In silico structural and functional analysis of the human cytomegalovirus (HHV5) genome

The open reading frames of human cytomegalovirus (human herpesvirus-5, HHV5) encode some 213 unique proteins with mostly unknown functions. Using the threading program, ProCeryon, we calculated possible matches between the amino acid sequences of these proteins and the Protein Data Bank library of three-dimensional structures. Thirty-six proteins were fully identified in terms of their structure and, often, function; 65 proteins were recognized as members of narrow structural/functional families (e.g. DNA-binding factors, cytokines, enzymes, signaling particles, cell surface receptors etc.); and 87 proteins were assigned to broad structural classes (e.g. all-beta, 3-layer-alphabetaalpha, multidomain, etc.). Genes encoding proteins with similar folds, or containing identical structural traits (extreme sequence length, runs of unstructured (Pro and/or Gly-rich) residues, transmembrane segments, etc.) often formed tandem clusters throughout the genome. In the course of this work, benchmarks on about 20 known folds were used to optimize adjustable parameters of threading calculations, i.e. gap penalty weights used in sequence/structure alignments; new scores obtained as simple combinations of existing scoring functions; and number of threading runs conducive to meaningful results. An introduction of summed, per-residue-normalized scores has been essential for discovery of subdomains (EGF-like, SH2, SH3) in longer protein sequences, such as the eight "open sandwich" cytokine domains, 60-70 amino acids long and having the 3beta1alpha fold with one or two disulfide bridges, present in otherwise unrelated proteins.     

A generic motif discovery algorithm for sequential data

MOTIVATION: Motif discovery in sequential data is a problem of great interest and with many applications. However, previous methods have been unable to combine exhaustive search with complex motif representations and are each typically only applicable to a certain class of problems. RESULTS: Here we present a generic motif discovery algorithm (Gemoda) for sequential data. Gemoda can be applied to any dataset with a sequential character, including both categorical and real-valued data. As we show, Gemoda deterministically discovers motifs that are maximal in composition and length. As well, the algorithm allows any choice of similarity metric for finding motifs. Finally, Gemoda's output motifs are representation-agnostic: they can be represented using regular expressions, position weight matrices or any number of other models for any type of sequential data. We demonstrate a number of applications of the algorithm, including the discovery of motifs in amino acids sequences, a new solution to the (l,d)-motif problem in DNA sequences and the discovery of conserved protein substructures. AVAILABILITY: Gemoda is freely available at http://web.mit.edu/bamel/gemoda     

Radio-iodination of plasma membranes of toad bladder epithelium

Summary The present report describes high yield enzymatic radio-iodination of the apical and basal-lateral plasma membranes of toad bladder epithelium, by a procedure that does not breach the functional integrity of the epithelium, as assessed by the basal and vasopressin-sensitive short-circuit current (SCC). Restriction of the label to the membrane surface was ascertained by light and electron-microscopic autoradiographs. On the apical surface, the grains were over the glycocalyx and the plasma membrane. Analysis of the labeled glycocalyx by agarose gel filtration, sodium dodecyl sulfate-polyacrylamide gel electrophoresis (SDS-PAGE), as well as enzymatic and pH-dependent hydrolysis indicated that the glycocalyx is a trichloro-acetic acid-soluble macromolecular complex of high molecular weight composed of a peptide moiety attached to large prosthetic groups (presumably carbohydrates) by O-glycosidic bonds. Analysis of the labeled apical plasma membrane components by agarose gel filtration and SDS-PAGE disclosed the presence of six major species of apparent molecular weights: 23,000, 28,000, 37,000, 44,000, 68,000, and 95,000. More than half of the membrane-associated radio-iodine was in two bands of molecular weights 37,000 and 44,000.Concentrations of vasopressin and cyclic AMP sufficient to increase the SCC significantly did not modify the extent of membrane labeling or the distribution of the label among the apical membrane components (presumably proteins) as assessed by SDS-PAGE. Iodination in the presence of amiloride inhibited incorporation but did not change the pattern of the distribution of the label among the components resolved by SDS-PAGE.Iodination of basal-lateral plasma membranes, at a yield comparable to that obtained with apical labeling, was attained after about 30 min of exposure of the intact bladder to the labeling solutions. Approximately 25% of the basal-lateral labeling was lost when the epithelial cells were harvested after collagenase treatment, implying that some iodination of the basement membrane had taken place. Less than 10% of iodination of the apical or basal-lateral surfaces was accounted for by lipid-labeling. Analysis of the labeled apical and basal-lateral species by enzymatic digestion and thin layer chromatography disclosed that virtually all the radioactivity was present as mono-iodotyrosine (MIT).     

Combinatorial pattern discovery in biological sequences: The TEIRESIAS algorithm [published erratum appears in Bioinformatics 1998;14(2):229]

MOTIVATION: The discovery of motifs in biological sequences is an important problem. RESULTS: This paper presents a new algorithm for the discovery of rigid patterns (motifs) in biological sequences. Our method is combinatorial in nature and able to produce all patterns that appear in at least a (user-defined) minimum number of sequences, yet it manages to be very efficient by avoiding the enumeration of the entire pattern space. Furthermore, the reported patterns are maximal: any reported pattern cannot be made more specific and still keep on appearing at the exact same positions within the input sequences. The effectiveness of the proposed approach is showcased on a number of test cases which aim to: (i) validate the approach through the discovery of previously reported patterns; (ii) demonstrate the capability to identify automatically highly selective patterns particular to the sequences under consideration. Finally, experimental analysis indicates that the algorithm is output sensitive, i.e. its running time is quasi- linear to the size of the generated output.