Structural correlations in bacterial metabolic networks

<p>Abstract</p> <p>Background</p> <p>Evolution of metabolism occurs through the acquisition and loss of genes whose products acts as enzymes in metabolic reactions, and from a presumably simple primordial metabolism the organisms living today have evolved complex and highly variable metabolisms. We have studied this phenomenon by comparing the metabolic networks of 134 bacterial species with known phylogenetic relationships, and by studying a neutral model of metabolic network evolution.</p> <p>Results</p> <p>We consider the 'union-network' of 134 bacterial metabolisms, and also the union of two smaller subsets of closely related species. Each reaction-node is tagged with the number of organisms it belongs to, which we denote organism degree (OD), a key concept in our study. Network analysis shows that common reactions are found at the centre of the network and that the average OD decreases as we move to the periphery. Nodes of the same OD are also more likely to be connected to each other compared to a random OD relabelling based on their occurrence in the real data. This trend persists up to a distance of around five reactions. A simple growth model of metabolic networks is used to investigate the biochemical constraints put on metabolic-network evolution. Despite this seemingly drastic simplification, a 'union-network' of a collection of unrelated model networks, free of any selective pressure, still exhibit similar structural features as their bacterial counterpart.</p> <p>Conclusions</p> <p>The OD distribution quantifies topological properties of the evolutionary history of bacterial metabolic networks, and lends additional support to the importance of horizontal gene transfer during bacterial metabolic evolution where new reactions are attached at the periphery of the network. The neutral model of metabolic network growth can reproduce the main features of real networks, but we observe that the real networks contain a smaller common core, while they are more similar at the periphery of the network. This suggests that natural selection and biochemical correlations can act both to diversify and to narrow down metabolic evolution.</p

Path to Facilitate the Prediction of Functional Amino Acid Substitutions in Red Blood Cell Disorders – A Computational Approach

A major area of effort in current genomics is to distinguish mutations that are functionally neutral from those that contribute to disease. Single Nucleotide Polymorphisms (SNPs) are amino acid substitutions that currently account for approximately half of the known gene lesions responsible for human inherited diseases. As a result, the prediction of non-synonymous SNPs (nsSNPs) that affect protein functions and relate to disease is an important task.In this study, we performed a comprehensive analysis of deleterious SNPs at both functional and structural level in the respective genes associated with red blood cell metabolism disorders using bioinformatics tools. We analyzed the variants in Glucose-6-phosphate dehydrogenase (G6PD) and isoforms of Pyruvate Kinase (PKLR & PKM2) genes responsible for major red blood cell disorders. Deleterious nsSNPs were categorized based on empirical rule and support vector machine based methods to predict the impact on protein functions. Furthermore, we modeled mutant proteins and compared them with the native protein for evaluation of protein structure stability.We argue here that bioinformatics tools can play an important role in addressing the complexity of the underlying genetic basis of Red Blood Cell disorders. Based on our investigation, we report here the potential candidate SNPs, for future studies in human Red Blood Cell disorders. Current study also demonstrates the presence of other deleterious mutations and also endorses with in vivo experimental studies. Our approach will present the application of computational tools in understanding functional variation from the perspective of structure, expression, evolution and phenotype

The structure of pyruvate kinase from Leishmania mexicana reveals details of the allosteric transition and unusual effector specificity

Glycolysis occupies a central role in cellular metabolism, and is of particular importance for the catabolic production of ATP in protozoan parasites such as Leishmania and Trypanosoma. In these organisms pyruvate kinase plays a key regulatory role, and is unique in responding to fructose 2,6-bisphosphate as allosteric activator. The determination of the first eukaryotic pyruvate kinase crystal structure in the T-state is reported. A comparison of the leishmania and yeast R-state enzymes reveals fewer differences than the previous comparison of Escherichia coli T-state and rabbit muscle non-allosteric enzymes. Structural changes related to the allosteric transition can therefore be distinguished from those that are a consequence of the inherent wide structural divergence between bacterial and mammalian proteins. The allosteric transition involves significant changes in a tightly packed array of eight alpha helices at the interface near the catalytic site. At the other interface the allosteric transition appears to be accompanied by the bending of a ten-stranded intersubunit beta sheet adjacent to the effector site. Helix Cell makes contacts to the N-terminal helical domain and bridges both interfaces. A comparison of the effector sites of the leishmania and yeast enzymes reveals the structural basis for the different effector specificity. Two loops comprising residues 443-453 and 480-489 adopt very different conformations in the two enzymes, and Lys453 and His480 that are a feature of trypanosomatid enzymes provide probable ligands for the 2-phospho group of the effector molecule. These differences offer an opportunity for the design of drugs that would bind to the trypanosomatid enzymes but not to those of the mammalian host. (C) 1999 Academic Press