1,721,621 research outputs found
Structure of FAD-bound L-aspartate oxidase: insight into substrate specificity and catalysis
No full textL-Aspartate oxidase (Laspo) catalyzes the conversion of L-Asp to iminoaspartate, the first step in the de novo biosynthesis of NAD(+). This bacterial pathway represents a potential drug target since it is absent in mammals. The Laspo R386L mutant was crystallized in the FAD-bound catalytically competent form and its three-dimensional structure determined at 2.5 A resolution in both the native state and in complex with succinate. Comparison of the R386L holoprotein with the wild-type apoenzyme [Mattevi, A., Tedeschi, G., Bacchella, L., Coda, A., Negri, A., and Ronchi, S. (1999) Structure 7, 745-756] reveals that cofactor incorporation leads to the ordering of two polypeptide segments (residues 44-53 and 104-141) and to a 27 degree rotation of the capping domain. This motion results in the formation of the active site cavity, located at the interface between the capping domain and the FAD-binding domain. The structure of the succinate complex indicates that the cavity surface is decorated by two clusters of H-bond donors that anchor the ligand carboxylates. Moreover, Glu121, which is strictly conserved among Laspo sequences, is positioned to interact with the L-Asp alpha-amino group. The architecture of the active site of the Laspo holoenzyme is remarkably similar to that of respiratory fumarate reductases, providing strong evidence for a common mechanism of catalysis in Laspo and flavoproteins of the succinate dehydrogenase/fumarate reductase family. This implies that Laspo is mechanistically distinct from other flavin-dependent amino acid oxidases, such as the prototypical D-amino acid oxidase
Degenerate (r-2)-dimensional subvarieties through the generic hyperplane section of a reduced irreducible complex curve in P^r
No full text
Interaction in agent-based economics: A survey on the network approach
No full textIn this paper we aim to introduce the reader to some basic concepts and instruments used in a wide range of economic networks models. In particular, we adopt the theory of random networks as the main tool to describe the relationship between the organization of interaction among individuals within different components of the economy and overall aggregate behavior. The focus is on the ways in which economic agents interact and the possible consequences of their interaction on the system. We show that network models are able to introduce complex phenomena in economic systems by allowing for the endogenous evolution of networks
Major trends in agent-based economics
No full textThe study of the economy by means of Agent-Based (AB) models is a relatively
new field. It dates back to the early 90’s, when the increasing availability of cheap
computing power has made possible to undertake the first computationally demanding
experiments required tomodel the interactions of a large number of boundedly rational
and heterogeneous agents (for a review, see Tesfatsion and Judd 2006), in an economy
characterized by non-equilibrium dynamics and information asymmetries
The impact of classes of innovators on Technology, Financial Fragility and Economic Growth
No full textIn this paper, we study innovation processes and technological change in an agent-based model. By including a behavioral switching among heterogeneous innovative firms, which can endogenously change among three different classes (single innovators, collaborative innovators and imitators) on the base of their R&D expenditures, the model is able to replicate, via simulations, well known industrial dynamic and growth type stylized facts. Moreover, we focus the analysis on the impact of these three innovation categories on micro, meso and macro aggregates. We find that collaborative companies are those having the highest positive impact on the economic system. The model is then used to study the effect that different innovation policies have on macroeconomic performance
Systemic risk on different interbank network topologies
No full textIn this paper we develop an interbank market with heterogeneous financial institutions that enter into lending agreements on different network structures. Credit relationships (links) evolve endogenously via a fitness mechanism based on agents' performance. By changing the agent's trust on its neighbor's performance, interbank linkages self-organize themselves into very different network architectures, ranging from random to scale-free topologies. We study which network architecture can make the financial system more resilient to random attacks and how systemic risk spreads over the network. To perturb the system, we generate a random attack via a liquidity shock. The hit bank is not automatically eliminated, but its failure is endogenously driven by its incapacity to raise liquidity in the interbank network. Our analysis shows that a random financial network can be more resilient than a scale free one in case of agents' heterogeneity. © 2012 Elsevier B.V. All rights reserved
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