02187nas a2200157   4500008004100000245009000041210006900131300001100200490000700211520142200218653023401640653001201874100001301886700002401899856010601923       2006                        eng d00aAccuracy of sequence alignment and fold assessment using reduced amino acid alphabets0 aAccuracy of sequence alignment and fold assessment using reduced  a986-950 v633 aReduced or simplified amino acid alphabets group the 20 naturally occurring amino acids into a smaller number of representative protein residues. To date, several reduced amino acid alphabets have been proposed, which have been derived and optimized by a variety of methods. The resulting reduced amino acid alphabets have been applied to pattern recognition, generation of consensus sequences from multiple alignments, protein folding, and protein structure prediction. In this work, amino acid substitution matrices and statistical potentials were derived based on several reduced amino acid alphabets and their performance assessed in a large benchmark for the tasks of sequence alignment and fold assessment of protein structure models, using as a reference frame the standard alphabet of 20 amino acids. The results showed that a large reduction in the total number of residue types does not necessarily translate into a significant loss of discriminative power for sequence alignment and fold assessment. Therefore, some definitions of a few residue types are able to encode most of the relevant sequence/structure information that is present in the 20 standard amino acids. Based on these results, we suggest that the use of reduced amino acid alphabets may allow to increasing the accuracy of current substitution matrices and statistical potentials for the prediction of protein structure of remote homologs.10aAmino Acid Sequence Amino Acids/*chemistry/classification/*metabolism Consensus Sequence Molecular Sequence Data Oxidation-Reduction *Protein Folding Proteins/*chemistry/*metabolism Sequence Alignment/*methods Structural Homology10aProtein1 aMelo, F.1 aMarti-Renom, M., A.  uhttp://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&dopt=Citation&list_uids=1650624302633nas a2200181   4500008004100000245011500041210006900156300001100225490000800236520169000244653015501934653019202089653001202281100001802293700001502311700001902326856010602345       2005                        eng d00aTracing the evolution of a large protein complex in the eukaryotes, NADH:ubiquinone oxidoreductase (Complex I)0 aTracing the evolution of a large protein complex in the eukaryot  a857-700 v3483 aThe increasing availability of sequenced genomes enables the reconstruction of the evolutionary history of large protein complexes. Here, we trace the evolution of NADH:ubiquinone oxidoreductase (Complex I), which has increased in size, by so-called supernumary subunits, from 14 subunits in the bacteria to 30 in the plants and algae, 37 in the fungi and 46 in the mammals. Using a combination of pair-wise and profile-based sequence comparisons at the levels of proteins and the DNA of the sequenced eukaryotic genomes, combined with phylogenetic analyses to establish orthology relationships, we were able to (1) trace the origin of six of the supernumerary subunits to the alpha-proteobacterial ancestor of the mitochondria, (2) detect previously unidentified homology relations between subunits from fungi and mammals, (3) detect previously unidentified subunits in the genomes of several species and (4) document several cases of gene duplications among supernumerary subunits in the eukaryotes. One of these, a duplication of N7BM (B17.2), is particularly interesting as it has been lost from genomes that have also lost Complex I proteins, making it a candidate for a Complex I interacting protein. A parsimonious reconstruction of eukaryotic Complex I evolution shows an initial increase in size that predates the separation of plants, fungi and metazoa, followed by a gradual adding and incidental losses of subunits in the various evolutionary lineages. This evolutionary scenario is in contrast to that for Complex I in the prokaryotes, for which the combination of several separate, and previously independently functioning modules into a single complex has been proposed.10aAmino Acid Sequence Animals Computational Biology Electron Transport Complex I/*chemistry/*genetics/metabolism Eukaryotic Cells/*enzymology *Evolution10aMolecular Humans Molecular Sequence Data Photosynthesis Phylogeny Plastids/enzymology Protein Binding Protein Subunits/chemistry/genetics/metabolism Sequence Alignment Structural Homology10aProtein1 aGabaldón, T.1 aRainey, D.1 aHuynen, M., A.  uhttp://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&dopt=Citation&list_uids=1584301802057nas a2200301   4500008004100000245006000041210005900101300001100160490000700171520105900178653002501237653001201262653007701274653003201351653007901383100001601462700001901478700002401497700001901521700002401540700001401564700001401578700001401592700001701606700001301623700001301636856010601649       2003                        eng d00aEVA: Evaluation of protein structure prediction servers0 aEVA Evaluation of protein structure prediction servers  a3311-50 v313 aEVA (http://cubic.bioc.columbia.edu/eva/) is a web server for evaluation of the accuracy of automated protein structure prediction methods. The evaluation is updated automatically each week, to cope with the large number of existing prediction servers and the constant changes in the prediction methods. EVA currently assesses servers for secondary structure prediction, contact prediction, comparative protein structure modelling and threading/fold recognition. Every day, sequences of newly available protein structures in the Protein Data Bank (PDB) are sent to the servers and their predictions are collected. The predictions are then compared to the experimental structures once a week; the results are published on the EVA web pages. Over time, EVA has accumulated prediction results for a large number of proteins, ranging from hundreds to thousands, depending on the prediction method. This large sample assures that methods are compared reliably. As a result, EVA provides useful information to developers as well as users of prediction methods.10aAutomation Databases10aProtein10aProtein Internet *Protein Conformation Protein Folding Protein Structure10aProtein Structural Homology10aSecondary Proteins/chemistry Reproducibility of Results *Sequence Analysis1 aKoh, I., Y.1 aEyrich, V., A.1 aMarti-Renom, M., A.1 aPrzybylski, D.1 aMadhusudhan, M., S.1 aEswar, N.1 aGrana, O.1 aPazos, F.1 aValencia, A.1 aSali, A.1 aRost, B.  uhttp://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&dopt=Citation&list_uids=12824315