01895nas a2200181 4500008004100000245013100041210006900172260001300241300001100254490000700265520119300272100002401465700002201489700002201511700002501533700002101558856013401579 2011 eng d00aN-glycosylation efficiency is determined by the distance to the C-terminus and the amino acid preceding an Asn-Ser-Thr sequon.0 aNglycosylation efficiency is determined by the distance to the C c2011 Jan a179-860 v203 a

N-glycosylation is the most common and versatile protein modification. In eukaryotic cells, this modification is catalyzed cotranslationally by the enzyme oligosaccharyltransferase, which targets the β-amide of the asparagine in an Asn-Xaa-Ser/Thr consensus sequon (where Xaa is any amino acid but proline) in nascent proteins as they enter the endoplasmic reticulum. Because modification of the glycosylation acceptor site on membrane proteins occurs in a compartment-specific manner, the presence of glycosylation is used to indicate membrane protein topology. Moreover, glycosylation sites can be added to gain topological information. In this study, we explored the determinants of N-glycosylation with the in vitro transcription/translation of a truncated model protein in the presence of microsomes and surveyed 25,488 glycoproteins, of which 2,533 glycosylation sites had been experimentally validated. We found that glycosylation efficiency was dependent on both the distance to the C-terminus and the nature of the amino acid that preceded the consensus sequon. These findings establish a broadly applicable method for membrane protein tagging in topological studies.

1 aBañó-Polo, Manuel1 aBaldin, Francesca1 aTamborero, Silvia1 aMarti-Renom, Marc, A1 aMingarro, Ismael uhttps://www.clinbioinfosspa.es/content/n-glycosylation-efficiency-determined-distance-c-terminus-and-amino-acid-preceding-asn-ser01872nas a2200145 4500008004100000245008600041210006900127260001300196300001000209490000700219520134300226100001701569700002501586856011501611 2011 eng d00aStructure determination of genomic domains by satisfaction of spatial restraints.0 aStructure determination of genomic domains by satisfaction of sp c2011 Jan a25-350 v193 a

The three-dimensional (3D) architecture of a genome is non-random and known to facilitate the spatial colocalization of regulatory elements with the genes they regulate. Determining the 3D structure of a genome may therefore probe an essential step in characterizing how genes are regulated. Currently, there are several experimental and theoretical approaches that aim at determining the 3D structure of genomes and genomic domains; however, approaches integrating experiments and computation to identify the most likely 3D folding of a genome at medium to high resolutions have not been widely explored. Here, we review existing methodologies and propose that the integrative modeling platform ( http://www.integrativemodeling.org ), a computational package developed for structurally characterizing protein assemblies, could be used for integrating diverse experimental data towards the determination of the 3D architecture of genomic domains and entire genomes at unprecedented resolution. Our approach, through the visualization of looping interactions between distal regulatory elements, will allow for the characterization of global chromatin features and their relation to gene expression. We illustrate our work by outlining the recent determination of the 3D architecture of the α-globin domain in the human genome.

1 aBaù, Davide1 aMarti-Renom, Marc, A uhttps://www.clinbioinfosspa.es/content/structure-determination-genomic-domains-satisfaction-spatial-restraints01797nas a2200217 4500008004100000245010400041210007000145260001300215300001100228490000700239520104100246100001701287700002001304700002101324700002201345700001501367700002401382700001601406700002501422856013201447 2011 eng d00aThe three-dimensional folding of the α-globin gene domain reveals formation of chromatin globules.0 athreedimensional folding of the αglobin gene domain reveals form c2011 Jan a107-140 v183 a

We developed a general approach that combines chromosome conformation capture carbon copy (5C) with the Integrated Modeling Platform (IMP) to generate high-resolution three-dimensional models of chromatin at the megabase scale. We applied this approach to the ENm008 domain on human chromosome 16, containing the α-globin locus, which is expressed in K562 cells and silenced in lymphoblastoid cells (GM12878). The models accurately reproduce the known looping interactions between the α-globin genes and their distal regulatory elements. Further, we find using our approach that the domain folds into a single globular conformation in GM12878 cells, whereas two globules are formed in K562 cells. The central cores of these globules are enriched for transcribed genes, whereas nontranscribed chromatin is more peripheral. We propose that globule formation represents a higher-order folding state related to clustering of transcribed genes around shared transcription machineries, as previously observed by microscopy.

1 aBaù, Davide1 aSanyal, Amartya1 aLajoie, Bryan, R1 aCapriotti, Emidio1 aByron, Meg1 aLawrence, Jeanne, B1 aDekker, Job1 aMarti-Renom, Marc, A uhttps://www.clinbioinfosspa.es/content/three-dimensional-folding-%CE%B1-globin-gene-domain-reveals-formation-chromatin-globules02049nas a2200181 4500008004100000245008700041210006900128260001300197300001100210490000700221520141100228100002401639700002201663700002501685700002101710700001701731856011901748 2009 eng d00aAlignment of multiple protein structures based on sequence and structure features.0 aAlignment of multiple protein structures based on sequence and s c2009 Sep a569-740 v223 a

Comparing the structures of proteins is crucial to gaining insight into protein evolution and function. Here, we align the sequences of multiple protein structures by a dynamic programming optimization of a scoring function that is a sum of an affine gap penalty and terms dependent on various sequence and structure features (SALIGN). The features include amino acid residue type, residue position, residue accessible surface area, residue secondary structure state and the conformation of a short segment centered on the residue. The multiple alignment is built by following the ’guide’ tree constructed from the matrix of all pairwise protein alignment scores. Importantly, the method does not depend on the exact values of various parameters, such as feature weights and gap penalties, because the optimal alignment across a range of parameter values is found. Using multiple structure alignments in the HOMSTRAD database, SALIGN was benchmarked against MUSTANG for multiple alignments as well as against TM-align and CE for pairwise alignments. On the average, SALIGN produces a 15% improvement in structural overlap over HOMSTRAD and 14% over MUSTANG, and yields more equivalent structural positions than TM-align and CE in 90% and 95% of cases, respectively. The utility of accurate multiple structure alignment is illustrated by its application to comparative protein structure modeling.

1 aMadhusudhan, M., S.1 aWebb, Benjamin, M1 aMarti-Renom, Marc, A1 aEswar, Narayanan1 aSali, Andrej uhttps://www.clinbioinfosspa.es/content/alignment-multiple-protein-structures-based-sequence-and-structure-features03094nas a2200385 4500008004100000022001400041245013400055210006900189260001300258300001200271490000700283520182800290653001502118653001002133653002602143653002302169653002802192653002502220653003802245653002202283653001802305653001102323653001802334653001902352653003602371653001302407653003302420100002202453700002102475700001802496700002002514700002002534700002502554856012902579 2008 eng d a1098-100400aUse of estimated evolutionary strength at the codon level improves the prediction of disease-related protein mutations in humans.0 aUse of estimated evolutionary strength at the codon level improv c2008 Jan a198-2040 v293 a

Predicting the functional impact of protein variation is one of the most challenging problems in bioinformatics. A rapidly growing number of genome-scale studies provide large amounts of experimental data, allowing the application of rigorous statistical approaches for predicting whether a given single point mutation has an impact on human health. Up until now, existing methods have limited their source data to either protein or gene information. Novel in this work, we take advantage of both and focus on protein evolutionary information by using estimated selective pressures at the codon level. Here we introduce a new method (SeqProfCod) to predict the likelihood that a given protein variant is associated with human disease or not. Our method relies on a support vector machine (SVM) classifier trained using three sources of information: protein sequence, multiple protein sequence alignments, and the estimation of selective pressure at the codon level. SeqProfCod has been benchmarked with a large dataset of 8,987 single point mutations from 1,434 human proteins from SWISS-PROT. It achieves 82% overall accuracy and a correlation coefficient of 0.59, indicating that the estimation of the selective pressure helps in predicting the functional impact of single-point mutations. Moreover, this study demonstrates the synergic effect of combining two sources of information for predicting the functional effects of protein variants: protein sequence/profile-based information and the evolutionary estimation of the selective pressures at the codon level. The results of large-scale application of SeqProfCod over all annotated point mutations in SWISS-PROT (available for download at http://sgu.bioinfo.cipf.es/services/Omidios/; last accessed: 24 August 2007), could be used to support clinical studies.

10aAlgorithms10aCodon10aComputational Biology10aDatabases, Protein10aDNA Mutational Analysis10aEvolution, Molecular10aGenetic Predisposition to Disease10aGenetic Variation10aGenome, Human10aHumans10aIduronic Acid10aPoint Mutation10aPolymorphism, Single Nucleotide10aProteins10aTumor Suppressor Protein p531 aCapriotti, Emidio1 aArbiza, Leonardo1 aCasadio, Rita1 aDopazo, Joaquin1 aDopazo, Hernán1 aMarti-Renom, Marc, A uhttps://www.clinbioinfosspa.es/content/use-estimated-evolutionary-strength-codon-level-improves-prediction-disease-related-002301nas a2200421 4500008004100000022001400041245005300055210005100108260001300159300001100172490000700183520104700190653001501237653002401252653002601276653003701302653002301339653001301362653002801375653002501403653001301428653002701441653002301468653003101491653003401522653001301556653003601569100002501605700001901630700002201649700001801671700002101689700001901710700002501729700002001754700001701774856008801791 2007 eng d a1362-496200aDBAli tools: mining the protein structure space.0 aDBAli tools mining the protein structure space c2007 Jul aW393-70 v353 a

The DBAli tools use a comprehensive set of structural alignments in the DBAli database to leverage the structural information deposited in the Protein Data Bank (PDB). These tools include (i) the DBAlit program that allows users to input the 3D coordinates of a protein structure for comparison by MAMMOTH against all chains in the PDB; (ii) the AnnoLite and AnnoLyze programs that annotate a target structure based on its stored relationships to other structures; (iii) the ModClus program that clusters structures by sequence and structure similarities; (iv) the ModDom program that identifies domains as recurrent structural fragments and (v) an implementation of the COMPARER method in the SALIGN command in MODELLER that creates a multiple structure alignment for a set of related protein structures. Thus, the DBAli tools, which are freely accessible via the World Wide Web at http://salilab.org/DBAli/, allow users to mine the protein structure space by establishing relationships between protein structures and their functions.

10aAlgorithms10aAmino Acid Sequence10aComputational Biology10aData Interpretation, Statistical10aDatabases, Protein10aInternet10aMolecular Sequence Data10aProtein Conformation10aProteins10aPseudomonas aeruginosa10aSequence Alignment10aSequence Analysis, Protein10aSequence Homology, Amino Acid10aSoftware10aStructure-Activity Relationship1 aMarti-Renom, Marc, A1 aPieper, Ursula1 aMadhusudhan, M, S1 aRossi, Andrea1 aEswar, Narayanan1 aDavis, Fred, P1 aAl-Shahrour, Fátima1 aDopazo, Joaquin1 aSali, Andrej uhttps://www.clinbioinfosspa.es/content/dbali-tools-mining-protein-structure-space-0