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PDB Reference: nicotinic acid mononucleotide adenylyltransferase, 3dv2, r3dv2sf.Nicotinic acid mononucleotide adenylyltransferase (NaMNAT; EC 2.7.7.18) is the penultimate enzyme in the biosynthesis of NAD + and catalyzes the adenylation of nicotinic acid mononucleotide (NaMN) by ATP to form nicotinic acid adenine dinucleotide (NaAD). This enzyme is regarded as a suitable candidate for antibacterial drug development; as such, Bacillus anthracis NaMNAT (BA NaMNAT) was heterologously expressed in Escherichia coli for the purpose of inhibitor discovery and crystallography. The crystal structure of BA NaMNAT was determined by molecular replacement, revealing two dimers per asymmetric unit, and was refined to an R factor and R free of 0.228 and 0.263, respectively, at 2.3 Å resolution. The structure is very similar to that of B. subtilis NaMNAT (BS NaMNAT), which is also a dimer, and another independently solved structure of BA NaMNATrecently released from the PDB along with two ligated forms. Comparison of these and other less related bacterial NaMNAT structures support the presence of considerable conformational heterogeneity and flexibility in three loops surrounding the substrate-binding area.

Adenosine kinase (Ado kinase) from Mycobacterium tuberculosis is structurally and biochemically unique from other known Ado kinases. This purine salvage enzyme catalyzes the first step in the conversion of the adenosine analog, 2-methyl-Ado (methyl-Ado), into a metabolite with antitubercular activity. Methyl-Ado has provided proof of concept that the purine salvage pathway from M. tuberculosis may be utilized for the development of antitubercular compounds with novel mechanisms of action. In order to utilize this enzyme, it is necessary to understand the topography of the active site to rationally design compounds that are more potent and selective substrates for Ado kinase. A previous structure-activity relationship identified modifications to the base moiety of adenosine (Ado) that result in substrate and inhibitor activity. In an extension of that work, sixtytwo Ado analogs with modifications to the ribofuranosyl moiety, modifications to the base and ribofuranosyl moiety, or modifications to the glycosidic bond position have been analyzed as substrates and inhibitors of M. tuberculosis Ado kinase. A subset of these compounds was further analyzed in human Ado kinase for the sake of comparison. Although no modifications to the ribose moiety resulted in compounds as active as Ado, the best substrates identified were carbocyclic-Ado, 8-aza-carbocyclic-Ado, and 9-[α-L-lyxofuranosyl]-adenine with 38%, 4.3%, and 3.8% of the activity of Ado respectively. The most potent inhibitor identified, 5′-amino-5′-deoxy-Ado, had a K i = 0.8 μM and a competitive mode of inhibition. MIC studies demonstrated that poor substrates could still have potent antitubercular activity.

Advances in genomics have yielded entire genetic sequences for a variety of prokaryotic and eukaryotic organisms. This accumulating information has escalated the demands for three-dimensional protein structure determinations. As a result, high-throughput structural genomics has become a major international research focus. This effort has already led to several significant improvements in X-ray crystallographic and nuclear magnetic resonance methodologies. Crystallography is currently the major contributor to three-dimensional protein structure information. However, the production of soluble, purified protein and diffraction-quality crystals are clearly the major roadblocks preventing the realization of high-throughput structure determination. This paper discusses a novel approach that may improve the efficiency and success rate for protein crystallization. An automated nanodispensing system is used to rapidly prepare crystallization conditions using minimal sample. Proteins are subjected to an incomplete factorial screen (balanced parameter screen), thereby efficiently searching the entire "crystallization space" for suitable conditions. The screen conditions and scored experimental results are subsequently analyzed using a neural network algorithm to predict new conditions likely to yield improved crystals. Results based on a small number of proteins suggest that the combination of a balanced incomplete factorial screen and neural network analysis may provide an efficient method for producing diffraction-quality protein crystals.