Competition Without Chaos

California heralded the New Year with a wave of rolling blackouts, spiraling wholesale electricity prices, and at least one utility bankruptcy. California, which symbolizes the electronic age and represents an eighth of the U.S. economy and its population, faces electricity supply issues not seen since the Great Depression and the collapse of the great utility holding companies. To what extent is California the bellwether for the restructured electric industry in the United States? We do not believe that the recent crisis in California is a signal that competition and deregulation have failed. Indeed, it remains our firm belief that market-oriented restructuring of the electric industry remains the best opportunity to provide consumer benefits and to develop reliable new sources of supply. After all, a major impetus for introducing competition into the generation and marketing of electricity has been the previous failures in long-term planning decisions made by public utilities and their regulators. The regulated monopoly regime simply did not provide the correct economic incentives for a company to provide electric service efficiently. To what extent can other states that have restructured their electric industries expect to see California-like dramatic sustained price increases and supply shortages resulting in rolling blackouts? The root cause of California's problems was its long-term failure to build generating plants during the most sustained economic boom in the state's history. California's most significant restructuring problem was also a local issue. The California restructuring law required utilities collecting stranded costs to retain fixed price obligations to retail customers, while preventing them from hedging their price risk in the wholesale market by entering into long-term supply contracts. The California market design flaws have been avoided in the restructuring legislation enacted by the twenty-four states and the District of Columbia that have restructured electricity markets. Among these states are Pennsylvania and Illinois, the states where Exelon conducts public utility businesses. The restructuring efforts in these other states are generally yielding results quite different from those in California and demonstrate that thoughtful, market-oriented, evolutionary restructuring can work well for all parties. This is not a reason, however, for complacency. Government agencies, utilities and all market stakeholders must work hard to make sure this answer remains valid a few years hence. This work includes establishing appropriate pricing and incentives to encourage the building of new supply and the development of demand-side management programs; establishing regional transmission organizations in order to support the expansion of and appropriate pricing for transmission; establishing appropriate rules and pricing regarding the utilities provider of last resort or default supply obligation. The default supply issue is one of the most significant challenges to the transition to competition. If the delivery companies retain primary responsibility for arranging supply and thus lock up most of the generation sources, the result is reliable service and stable rates for customers. However, new market entrants' access to supply sources will be limited and at high prices, making it difficult for them to compete. To resolve this dilemma, we propose a bifurcated approach to default service offerings and pricing. For large customers, who have the most desirable service characteristics to competitive suppliers and thus more opportunity to hedge their price risk, the utilities' only default service obligation would be unbundled energy at a market price. For mass market customers, who lack hedging ability because of limited, if any, market development, the utilities would provide a fixed price, multi-year energy supply offering. The price for both offerings must include a risk premium adequate to compensate the utility for the risk it assumes and to avoid rates that are too low to allow alternative suppliers to compete. We believe our default supply resolution will achieve the competing goals of price stability, reliability, and the development of a mature competitive market. The California experience is not an accident or the product of bad luck. It is the product of choices, long-term choices about siting generation and transmission, and the more recent choice of a market design that imposed asymmetric risks on utilities to the ultimate detriment of all. If other states make similar choices, similar consequences can be expected to follow. In short, the California experience is no reason to reject restructuring; it is rather a forceful lesson on the importance of doing it right.

Using electrostatic potentials to predict DNA-binding sites on DNA-binding proteins

A method to detect DNA-binding sites on the surface of a protein structure is important for functional annotation. This work describes the analysis of residue patches on the surface of DNA-binding proteins and the development of a method of predicting DNA-binding sites using a single feature of these surface patches. Surface patches and the DNA-binding sites were initially analysed for accessibility, electrostatic potential, residue propensity, hydrophobicity and residue conservation. From this, it was observed that the DNA-binding sites were, in general, amongst the top 10% of patches with the largest positive electrostatic scores. This knowledge led to the development of a prediction method in which patches of surface residues were selected such that they excluded residues with negative electrostatic scores. This method was used to make predictions for a data set of 56 non-homologous DNA-binding proteins. Correct predictions made for 68% of the data set

The European Bioinformatics Institute's data resources: towards systems biology

Genomic and post-genomic biological research has provided fine-grain insights into the molecular processes of life, but also threatens to drown biomedical researchers in data. Moreover, as new high-throughput technologies are developed, the types of data that are gathered en masse are diversifying. The need to collect, store and curate all this information in ways that allow its efficient retrieval and exploitation is greater than ever. The European Bioinformatics Institute's (EBI's) databases and tools have evolved to meet the changing needs of molecular biologists: since we last wrote about our services in the 2003 issue of Nucleic Acids Research, we have launched new databases covering protein–protein interactions (IntAct), pathways (Reactome) and small molecules (ChEBI). Our existing core databases have continued to evolve to meet the changing needs of biomedical researchers, and we have developed new data-access tools that help biologists to move intuitively through the different data types, thereby helping them to put the parts together to understand biology at the systems level. The EBI's data resources are all available on our website at http://www.ebi.ac.uk

Detecting DNA-binding helix–turn–helix structural motifs using sequence and structure information

In this work, we analyse the potential for using structural knowledge to improve the detection of the DNA-binding helix–turn–helix (HTH) motif from sequence. Starting from a set of DNA-binding protein structures that include a functional HTH motif and have no apparent sequence similarity to each other, two different libraries of hidden Markov models (HMMs) were built. One library included sequence models of whole DNA-binding domains, which incorporate the HTH motif, the second library included shorter models of ‘partial’ domains, representing only the fraction of the domain that corresponds to the functionally relevant HTH motif itself. The libraries were scanned against a dataset of protein sequences, some containing the HTH motifs, others not. HMM predictions were compared with the results obtained from a previously published structure-based method and subsequently combined with it. The combined method proved more effective than either of the single-featured approaches, showing that information carried by motif sequences and motif structures are to some extent complementary and can successfully be used together for the detection of DNA-binding HTHs in proteins of unknown function

Functional Coverage of the Human Genome by Existing Structures, Structural Genomics Targets, and Homology Models

The bias in protein structure and function space resulting from experimental limitations and targeting of particular functional classes of proteins by structural biologists has long been recognized, but never continuously quantified. Using the Enzyme Commission and the Gene Ontology classifications as a reference frame, and integrating structure data from the Protein Data Bank (PDB), target sequences from the structural genomics projects, structure homology derived from the SUPERFAMILY database, and genome annotations from Ensembl and NCBI, we provide a quantified view, both at the domain and whole-protein levels, of the current and projected coverage of protein structure and function space relative to the human genome. Protein structures currently provide at least one domain that covers 37% of the functional classes identified in the genome; whole structure coverage exists for 25% of the genome. If all the structural genomics targets were solved (twice the current number of structures in the PDB), it is estimated that structures of one domain would cover 69% of the functional classes identified and complete structure coverage would be 44%. Homology models from existing experimental structures extend the 37% coverage to 56% of the genome as single domains and 25% to 31% for complete structures. Coverage from homology models is not evenly distributed by protein family, reflecting differing degrees of sequence and structure divergence within families. While these data provide coverage, conversely, they also systematically highlight functional classes of proteins for which structures should be determined. Current key functional families without structure representation are highlighted here; updated information on the “most wanted list” that should be solved is available on a weekly basis from http://function.rcsb.org:8080/pdb/function_distribution/index.html

Evolutionary Models for Formation of Network Motifs and Modularity in the Saccharomyces Transcription Factor Network

Many natural and artificial networks contain overrepresented subgraphs, which have been termed network motifs. In this article, we investigate the processes that led to the formation of the two most common network motifs in eukaryote transcription factor networks: the bi-fan motif and the feed-forward loop. Around 100 million y ago, the common ancestor of the Saccharomyces clade underwent a whole-genome duplication event. The simultaneous duplication of the genes created by this event enabled the origin of many network motifs to be established. The data suggest that there are two primary mechanisms that are involved in motif formation. The first mechanism, enabled by the substantial plasticity in promoter regions, is rewiring of connections as a result of positive environmental selection. The second is duplication of transcription factors, which is also shown to be involved in the formation of intermediate-scale network modularity. These two evolutionary processes are complementary, with the pre-existence of network motifs enabling duplicated transcription factors to bind different targets despite structural constraints on their DNA-binding specificities. This process may facilitate the creation of novel expression states and the increases in regulatory complexity associated with higher eukaryotes

Sequence and Structural Differences between Enzyme and Nonenzyme Homologs

AbstractTo improve our understanding of the evolution of novel functions, we performed a sequence, structural, and functional analysis of homologous enzymes and nonenzymes of known three-dimensional structure. In most examples identified, the nonenzyme is derived from an ancestral catalytic precursor (as opposed to the reverse evolutionary scenario, nonenzyme to enzyme), and the active site pocket has been disrupted in some way, owing to the substitution of critical catalytic residues and/or steric interactions that impede substrate binding and catalysis. Pairwise sequence identity is typically insignificant, and almost one-half of the enzyme and nonenzyme pairs do not share any similarity in function. Heterooligomeric enzymes comprising homologous subunits in which one chain is catalytically inactive and enzyme polypeptides that contain internal catalytic and noncatalytic duplications of an ancient enzyme domain are also discussed

Computational biology for ageing

High-throughput genomic and proteomic technologies have generated a wealth of publicly available data on ageing. Easy access to these data, and their computational analysis, is of great importance in order to pinpoint the causes and effects of ageing. Here, we provide a description of the existing databases and computational tools on ageing that are available for researchers. We also describe the computational approaches to data interpretation in the field of ageing including gene expression, comparative and pathway analyses, and highlight the challenges for future developments. We review recent biological insights gained from applying bioinformatics methods to analyse and interpret ageing data in different organisms, tissues and conditions