Evolutionary and molecular foundations of multiple contemporary functions of the nitroreductase superfamily.

Insight regarding how diverse enzymatic functions and reactions have evolved from ancestral scaffolds is fundamental to understanding chemical and evolutionary biology, and for the exploitation of enzymes for biotechnology. We undertook an extensive computational analysis using a unique and comprehensive combination of tools that include large-scale phylogenetic reconstruction to determine the sequence, structural, and functional relationships of the functionally diverse flavin mononucleotide-dependent nitroreductase (NTR) superfamily (>24,000 sequences from all domains of life, 54 structures, and >10 enzymatic functions). Our results suggest an evolutionary model in which contemporary subgroups of the superfamily have diverged in a radial manner from a minimal flavin-binding scaffold. We identified the structural design principle for this divergence: Insertions at key positions in the minimal scaffold that, combined with the fixation of key residues, have led to functional specialization. These results will aid future efforts to delineate the emergence of functional diversity in enzyme superfamilies, provide clues for functional inference for superfamily members of unknown function, and facilitate rational redesign of the NTR scaffold

Functional and computational identification of a rescue mutation near the active site of an mRNA methyltransferase

RNA-based drugs are an emerging class of therapeutics combining the immense potential of DNA gene-therapy with the absence of genome integration-associated risks. While the synthesis of such molecules is feasible, large scale in vitro production of humanised mRNA remains a biochemical and economical challenge. Human mRNAs possess two post-transcriptional modifcations at their 5′ end: an inverted methylated guanosine and a unique 2′O-methylation on the ribose of the penultimate nucleotide. One strategy to precisely methylate the 2′ oxygen is to use viral mRNA methyltransferases that have evolved to escape the host’s cell immunity response following virus infection. However, these enzymes are ill-adapted to industrial processes and sufer from low turnovers. We have investigated the efects of homologous and orthologous active-site mutations on both stability and transferase activity, and identifed new functional motifs in the interaction network surrounding the catalytic lysine. Our fndings suggest that despite their low catalytic efciency, the active-sites of viral mRNA methyltransferases have low mutational plasticity, while mutations in a defned third shell around the active site have strong efects on folding, stability and activity in the variant enzymes, mostly via network-mediated efects

Previsão e análise da estrutura e dinâmica de redes biológicas

Increasing knowledge about the biological processes that govern the dynamics of living organisms has fostered a better understanding of the origin of many diseases as well as the identification of potential therapeutic targets. Biological systems can be modeled through biological networks, allowing to apply and explore methods of graph theory in their investigation and characterization. This work had as main motivation the inference of patterns and rules that underlie the organization of biological networks. Through the integration of different types of data, such as gene expression, interaction between proteins and other biomedical concepts, computational methods have been developed so that they can be used to predict and study diseases. The first contribution, was the characterization a subsystem of the human protein interactome through the topological properties of the networks that model it. As a second contribution, an unsupervised method using biological criteria and network topology was used to improve the understanding of the genetic mechanisms and risk factors of a disease through co-expression networks. As a third contribution, a methodology was developed to remove noise (denoise) in protein networks, to obtain more accurate models, using the network topology. As a fourth contribution, a supervised methodology was proposed to model the protein interactome dynamics, using exclusively the topology of protein interactions networks that are part of the dynamic model of the system. The proposed methodologies contribute to the creation of more precise, static and dynamic biological models through the identification and use of topological patterns of protein interaction networks, which can be used to predict and study diseases.O conhecimento crescente sobre os processos biológicos que regem a dinâmica dos organismos vivos tem potenciado uma melhor compreensão da origem de muitas doenças, assim como a identificação de potenciais alvos terapêuticos. Os sistemas biológicos podem ser modelados através de redes biológicas, permitindo aplicar e explorar métodos da teoria de grafos na sua investigação e caracterização. Este trabalho teve como principal motivação a inferência de padrões e de regras que estão subjacentes à organização de redes biológicas. Através da integração de diferentes tipos de dados, como a expressão de genes, interação entre proteínas e outros conceitos biomédicos, foram desenvolvidos métodos computacionais, para que possam ser usados na previsão e no estudo de doenças. Como primeira contribuição, foi proposto um método de caracterização de um subsistema do interactoma de proteínas humano através das propriedades topológicas das redes que o modelam. Como segunda contribuição, foi utilizado um método não supervisionado que utiliza critérios biológicos e topologia de redes para, através de redes de co-expressão, melhorar a compreensão dos mecanismos genéticos e dos fatores de risco de uma doença. Como terceira contribuição, foi desenvolvida uma metodologia para remover ruído (denoise) em redes de proteínas, para obter modelos mais precisos, utilizando a topologia das redes. Como quarta contribuição, propôs-se uma metodologia supervisionada para modelar a dinâmica do interactoma de proteínas, usando exclusivamente a topologia das redes de interação de proteínas que fazem parte do modelo dinâmico do sistema. As metodologias propostas contribuem para a criação de modelos biológicos, estáticos e dinâmicos, mais precisos, através da identificação e uso de padrões topológicos das redes de interação de proteínas, que podem ser usados na previsão e no estudo doenças.Programa Doutoral em Engenharia Informátic

Global existence results for complex hyperbolic models of bacterial chemotaxis

Bacteria are able to respond to environmental signals by changing their rules of movement. When we take into account chemical signals in the environment, this behaviour is often called chemotaxis. At the individual-level, chemotaxis consists of several steps. First, the cell detects the extracellular signal using receptors on its membrane. Then, the cell processes the signal information through the intracellular signal transduction network, and finally it responds by altering its motile behaviour accordingly. At the population level, chemotaxis can lead to aggregation of bacteria, travelling waves or pattern formation, and the important task is to explain the population-level behaviour in terms of individual-based models. It has been previously shown that the transport equation framework is suitable for connecting different levels of modelling of bacterial chemotaxis. In this paper, we couple the transport equation for bacteria with the (parabolic/elliptic) equation for the extracellular signals. We prove global existence of solutions for the general hyperbolic chemotaxis models of cells which process the information about the extracellular signal through the intracellular biochemical network and interact by altering the extracellular signal as well. The conditions for global existence in terms of the properties of the signal transduction model are given.Comment: 22 pages, submitted to Discrete and Continuous Dynamical Systems Series

Structure and mechanism to function: allosteric activation of phosphomannomutase 1 and substrate selectivity in Hotdog Fold thioesterases

Two superfamilies were used to explore the structure/function relationship as it pertains to enzyme specificity. The structures and mechanisms of phosphatases belonging to the Haloalkanoate Dehalogenase Superfamily (HADSF) and thioesterases of the Hotdog Fold Superfamily (HDFSF) were determined using X-ray crystallography and other biophysical tools in combination with steady-state kinetics and site-directed mutagenesis. Together, the specific structural components of enzymes crucial for substrate recognition, substrate promiscuity, and catalysis were uncovered. In the HADSF, the phosphomannomutases (PMMs) catalyze the interconversion of mannose 6-phosphate and mannose 1-phosphate, an essential step in the protein glycosylation pathway. In humans, two isoforms PMM1 and PMM2 catalyze this reaction. Deficiency in PMM2 activity is the major cause of congenital disorders of glycosylation (CDG-1a). However, PMM1 activity is not sufficient to replace PMM2 in protein glycosylation. Instead, PMM1 functions as a glucose-1,6-bisphosphate phosphatase in the presence of IMP and enables the temporary rescue of glycolysis during brain ischemia. Herein, the structure of IMP bound to PMM1 in combination with kinetics revealed a mechanism for the differential substrate preference and the mechanistic switch from a mutase to phosphatase activity. In the HDFSF, the majority of which function as thioesterases of aliphatic or aromatic compounds bound to coenzyme A or acyl carrier protein (ACP), the structural determinants for substrate preference were identified in PA1618, an enzyme with high substrate promiscuity. The structural determinants of the specific thiosterases MA0038 and BVU1957 were also identified. The variation in substrate range observed among these enzymes, from specific to promiscuous, led to the design of a comprehensive thioester screen to identify HDFSF thioesterase substrates. The profiles of substrate specificities from 42 previously uncharacterized thioesterases were determined allowing comparison of the sequence/substrate relationships across a representative selection of thioesterases. Examples drawn from both HADSF and HDFSF enzymes suggested a model relating substrate promiscuity and specificity to regions of protein flexibility. The motion of a domain within a multidomain protein or a flexible loop near the active site was correlated with the occurrence of substrate promiscuity/specificity

Implications of divergence of methionine adenosyltransferase in archaea

Methionine adenosyltransferase (MAT) catalyzes the biosynthesis of S-adenosylmethionine from L-methionine and adenosine triphosphate. MAT enzymes are ancient, believed to share a common ancestor, and are highly conserved in all three domains of life. However, the sequences of archaeal MATs show considerable divergence compared to their bacterial and eukaryotic counterparts. Furthermore, the structural and functional significance of this sequence divergence are not well understood. In the present study, we employed structural analysis and ancestral sequence reconstruction (ASR) to investigate archaeal MAT divergence. We observed that the dimer interface containing the active site (which is usually well-conserved) diverged considerably between the bacterial/eukaryotic MATs and archaeal MAT. A detailed investigation of the available structures supports the sequence analysis outcome: the protein domains and subdomains of bacterial and eukaryotic MAT are more similar than those of archaea. Finally, we resurrected archaeal MAT ancestors. Interestingly, archaeal MAT ancestors show substrate specificity, which is lost during evolution. This observation supports the hypothesis of a common MAT ancestor for the three domains of life. In conclusion, we have demonstrated that archaeal MAT is an ideal system for studying an enzyme family that evolved differently in one domain compared to others while maintaining the same catalytic activity

Metals in enzyme catalysis and visualization methods

Metal ions play essential roles in biological functions including catalysis, protein stability, DNA-protein interactions and cell signaling. It is estimated that 30% of proteins utilize metals in some fashion. Additionally, methods by which metal ions can be visualized have been utilized to study metal concentrations and localizations in relation to disease. Understanding the roles metals play in biological systems has great potential in medicine and technology. Chapters 1 and 2 of this dissertation analyzes the structure and function of the Mn-dependent enzyme oxalate decarboxylase (OxDc) and Chapter 2 presents a bioinformatic analysis of the cupin superfamily that provides the structural scaffold of the decarboxylase. The X-ray crystal structure of the W132F variant was determined and utilized together with EPR data to develop a computational approach to determining EPR spectra of the enzyme’s two metal-binding centers. Furthermore, a variant in which the catalytic Glu162 was deleted revealed the binding mode of oxalate, the first substrate-bound structure of OxDc. OxDc is a member of the cupin superfamily, which comprises a wide variety of proteins and enzymes with great sequence and functional diversity. A bioinformatics analysis of the superfamily was performed to analyze how sequence variation determines function and metal utilization. Chapters 3 and 4 discuss the expansion of lanthanide-binding tags (LBTs) to in cellulo studies. Lanthanide-binding tags are short sequences of amino acids that have high affinity and selectivity for lanthanide ions. An EGF-LBT construct used to quantify EGF receptors on the surface of A431 and HeLa cells. The results from the LBT quantification are consistent with previous studies of EGFR receptors in these cell types, validating the use of this method for future studies. The potential of using LBTs for X-ray fluorescence microscopy (XFM) was also investigated. LBT-labeled constructs were utilized to investigate if membrane bound as well as cytosolic LBT-containing proteins could be visualized and localized to their cell compartments via XFM; both membrane-localized and cytosolic proteins were successfully visualized. With the high resolution (< 150 Å) obtainable with new synchrotron beamline configurations LBTs could be used to study nanoscale biological structures in their near-native state

Multi-equilibrium property of metabolic networks: Exclusion of multi-stability for SSN metabolic modules

SUMMARY It is a fundamental and important problem whether or not a metabolic network can admit multiple equilibria in a living organism. Due to the complexity of the metabolic network, it is generally a difficult task to study the problem as a whole from both analytical and numerical viewpoints. In this paper, a structure-oriented modularization research framework is proposed to analyze the multi-stability of metabolic networks. We first decompose a metabolic network into four types of basic building blocks (called metabolic modules) according to the particularity of its structure, and then focus on one type of these basic building blocksthe single substrate and single product with no inhibition (SSN) module, by deriving a nonlinear ordinary differential equation (ODE) model based on the Hill kinetics. We show that the injectivity of the vector field of the ODE model is equivalent to the nonsingularity of its Jacobian matrix, which enables us equivalently to convert an unverifiable sufficient condition for the absence of multiple equilibria of an SSN module into a verifiable one. Moreover, we prove that this sufficient condition holds for the SSN module in a living organism. Such a theoretical result not only provides a general framework for modeling metabolic networks, but also shows that the SSN module in a living organism cannot be multi-stable

SmCL3, a Gastrodermal Cysteine Protease of the Human Blood Fluke Schistosoma mansoni

Parasitic infection caused by blood flukes of the genus Schistosoma is a major global health problem. More than 200 million people are infected. Identifying and characterizing the constituent enzymes of the parasite's biochemical pathways should reveal opportunities for developing new therapies (i.e., vaccines, drugs). Schistosomes feed on host blood, and a number of proteolytic enzymes (proteases) contribute to this process. We have identified and characterized a new protease, SmCL3 (for Schistosoma mansoni cathepsin L3), that is found within the gut tissue of the parasite. We have employed various biochemical and molecular biological methods and sequence similarity analyses to characterize SmCL3 and obtain insights into its possible functions in the parasite, as well as its evolutionary position among cathepsin L proteases in general. SmCL3 hydrolyzes major host blood proteins (serum albumin and hemoglobin) and is expressed in parasite life stages infecting the mammalian host. Enzyme substrate specificity detected by positional scanning-synthetic combinatorial library was confirmed by molecular modeling. A sequence analysis placed SmCL3 to the cluster of other cathepsins L in accordance with previous phylogenetic analyses