L. Aravind

IMPALA: matching a protein sequence against a collection of PSI-BLAST-constructed position-specific score matrices

MOTIVATIONnMany studies have shown that database searches using position-specific score matrices (PSSMs) or profiles as queries are more effective at identifying distant protein relationships than are searches that use simple sequences as queries. One popular program for constructing a PSSM and comparing it with a database of sequences is Position-Specific Iterated BLAST (PSI-BLAST).nnnRESULTSnThis paper describes a new software package, IMPALA, designed for the complementary procedure of comparing a single query sequence with a database of PSI-BLAST-generated PSSMs. We illustrate the use of IMPALA to search a database of PSSMs for protein folds, and one for protein domains involved in signal transduction. IMPALAs sensitivity to distant biological relationships is very similar to that of PSI-BLAST. However, IMPALA employs a more refined analysis of statistical significance and, unlike PSI-BLAST, guarantees the output of the optimal local alignment by using the rigorous Smith-Waterman algorithm. Also, it is considerably faster when run with a large database of PSSMs than is BLAST or PSI-BLAST when run against the complete non-redundant protein database.

The STAS domain — a link between anion transporters and antisigma-factor antagonists

So, the question remains, whichof the available techniques forexpression pattern analysis mostaccurately reflects biological reality?The best answer may be ‘all of theabove’. No one techniquenecessarily gives the whole picture.Each can provide qualitativelydifferent types of information, andall can help in the quest tounderstand biological systems.

A novel superfamily of predicted cysteine proteases from eukaryotes, viruses and Chlamydia pneumoniae

We thank Anna Panchenko for performing the threading analysis and Vishva Dixit, Robert King and Natalia Mal’ceva for useful discussions.

Novel Predicted RNA-Binding Domains Associated with the Translation Machinery

Abstract. Two previously undetected domains were identified in a variety of RNA-binding proteins, particularly RNA-modifying enzymes, using methods for sequence profile analysis. A small domain consisting of 60–65 amino acid residues was detected in the ribosomal protein S4, two families of pseudouridine synthases, a novel family of predicted RNA methylases, a yeast protein containing a pseudouridine synthetase and a deaminase domain, bacterial tyrosyl-tRNA synthetases, and a number of uncharacterized, small proteins that may be involved in translation regulation. Another novel domain, designated PUA domain, after PseudoUridine synthase and Archaeosine transglycosylase, was detected in archaeal and eukaryotic pseudouridine synthases, archaeal archaeosine synthases, a family of predicted ATPases that may be involved in RNA modification, a family of predicted archaeal and bacterial rRNA methylases. Additionally, the PUA domain was detected in a family of eukaryotic proteins that also contain a domain homologous to the translation initiation factor eIF1/SUI1; these proteins may comprise a novel type of translation factors. Unexpectedly, the PUA domain was detected also in bacterial and yeast glutamate kinases; this is compatible with the demonstrated role of these enzymes in the regulation of the expression of other genes. We propose that the S4 domain and the PUA domain bind RNA molecules with complex folded structures, adding to the growing collection of nucleic acid-binding domains associated with DNA and RNA modification enzymes. The evolution of the translation machinery components containing the S4, PUA, and SUI1 domains must have included several events of lateral gene transfer and gene loss as well as lineage-specific domain fusions.

The Histone Database: a comprehensive WWW resource for histones and histone fold-containing proteins

The Histone Database (HDB) is an annotated and searchable collection of all full-length sequences and structures of histone and non-histone proteins containing the histone fold motif. These sequences are both eukaryotic and archaeal in origin. Several new histone fold-containing proteins have been identified, including Spt7p, and a few false positives have been removed from the earlier version of HDB. Database contents include compilations of post-translational modifications for each of the core and linker histones, as well as genomic information in the form of map loci for the human histone gene complement, with the genetic loci linked to Online Mendelian Inheritance in Man (OMIM). Conflicts between similar sequence entries from a number of source databases are also documented. Newly added to the HDB are multiple sequence alignments in which predicted functions of histone fold amino acid residues are annotated. The database is freely accessible through the WWW at http://genome.nhgri.nih.gov/histones/

Genomics: Re-evaluation of translation machinery evolution

Experiments based on genome sequence analysis have revealed unexpected complexity in the evolution of the translation apparatus, including concerted evolution of Gln-tRNA synthetase and Glu-tRNAGln amidotransferase, and a novel, class I Lys-tRNA synthetase shared by archaea and spirochaetes.

Biology in silico – a mixed bag: Computational Methods in Molecular Biology (New Comprehensive Biochemistry Vol. 32) edited by S. L. Salzberg, D. B. Searls and S. Kasif

Elsevier, 1998. US

Conserved domains in DNA repair proteins and evolution of repair systems

59.00 (xxvi + 371 pages)ISBN 0 444 502041The past decade has seen the spectacular rise of yet another ‘flavor’ of biology – computational biology (or bioinformatics). As a computational biologist, I have always felt that this discipline has the potential to bridge the gap between several disparate aspects of biological research. However, given that the founders of this field hail from backgrounds as diverse as computer science, the physical sciences and biology, there is a certain degree of heterogeneity in its practice. It has even lead to the question of whether computational biology can be considered to be a coherent discipline or merely a bag of support tools to aid the experimental biologist in the data-rich environment of the 1990s. This might also have occurred to the cursory reader of this book, although, admittedly, the title of Computational Methods in Molecular Biology probably justifies the lack of a unified approach. An attempt at gelling the discrete parts is made by the well-written introductory or tutorial chapters by Searls and Salzberg, which, to some extent, also offer the basic conceptual introduction requisite for further reading. In spite of this, the reader is at the mercy of the variable explanatory skills of the individual authors in the subsequent chapters. Of note are the chapters on hidden Markov models in sequence analysis by Krogh and on splice-site-finding by Burge, which provide good introductory accounts of these topics.Undoubtedly, gene screening and biopolymer sequence analysis are two of the most important aspects of computational biology. Although a promising overview of comparative techniques in sequence analysis is offered in the chapter by States and Reisdorf, the details receive insufficient attention. There is a particular deficit in the description of the methodologies of generating and evaluating multiple sequence alignments and evolutionary reconstructions based on protein sequences. Further, the tome already feels the adversity of the rapid burgeoning of the field – PSI-BLAST, a redoubtable addition to the sequence analysis armamentarium made its advent after the book was compiled. In terms of gene prediction, the discussion is more complete but would have benefited from a more extensive discussion of homology-based techniques that could augment the basic statistical and machine-learning-based techniques. These two basic aspects of computational biology are linked to the major challenges that face today’s researchers – genome analysis and annotation. This area receives the attention of a single chapter that describes certain aspects, but, unfortunately, this hardly does justice to the entire range of issues in this area including protein function prediction and reconstruction of an organism’s biology based on its genome sequence.The third important area of ‘in silico’ biology is protein structure prediction, protein structure comparison and related issues. About a third of this volume is devoted to this and several chapters are focused specifically on protein structure prediction using threading and ligand docking. The chapter by Jones in particular provides a good basic introduction to the problem and the different possible approaches, which included his method that met with considerable success in the 1994 edition of the Critical Assessment (of Techniques for Protein) Structure Prediction (CASP) contest. Apart from this, the section on structural aspects of computational biology lacks important topics such as secondary structure prediction and protein structure comparison and alignment. It is becoming increasingly clear that establishment of homology with known structures is likely to be the most powerful means of large-scale fold recognition. Unfortunately, the book is already out of date in this respect.With the increasing availability of information in terms of quantity and phylogenetic range as never before, computational biology is becoming increasingly relevant in all branches of the life sciences. Even the most myopic graduate student and bench biologist are certain to see the need to educate themselves in this field. What is the relevance of this book in the education of such aspirants? It is certainly no introductory textbook, given the vastly different quality and relevance of the various chapters, as well as the number of lacunae in the key subjects. Nor does it serve as a protocol book that guides the user through practical applications. Nevertheless, a student in the middle of his or her learning curve could make successful use of some of the chapters as a platform to explore certain topics in greater detail. Besides, the book can have some use as reference material for those interested in theoretical aspects of particular methodologies of gene prediction and protein structure studies.