assisted modeling, virtual screening, inhibitory analysis, co-crystallization, and 3D structural analysis will be used for iterative optimization of highly ranked NMNAT inhibitors. Inhibitor testing will include ex vivo experiments in gram-positive and gram-negative bacterial models. In addition to setting the stage for the development of new antibiotics, this study will impact our understanding of an important class of key biosynthetic enzymes in the vitamin/cofactor metabolism of bacterial pathogens.
