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M Gerstein

Publications and source records attributed to M Gerstein.

At least 37 records · Page 2Linked to original sources
PubMed2001

What is bioinformatics? A proposed definition and overview of the field.

BACKGROUND: The recent flood of data from genome sequences and functional genomics has given rise to new field, bioinformatics, which combines elements of biology and computer science. OBJECTIVES: Here we propose a definition for this new field and review some of the research that is being pursued, particularly in relation to transcriptional regulatory systems. METHODS: Our definition is as follows: Bioinformatics is conceptualizing biology in terms of macromolecules (in the sense of physical-chemistry) and then applying "informatics" techniques (derived from disciplines such as applied maths, computer science, and statistics) to understand and organize the information associated with these molecules, on a large-scale. RESULTS AND CONCLUSIONS: Analyses in bioinformatics predominantly focus on three types of large datasets available in molecular biology: macromolecular structures, genome sequences, and the results of functional genomics experiments (e.g. expression data). Additional information includes the text of scientific papers and "relationship data" from metabolic pathways, taxonomy trees, and protein-protein interaction networks. Bioinformatics employs a wide range of computational techniques including sequence and structural alignment, database design and data mining, macromolecular geometry, phylogenetic tree construction, prediction of protein structure and function, gene finding, and expression data clustering. The emphasis is on approaches integrating a variety of computational methods and heterogeneous data sources. Finally, bioinformatics is a practical discipline. We survey some representative applications, such as finding homologues, designing drugs, and performing large-scale censuses. Additional information pertinent to the review is available over the web at http://bioinfo.mbb.yale.edu/what-is-it.

Computational Biology↗
PubMed2000

A Bayesian system integrating expression data with sequence patterns for localizing proteins: comprehensive application to the yeast genome.

We develop a probabilistic system for predicting the subcellular localization of proteins and estimating the relative population of the various compartments in yeast. Our system employs a Bayesian approach, updating a protein's probability of being in a compartment, based on a diverse range of 30 features. These range from specific motifs (e.g. signal sequences or the HDEL motif) to overall properties of a sequence (e.g. surface composition or isoelectric point) to whole-genome data (e.g. absolute mRNA expression levels or their fluctuations). The strength of our approach is the easy integration of many features, particularly the whole-genome expression data. We construct a training and testing set of approximately 1300 yeast proteins with an experimentally known localization from merging, filtering, and standardizing the annotation in the MIPS, Swiss-Prot and YPD databases, and we achieve 75 % accuracy on individual protein predictions using this dataset. Moreover, we are able to estimate the relative protein population of the various compartments without requiring a definite localization for every protein. This approach, which is based on an analogy to formalism in quantum mechanics, gives better accuracy in determining relative compartment populations than that obtained by simply tallying the localization predictions for individual proteins (on the yeast proteins with known localization, 92% versus 74%). Our training and testing also highlights which of the 30 features are informative and which are redundant (19 being particularly useful). After developing our system, we apply it to the 4700 yeast proteins with currently unknown localization and estimate the relative population of the various compartments in the entire yeast genome. An unbiased prior is essential to this extrapolated estimate; for this, we use the MIPS localization catalogue, and adapt recent results on the localization of yeast proteins obtained by Snyder and colleagues using a minitransposon system. Our final localizations for all approximately 6000 proteins in the yeast genome are available over the web at: http://bioinfo.mbb.yale. edu/genome/localize.

Amino Acid Motifs↗
PubMed2000

Proteomics of Mycoplasma genitalium: identification and characterization of unannotated and atypical proteins in a small model genome.

We present the results of a comprehensive analysis of the proteome of Mycoplasma genitalium (MG), the smallest autonomously replicating organism that has been completely sequenced. Our aim was to identify and characterize all soluble proteins in MG that are structurally and functionally uncharacterized. We were particularly interested in identifying proteins that differed significantly from typical globular proteins, for example, proteins which are unstructured in the absence of a 'partner' molecule or those that exhibit unusual thermodynamic properties. This work is complementary to other structural genomics projects whose primary aim is to determine the three-dimensional structures of proteins with unknown folds. We have identified all the full-length open reading frames (ORFs) in MG that have no homologs of known structure and are of unknown function. Twenty-five of the total 483 ORFs fall into this category and we have expressed, purified and characterized 11 of them. We have used circular dichroism (CD) to rapidly investigate their biophysical properties. Our studies reveal that these proteins have a wide range of structures varying from highly helical to partially structured to unfolded or random coil. They also display a variety of thermodynamic properties ranging from cooperative unfolding to no detectable unfolding upon thermal denaturation. Several of these proteins are highly conserved from mycoplasma to man. Further information about target selection and CD results is available at http://bioinfo.mbb.yale.edu/genome

Amino Acid Sequence↗
PubMed2000

The morph server: a standardized system for analyzing and visualizing macromolecular motions in a database framework.

The number of solved structures of macromolecules that have the same fold and thus exhibit some degree of conformational variability is rapidly increasing. It is consequently advantageous to develop a standardized terminology for describing this variability and automated systems for processing protein structures in different conformations. We have developed such a system as a 'front-end' server to our database of macromolecular motions. Our system attempts to describe a protein motion as a rigid-body rotation of a small 'core' relative to a larger one, using a set of hinges. The motion is placed in a standardized coordinate system so that all statistics between any two motions are directly comparable. We find that while this model can accommodate most protein motions, it cannot accommodate all; the degree to which a motion can be accommodated provides an aid in classifying it. Furthermore, we perform an adiabatic mapping (a restrained interpolation) between every two conformations. This gives some indication of the extent of the energetic barriers that need to be surmounted in the motion, and as a by-product results in a 'morph movie'. We make these movies available over the Web to aid in visualization. Many instances of conformational variability occur between proteins with somewhat different sequences. We can accommodate these differences in a rough fashion, generating an 'evolutionary morph'. Users have already submitted hundreds of examples of protein motions to our server, producing a comprehensive set of statistics. So far the statistics show that the median submitted motion has a rotation of approximately 10 degrees and a maximum Calpha displacement of 17 A. Almost all involve at least one large torsion angle change of >140 degrees. The server is accessible at http://bioinfo.mbb.yale. edu/MolMovDB

Computer Graphics↗
PubMed2000

Assessing annotation transfer for genomics: quantifying the relations between protein sequence, structure and function through traditional and probabilistic scores.

Measuring in a quantitative, statistical sense the degree to which structural and functional information can be "transferred" between pairs of related protein sequences at various levels of similarity is an essential prerequisite for robust genome annotation. To this end, we performed pairwise sequence, structure and function comparisons on approximately 30,000 pairs of protein domains with known structure and function. Our domain pairs, which are constructed according to the SCOP fold classification, range in similarity from just sharing a fold, to being nearly identical. Our results show that traditional scores for sequence and structure similarity have the same basic exponential relationship as observed previously, with structural divergence, measured in RMS, being exponentially related to sequence divergence, measured in percent identity. However, as the scale of our survey is much larger than any previous investigations, our results have greater statistical weight and precision. We have been able to express the relationship of sequence and structure similarity using more "modern scores," such as Smith-Waterman alignment scores and probabilistic P-values for both sequence and structure comparison. These modern scores address some of the problems with traditional scores, such as determining a conserved core and correcting for length dependency; they enable us to phrase the sequence-structure relationship in more precise and accurate terms. We found that the basic exponential sequence-structure relationship is very general: the same essential relationship is found in the different secondary-structure classes and is evident in all the scoring schemes. To relate function to sequence and structure we assigned various levels of functional similarity to the domain pairs, based on a simple functional classification scheme. This scheme was constructed by combining and augmenting annotations in the enzyme and fly functional classifications and comparing subsets of these to the Escherichia coli and yeast classifications. We found sigmoidal relationships between similarity in function and sequence, with clear thresholds for different levels of functional conservation. For pairs of domains that share the same fold, precise function appears to be conserved down to approximately 40 % sequence identity, whereas broad functional class is conserved to approximately 25 %. Interestingly, percent identity is more effective at quantifying functional conservation than the more modern scores (e.g. P-values). Results of all the pairwise comparisons and our combined functional classification scheme for protein structures can be accessed from a web database at http://bioinfo.mbb.yale.edu/alignCopyright 2000 Academic Press.

Animals↗
PubMed2000

Analysis of the yeast transcriptome with structural and functional categories: characterizing highly expressed proteins.

We analyzed 10 genome expression data sets by large-scale cross-referencing against broad structural and functional categories. The data sets, generated by different techniques (e.g. SAGE and gene chips), provide various representations of the yeast transcriptome (the set of all yeast genes, weighted by transcript abundance). Our analysis enabled us to determine features more prevalent in the transcriptome than the genome: i.e. those that are common to highly expressed proteins. Starting with simplest categories, we find that, relative to the genome, the transcriptome is enriched in Ala and Gly and depleted in Asn and very long proteins. We find, furthermore, that protein length and maximum expression level have a roughly inverse relationship. To relate expression level and protein structure, we assigned transmembrane helices and known folds (using PSI-blast) to each protein in the genome; this allowed us to determine that the transcriptome is enriched in mixed alpha-beta structures and depleted in membrane proteins relative to the genome. In particular, some enzymatic folds, such as the TIM barrel and the G3P dehydrogenase fold, are much more prevalent in the transcriptome than the genome, whereas others, such as the protein-kinase and leucine-zipper folds, are depleted. The TIM barrel, in fact, is overwhelmingly the 'top fold' in the transcriptome, while it only ranks fifth in the genome. The most highly enriched functional categories in the transcriptome (based on the MIPS system) are energy production and protein synthesis, while categories such as transcription, transport and signaling are depleted. Furthermore, for a given functional category, transcriptome enrichment varies quite substantially between the different expression data sets, with a variation an order of magnitude larger than for the other categories cross-referenced (e.g. amino acids). One can readily see how the enrichment and depletion of the various functional categories relates directly to that of particular folds.

Amino Acids↗
PubMed2000

Statistical analysis of amino acid patterns in transmembrane helices: the GxxxG motif occurs frequently and in association with beta-branched residues at neighboring positions.

To find motifs that mediate helix-helix interactions in membrane proteins, we have analyzed frequently occurring combinations of residues in a database of transmembrane domains. Our analysis was performed with a novel formalism, which we call TMSTAT, for exactly calculating the expectancies of all pairs and triplets of residues in individual sequences, taking into account differential sequence composition and the substantial effect of finite length in short segments. We found that the number of significantly over and under-represented pairs and triplets was much greater than the random expectation. Isoleucine, glycine and valine were the most common residues in these extreme cases. The main theme observed is patterns of small residues (Gly, Ala and Ser) at i and i+4 found in association with large aliphatic residues (Ile, Val and Leu) at neighboring positions (i.e. i+/-1 and i+/-2). The most over-represented pair is formed by two glycine residues at i and i+4 (GxxxG, 31.6 % above expectation, p<1x10(-33)) and it is strongly associated with the neighboring beta-branched residues Ile and Val. In fact, the GxxxG pair has been described as part of the strong interaction motif in the glycophorin A transmembrane dimer, in which the pair is associated with two Val residues (GVxxGV). GxxxG is also the major motif identified using TOXCAT, an in vivo selection system for transmembrane oligomerization motifs. In conjunction with these experimental observations, our results highlight the importance of the GxxxG+beta-branched motif in transmembrane helix-helix interactions. In addition, the special role for the beta-branched residues Ile and Val suggested here is consistent with the hypothesis that residues with constrained rotameric freedom in helical conformation might reduce the entropic cost of folding in transmembrane proteins. Additional material is available at http://engelman.csb.yale. edu/tmstat and http://bioinfo.mbb.yale. edu/tmstat.

Amino Acid Motifs↗
PubMed2000

Measuring shifts in function and evolutionary opportunity using variability profiles: a case study of the globins.

Variability profiles measured over a set of aligned sequences can be used to estimate evolutionary freedom to vary. Differences in variability profiles between clades can be used to identify shifts in function at the molecular level. We demonstrate such a shift between the alpha and beta subunits of hemoglobin. We also show that the variability profiles for myoglobin are different between whales and primates and speculate that the differences between the two clades may reflect a shift associated with the novel oxygen storage demands in the lineage leading to whales. We discuss the relationship between sequence variability and "evolutionary opportunity" and explore the utility of Maynard Smith's multidimensional evolutionary opportunity space metaphor for exploring functional constraints, genetic redundancy, and the context dependency of the genotype-phenotype map. This work has implications for quantitatively defining and comparing protein function. Supplementary data is available from bioinfo.mbb.yale. edu/align.

Animals↗
PubMed2000

The stability of thermophilic proteins: a study based on comprehensive genome comparison.

We address the question of the thermal stability of proteins in thermophiles through comprehensive genome comparison, focussing on the occurrence of salt bridges. We compared a set of 12 genomes (from four thermophilic archaeons, one eukaryote, six mesophilic eubacteria, and one thermophilic eubacteria). Our results showed that thermophiles have a greater content of charged residues than mesophiles, both at the overall genomic level and in alpha helices. Furthermore, we found that in thermophiles the charged residues in helices tend to be preferentially arranged with a 1-4 helical spacing and oriented so that intra-helical charge pairs agree with the helix dipole. Collectively, these results imply that intra-helical salt bridges are more prevalent in thermophiles than mesophiles and thus suggest that they are an important factor stabilizing thermophilic proteins. We also found that the proteins in thermophiles appear to be somewhat shorter than those in mesophiles. However, this later observation may have more to do with evolutionary relationships than with physically stabilizing factors. In all our statistics we were careful to controls for various biases. These could have, for instance, arisen due to repetitive or duplicated sequences. In particular, we repeated our calculation using a variety of random and directed sampling schemes. One of these involved making a "stratified sample," a representative cross-section of the genomes derived from a set of 52 orthologous proteins present roughly once in each genome. For another sample, we focused on the subset of the 52 orthologs that had a known 3D structure. This allowed us to determine the frequency of tertiary as well as main-chain salt bridges. Our statistical controls supported our overall conclusion about the prevalence of salt bridges in thermophiles in comparison to mesophiles.

Amino Acid Sequence↗
PubMed2000

The current excitement in bioinformatics-analysis of whole-genome expression data: how does it relate to protein structure and function?

Whole-genome expression profiles provide a rich new data-trove for bioinformatics. Initial analyses of the profiles have included clustering and cross-referencing to 'external' information on protein structure and function. Expression profile clusters do relate to protein function, but the correlation is not perfect, with the discrepancies partially resulting from the difficulty in consistently defining function. Other attributes of proteins can also be related to expression-in particular, structure and localization-and sometimes show a clearer relationship than function.

Computational Biology↗
PubMed2000

Integrative database analysis in structural genomics.

An important aspect of structural genomics is connecting coordinate data with whole-genome information related to phylogenetic occurrence, protein function, gene expression, and protein-protein interactions. Integrative database analysis allows one to survey the 'finite parts list' of protein folds from many perspectives, highlighting certain folds and structural features that stand out in particular ways.

Computational Biology↗
PubMed2000

Analysis of yeast protein kinases using protein chips.

We have developed a novel protein chip technology that allows the high-throughput analysis of biochemical activities, and used this approach to analyse nearly all of the protein kinases from Saccharomyces cerevisiae. Protein chips are disposable arrays of microwells in silicone elastomer sheets placed on top of microscope slides. The high density and small size of the wells allows for high-throughput batch processing and simultaneous analysis of many individual samples. Only small amounts of protein are required. Of 122 known and predicted yeast protein kinases, 119 were overexpressed and analysed using 17 different substrates and protein chips. We found many novel activities and that a large number of protein kinases are capable of phosphorylating tyrosine. The tyrosine phosphorylating enzymes often share common amino acid residues that lie near the catalytic region. Thus, our study identified a number of novel features of protein kinases and demonstrates that protein chip technology is useful for high-throughput screening of protein biochemical activity.

Adenosine Triphosphate↗
PubMed2000

Structural proteomics of an archaeon.

A set of 424 nonmembrane proteins from Methanobacterium thermoautotrophicum were cloned, expressed and purified for structural studies. Of these, approximately 20% were found to be suitable candidates for X-ray crystallographic or NMR spectroscopic analysis without further optimization of conditions, providing an estimate of the number of the most accessible structural targets in the proteome. A retrospective analysis of the experimental behavior of these proteins suggested some simple relations between sequence and solubility, implying that data bases of protein properties will be useful in optimizing high throughput strategies. Of the first 10 structures determined, several provided clues to biochemical functions that were not detectable from sequence analysis, and in many cases these putative functions could be readily confirmed by biochemical methods. This demonstrates that structural proteomics is feasible and can play a central role in functional genomics.

Cloning, Molecular↗
PubMed2000

Whole-genome trees based on the occurrence of folds and orthologs: implications for comparing genomes on different levels.

We built whole-genome trees based on the presence or absence of particular molecular features, either orthologs or folds, in the genomes of a number of recently sequenced microorganisms. To put these genomic trees into perspective, we compared them to the traditional ribosomal phylogeny and also to trees based on the sequence similarity of individual orthologous proteins. We found that our genomic trees based on the overall occurrence of orthologs did not agree well with the traditional tree. This discrepancy, however, vanished when one restricted the tree to proteins involved in transcription and translation, not including problematic proteins involved in metabolism. Protein folds unite superficially unrelated sequence families and represent a most fundamental molecular unit described by genomes. We found that our genomic occurrence tree based on folds agreed fairly well with the traditional ribosomal phylogeny. Surprisingly, despite this overall agreement, certain classes of folds, particularly all-beta ones, had a somewhat different phylogenetic distribution. We also compared our occurrence trees to whole-genome clusters based on the composition of amino acids and di-nucleotides. Finally, we analyzed some technical aspects of genomic trees-e.g., comparing parsimony versus distance-based approaches and examining the effects of increasing numbers of organisms. Additional information (e.g. clickable trees) is available from http://bioinfo.mbb.yale.edu/genome/trees.

Computational Biology↗
PubMed2000

Protein folds in the worm genome.

We survey the protein folds in the worm genome, using pairwise and multiple-sequence comparison methods (i.e. FASTA and PSI-blast). Overall, we find that approximately 250 folds match approximately 8000 domains in approximately 4500 ORFs, about 32 matches per fold involving a quarter of the total worm ORFs. We compare the folds in the worm genome to those in other model organisms, in particular yeast and E. coli, and find that the worm shares more folds with the phylogenetically closer yeast than with E. coli. There appear to be 36 folds unique to the worm compared to these two model organisms, and many of these are obviously implicated in aspects of multicellularity. The most common fold in the worm genome is the immunoglobulin fold, and many of the common folds are repeated in various combinations and permutations in multidomain proteins. In addition, an approach is presented for the identification of "sure" and "marginal" membrane proteins. When applied to the worm genome, this reveals a much greater relative prevalence of proteins with seven transmembrane helices in comparison to the other completely sequenced genomes, which are not of metazoans. Combining these analyses with some other simple filters allows one to identify ORFs that potentially code for soluble proteins of unknown fold, which may be promising targets for experimental investigation in structural genomics. A regularly updated worm fold analysis will be available from bioinfo.mbb.yale.edu/genome/worm.

Animals↗