Genomics-driven growth in the number of enzymes of unknown function has created a need for better strategies to characterize them. Since enzyme inhibitors have traditionally served this purpose, we present here an efficient systems-based inhibitor design strategy, enabled by bioinformatic and NMR structural developments. First, we parse the oxidoreductase gene family into structural subfamilies termed pharmacofamilies, which share pharmacophore features in their cofactor binding sites. Then we identify a ligand for this site and use NMR-based binding site mapping (NMR SOLVE) to determine where to extend a combinatorial library, such that diversity elements are directed into the adjacent substrate site. The cofactor mimic is reused in the library in a manner that parallels the reuse of cofactor domains in the oxidoreductase gene family. A library designed in this manner yielded specific inhibitors for multiple oxidoreductases.
A novel method to organize protein structural information based solely on sequence is presented. The method clusters proteins into families that correlate with the three-dimensional protein structure and the conformation of the bound ligands. This procedure was applied to nicotinamide adenine dinucleotide [NAD(P)]-utilizing enzymes to identify a total of 94 sequence families, 53 of which are structurally characterized. Each of the structurally characterized proteins within a sequence family correlates to a single protein fold and to a common bound conformation of NAD(P). A wide range of structural folds is identified that recognize NAD(P), including Rossmann folds and beta/alpha barrels. The defined sequence families can be used to identify the type and prevalence of NAD(P)-utilizing enzymes in the proteomes of sequenced organisms. The proteome of Mycobacterium tuberculosis was mined to generate a proteome-wide profile of NAD(P)-utilizing enzymes coded by this organism. This enzyme family comprises approximately 6% of the open reading frames, with the largest subgroup being the Rossmann fold, short-chain dehydrogenases. The preponderance of short-chain dehydrogenases correlates strongly with the phenotype of M. tuberculosis, which is characterized as having one of the most complex prokaryotic cell walls.
Enzymes that utilize nicotinamide adenine dinucleotide (NAD) or its 2'-phosphate derivative (NADP) are found throughout the kingdoms of life. These enzymes are fundamental to many biochemical pathways, including central intermediary metabolism and mechanisms for cell survival and defense. The complete genomes of 25 organisms representing bacteria, protists, fungi, plants, and animals, and 811 viruses, were mined to identify and classify NAD(P)-dependent enzymes. An average of 3.4% of the proteins in these genomes was categorized as NAD(P)-utilizing proteins, with highest prevalence in the medium-chain oxidoreductase and short-chain oxidoreductase families. In general, the distribution of these enzymes by oxidoreductase family was correlated to the number of different catalytic mechanisms in each family. Organisms with smaller genomes encoded a larger proportion of NAD(P)-dependent enzymes in their proteome (approximately 6%) as compared to the larger genomes of eukaryotes (approximately 3%). Among viruses, those with large, double-strand DNA genomes were shown to encode oxidoreductases. Gram-positive and gram-negative bacteria showed some differences in the distribution of NAD(P)-dependent proteins. Several organisms such as M. tuberculosis, P. falciparum, and A. thaliana showed unique distributions of oxidoreductases corresponding to some phenotypic features.
Genome sequencing projects have dramatically increased our understanding of the pathways and proteins involved in biological systems. The NAD(P)-utilizing family of enzymes is one of the most important gene families representing 15% of all known enzyme functions. We have performed a complete characterization of this gene family on a sequence, structural, and NAD(P)-pharmacophore level. Genome-wide analysis was performed to gain a complete understanding of the structures and functional importance of NAD(P)-utilizing enzymes in 17 different genomes.
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