The protein kinase resource

KinFams: De-Novo Classification of Protein Kinases Using CATH Functional Units

Protein kinases are important targets for treating human disorders, and they are the second most targeted families after G-protein coupled receptors. Several resources provide classification of kinases into evolutionary families (based on sequence homology); however, very few systematically classify functional families (FunFams) comprising evolutionary relatives that share similar functional properties. We have developed the FunFam-MARC (Multidomain ARchitecture-based Clustering) protocol, which uses multi-domain architectures of protein kinases and specificity-determining residues for functional family classification. FunFam-MARC predicts 2210 kinase functional families (KinFams), which have increased functional coherence, in terms of EC annotations, compared to the widely used KinBase classification. Our protocol provides a comprehensive classification for kinase sequences from >10,000 organisms. We associate human KinFams with diseases and drugs and identify 28 druggable human KinFams, i.e., enriched in clinically approved drugs. Since relatives in the same druggable KinFam tend to be structurally conserved, including the drug-binding site, these KinFams may be valuable for shortlisting therapeutic targets. Information on the human KinFams and associated 3D structures from AlphaFold2 are provided via our CATH FTP website and Zenodo. This gives the domain structure representative of each KinFam together with information on any drug compounds available. For 32% of the KinFams, we provide information on highly conserved residue sites that may be associated with specificity.

Advances in kinome research of parasitic worms - implications for fundamental research and applied biotechnological outcomes

Protein kinases are enzymes that play essential roles in the regulation of many cellular processes. Despite expansions in the fields of genomics, transcriptomics and bioinformatics, there is limited information on the kinase complements (kinomes) of most eukaryotic organisms, including parasitic worms that cause serious diseases of humans and animals. The biological uniqueness of these worms and the draft status of their genomes pose challenges for the identification and classification of protein kinases using established tools. In this article, we provide an account of kinase biology, the roles of kinases in diseases and their importance as drug targets, and drug discovery efforts in key socioeconomically important parasitic worms. In this context, we summarise methods and resources commonly used for the curation, identification, classification and functional annotation of protein kinase sequences from draft genomes; review recent advances made in the characterisation of the worm kinomes; and discuss the implications of these advances for investigating kinase signalling and developing small-molecule inhibitors as new anti-parasitic drugs.

Isofunctional Protein Subfamily Detection Using Data Integration and Spectral Clustering

As increasingly more genomes are sequenced, the vast majority of proteins may only be annotated computationally, given experimental investigation is extremely costly. This highlights the need for computational methods to determine protein functions quickly and reliably. We believe dividing a protein family into subtypes which share specific functions uncommon to the whole family reduces the function annotation problem's complexity. Hence, this work's purpose is to detect isofunctional subfamilies inside a family of unknown function, while identifying differentiating residues. Similarity between protein pairs according to various properties is interpreted as functional similarity evidence. Data are integrated using genetic programming and provided to a spectral clustering algorithm, which creates clusters of similar proteins. The proposed framework was applied to well-known protein families and to a family of unknown function, then compared to ASMC. Results showed our fully automated technique obtained better clusters than ASMC for two families, besides equivalent results for other two, including one whose clusters were manually defined. Clusters produced by our framework showed great correspondence with the known subfamilies, besides being more contrasting than those produced by ASMC. Additionally, for the families whose specificity determining positions are known, such residues were among those our technique considered most important to differentiate a given group. When run with the crotonase and enolase SFLD superfamilies, the results showed great agreement with this gold-standard. Best results consistently involved multiple data types, thus confirming our hypothesis that similarities according to different knowledge domains may be used as functional similarity evidence. Our main contributions are the proposed strategy for selecting and integrating data types, along with the ability to work with noisy and incomplete data; domain knowledge usage for detecting subfamilies in a family with different specificities, thus reducing the complexity of the experimental function characterization problem; and the identification of residues responsible for specificity.

Novel pyrrole derivatives as selective CHK1 inhibitors: design, regioselective synthesis and molecular modeling

3D binding interactions of 7a (magenta-colored carbons) and the co-crystallized ligand (cyan-colored carbons) with the active site amino acids of CHK1.

Kinannote, a computer program to identify and classify members of the eukaryotic protein kinase superfamily

Motivation: Kinases of the eukaryotic protein kinase superfamily are key regulators of most aspects eukaryotic cellular behavior and have provided several drug targets including kinases dysregulated in cancers. The rapid increase in the number of genomic sequences has created an acute need to identify and classify members of this important class of enzymes efficiently and accurately.

Results: Kinannote produces a draft kinome and comparative analyses for a predicted proteome using a single line command, and it is currently the only tool that automatically classifies protein kinases using the controlled vocabulary of Hanks and Hunter [Hanks and Hunter (1995)]. A hidden Markov model in combination with a position-specific scoring matrix is used by Kinannote to identify kinases, which are subsequently classified using a BLAST comparison with a local version of KinBase, the curated protein kinase dataset from www.kinase.com. Kinannote was tested on the predicted proteomes from four divergent species. The average sensitivity and precision for kinome retrieval from the test species are 94.4 and 96.8%. The ability of Kinannote to classify identified kinases was also evaluated, and the average sensitivity and precision for full classification of conserved kinases are 71.5 and 82.5%, respectively. Kinannote has had a significant impact on eukaryotic genome annotation, providing protein kinase annotations for 36 genomes made public by the Broad Institute in the period spanning 2009 to the present.

Availability: Kinannote is freely available at http://sourceforge.net/projects/kinannote.

Contact:jmgold@broadinstitute.org

Supplementary information:Supplementary data are available at Bioinformatics online.

Change of carbon source causes dramatic effects in the phospho-proteome of the archaeon Sulfolobus solfataricus

Protein phosphorylation is known to occur in Archaea. However, knowledge of phosphorylation in the third domain of life is rather scarce. Homology-based searches of archaeal genome sequences reveals the absence of two-component systems in crenarchaeal genomes but the presence of eukaryotic-like protein kinases and protein phosphatases. Here, the influence of the offered carbon source (glucose versus tryptone) on the phospho-proteome of Sulfolobus solfataricus P2 was studied by precursor acquisition independent from ion count (PAcIFIC). In comparison to previous phospho-proteome studies, a high number of phosphorylation sites (1318) located on 690 phospho-peptides from 540 unique phospho-proteins were detected, thus increasing the number of currently known archaeal phospho-proteins from 80 to 621. Furthermore, a 25.8/20.6/53.6 Ser/Thr/Tyr percentage ratio with an unexpectedly high predominance of tyrosine phosphorylation was detected. Phospho-proteins in most functional classes (21 out of 26 arCOGs) were identified, suggesting an important regulatory role in S. solfataricus. Focusing on the central carbohydrate metabolism in response to the offered carbon source, significant changes were observed. The observed complex phosphorylation pattern hints at an important physiological function of protein phosphorylation in control of the central carbohydrate metabolism, which might particularly operate in channeling carbon flux into the respective metabolic pathways.

The Protein Kinase Resource: everything you always wanted to know about protein kinases but were afraid to ask

Protein kinases and phosphatases play crucial roles in all the major cellular processes, such as signal transduction, cell differentiation, cell proliferation and cell cycle progression. Protein phosphorylation or dephosphorylation can form the basis of many critical processes, including enzyme activation or inactivation, protein localization and protein degradation. Given the importance of protein kinases to cellular development and function, it is critical that there are effective ways of disseminating information on protein kinases to the research community. This review describes such a web resource, 'The Protein Kinase Resource' (http://pkr.sdsc.edu/html/index.shtml), which serves as a repository for cellular and molecular data on protein kinases.

The age of protein kinases

Major progress has been made in unravelling of regulatory mechanisms in eukaryotic cells. Modification of target protein properties by reversible phosphorylation events has been found to be one of the most prominent cellular control processes in all organisms. The phospho-status of a protein is dynamically controlled by protein kinases and counteracting phosphatases. Therefore, monitoring of kinase and phosphatase activities, identification of specific phosphorylation sites, and assessment of their functional significance are of crucial importance to understand development and homeostasis. Recent advances in the area of molecular biology and biochemistry, for instance, mass spectrometry-based phosphoproteomics or fluorescence spectroscopical methods, open new possibilities to reach an unprecidented depth and a proteome-wide understanding of phosphorylation processes in plants and other species. In addition, the growing number of model species allows now deepening evolutionary insights into signal transduction cascades and the use of kinase/phosphatase systems. Thus, this is the age where we move from an understanding of the structure and function of individual protein modules to insights how these proteins are organized into pathways and networks. In this introductory chapter, we briefly review general definitions, methodology, and current concepts of the molecular mechanisms of protein kinase function as a foundation for this methods book. We briefly review biochemistry and structural biology of kinases and provide selected examples for the role of kinases in biological systems.

Proteomics of dense core secretory vesicles reveal distinct protein categories for secretion of neuroeffectors for cell-cell communication

Regulated secretion of neurotransmitters and neurohumoral factors from dense core secretory vesicles provides essential neuroeffectors for cell-cell communication in the nervous and endocrine systems. This study provides comprehensive proteomic characterization of the categories of proteins in chromaffin dense core secretory vesicles that participate in cell-cell communication from the adrenal medulla. Proteomic studies were conducted by nano-HPLC Chip MS/MS tandem mass spectrometry. Results demonstrate that these secretory vesicles contain proteins of distinct functional categories consisting of neuropeptides and neurohumoral factors, protease systems, neurotransmitter enzymes and transporters, receptors, enzymes for biochemical processes, reduction/oxidation regulation, ATPases, protein folding, lipid biochemistry, signal transduction, exocytosis, calcium regulation, as well as structural and cell adhesion proteins. The secretory vesicle proteomic data identified 371 proteins in the soluble fraction and 384 membrane proteins, for a total of 686 distinct secretory vesicle proteins. Notably, these proteomic analyses illustrate the presence of several neurological disease-related proteins in these secretory vesicles, including huntingtin interacting protein, cystatin C, ataxin 7, and prion protein. Overall, these findings demonstrate that multiple protein categories participate in dense core secretory vesicles for production, storage, and secretion of bioactive neuroeffectors for cell-cell communication in health and disease.

Classification of protein kinases on the basis of both kinase and non-kinase regions

Background

Protein phosphorylation is a generic way to regulate signal transduction pathways in all kingdoms of life. In many organisms, it is achieved by the large family of Ser/Thr/Tyr protein kinases which are traditionally classified into groups and subfamilies on the basis of the amino acid sequence of their catalytic domains. Many protein kinases are multi-domain in nature but the diversity of the accessory domains and their organization are usually not taken into account while classifying kinases into groups or subfamilies.

Methodology

Here, we present an approach which considers amino acid sequences of complete gene products, in order to suggest refinements in sets of pre-classified sequences. The strategy is based on alignment-free similarity scores and iterative Area Under the Curve (AUC) computation. Similarity scores are computed by detecting common patterns between two sequences and scoring them using a substitution matrix, with a consistent normalization scheme. This allows us to handle full-length sequences, and implicitly takes into account domain diversity and domain shuffling. We quantitatively validate our approach on a subset of 212 human protein kinases. We then employ it on the complete repertoire of human protein kinases and suggest few qualitative refinements in the subfamily assignment stored in the KinG database, which is based on catalytic domains only. Based on our new measure, we delineate 37 cases of potential hybrid kinases: sequences for which classical classification based entirely on catalytic domains is inconsistent with the full-length similarity scores computed here, which implicitly consider multi-domain nature and regions outside the catalytic kinase domain. We also provide some examples of hybrid kinases of the protozoan parasite Entamoeba histolytica.

Conclusions

The implicit consideration of multi-domain architectures is a valuable inclusion to complement other classification schemes. The proposed algorithm may also be employed to classify other families of enzymes with multi-domain architecture.

Novel molecular imaging platform for monitoring oncological kinases

Recent advances in oncology have lead to identification of a plethora of alterations in signaling pathways that are critical to oncogenesis and propagation of malignancy. Among the biomarkers identified, dysregulated kinases and associated changes in signaling cascade received the lion's share of scientific attention and have been under extensive investigations with goal of targeting them for anti-cancer therapy. Discovery of new drugs is immensely facilitated by molecular imaging technology which enables non-invasive, real time, dynamic imaging and quantification of kinase activity. Here, we review recent development of novel kinase reporters based on conformation dependent complementation of firefly luciferase to monitor kinase activity. Such reporter system provides unique insights into the pharmacokinetics and pharmacodynamics of drugs that modulate kinase signaling and have a huge potential in drug discovery, validation, and drug-target interactions.

Serum-dependent selective expression of EhTMKB1-9, a member of Entamoeba histolytica B1 family of transmembrane kinases

Entamoeba histolytica transmembrane kinases (EhTMKs) can be grouped into six distinct families on the basis of motifs and sequences. Analysis of the E. histolytica genome revealed the presence of 35 EhTMKB1 members on the basis of sequence identity (≥95%). Only six homologs were full length containing an extracellular domain, a transmembrane segment and an intracellular kinase domain. Reverse transcription followed by polymerase chain reaction (RT-PCR) of the kinase domain was used to generate a library of expressed sequences. Sequencing of randomly picked clones from this library revealed that about 95% of the clones were identical with a single member, EhTMKB1-9, in proliferating cells. On serum starvation, the relative number of EhTMKB1-9 derived sequences decreased with concomitant increase in the sequences derived from another member, EhTMKB1-18. The change in their relative expression was quantified by real time PCR. Northern analysis and RNase protection assay were used to study the temporal nature of EhTMKB1-9 expression after serum replenishment of starved cells. The results showed that the expression of EhTMKB1-9 was sinusoidal. Specific transcriptional induction of EhTMKB1-9 upon serum replenishment was further confirmed by reporter gene (luciferase) expression and the upstream sequence responsible for serum responsiveness was identified. EhTMKB1-9 is one of the first examples of an inducible gene in Entamoeba. The protein encoded by this member was functionally characterized. The recombinant kinase domain of EhTMKB1-9 displayed protein kinase activity. It is likely to have dual specificity as judged from its sensitivity to different kinase inhibitors. Immuno-localization showed EhTMKB1-9 to be a surface protein which decreased on serum starvation and got relocalized on serum replenishment. Cell lines expressing either EhTMKB1-9 without kinase domain, or EhTMKB1-9 antisense RNA, showed decreased cellular proliferation and target cell killing. Our results suggest that E. histolytica TMKs of B1 family are functional kinases likely to be involved in serum response and cellular proliferation.

The presence of a vast array of putative transmembrane kinase genes suggests an extensive network of signaling systems in E. histolytica, particularly the ability to perceive signals from the extracellular environment and transduce these intracellularly. However, it has been very difficult to work with these molecules due to the presence of a large number of homologs. It is also not clear if these molecules are indeed protein kinases, as no kinase activity has yet been shown associated with these molecules. In this report, we show that EhTMKB1-9 is a protein kinase and it is one of the early serum-induced genes. It is a predominant EhTMKB1 molecule that is expressed in proliferating cells and its expression is modulated by serum. Cells containing a reduced level of EhTMKB1-9 or high level of a mutant protein result in decreased proliferation, target cell killing and adherence. The results presented in this report suggest that EhTMKB1-9 is an important signaling molecule likely to be involved in E. histolytica proliferation and virulence. We have also identified a serum starvation induced response where expression of EhTMKB1-18 was found to be induced.

Combining structure and sequence information allows automated prediction of substrate specificities within enzyme families

An important aspect of the functional annotation of enzymes is not only the type of reaction catalysed by an enzyme, but also the substrate specificity, which can vary widely within the same family. In many cases, prediction of family membership and even substrate specificity is possible from enzyme sequence alone, using a nearest neighbour classification rule. However, the combination of structural information and sequence information can improve the interpretability and accuracy of predictive models. The method presented here, Active Site Classification (ASC), automatically extracts the residues lining the active site from one representative three-dimensional structure and the corresponding residues from sequences of other members of the family. From a set of representatives with known substrate specificity, a Support Vector Machine (SVM) can then learn a model of substrate specificity. Applied to a sequence of unknown specificity, the SVM can then predict the most likely substrate. The models can also be analysed to reveal the underlying structural reasons determining substrate specificities and thus yield valuable insights into mechanisms of enzyme specificity. We illustrate the high prediction accuracy achieved on two benchmark data sets and the structural insights gained from ASC by a detailed analysis of the family of decarboxylating dehydrogenases. The ASC web service is available at http://asc.informatik.uni-tuebingen.de/.

Prediction of enzymatic function of experimentally uncharacterised sequences is an important task in annotation of sequence databases. While all the information on an enzyme's specificity is necessarily contained in its sequence, prediction methods using sequence alone often do not perform all that well. Obviously, structural information – if available – will yield precious hints on the function and relative importance of specific sequence positions with respect to substrate specificity. We propose a novel method (Active Site Classification, ASC) for enzyme classification bringing together structural information and sequence information. Our ASC web server allows users to build predictive models in an automated way focused on relevant enzyme residues and furthermore to interpret the models to gain insights into the mechanism of enzyme substrate specificity.

Clustering of protein domains for functional and evolutionary studies

Background

The number of protein family members defined by DNA sequencing is usually much larger than those characterised experimentally. This paper describes a method to divide protein families into subtypes purely on sequence criteria. Comparison with experimental data allows an independent test of the quality of the clustering.

Results

An evolutionary split statistic is calculated for each column in a protein multiple sequence alignment; the statistic has a larger value when a column is better described by an evolutionary model that assumes clustering around two or more amino acids rather than a single amino acid. The user selects columns (typically the top ranked columns) to construct a motif. The motif is used to divide the family into subtypes using a stochastic optimization procedure related to the deterministic annealing EM algorithm (DAEM), which yields a specificity score showing how well each family member is assigned to a subtype. The clustering obtained is not strongly dependent on the number of amino acids chosen for the motif. The robustness of this method was demonstrated using six well characterized protein families: nucleotidyl cyclase, protein kinase, dehydrogenase, two polyketide synthase domains and small heat shock proteins. Phylogenetic trees did not allow accurate clustering for three of the six families.

Conclusion

The method clustered the families into functional subtypes with an accuracy of 90 to 100%. False assignments usually had a low specificity score.

A surface of the kinase domain critical for the allosteric activation of G protein-coupled receptor kinases

G protein-coupled receptor (GPCR) kinases (GRKs) phosphorylate activated GPCRs and initiate their desensitization. Many prior studies suggest that activated GPCRs dock to an allosteric site on the GRKs and thereby stimulate kinase activity. The extreme N-terminal region of GRKs is clearly involved in this process, but its role is not understood. Using our recent structure of bovine GRK1 as a guide, we generated mutants of solvent-exposed residues in the GRK1 kinase domain that are conserved among GRKs but not in the extended protein kinase A, G, and C family and evaluated their catalytic activity. Mutation of select residues in strands beta1 and beta3 of the kinase small lobe, alphaD of the kinase large lobe, and the protein kinase A, G, and C kinase C-tail greatly impaired receptor phosphorylation. The most dramatic effect was observed for mutation of an invariant arginine on the beta1-strand (approximately 1000-fold decrease in k(cat)/K(m)). These residues form a continuous surface that is uniquely available in GRKs for protein-protein interactions. Surprisingly, these mutants, as well as a 19-amino acid N-terminal truncation of GRK1, also show decreased catalytic efficiency for peptide substrates, although to a lesser extent than for receptor phosphorylation. Our data suggest that the N-terminal region and the newly identified surface interact and stabilize the closed, active conformation of the kinase domain. Receptor binding is proposed to promote this interaction, thereby enhancing GRK activity.

Protein functional surfaces: global shape matching and local spatial alignments of ligand binding sites

Background

Protein surfaces comprise only a fraction of the total residues but are the most conserved functional features of proteins. Surfaces performing identical functions are found in proteins absent of any sequence or fold similarity. While biochemical activity can be attributed to a few key residues, the broader surrounding environment plays an equally important role.

Results

We describe a methodology that attempts to optimize two components, global shape and local physicochemical texture, for evaluating the similarity between a pair of surfaces. Surface shape similarity is assessed using a three-dimensional object recognition algorithm and physicochemical texture similarity is assessed through a spatial alignment of conserved residues between the surfaces. The comparisons are used in tandem to efficiently search the Global Protein Surface Survey (GPSS), a library of annotated surfaces derived from structures in the PDB, for studying evolutionary relationships and uncovering novel similarities between proteins.

Conclusion

We provide an assessment of our method using library retrieval experiments for identifying functionally homologous surfaces binding different ligands, functionally diverse surfaces binding the same ligand, and binding surfaces of ubiquitous and conformationally flexible ligands. Results using surface similarity to predict function for proteins of unknown function are reported. Additionally, an automated analysis of the ATP binding surface landscape is presented to provide insight into the correlation between surface similarity and function for structures in the PDB and for the subset of protein kinases.

Classification of proteins based on similarity of two-dimensional protein maps

Data reduction techniques are now a vital part of numerical analysis and principal component analysis is often used to identify important molecular features from a set of descriptors. We now take a different approach and apply data reduction techniques directly to protein structure. With this we can reduce the three-dimensional structural data into two-dimensions while preserving the correct relationships. With two-dimensional representations, structural comparisons between proteins are accelerated significantly. This means that protein-protein similarity comparisons are now feasible on a large scale. We show how the approach can help to predict the function of kinase structures according to the Hanks' classification based on their structural similarity to different kinase classes.

Determinants of protein function revealed by combinatorial entropy optimization

We use a new algorithm (combinatorial entropy optimization [CEO]) to identify specificity residues and functional subfamilies in sets of proteins related by evolution. Specificity residues are conserved within a subfamily but differ between subfamilies, and they typically encode functional diversity. We obtain good agreement between predicted specificity residues and experimentally known functional residues in protein interfaces. Such predicted functional determinants are useful for interpreting the functional consequences of mutations in natural evolution and disease.

ProCKSI: a decision support system for Protein (structure) Comparison, Knowledge, Similarity and Information

Background

We introduce the decision support system for Protein (Structure) Comparison, Knowledge, Similarity and Information (ProCKSI). ProCKSI integrates various protein similarity measures through an easy to use interface that allows the comparison of multiple proteins simultaneously. It employs the Universal Similarity Metric (USM), the Maximum Contact Map Overlap (MaxCMO) of protein structures and other external methods such as the DaliLite and the TM-align methods, the Combinatorial Extension (CE) of the optimal path, and the FAST Align and Search Tool (FAST). Additionally, ProCKSI allows the user to upload a user-defined similarity matrix supplementing the methods mentioned, and computes a similarity consensus in order to provide a rich, integrated, multicriteria view of large datasets of protein structures.

Results

We present ProCKSI's architecture and workflow describing its intuitive user interface, and show its potential on three distinct test-cases. In the first case, ProCKSI is used to evaluate the results of a previous CASP competition, assessing the similarity of proposed models for given targets where the structures could have a large deviation from one another. To perform this type of comparison reliably, we introduce a new consensus method. The second study deals with the verification of a classification scheme for protein kinases, originally derived by sequence comparison by Hanks and Hunter, but here we use a consensus similarity measure based on structures. In the third experiment using the Rost and Sander dataset (RS126), we investigate how a combination of different sets of similarity measures influences the quality and performance of ProCKSI's new consensus measure. ProCKSI performs well with all three datasets, showing its potential for complex, simultaneous multi-method assessment of structural similarity in large protein datasets. Furthermore, combining different similarity measures is usually more robust than relying on one single, unique measure.

Conclusion

Based on a diverse set of similarity measures, ProCKSI computes a consensus similarity profile for the entire protein set. All results can be clustered, visualised, analysed and easily compared with each other through a simple and intuitive interface.

ProCKSI is publicly available at for academic and non-commercial use.

Development of a heme protein structure-electrochemical function database

Proteins containing heme, iron(protoporphyrin IX) and its variants, continue to be one of the most-studied classes of biomolecules due to their diverse range of biological functions. The literature is abundant with reports of structural and functional characterization of individual heme proteins which demonstrate that heme protein reduction potential values, E_m, span the range from –550 mV to +450 mV versus SHE. In order to unite these data for the purposes of global analysis, a new web-based resource of heme protein structure–function relationships is presented: the Heme Protein Database (HPD). This database is the first of its kind to combine heme protein structural classifications including protein fold, heme type and heme axial ligands, with heme protein reduction potential values in a web-searchable format. The HPD is located at http://heme.chem.columbia.edu/heme.php. The data illustrate that heme protein E_m values are modulated over a 300 mV range by the type of global protein fold, a 600 mV range by the type of porphyrin and an 800 mV range by the axial ligands. Thus, the 1 V range observed in heme protein reduction potential values in biological systems arises from subtle combinations of these various factors.

Ruthenium half-sandwich complexes as protein kinase inhibitors: an N-succinimidyl ester for rapid derivatizations of the cyclopentadienyl moiety

Cyclopentadienyl half-sandwich ruthenium complexes have been demonstrated to be promising scaffolds as protein kinase inhibitors. In order to rapidly identify derivatives which display modified pharmacological properties, we developed the synthesis of an organoruthenium compound bearing an N-succinimidyl ester at the cyclopentadienyl moiety. The quenching of this activated ester with a library of primary amines, followed by testing of the resulting amide library, led to the identification of organometallic Pim-1 and GSK-3 inhibitors with improved potencies and kinase selectivities. [structure: see text].

Con-Struct Map: a comparative contact map analysis tool

Con-Struct Map is a graphical tool for the comparative study of protein structures. The tool detects potential conserved residue contacts shared by multiple protein structures by superimposing their contact maps according to a multiple structure alignment. In general, Con-Struct Map allows the study of structural changes resulting from, e.g. sequence substitutions, or alternatively, the study of conserved components of a structure framework across structurally aligned proteins. Specific applications include the study of sequence-structure relationship in distantly related proteins and the comparisons of wild type and mutant proteins.

AVAILABILITY

http://pdbrs3.sdsc.edu/ConStructMap/viewer_argument_generator/singleArguments.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

EpitopeViewer: a Java application for the visualization and analysis of immune epitopes in the Immune Epitope Database and Analysis Resource (IEDB)

BACKGROUND

Structural information about epitopes, particularly the three-dimensional (3D) structures of antigens in complex with immune receptors, presents a valuable source of data for immunology. This information is available in the Protein Data Bank (PDB) and provided in curated form by the Immune Epitope Database and Analysis Resource (IEDB). With continued growth in these data and the importance in understanding molecular level interactions of immunological interest there is a need for new specialized molecular visualization and analysis tools.

RESULTS

The EpitopeViewer is a platform-independent Java application for the visualization of the three-dimensional structure and sequence of epitopes and analyses of their interactions with antigen-specific receptors of the immune system (antibodies, T cell receptors and MHC molecules). The viewer renders both 3D views and two-dimensional plots of intermolecular interactions between the antigen and receptor(s) by reading curated data from the IEDB and/or calculated on-the-fly from atom coordinates from the PDB. The 3D views and associated interactions can be saved for future use and publication. The EpitopeViewer can be accessed from the IEDB Web site http://www.immuneepitope.org through the quick link 'Browse Records by 3D Structure.'

CONCLUSION

The EpitopeViewer is designed and been tested for use by immunologists with little or no training in molecular graphics. The EpitopeViewer can be launched from most popular Web browsers without user intervention. A Java Runtime Environment (RJE) 1.4.2 or higher is required.

Expression and function of a family of transmembrane kinases from the protozoan parasite Entamoeba histolytica

The signaling proteome of Entamoeba histolytica is made of transmembrane kinases (TMKs) that are rarely found in unicellular eukaryotes. There are 90 TMK genes reported for E. histolytica, and these have been grouped into nine distinct families based on motifs present on both extracellular and kinase domains. Of these, the B1 family was chosen for further analysis. Genomic sequencing revealed the presence of 28 members belonging to this family. Genes corresponding to the majority of these were truncated and not considered for further analysis. Only five members were full length and contained both extracellular and cytosolic kinase domains. BLAST analysis revealed the presence of homologs of these B1 TMKs in the nonpathogenic Entamoeba dispar. However, the ligand binding domains of the orthologous B1 TMKs of the two species showed considerable divergence, indicating the possibility of a correlation with the pathogenic potential of the organism. Only two of the five full-length copies (B1.I.1 and B1.I.2) were expressed in E. histolytica under the culture conditions used. Antisera generated against the extracellular domain of B1.I.1 stained the cell surface, particularly the areas of contact between the trophozoites. Staining was also seen in the frontal and posterior regions of the motile amoeba. An amoebic cell line expressing a truncated version of the B1.I.1 that lacked the kinase domain was generated. Inducible expression of the truncated TMK resulted in a decrease in cellular proliferation and an increase in sensitivity to serum starvation. Our data indicate that the B1.I class of TMKs is involved in parasite proliferation.

Rank information: a structure-independent measure of evolutionary trace quality that improves identification of protein functional sites

Protein functional sites are key targets for drug design and protein engineering, but their large-scale experimental characterization remains difficult. The evolutionary trace (ET) is a computational approach to this problem that has been useful in a variety of case studies, but its proteomic scale application is partially hindered because automated retrieval of input sequences from databases often includes some with errors that degrade functional site identification. To recognize and purge these sequences, this study introduces a novel and structure-free measure of ET quality called rank information (RI). It is shown that RI decreases in response to errors in sequences, alignments, or functional classifications. Conversely, an automated procedure to increase RI by selectively removing sequences improves functional site identification so as to nearly match manually curated traces in kinases and in a test set of 79 diverse proteins. Thus we conclude that RI partially reflects the evolutionary consistency of sequence, structure, and function. In practice, as the size of the proteome continues to grow exponentially, it provides a novel and structure-free measure of ET quality that increases its accuracy for large-scale automated annotation of protein functional sites.

Protein kinase resource: an integrated environment for phosphorylation research

The protein kinase superfamily is an important group of enzymes controlling cellular signaling cascades. The increasing amount of available experimental data provides a foundation for deeper understanding of details of signaling systems and the underlying cellular processes. Here, we describe the Protein Kinase Resource, an integrated online service that provides access to information relevant to cell signaling and enables kinase researchers to visualize and analyze the data directly in an online environment. The data set is synchronized with Uniprot and Protein Data Bank (PDB) databases and is regularly updated and verified. Additional annotation includes interactive display of domain composition, cross-references between orthologs and functional mapping to OMIM records. The Protein Kinase Resource provides an integrated view of the protein kinase superfamily by linking data with their visual representation. Thus, human kinases can be mapped onto the human kinome tree via an interactive display. Sequence and structure data can be easily displayed using applications developed for the PKR and integrated with the website and the underlying database. Advanced search mechanisms, such as multiparameter lookup, sequence pattern, and blast search, enable fast access to the desired information, while statistics tools provide the ability to analyze the relationships among the kinases under study. The integration of data presentation and visualization implemented in the Protein Kinase Resource can be adapted by other online providers of scientific data and should become an effective way to access available experimental information.

LGICdb: a manually curated sequence database after the genomes

Ligand-gated ion channels form transmembrane ionic pores controlled by the binding of chemicals. The LGICdb aims to be a non-redundant, manually curated resource offering access to the large number of subunits composing extracellularly activated ligand-gated ion channels, such as nicotinic, ATP, GABA and glutamate ionotropic receptors. Composed of more than 500 human curated entries, the XML native database has been relocated in 2004 to the EBI. Its facilities have been enhanced with a new search system, customized multiple sequence alignments and manipulation of protein structures (). Despite the vast improvement of general sequence resources, the LGICdb still provide sequences unavailable elsewhere.

Identification of functional domains within the septation initiation network kinase, Cdc7

The septation initiation network (SIN) serves to coordinate cytokinesis with mitotic exit in the fission yeast Schizosaccharomyces pombe. SIN components Spg1 and Cdc7 together play a central role in regulating the onset of septation and cytokinesis. Spg1, a Ras-like GTPase, localizes to the spindle pole bodies (SPBs) throughout the cell cycle. It is converted to its GTP-bound (active) state during mitosis, only to become inactivated at one SPB during anaphase and at both SPBs as cells exit mitosis. Cdc7 functions as an effector kinase for Spg1, binding to Spg1 in its GTP-bound state, and therefore is present at both SPBs during mitosis and asymmetrically at only one during anaphase. Interestingly, the kinase activity of Cdc7 does not vary across the cell cycle, suggesting the possibility that Cdc7 kinase activity is independent of Spg1 binding. Consistent with this, we found that Cdc7 associates with Spg1 only during mitosis. To learn more about the essential role of Cdc7 kinase in the SIN and its regulation, we undertook a structure/function analysis and identified independent functional domains within Cdc7. We found that a region adjacent to the kinase domain is responsible for Spg1 association and identified an overlapping but distinct SPB localization domain. In addition Cdc7 associates with itself and exists as a dimer in vivo.

Substrate specificity of protein kinases and computational prediction of substrates

To ensure signalling fidelity, kinases must act only on a defined subset of cellular targets. Appreciating the basis for this substrate specificity is essential for understanding the role of an individual protein kinase in a particular cellular process. The specificity in the cell is determined by a combination of "peptide specificity" of the kinase (the molecular recognition of the sequence surrounding the phosphorylation site), substrate recruitment and phosphatase activity. Peptide specificity plays a crucial role and depends on the complementarity between the kinase and the substrate and therefore on their three-dimensional structures. Methods for experimental identification of kinase substrates and characterization of specificity are expensive and laborious, therefore, computational approaches are being developed to reduce the amount of experimental work required in substrate identification. We discuss the structural basis of substrate specificity of protein kinases and review the experimental and computational methods used to obtain specificity information.

Sequence survey of receptor tyrosine kinases reveals mutations in glioblastomas

It is now clear that tyrosine kinases represent attractive targets for therapeutic intervention in cancer. Recent advances in DNA sequencing technology now provide the opportunity to survey mutational changes in cancer in a high-throughput and comprehensive manner. Here we report on the sequence analysis of members of the receptor tyrosine kinase (RTK) gene family in the genomes of glioblastoma brain tumors. Previous studies have identified a number of molecular alterations in glioblastoma, including amplification of the RTK epidermal growth factor receptor. We have identified mutations in two other RTKs: (i) fibroblast growth receptor 1, including the first mutations in the kinase domain in this gene observed in any cancer, and (ii) a frameshift mutation in the platelet-derived growth factor receptor-alpha gene. Fibroblast growth receptor 1, platelet-derived growth factor receptor-alpha, and epidermal growth factor receptor are all potential entry points to the phosphatidylinositol 3-kinase and mitogen-activated protein kinase intracellular signaling pathways already known to be important for neoplasia. Our results demonstrate the utility of applying DNA sequencing technology to systematically assess the coding sequence of genes within cancer genomes.

Kinetic analysis of inhibition of cAMP-dependent protein kinase catalytic subunit by the peptide-nucleoside conjugate AdcAhxArg6

Kinetic analysis of the inhibition of the phosphorylation of Kemptide, (LRRASLG), catalyzed by the catalytic subunit of cAMP-dependent protein kinase, by a peptide-nucleoside conjugate inhibitor AdcAhxArg6 was carried out over a wide range of ATP and peptide concentrations. A simple procedure was proposed for characterization of the interaction of this inhibitor with the free enzyme, and with the enzyme-ATP and enzyme-peptide complexes. The second-order rate constants, calculated from the steady-state reaction kinetics, were used for this analysis to avoid the complications related to the complex catalytic mechanism of the protein kinase catalyzed reaction.

Bisubstrate analog probes for the insulin receptor protein tyrosine kinase: molecular yardsticks for analyzing catalytic mechanism and inhibitor design

Bisubstrate analogs have the potential to provide enhanced specificity for protein kinase inhibition and tools to understand catalytic mechanism. Previous efforts led to the design of a peptide-ATP conjugate bisubstrate analog utilizing aminophenylalanine in place of tyrosine and a thioacetyl linker to the gamma-phosphate of ATP which was a potent inhibitor of the insulin receptor kinase (IRK). In this study, we have examined the contributions of various electrostatic and structural elements in the bisubstrate analog to IRK binding affinity. Three types of changes (seven specific analogs in all) were introduced: a Tyr isostere of the previous aminophenylalanine moiety, modifications of the spacer between the adenine and the peptide, and deletions and substitutions within the peptide moiety. These studies allowed a direct evaluation of the hydrogen bond strength between the anilino nitrogen of the bisubstrate analog and the enzyme catalytic base Asp and showed that it contributes 2.5 kcal/mol of binding energy, in good agreement with previous predictions. Modifications of the linker length resulted in weakened inhibitory affinity, consistent with the geometric requirements of an enzyme-catalyzed dissociative transition state. Alterations in the peptide motif generally led to diminished inhibitory potency, and only some of these effects could be rationalized based on prior kinetic and structural studies. Taken together, these results suggest that a combination of mechanism-based design and empirical synthetic manipulation will be necessary in producing optimized protein kinase bisubstrate analog inhibitors.

Casein Kinase 1α Interacts with Retinoid X Receptor and Interferes with Agonist-induced Apoptosis

Agonists of retinoid X receptors (RXRs), which include the natural 9-cis-retinoic acid and synthetic analogs, are potent inducers of growth arrest and apoptosis in some cancer cells. As such, they are being used in clinical trials for the treatment and prevention of solid tumors and are used to treat cutaneous T cell lymphoma. However, the molecular mechanisms that underlie the anti-cancer effects of RXR agonists remain unclear. Here, we show that a novel pro-apoptotic pathway that is induced by RXR agonist is negatively regulated by casein kinase 1alpha (CK1alpha). CK1alpha associates with RXR in an agonist-dependent manner and phosphorylates RXR. The ability of an RXR agonist to recruit CK1alpha to a complex with RXR in cells correlates inversely with its ability to inhibit growth. Remarkably, depletion of CK1alpha in resistant cells renders them susceptible to RXR agonist-induced growth inhibition and apoptosis. Our study shows that CK1alpha can promote cell survival by interfering with RXR agonist-induced apoptosis. Inhibition of CK1alpha may enhance the anti-cancer effects of RXR agonists.

Protein structural alignment for detection of maximally conserved regions

An algorithm for comparison of homologous protein structures and for study of conformational changes in proteins, has been developed. The method is based on identification of pieces of the two molecules that have similar shapes, as determined by the local conformation of the polypeptide chain. Pieces that superpose within a specified tolerance are assembled into domains based on similar transformations for superposition. The result is sets of pieces that represent conserved structural elements and conserved spatial relationships between structural elements within the proteins being compared. A similarity criterion based on maximum distance rather than on root mean square deviation reduces bias by outliers. The utility of the method is demonstrated by using examples from the protein kinase family.

KinG: a database of protein kinases in genomes

The KinG database is a comprehensive collection of serine/threonine/tyrosine-specific kinases and their homologues identified in various completed genomes using sequence and profile search methods. The database hosted at http://hodgkin. mbu.iisc.ernet.in/ approximately king provides the amino acid sequences, functional domain assignments and classification of gene products containing protein kinase domains. A search tool enabling the retrieval of protein kinases with specified subfamily and domain combinations is one of the key features of the resource. Identification of a kinase catalytic domain in the user's query sequence is possible using another search tool. The occurrence and location of critical catalytic residues if the query has a catalytic kinase domain, recognition of non-kinase domains in the sequence and subfamily classification of the kinase in the query will help in deciphering the biological role of the kinase. This online compilation can also be used to compare the protein kinases of a given subfamily and domain combinations across various genomes. Another exclusive feature of the database is the collection of the Ser/Thr/Tyr protein kinases and similar sequences encoded in the genomes of archaea and bacteria.

Cloning and characterization of a novel radish protein kinase which is homologous to fungal cot-I like and animal Ndr protein kinases

According to the similarity of the amino acid sequences in their catalytic domains, eukaryotic protein kinases have been classified into the five main groups: 'AGC', 'CaMK', 'CMGC', 'PTK' and 'other'. The AGC group, represented by the cyclic nucleotide-dependent kinases (PKA and PKG), the calcium-phospholipid-dependent kinases (PKC) and the ribosomal S6 protein kinases, are poorly characterized in plants except for a few cases. In this study, in order to gain a better understanding of plant protein kinases in the AGC group, three cDNAs encoding novel protein kinases, RsNdr1 and RsNdr2a/b, were cloned from radish and characterized by molecular and biochemical methods. The deduced amino acid sequences of RsNdr1 and RsNdr2a/b contained all 12 conserved catalytic subdomains which are characteristic of the eukaryotic Ser/Thr protein kinases. A cell lysate from E. coli overexpressing RsNdr1 fusion protein had protein kinase activity toward a conventional protein substrate (myelin basic protein), whereas that from E. coli harboring a fusion plasmid encoding kinase-dead RsNdr1 or RsNdr2 did not show any protein kinase activity. A phylogenetic tree for 17 protein kinases from various organisms showed that the RsNdrs are more closely related to the protein kinases in a particular subgroup of the 'AGC' (fungal cot1-like and animal Ndr kinases) than to the authentic 'AGC' protein kinases, such as PKA, PKC or ribosomal S6 kinase.

Structural basis for UCN-01 (7-hydroxystaurosporine) specificity and PDK1 (3-phosphoinositide-dependent protein kinase-1) inhibition

PDK1 (3-phosphoinositide-dependent protein kinase-1) is a member of the AGC (cAMP-dependent, cGMP-dependent, protein kinase C) family of protein kinases, and has a key role in insulin and growth-factor signalling through phosphorylation and subsequent activation of a number of other AGC kinase family members, such as protein kinase B. The staurosporine derivative UCN-01 (7-hydroxystaurosporine) has been reported to be a potent inhibitor for PDK1, and is currently undergoing clinical trials for the treatment of cancer. Here, we report the crystal structures of staurosporine and UCN-01 in complex with the kinase domain of PDK1. We show that, although staurosporine and UCN-01 interact with the PDK1 active site in an overall similar manner, the UCN-01 7-hydroxy group, which is not present in staurosporine, generates direct and water-mediated hydrogen bonds with active-site residues. Inhibition data from UCN-01 tested against a panel of 29 different kinases show a different pattern of inhibition compared with staurosporine. We discuss how these differences in inhibition could be attributed to specific interactions with the additional 7-hydroxy group, as well as the size of the 7-hydroxy-group-binding pocket. This information could lead to opportunities for structure-based optimization of PDK1 inhibitors.

Exploring the nonlinear geometry of protein homology

The explosion of biological data resulting from genomic and proteomic research has created a pressing need for data analysis techniques that work effectively on a large scale. An area of particular interest is the organization and visualization of large families of protein sequences. An increasingly popular approach is to embed the sequences into a low-dimensional Euclidean space in a way that preserves some predefined measure of sequence similarity. This method has been shown to produce maps that exhibit global order and continuity and reveal important evolutionary, structural, and functional relationships between the embedded proteins. However, protein sequences are related by evolutionary pathways that exhibit highly nonlinear geometry, which is invisible to classical embedding procedures such as multidimensional scaling (MDS) and nonlinear mapping (NLM). Here, we describe the use of stochastic proximity embedding (SPE) for producing Euclidean maps that preserve the intrinsic dimensionality and metric structure of the data. SPE extends previous approaches in two important ways: (1) It preserves only local relationships between closely related sequences, thus allowing the map to unfold and reveal its intrinsic dimension, and (2) it scales linearly with the number of sequences and therefore can be applied to very large protein families. The merits of the algorithm are illustrated using examples from the protein kinase and nuclear hormone receptor superfamilies.

A computational model of binding thermodynamics: the design of cyclin-dependent kinase 2 inhibitors

The cyclin-dependent protein kinases are important targets in drug discovery because of their role in cell cycle regulation. In this computational study, we have applied a continuum solvent model to study the interactions between cyclin-dependent kinase 2 (CDK2) and analogues of the clinically tested anticancer agent flavopiridol. The continuum solvent model uses Coulomb's law to account for direct electrostatic interactions, solves the Poisson equation to obtain the electrostatic contributions to solvation energy, and calculates scaled solvent-accessible surface area to account for hydrophobic interactions. The computed free energy of binding gauges the strength of protein-ligand interactions. Our model was first validated through a study on the binding of a number of flavopiridol derivatives to CDK2, and its ability to identify potent inhibitors was observed. The model was then used to aid in the design of novel CDK2 inhibitors with the aid of a computational sensitivity analysis. Some of these hypothetical structures could be significantly more potent than the lead compound flavopiridol. We applied two approaches to gain insights into designing selective inhibitors. One relied on the comparative analysis of the binding pocket for several hundred protein kinases to identify the parts of a lead compound whose modifications might lead to selective compounds. The other was based on building and using homology models for energy calculations. The homology models appear to be able to classify ligand potency into groups but cannot yet give reliable quantitative results.

CASTp: Computed Atlas of Surface Topography of proteins

Computed Atlas of Surface Topography of proteins (CASTp) provides an online resource for locating, delineating and measuring concave surface regions on three-dimensional structures of proteins. These include pockets located on protein surfaces and voids buried in the interior of proteins. The measurement includes the area and volume of pocket or void by solvent accessible surface model (Richards' surface) and by molecular surface model (Connolly's surface), all calculated analytically. CASTp can be used to study surface features and functional regions of proteins. CASTp includes a graphical user interface, flexible interactive visualization, as well as on-the-fly calculation for user uploaded structures. CASTp is updated daily and can be accessed at http://cast.engr.uic.edu.

Receptor kinase signaling in plant development

The Arabidopsis genome sequence has revealed that plants contain a much larger complement of receptor kinase genes than other organisms. Early analysis of these genes revealed involvement in a diverse array of developmental and defense functions that included gametophyte development, pollen-pistil interactions, shoot apical meristem equilibrium, hormone perception, and cell morphogenesis. Amino acid sequence motifs and binding studies indicate that the ectodomains are capable of binding, either directly or indirectly, various classes of molecules including proteins, carbohydrates, and steroids. Genetic and biochemical approaches have begun to identify other components of several signal transduction pathways. Some receptor-like kinases (RLKs) appear to function with coreceptors lacking kinase domains, and genome analysis suggests this might be true for many RLKs. The KAPP protein phosphatase functions as a negative regulator of at least two RLK systems, and in vitro studies suggest it could be a common component of more. Whether plant signaling systems display a modularity similar to animal systems remains to be determined. Future efforts will reveal unknown functions of other RLKs and elucidate the relationships among their signaling networks.

Utilising structural knowledge in drug design strategies: applications using Relibase

The concept of structure-based drug design is based upon an in-depth understanding of the principles of molecular recognition. Despite our lack of a thorough comprehension of these principles, the wealth of protein structures available opens up unprecedented possibilities for new insights from the analysis of these data. Unravelling universal rules of molecular recognition is certainly one of the most appealing goals. But our knowledge is enhanced also when studying the specific determinants that characterise single targets or target families only, and the factors governing and discriminating their recognition properties.Here, we illustrate how the structure-based design process can benefit from the consequent incorporation of database query tools. We discuss representative examples to address issues such as protein flexibility, water molecules in binding pockets, and ligand specificity as some of the most critical aspects of drug design. All studies are carried out using our database system Relibase. We also show the application of Relibase in searching for preferred geometrical patterns between interacting molecular fragments.

Crystal structure of an inactive Akt2 kinase domain

Akt/PKB represents a subfamily of three isoforms from the AGC serine/threonine kinase family. Amplification of Akt activity has been implicated in diseases that involve inappropriate cell survival, including a number of human malignancies. The structure of an inactive and unliganded Akt2 kinase domain reveals several features that distinguish it from other kinases. Most of the alpha helix C is disordered. The activation loop in this structure adopts a conformation that appears to sterically hinder the binding of both ATP and peptide substrate. In addition, an intramolecular disulfide bond is observed between two cysteines in the activation loop. Residues within the linker region between the N- and C-terminal lobes also contribute to the inactive conformation by partially occupying the ATP binding site.

The evolution of structural databases

Starting with the Protein Data Bank (PDB) as a common ancestor, the evolution of structural databases has been driven by the rapprochement of the structural world and the practical applications. The result is an impressive number of secondary structural databases that is welcomed by structural biologists and bioinformaticians but runs the risk of producing an embarrassment of riches among non-specialist users. Given that any profit depends on the number of customers, efficient interfaces between many structural data banks must be available to make their contents easily accessible. Increasing the information content of central structural repositories might be the best way to guide users through the many, sometimes overlapping databases.

Regulation of cAMP-dependent protein kinase activity by glutathionylation

The catalytic subunit of cAMP-dependent protein kinase (cAPK) is susceptible to inactivation by a number of thiol-modifying reagents. Inactivation occurs through modification of cysteine 199, which is located near the active site. Because cysteine 199 is reactive at physiological pH, and modification of this site inhibits activity, we hypothesized that cAPK is a likely target for regulation by an oxidative mechanism, specifically glutathionylation. In vitro studies demonstrated the susceptibility of kinase activity to the sulfhydryl oxidant diamide, which inhibited by promoting an intramolecular disulfide bond between cysteines 199 and 343. In the presence of a low concentration of diamide and reduced glutathione, the kinase was rapidly and reversibly inhibited by glutathionylation. Mutant kinase containing an alanine to cysteine mutation at position 199 was resistant to inhibition by both diamide and glutathionylation, thus implicating this as the oxidation-sensitive site. Mouse fibroblast cells treated with diamide showed a reversible decrease in cAPK activity. Inhibition was dramatically enhanced when cells were first treated with cAPK activators. Using biotin-cysteine as means for detecting and purifying thiolated cAPK from cells, we were able to show that, under conditions in which cAPK is inactivated by diamide, it is also readily thiolated.

In silico identification of novel therapeutic targets

The availability of the human genome sequence is a 'once in a lifetime' opportunity for scientists to uncover all possible human drug-targets. As the sequence is very large, the best way to identify new genes rapidly is by computational (in silico) methods. There are now many examples in which pharmaceutical companies have identified genes of interest initially by in silico analysis. High-throughput data-generation techniques, such as microarray analysis, are key to the generation of human genome data. Bioinformatics techniques are therefore certain to play an increasingly important role in drug discovery.

Lipopolysaccharide phosphorylating enzymes encoded in the genomes of Gram-negative bacteria are related to the eukaryotic protein kinases

By means of profile-matching procedures, conservation of functionally important residues, and fold-recognition techniques, we show that two distinct families of lipopolysaccharide kinases encoded in the genomes of Gram-negative bacteria are related to each other and to two distinct classes of proteins, namely eukaryotic protein kinases and right open reading frame (RIO1). Members of one of the lipopolysaccharide kinase families are identified only in pathogenic bacteria. Phosphorylation by these enzymes is relevant in the construction of outer membrane, immune response, and pathogenic virulence. The class of proteins called RIO1, also related to eukaryotic protein kinases and previously known to occur only in archaea and eukaryotes, are now identified in eubacteria as well. It has been suggested here that RIO1 proteins are intermediately related to lipopolysaccharide kinases and eukaryotic protein kinases implying an evolutionary relationship between the three classes of proteins.