The four members of the recently identified suppressor of cytokines signaling family (SOCS-1, SOCS-2, SOCS-3, and CIS, where CIS is cytokine-inducible SH2-containing protein) appear, by various means, to negatively regulate cytokine signal transduction. Structurally, the SOCS proteins are composed of an N-terminal region of variable length and amino acid composition, a central SH2 domain, and a previously unrecognized C-terminal motif that we have called the SOCS box. By using the SOCS box amino acid sequence consensus, we have searched DNA databases and have identified a further 16 proteins that contain this motif. These proteins fall into five classes based on the protein motifs found N-terminal of the SOCS box. In addition to four new SOCS proteins (SOCS-4 to SOCS-7) containing an SH2 domain and a SOCS box, we describe three new families of proteins that contain either WD-40 repeats (WSB-1 and -2), SPRY domains (SSB-1 to -3) or ankyrin repeats (ASB-1 to -3) N-terminal of the SOCS box. In addition, we show that a class of small GTPases also contains a SOCS box. The expression of representative members of each class of proteins differs markedly, as does the regulation of expression by cytokines. The function of the WSB, SSB, and ASB protein families remains to be determined.

https://www.pnas.org/content/pnas/95/1/114.full.pdf

Twenty proteins containing a C-terminal SOCS box form five structural classes

https://epublications.marquette.edu/cgi/viewcontent.cgi?article=1330&context=chem_fac

The proteomics of N-terminal methionine cleavage.

On the basis of function and sequence similarities, the vertebrate fucosyltransferases can be classified into three groups: alpha-2-, alpha-3-, and alpha-6-fucosyltransferases. Thirty new putative fucosyltransferase genes from invertebrates and bacteria and six conserved peptide motifs have been identified in DNA and protein databanks. Two of these motifs are specific of alpha-3-fucosyltransferases, one is specific of alpha-2-fucosyltransferases, another is specific of alpha-6-fucosyltransferases, and two are shared by both alpha-2- and alpha-6-fucosyltranserases. Based on these data, literature data, and the phylogenetic analysis of the conserved peptide motifs, a model for the evolution offucosyltransferase genes by successive duplications, followed by divergent evolution is proposed, with either two different ancestors, one for the alpha-2/6-fucosyltransferases and one for the alpha-3-fucosyltransferases or a single common ancestor for the two families. The expected properties of such an hypothetical ancestor suggest that the plant or insect alpha-3-fucosyltransferases using chitobiose as acceptor might be the present forms of this ancestor, since fucosyltransferases using chitobiose as acceptor are expected to be of earlier appearance in evolution than enzymes using N -acetyllactosamine. However, an example of convergent evolution of fucosyltransferase genes is suggested for the appearance of the Leaepitopes found in plants and primates.

Divergent evolution of fucosyltransferase genes from vertebrates, invertebrates, and bacteria.

1. Molecular Biology for Computer Scientists, Lawrence Hunter. 2. The Computational Linguistics of Biological Sequences, David B. Searls. 3. Neural Networks, Adaptive Optimisation, and RNA Secondary Structure Prediction, Evan W Steeg. 4. Predicting Protein Structural Features With Artificial Neural Networks, Stephen R. Holbrook, et al 5. Developing Hierarchical Representations for Protein Structures: An Incremental Approach, Xiru Zhang and David Waltz. 6. Integrating AI with Sequence Analysis, Richard H. Lathrop, et al. 7. Planning to Learn about Protein Structure, Lawrence Hunter. 8. A Qualitative Biochemistry and its Application to the Regulation of the Tryptophan Operon, Peter D. Karp. 9. Identification of Qualitatively Feasible Metabolic Pathways, Michael L Mavrovouniotis. 10. Knowledge-Based Simulation of DNA Metabolism: Prediction of Action and Envisionment of Pathways, Adam R. Galper, et al. 11. An AI Approach to the Interpretation of the NMR Spectra of Proteins, Peter Edwards, et al. 12. Molecular Scene Analysis: Crystal Structure Determination Through Imagery, Janice I. Glasgow, et al. Afterword: The Anti-Expert System-Thirteen Hypotheses an AI Program Should Have Seen Through, Joshua Lederberg.

Artificial intelligence and molecular biology

The membrane-bound tetrachloroethene reductive dehalogenase (PCE-RDase) (PceA; EC 1.97.1.8), the terminal component of the respiratory chain of Dehalobacter restrictus, was purified 25-fold to apparent electrophoretic homogeneity. Sodium dodecyl sulfate-polyacrylamide gel electrophoresis revealed a single band with an apparent molecular mass of 60 +/- 1 kDa, whereas the native molecular mass was 71 +/- 8 kDa according to size exclusion chromatography in the presence of the detergent octyl-beta-D-glucopyranoside. The monomeric enzyme contained (per mol of the 60-kDa subunit) 1.0 +/- 0.1 mol of cobalamin, 0.6 +/- 0.02 mol of cobalt, 7.1 +/- 0.6 mol of iron, and 5.8 +/- 0.5 mol of acid-labile sulfur. Purified PceA catalyzed the reductive dechlorination of tetrachloroethene and trichloroethene to cis-1,2-dichloroethene with a specific activity of 250 +/- 12 nkat/mg of protein. In addition, several chloroethanes and tetrachloromethane caused methyl viologen oxidation in the presence of PceA. The K-m values for tetrachloro.ethene, trichloroethene, and methyl viologen were 20.4 +/- 3.2, 23.7 +/- 5.2, and 47 +/- 10 muM, respectively. The PceA exhibited the highest activity at pH 8.1 and was oxygen sensitive, with a half-life of activity of 280 min upon exposure to air. Based on the almost identical N-terminal amino acid sequences of PceA of Dehalobacter restrictus, Desulfitobacterium hafniense strain TCE1 (formerly Desulfitobacterium frappieri strain TCE1), and Desulfitobacterium hafniense strain PCE-S (formerly Desulfitobacterium frappieri strain PCE-S), the pceA genes of the first two organisms were cloned and sequenced. Together with the pceA genes of Desulfitobacterium hafniense strains PCE-S and Y51, the pceA genes of Desulfitobacterium hafniense strain TCE1 and Dehalobacter restrictus form a coherent group of reductive dehalogenases with almost 100% sequence identity. Also, the pceB genes, which may code for a membrane anchor protein of PceA, and the intergenic regions of Dehalobacter restrictus and the three desultitobacteria had identical sequences. Whereas the cprB (chlorophenol reductive dehalogenase) genes of chlorophenol-dehalorespiring bacteria are always located upstream of cprA, all pceB genes known so far are located downstream of pceA. The possible consequences of this feature for the annotation of putative reductive dehalogenase genes are discussed, as are the sequence around the iron-sulfur cluster binding motifs and the type of iron-sulfur clusters of the reductive dehalogenases of Dehalobacter restrictus and Desulfitobacterium dehalogenans identified by electron paramagnetic resonance spectroscopy.

https://aem.asm.org/content/aem/69/8/4628.full.pdf

Characterization of the Corrinoid Iron-Sulfur Protein Tetrachloroethene Reductive Dehalogenase of Dehalobacter restrictus

Two programs, MOTIF and PATTERN, that scan sequences for matches to user-defined motifs and patterns of motifs based on identity and set membership are described. The programs use a simple and logical notation to define motifs, and may be used either interactively or by using command line parameters (suitable for batch processing). The two programs described also incorporate a simple, yet reliable, algorithm that automatically detects in which of six possible formats the sequence entry is written.

Kerri Y. Cockwell

Papers

Software tools for motif and pattern scanning: program descriptions including a universal sequence reading algorithm.