A database and tools for 3-D protein structure comparison and alignment using the Combinatorial Extension (CE) algorithm

Molecular modelling evaluation of exon 18 His845_Asn848delinsPro PDGFRα mutation in a metastatic GIST patient responding to imatinib

Platelet-Derived Growth Factor Receptor Alpha (PDGFRA) mutations occur in approximately 5-7% of gastrointestinal stromal tumours (GIST). Over half of all PDGFRA mutations are represented by the substitution at position 842 in the A-loop of an aspartic acid (D) with a valine (V), recognized as D842V, conferring primary resistance to imatinib in vitro and in clinical observations due to the conformation of the kinase domain, which negatively affects imatinib binding. The lack of interaction between imatinib and the D842V PDGFRA mutated model has been established and widely confirmed in vivo. However, for the other PDGFRA mutations, the correlation between pre-clinical and clinical data is still unclear. An in silico evaluation of the p.His845_Asn848delinsPro mutation involving exon 18 of PDGFRA in a metastatic GIST patient responding to first-line imatinib has been provided. Docking analyses were performed, and the ligand-receptor interactions were evaluated with the jCE algorithm for structural alignment. The docking simulation and structural superimposition analysis show that PDGFRA p.His845_Asn848delinsPro stabilizes the imatinib binding site with the residues that are conserved in KIT. The in vivo evidence that PDGFRA p.His845_Asn848delinsPro is sensitive to imatinib was confirmed by the molecular modelling, which may represent a reliable tool for the prediction of clinical outcomes and treatment selection in GIST, especially for rare mutations.

Assessing Human Genetic Variations in Glucose Transporter SLC2A10 and Their Role in Altering Structural and Functional Properties

Purpose: Demand is increasing for clinical genomic sequencing to provide diagnoses for patients presenting phenotypes indicative of genetic diseases, but for whom routine genetic testing failed to yield a diagnosis. DNA-based testing using high-throughput technologies often identifies variants with insufficient evidence to determine whether they are disease-causal or benign, leading to categorization as variants of uncertain significance (VUS). Methods: We used molecular modeling and simulation to generate specific hypotheses for the molecular effects of variants in the human glucose transporter, GLUT10 (SLC2A10). Similar to many disease-relevant membrane proteins, no experimentally derived 3D structure exists. An atomic model was generated and used to evaluate multiple variants, including pathogenic, benign, and VUS. Results: These analyses yielded detailed mechanistic data, not currently predictable from sequence, including altered protein stability, charge distribution of ligand binding surfaces, and shifts toward or away from transport-competent conformations. Consideration of the two major conformations of GLUT10 was important as variants have conformation-specific effects. We generated detailed molecular hypotheses for the functional impact of variants in GLUT10 and propose means to determine their pathogenicity. Conclusion: The type of workflow we present here is valuable for increasing the throughput and resolution with which VUS effects can be assessed and interpreted.

Structure, Function, and Inhibition of Staphylococcus aureus Heptaprenyl Diphosphate Synthase

We report the first structure of heptaprenyl diphosphate synthase from Staphylococcus aureus (SaHepPPS), together with an investigation of its mechanism of action and inhibition. The protein is involved in the formation of menaquinone, a key electron transporter in many bacteria, including pathogens. SaHepPPS consists of a "catalytic " subunit (SaHepPPS-2) having two "DDXXD" motifs and a "regulatory" subunit (SaHepPPS-1) that lacks these motifs. High concentrations of the substrates, isopentenyl diphosphate and farnesyl diphosphate, inhibit the enzyme, which is also potently inhibited by bisphosphonates. The most active inhibitors (Ki ∼200 nm) were N-alkyl analogues of zoledronate containing ∼C6 alkyl side chains. They were modestly active against S. aureus cell growth, and growth inhibition was partially "rescued" by the addition of menaquinone-7. Because SaHepPPS is essential for S. aureus cell growth, its structure is of interest in the context of the development of menaquinone biosynthesis inhibitors as potential antibiotic leads.

Proteome-wide prediction of targets for aspirin: new insight into the molecular mechanism of aspirin

Besides its anti-inflammatory, analgesic and anti-pyretic properties, aspirin is used for the prevention of cardiovascular disease and various types of cancer. The multiple activities of aspirin likely involve several molecular targets and pathways rather than a single target. Therefore, systematic identification of these targets of aspirin can help us understand the underlying mechanisms of the activities. In this study, we identified 23 putative targets of aspirin in the human proteome by using binding pocket similarity detecting tool combination with molecular docking, free energy calculation and pathway analysis. These targets have diverse folds and are derived from different protein family. However, they have similar aspirin-binding pockets. The binding free energy with aspirin for newly identified targets is comparable to that for the primary targets. Pathway analysis revealed that the targets were enriched in several pathways such as vascular endothelial growth factor (VEGF) signaling, Fc epsilon RI signaling and arachidonic acid metabolism, which are strongly involved in inflammation, cardiovascular disease and cancer. Therefore, the predicted target profile of aspirin suggests a new explanation for the disease prevention ability of aspirin. Our findings provide a new insight of aspirin and its efficacy of disease prevention in a systematic and global view.

A novel esterase subfamily with α/β-hydrolase fold suggested by structures of two bacterial enzymes homologous to L-homoserine O-acetyl transferases

MekB from Pseudomonas veronii and CgHle from Corynebacteriumglutamicum belong to the superfamily of α/β-hydrolase fold proteins. Based on sequence comparisons, they are annotated as homoserine transacetylases in popular databases like UNIPROT, PFAM or ESTHER. However, experimentally, MekB and CgHle were shown to be esterases that hydrolyse preferentially acetic acid esters. We describe the x-ray structures of these enzymes solved to high resolution. The overall structures confirm the close relatedness to experimentally validated homoserine acetyl transferases, but simultaneously the structures exclude the ability of MekB and CgHle to bind homoserine and acetyl-CoA. Insofar the MekB and CgHle structures suggest dividing the homoserine transacetylase family into subfamilies, namely genuine acetyl transferases and acetyl esterases with MekB and CgHle as constituting members of the latter.

Assembly and analysis of eukaryotic Argonaute-RNA complexes in microRNA-target recognition

Experimental studies have uncovered a variety of microRNA (miRNA)–target duplex structures that include perfect, imperfect and seedless duplexes. However, non-canonical binding modes from imperfect/seedless duplexes are not well predicted by computational approaches, which rely primarily on sequence and secondary structural features, nor have their tertiary structures been characterized because solved structures to date are limited to near perfect, straight duplexes in Argonautes (Agos). Here, we use structural modeling to examine the role of Ago dynamics in assembling viable eukaryotic miRNA-induced silencing complexes (miRISCs). We show that combinations of low-frequency, global modes of motion of Ago domains are required to accommodate RNA duplexes in model human and C. elegans Ago structures. Models of viable miRISCs imply that Ago adopts variable conformations at distinct target sites that generate distorted, imperfect miRNA-target duplexes. Ago's ability to accommodate a duplex is dependent on the region where structural distortions occur: distortions in solvent-exposed seed and 3′-end regions are less likely to produce steric clashes than those in the central duplex region. Energetic analyses of assembled miRISCs indicate that target recognition is also driven by favorable Ago-duplex interactions. Such structural insights into Ago loading and target recognition mechanisms may provide a more accurate assessment of miRNA function.

UniAlign: protein structure alignment meets evolution

MOTIVATION

During the evolution, functional sites on the surface of the protein as well as the hydrophobic core maintaining the structural integrity are well-conserved. However, available protein structure alignment methods align protein structures based solely on the 3D geometric similarity, limiting their ability to detect functionally relevant correspondences between the residues of the proteins, especially for distantly related homologous proteins.

RESULTS

In this article, we propose a new protein pairwise structure alignment algorithm (UniAlign) that incorporates additional evolutionary information captured in the form of sequence similarity, sequence profiles and residue conservation. We define a per-residue score (UniScore) as a weighted sum of these and other features and develop an iterative optimization procedure to search for an alignment with the best overall UniScore. Our extensive experiments on CDD, HOMSTRAD and BAliBASE benchmark datasets show that UniAlign outperforms commonly used structure alignment methods. We further demonstrate UniAlign's ability to develop family-specific models to drastically improve the quality of the alignments.

AVAILABILITY AND IMPLEMENTATION

UniAlign is available as a web service at: http://sacan.biomed.drexel.edu/unialign

CONTACT

ahmet.sacan@drexel.edu

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Fractal nature of protein surface roughness: a note on quantification of change of surface roughness in active sites, before and after binding

Year 2010 marked the 25th year since we came to know that roughness of a protein surface has fractal symmetry. Ever since the publication of Lewis and Rees' paper, hundreds of works from a spectrum of perspectives have established that fractal dimension (FD) can be considered as a reliable marker that describes roughness of protein surface objectively. In this article, we introduce readers to the fundamentals of fractals and present categorical biophysical and geometrical reasons as to why FD-based constructs can describe protein surface roughness more accurately. We then review the commonality (and the lack of it) between numerous approaches that have attempted to investigate protein surface with fractal measures, before exploring the patterns in the results that they have produced. Apart from presenting the genealogy of approaches and results, we present an analysis that quantifies the difference in surface roughness in stretches of protein surface containing the active site, before and after binding to ligands, to underline the utility of FD-based measures further. It has been found that surface stretches containing the active site, in general, undergo a significant increment in its roughness after binding. After presenting the entire repertoire of FD-based surface roughness studies, we talk about two yet-unexplored problems where application of FD-based techniques can help in deciphering underlying patterns of surface interactions. Finally, we list the limitations of FD-based constructs and put down several precautions that one must take while working with them.

Catalytic site identification--a web server to identify catalytic site structural matches throughout PDB

The catalytic site identification web server provides the innovative capability to find structural matches to a user-specified catalytic site among all Protein Data Bank proteins rapidly (in less than a minute). The server also can examine a user-specified protein structure or model to identify structural matches to a library of catalytic sites. Finally, the server provides a database of pre-calculated matches between all Protein Data Bank proteins and the library of catalytic sites. The database has been used to derive a set of hypothesized novel enzymatic function annotations. In all cases, matches and putative binding sites (protein structure and surfaces) can be visualized interactively online. The website can be accessed at http://catsid.llnl.gov.

Rapid catalytic template searching as an enzyme function prediction procedure

We present an enzyme protein function identification algorithm, Catalytic Site Identification (CatSId), based on identification of catalytic residues. The method is optimized for highly accurate template identification across a diverse template library and is also very efficient in regards to time and scalability of comparisons. The algorithm matches three-dimensional residue arrangements in a query protein to a library of manually annotated, catalytic residues--The Catalytic Site Atlas (CSA). Two main processes are involved. The first process is a rapid protein-to-template matching algorithm that scales quadratically with target protein size and linearly with template size. The second process incorporates a number of physical descriptors, including binding site predictions, in a logistic scoring procedure to re-score matches found in Process 1. This approach shows very good performance overall, with a Receiver-Operator-Characteristic Area Under Curve (AUC) of 0.971 for the training set evaluated. The procedure is able to process cofactors, ions, nonstandard residues, and point substitutions for residues and ions in a robust and integrated fashion. Sites with only two critical (catalytic) residues are challenging cases, resulting in AUCs of 0.9411 and 0.5413 for the training and test sets, respectively. The remaining sites show excellent performance with AUCs greater than 0.90 for both the training and test data on templates of size greater than two critical (catalytic) residues. The procedure has considerable promise for larger scale searches.

Assessment of 3D models for allergen research

Allergenic proteins must crosslink specific IgE molecules, bound to the surface of mast cells and basophils, to stimulate an immune response. A structural understanding of the allergen-IgE interface is needed to predict cross-reactivities between allergens and to design hypoallergenic proteins. However, there are less than 90 experimentally determined structures available for the approximately 1500 sequences of allergens and isoallergens cataloged in the Structural Database of Allergenic Proteins. To provide reliable structural data for the remaining proteins, we previously produced more than 500 3D models using an automated procedure, with strict controls on template choice and model quality evaluation. Here, we assessed how well the fold and residue surface exposure of 10 of these models correlated with recently published experimental 3D structures determined by X-ray crystallography or NMR. We also discuss the impact of intrinsically disordered regions on the structural comparison and epitope prediction. Overall, for seven allergens with sequence identities to the original templates higher than 27%, the backbone root-mean square deviations were less than 2 Å between the models and the subsequently determined experimental structures for the ordered regions. Further, the surface exposure of the known IgE epitopes on the models of three major allergens, from peanut (Ara h 1), latex (Hev b 2), and soy (Gly m 4), was very similar to the experimentally determined structures. For the three remaining allergens with lower sequence identities to the modeling templates, the 3D folds were correctly identified. However, the accuracy of those models is not sufficient for a reliable epitope mapping.

Nucleotide-dependent control of internal strains in ring-shaped AAA+ motors

The AAA+ (ATPase Associated with various cellular Activities) machinery represents an extremely successful and widely used design plan for biological motors. Recently found crystal structures are beginning to reveal nucleotide-dependent conformational changes in the canonical hexameric rings of the AAA+ motors. However, the physical mechanism by which ATP binding on one subunit allosterically propagates across the entire ring remains to be found. Here we analyze and compare structural organization of three ring-shaped AAA+ motors, ClpX, HslU, and dynein. By constructing multimers using subunits of identical conformations, we find that individual subunits locally possess helical geometries with varying pitch, radius, chirality, and symmetry number. These results suggest that binding of an ATP to a subunit imposes conformational constraint that must be accommodated by more flexible nucleotide-free subunits to relieve mechanical strain on the ring. Local deformation of the ring contour and subsequent propagation of strains may be a general strategy that AAA+ motors adopt to generate force while achieving functional diversity.

SAPIN: a framework for the structural analysis of protein interaction networks

SUMMARY

Protein interaction networks are widely used to depict the relationships between proteins. These networks often lack the information on physical binary interactions, and they do not inform whether there is incompatibility of structure between binding partners. Here, we introduce SAPIN, a framework dedicated to the structural analysis of protein interaction networks. SAPIN first identifies the protein parts that could be involved in the interaction and provides template structures. Next, SAPIN performs structural superimpositions to identify compatible and mutually exclusive interactions. Finally, the results are displayed using Cytoscape Web.

AVAILABILITY

The SAPIN server is available at http://sapin.crg.es.

CONTACT

jae-seong.yang@crg.eu or christina.kiel@crg.eu.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics Online.

Defining and searching for structural motifs using DeepView/Swiss-PdbViewer

Background

Today, recognition and classification of sequence motifs and protein folds is a mature field, thanks to the availability of numerous comprehensive and easy to use software packages and web-based services. Recognition of structural motifs, by comparison, is less well developed and much less frequently used, possibly due to a lack of easily accessible and easy to use software.

Results

In this paper, we describe an extension of DeepView/Swiss-PdbViewer through which structural motifs may be defined and searched for in large protein structure databases, and we show that common structural motifs involved in stabilizing protein folds are present in evolutionarily and structurally unrelated proteins, also in deeply buried locations which are not obviously related to protein function.

Conclusions

The possibility to define custom motifs and search for their occurrence in other proteins permits the identification of recurrent arrangements of residues that could have structural implications. The possibility to do so without having to maintain a complex software/hardware installation on site brings this technology to experts and non-experts alike.

SEGA: semiglobal graph alignment for structure-based protein comparison

Comparative analysis is a topic of utmost importance in structural bioinformatics. Recently, a structural counterpart to sequence alignment, called multiple graph alignment, was introduced as a tool for the comparison of protein structures in general and protein binding sites in particular. Using approximate graph matching techniques, this method enables the identification of approximately conserved patterns in functionally related structures. In this paper, we introduce a new method for computing graph alignments motivated by two problems of the original approach, a conceptual and a computational one. First, the existing approach is of limited usefulness for structures that only share common substructures. Second, the goal to find a globally optimal alignment leads to an optimization problem that is computationally intractable. To overcome these disadvantages, we propose a semiglobal approach to graph alignment in analogy to semiglobal sequence alignment that combines the advantages of local and global graph matching.

Surface-based protein binding pocket similarity

Protein similarity comparisons may be made on a local or global basis and may consider sequence information or differing levels of structural information. We present a local three-dimensional method that compares protein binding site surfaces in full atomic detail. The approach is based on the morphological similarity method which has been widely applied for global comparison of small molecules. We apply the method to all-by-all comparisons two sets of human protein kinases, a very diverse set of ATP-bound proteins from multiple species, and three heterogeneous benchmark protein binding site data sets. Cases of disagreement between sequence-based similarity and binding site similarity yield informative examples. Where sequence similarity is very low, high pocket similarity can reliably identify important binding motifs. Where sequence similarity is very high, significant differences in pocket similarity are related to ligand binding specificity and similarity. Local protein binding pocket similarity provides qualitatively complementary information to other approaches, and it can yield quantitative information in support of functional annotation.

On position-specific scoring matrix for protein function prediction

While genome sequencing projects have generated tremendous amounts of protein sequence data for a vast number of genomes, substantial portions of most genomes are still unannotated. Despite the success of experimental methods for identifying protein functions, they are often lab intensive and time consuming. Thus, it is only practical to use in silico methods for the genome-wide functional annotations. In this paper, we propose new features extracted from protein sequence only and machine learning-based methods for computational function prediction. These features are derived from a position-specific scoring matrix, which has shown great potential in other bininformatics problems. We evaluate these features using four different classifiers and yeast protein data. Our experimental results show that features derived from the position-specific scoring matrix are appropriate for automatic function annotation.

INTEGRATING COMPUTATIONAL PROTEIN FUNCTION PREDICTION INTO DRUG DISCOVERY INITIATIVES

Pharmaceutical researchers must evaluate vast numbers of protein sequences and formulate innovative strategies for identifying valid targets and discovering leads against them as a way of accelerating drug discovery. The ever increasing number and diversity of novel protein sequences identified by genomic sequencing projects and the success of worldwide structural genomics initiatives have spurred great interest and impetus in the development of methods for accurate, computationally empowered protein function prediction and active site identification. Previously, in the absence of direct experimental evidence, homology-based protein function annotation remained the gold-standard for in silico analysis and prediction of protein function. However, with the continued exponential expansion of sequence databases, this approach is not always applicable, as fewer query protein sequences demonstrate significant homology to protein gene products of known function. As a result, several non-homology based methods for protein function prediction that are based on sequence features, structure, evolution, biochemical and genetic knowledge have emerged. Herein, we review current bioinformatic programs and approaches for protein function prediction/annotation and discuss their integration into drug discovery initiatives. The development of such methods to annotate protein functional sites and their application to large protein functional families is crucial to successfully utilizing the vast amounts of genomic sequence information available to drug discovery and development processes.

Structural analysis of bacteriophage T4 DNA replication: a review in the Virology Journal series on bacteriophage T4 and its relatives

The bacteriophage T4 encodes 10 proteins, known collectively as the replisome, that are responsible for the replication of the phage genome. The replisomal proteins can be subdivided into three activities; the replicase, responsible for duplicating DNA, the primosomal proteins, responsible for unwinding and Okazaki fragment initiation, and the Okazaki repair proteins. The replicase includes the gp43 DNA polymerase, the gp45 processivity clamp, the gp44/62 clamp loader complex, and the gp32 single-stranded DNA binding protein. The primosomal proteins include the gp41 hexameric helicase, the gp61 primase, and the gp59 helicase loading protein. The RNaseH, a 5' to 3' exonuclease and T4 DNA ligase comprise the activities necessary for Okazaki repair. The T4 provides a model system for DNA replication. As a consequence, significant effort has been put forth to solve the crystallographic structures of these replisomal proteins. In this review, we discuss the structures that are available and provide comparison to related proteins when the T4 structures are unavailable. Three of the ten full-length T4 replisomal proteins have been determined; the gp59 helicase loading protein, the RNase H, and the gp45 processivity clamp. The core of T4 gp32 and two proteins from the T4 related phage RB69, the gp43 polymerase and the gp45 clamp are also solved. The T4 gp44/62 clamp loader has not been crystallized but a comparison to the E. coli gamma complex is provided. The structures of T4 gp41 helicase, gp61 primase, and T4 DNA ligase are unknown, structures from bacteriophage T7 proteins are discussed instead. To better understand the functionality of T4 DNA replication, in depth structural analysis will require complexes between proteins and DNA substrates. A DNA primer template bound by gp43 polymerase, a fork DNA substrate bound by RNase H, gp43 polymerase bound to gp32 protein, and RNase H bound to gp32 have been crystallographically determined. The preparation and crystallization of complexes is a significant challenge. We discuss alternate approaches, such as small angle X-ray and neutron scattering to generate molecular envelopes for modeling macromolecular assemblies.

Mechanism of action and inhibition of dehydrosqualene synthase

"Head-to-head" terpene synthases catalyze the first committed steps in sterol and carotenoid biosynthesis: the condensation of two isoprenoid diphosphates to form cyclopropylcarbinyl diphosphates, followed by ring opening. Here, we report the structures of Staphylococcus aureus dehydrosqualene synthase (CrtM) complexed with its reaction intermediate, presqualene diphosphate (PSPP), the dehydrosqualene (DHS) product, as well as a series of inhibitors. The results indicate that, on initial diphosphate loss, the primary carbocation so formed bends down into the interior of the protein to react with C2,3 double bond in the prenyl acceptor to form PSPP, with the lower two-thirds of both PSPP chains occupying essentially the same positions as found in the two farnesyl chains in the substrates. The second-half reaction is then initiated by the PSPP diphosphate returning back to the Mg(2+) cluster for ionization, with the resultant DHS so formed being trapped in a surface pocket. This mechanism is supported by the observation that cationic inhibitors (of interest as antiinfectives) bind with their positive charge located in the same region as the cyclopropyl carbinyl group; that S-thiolo-diphosphates only inhibit when in the allylic site; activity results on 11 mutants show that both DXXXD conserved domains are essential for PSPP ionization; and the observation that head-to-tail isoprenoid synthases as well as terpene cyclases have ionization and alkene-donor sites which spatially overlap those found in CrtM.

Dominant negative mutations affect oligomerization of human pyruvate kinase M2 isozyme and promote cellular growth and polyploidy

This study was designed to understand the mechanism and functional implication of the two heterozygous mutations (H391Y and K422R) of human pyruvate kinase M2 isozyme (PKM(2)) observed earlier in a Bloom syndrome background. The co-expression of homotetrameric wild type and mutant PKM(2) in the cellular milieu resulting in the interaction between the two at the monomer level was substantiated further by in vitro experiments. The cross-monomer interaction significantly altered the oligomeric state of PKM(2) by favoring dimerization and heterotetramerization. In silico study provided an added support in showing that hetero-oligomerization was energetically favorable. The hetero-oligomeric populations of PKM(2) showed altered activity and affinity, and their expression resulted in an increased growth rate of Escherichia coli as well as mammalian cells, along with an increased rate of polyploidy. These features are known to be essential to tumor progression. This study provides insight in understanding the modulated role of large oligomeric multifunctional proteins such as PKM(2) by affecting cellular behavior, which is an essential observation to understand tumor sustenance and progression and to design therapeutic intervention in future.

The central portion of factor H (modules 10-15) is compact and contains a structurally deviant CCP module

The first eight and the last two of 20 complement control protein (CCP) modules within complement factor H (fH) encompass binding sites for C3b and polyanionic carbohydrates. These binding sites cooperate self-surface selectively to prevent C3b amplification, thus minimising complement-mediated damage to host. Intervening fH CCPs, apparently devoid of such recognition sites, are proposed to play a structural role. One suggestion is that the generally small CCPs 10–15, connected by longer-than-average linkers, act as a flexible tether between the two functional ends of fH; another is that the long linkers induce a 180° bend in the middle of fH. To test these hypotheses, we determined the NMR-derived structure of fH12–13 consisting of module 12, shown here to have an archetypal CCP structure, and module 13, which is uniquely short and features a laterally protruding helix-like insertion that contributes to a prominent electropositive patch. The unusually long fH12–13 linker is not flexible. It packs between the two CCPs that are not folded back on each other but form a shallow vee shape; analytical ultracentrifugation and X-ray scattering supported this finding. These two techniques additionally indicate that flanking modules (within fH11–14 and fH10–15) are at least as rigid and tilted relative to neighbours as are CCPs 12 and 13 with respect to one another. Tilts between successive modules are not unidirectional; their principal axes trace a zigzag path. In one of two arrangements for CCPs 10–15 that fit well with scattering data, CCP 14 is folded back onto CCP 13. In conclusion, fH10–15 forms neither a flexible tether nor a smooth bend. Rather, it is compact and has embedded within it a CCP module (CCP 13) that appears to be highly specialised given both its deviant structure and its striking surface charge distribution. A passive, purely structural role for this central portion of fH is unlikely.

Towards prediction of metabolic products of polyketide synthases: an in silico analysis

Sequence data arising from an increasing number of partial and complete genome projects is revealing the presence of the polyketide synthase (PKS) family of genes not only in microbes and fungi but also in plants and other eukaryotes. PKSs are huge multifunctional megasynthases that use a variety of biosynthetic paradigms to generate enormously diverse arrays of polyketide products that posses several pharmaceutically important properties. The remarkable conservation of these gene clusters across organisms offers abundant scope for obtaining novel insights into PKS biosynthetic code by computational analysis. We have carried out a comprehensive in silico analysis of modular and iterative gene clusters to test whether chemical structures of the secondary metabolites can be predicted from PKS protein sequences. Here, we report the success of our method and demonstrate the feasibility of deciphering the putative metabolic products of uncharacterized PKS clusters found in newly sequenced genomes. Profile Hidden Markov Model analysis has revealed distinct sequence features that can distinguish modular PKS proteins from their iterative counterparts. For iterative PKS proteins, structural models of iterative ketosynthase (KS) domains have revealed novel correlations between the size of the polyketide products and volume of the active site pocket. Furthermore, we have identified key residues in the substrate binding pocket that control the number of chain extensions in iterative PKSs. For modular PKS proteins, we describe for the first time an automated method based on crucial intermolecular contacts that can distinguish the correct biosynthetic order of substrate channeling from a large number of non-cognate combinatorial possibilities. Taken together, our in silico analysis provides valuable clues for formulating rules for predicting polyketide products of iterative as well as modular PKS clusters. These results have promising potential for discovery of novel natural products by genome mining and rational design of novel natural products.

Mechanism of alpha-synuclein oligomerization and membrane interaction: theoretical approach to unstructured proteins studies

Misfolding and oligomerization of unstructured proteins is involved in the pathogenesis of Parkinson's disease (PD), Alzheimer's disease, Huntington's disease, and other neurodegenerative disorders. Elucidation of possible conformations of these proteins and their interactions with the membrane is necessary to understand the molecular mechanisms of neurodegeneration. We developed a strategy that makes it possible to elucidate the molecular mechanisms of alpha-synuclein aggregation-a key molecular event in the pathogenesis of PD. This strategy can be also useful for the study of other unstructured proteins involved in neurodegeneration. The results of these theoretical studies have been confirmed with biochemical and electrophysiological studies. Our studies provide insights into the molecular mechanism for PD initiation and progression, and provide a useful paradigm for identifying possible therapeutic interventions through computational modeling.

Introduction to cheminformatics

Cheminformatics is a relatively new field of information technology that focuses on the collection, storage, analysis, and manipulation of chemical data. The chemical data of interest typically includes information on small molecule formulas, structures, properties, spectra, and activities (biological or industrial). Cheminformatics originally emerged as a vehicle to help the drug discovery and development process, however cheminformatics now plays an increasingly important role in many areas of biology, chemistry, and biochemistry. The intent of this unit is to give readers some introduction into the field of cheminformatics and to show how cheminformatics not only shares many similarities with the field of bioinformatics, but that it can also enhance much of what is currently done in bioinformatics.

Common occurrence of internal repeat symmetry in membrane proteins

Symmetry plays significant roles in protein structure and function. Particularly, symmetric interfaces are known to act as switches for two-state conformational change. Membrane proteins often undergo two-state conformational change during the transport process of ion channels or the active/inactive transitions in receptors. Here, we provide the first comprehensive analyses of internal repeat symmetry in membrane proteins. We examined the known membrane protein structures and found that, remarkably, nearly half of them have internal repeat symmetry. Moreover, we found that the conserved cores of these internal repeats are positioned at the interface of symmetric units when they are mapped on structures. Because of the large sequence divergence that occurs between internal repeats, the inherent symmetry present in protein sequences often has only been detected after structure determination. We therefore developed a sensitive procedure to predict the internal repeat symmetry from sequence information and identified 4653 proteins that are likely to have internal repeat symmetry.

Protein sequence and structure alignments within one framework

Background

Protein structure alignments are usually based on very different techniques to sequence alignments. We propose a method which treats sequence, structure and even combined sequence + structure in a single framework. Using a probabilistic approach, we calculate a similarity measure which can be applied to fragments containing only protein sequence, structure or both simultaneously.

Results

Proof-of-concept results are given for the different problems. For sequence alignments, the methodology is no better than conventional methods. For structure alignments, the techniques are very fast, reliable and tolerant of a range of alignment parameters. Combined sequence and structure alignments may provide a more reliable alignment for pairs of proteins where pure structural alignments can be misled by repetitive elements or apparent symmetries.

Conclusion

The probabilistic framework has an elegance in principle, merging sequence and structure descriptors into a single framework. It has a practical use in fast structural alignments and a potential use in finding those examples where sequence and structural similarities apparently disagree.

Searching distant homologs of the regulatory ACT domain in phenylalanine hydroxylase

High sequence divergence, evolutionary mobility, and superfold topology characterize the ACT domain. Frequently found in multidomain proteins, these domains induce allosteric effects by binding a regulatory ligand usually to an ACT domain dimer interface. In mammalian phenylalanine hydroxylase (PAH), no contacts are formed between ACT domains, and the domain promotes an allosteric effect despite the apparent lack of ligand binding. The increased functional scenario of this abundant domain encouraged us to search for distant homologs, aiming to enhance the understanding of the ACT domain in general and the ACT domain of PAH in particular. The PDB was searched using the FATCAT server with the ACT domain of PAH as a query. The hits that were confirmed by the SSAP algorithm were divided into known ACT domains (KADs) and potential ACT domains (PADs). The FATCAT/SSAP procedure recognized most of the established KADs, as well 18 so far unrecognized non-redundant PADs with extremely low sequence identities and high divergence in functionality and oligomerization. However, analysis of the structural similarity provides remarkable clustering of the proteins according to similarities in ligand binding. Despite enormous sequence divergence and high functional variability, there is a common regulatory theme among these domains. The results reveal the close relationships of the ACT domain of PAH with amino acid binding and metallobinding ACT domains and with acylphosphatase.

Defining functional distance using manifold embeddings of gene ontology annotations

Although rigorous measures of similarity for sequence and structure are now well established, the problem of defining functional relationships has been particularly daunting. Here, we present several manifold embedding techniques to compute distances between Gene Ontology (GO) functional annotations and consequently estimate functional distances between protein domains. To evaluate accuracy, we correlate the functional distance to the well established measures of sequence, structural, and phylogenetic similarities. Finally, we show that manual classification of structures into folds and superfamilies is mirrored by proximity in the newly defined function space. We show how functional distances place structure-function relationships in biological context resulting in insight into divergent and convergent evolution. The methods and results in this paper can be readily generalized and applied to a wide array of biologically relevant investigations, such as accuracy of annotation transference, the relationship between sequence, structure, and function, or coherence of expression modules.

Identification of protein fold topology shared between different folds inhibited by natural products

Natural products have withstood the test of time as therapeutics, but new lead-generation strategies have focussed away from natural products. A new approach that uses natural-product recognition to drive an understanding of biological space might provide an impetus for renewed focus on natural-product starting points. Protein fold topology (PFT) has been shown to be an underlying factor for natural-product recognition. An investigation of natural product inhibitors of the Zincin-like fold has demonstrated their capacity also to inhibit targets of different fold types. Analysis of crystal structure complexes for natural products cocrystallised within different fold types has shown similarity at the PFT level. Two new PFT(T) (where subscript T denotes PFT shared between therapeutic targets) relationships have been established: the Zincin-like- metallohydrolase/oxidoreductase PFT(T) and the Zincin-like-phosphorylase/hydrolase PFT(T). The PFT relationship between a natural product's biosynthetic enzyme and therapeutic target, and now between different fold targets of the same natural product, suggests that PFT is the simplest descriptor of biological space. This fundamental factor for recognition could facilitate a rational approach to drug development guided by natural products.

BIOCOMPUTATIONAL ANALYSIS AND CHARACTERIZATION OF SOME ANTIFREEZE PROTEINS

Novel bioinformatic procedures and computational methods have been used to analyze, characterize and provide more detailed description of some selected fish antifreeze proteins (AFPs) retrieved from Swiss–Prot database. Analysis shows that AFPs are rich in non-polar residues and that the AFPs Q01758 and P05140 contain SS bonds. The aliphatic index computed by ExPasy's ProtParam infers that AFPs may be stable for a wide range of temperatures and the AFP P80961 is classified as an unstable protein. The very low GRAVY index of AFP P80961 infers its higher hydrosolubility. Secondary structure analysis shows that the flounder and sculpin fish AFPs are found to be of predominant ∝–helical structures and the rest of them are with mixed secondary structures. The average molecular weight of AFPs computed is 9584 Da. SOSUI server predicts one transmembrane region in P04002 (winter flounder fish) and two regions in P09031 (yellowtail flounder fish). The predicted transmembrane regions were visualized and analyzed using helical wheel plots generated by EMBOSS pepwheel tool. The residues A, L, G and N are identified as the antigenic sites by EMBOSS antigenic program. The presence of 11 Cys residues in AFPs Q01758 (rainbow smelt fish) and P05140 (sea raven fish) indicates the presence of disulfide bridges (SS bonds) in these AFPs, and it is also recognized by CYS_REC tool and well documented from the three dimensional structure using Rasmol tool.

Genetic and biochemical characterization of Drosophila Snipper: A promiscuous member of the metazoan 3'hExo/ERI-1 family of 3' to 5' exonucleases

The DnaQ-H family exonuclease Snipper (Snp) is a 33-kDa Drosophila melanogaster homolog of 3'hExo and ERI-1, exoribonucleases implicated in the degradation of histone mRNA in mammals and in the negative regulation of RNA interference (RNAi) in Caenorhabditis elegans, respectively. In metazoans, Snp, Exod1, 3'hExo, ERI-1, and the prpip nucleases define a new subclass of structure-specific 3'-5' exonucleases that bind and degrade double-stranded RNA and/or DNA substrates with 3' overhangs of 2-5 nucleotides (nt) in the presence of Mg2+ with no apparent sequence specificity. These nucleases are also capable of degrading linear substrates. Snp efficiently degrades structured RNA and DNA substrates as long as there exists a minimum 3' overhang of 2 nt to initiate degradation. We identified a Snp mutant and used it to test whether Snp plays a role in regulating histone mRNA degradation or RNAi in vivo. Snp mutant flies are viable, and display no obvious developmental abnormalities. The expression pattern and level of histone H3 mRNA in Snp mutant embryos and third instar imaginal eye discs was indistinguishable from wild type, suggesting that Snp does not play a significant role in the turnover of histone mRNA at the end of the S phase. The loss of Snp was also unable to enhance the silencing capability of two different RNAi transgenes targeting the white and yellow genes, suggesting that Snp does not negatively modulate RNAi. Therefore, Snp is a nonessential exonuclease that is not a functional ortholog of either 3'hExo or ERI-1.

The structure of the endoribonuclease XendoU: From small nucleolar RNA processing to severe acute respiratory syndrome coronavirus replication

Small nucleolar RNAs (snoRNAs) play a key role in eukaryotic ribosome biogenesis. In most cases, snoRNAs are encoded in introns and are released through the splicing reaction. Some snoRNAs are, instead, produced by an alternative pathway consisting of endonucleolytic processing of pre-mRNA. XendoU, the endoribonuclease responsible for this activity, is a U-specific, metal-dependent enzyme that releases products with 2'-3' cyclic phosphate termini. XendoU is broadly conserved among eukaryotes, and it is a genetic marker of nidoviruses, including the severe acute respiratory syndrome coronavirus, where it is essential for replication and transcription. We have determined by crystallography the structure of XendoU that, by refined search methodologies, appears to display a unique fold. Based on sequence conservation, mutagenesis, and docking simulations, we have identified the active site. The conserved structural determinants of this site may provide a framework for attempting to design antiviral drugs to interfere with the infectious nidovirus life cycle.

How well are protein structures annotated in secondary databases?

We investigated to what extent Protein Data Bank (PDB) entries are annotated with second-party information based on existing cross-references between PDB and 15 other databases. We report 2 interesting findings. First, there is a clear "annotation gap" for structures less than 7 years old for secondary databases that are manually curated. Second, the examined databases overlap with each other quite well, dividing the PDB into 2 well-annotated thirds and one poorly annotated third. Both observations should be taken into account in any study depending on the selection of protein structures by their annotation.

Large amplitude conformational change in proteins explored with a plastic network model: adenylate kinase

The plastic network model (PNM) is used to generate a conformational change pathway for Escherichia coli adenylate kinase based on two crystal structures, namely that of an open and a closed conformer. In this model, the energy basins corresponding to known conformers are connected at their lowest common energies. The results are used to evaluate and analyze the minimal energy pathways between these basins. The open to closed transition analysis provides an identification of hinges that is in agreement with the existing definitions based on the available X-ray structures. The elastic energy distribution and the C(alpha) pseudo-dihedral variation provide similar information on these hinges. The ensemble of the 45 published structures for this protein and closely related proteins is shown to always be within 3.0 A of the pathway, which corresponds to a conformational change between two end structures that differ by a C(alpha)-atom root-mean-squared deviation of 7.1A.

Structural evolution of the protein kinase-like superfamily

The protein kinase family is large and important, but it is only one family in a larger superfamily of homologous kinases that phosphorylate a variety of substrates and play important roles in all three superkingdoms of life. We used a carefully constructed structural alignment of selected kinases as the basis for a study of the structural evolution of the protein kinase-like superfamily. The comparison of structures revealed a "universal core" domain consisting only of regions required for ATP binding and the phosphotransfer reaction. Remarkably, even within the universal core some kinase structures display notable changes, while still retaining essential activity. Hence, the protein kinase-like superfamily has undergone substantial structural and sequence revision over long evolutionary timescales. We constructed a phylogenetic tree for the superfamily using a novel approach that allowed for the combination of sequence and structure information into a unified quantitative analysis. When considered against the backdrop of species distribution and other metrics, our tree provides a compelling scenario for the development of the various kinase families from a shared common ancestor. We propose that most of the so-called "atypical kinases" are not intermittently derived from protein kinases, but rather diverged early in evolution to form a distinct phyletic group. Within the atypical kinases, the aminoglycoside and choline kinase families appear to share the closest relationship. These two families in turn appear to be the most closely related to the protein kinase family. In addition, our analysis suggests that the actin-fragmin kinase, an atypical protein kinase, is more closely related to the phosphoinositide-3 kinase family than to the protein kinase family. The two most divergent families, alpha-kinases and phosphatidylinositol phosphate kinases (PIPKs), appear to have distinct evolutionary histories. While the PIPKs probably have an evolutionary relationship with the rest of the kinase superfamily, the relationship appears to be very distant (and perhaps indirect). Conversely, the alpha-kinases appear to be an exception to the scenario of early divergence for the atypical kinases: they apparently arose relatively recently in eukaryotes. We present possible scenarios for the derivation of the alpha-kinases from an extant kinase fold.

Protein structure similarity clustering (PSSC) and natural product structure as inspiration sources for drug development and chemical genomics

Finding small molecules that modulate protein function is of primary importance in drug development and in the emerging field of chemical genomics. To facilitate the identification of such molecules, we developed a novel strategy making use of structural conservatism found in protein domain architecture and natural product inspired compound library design. Domains and proteins identified as being structurally similar in their ligand-sensing cores are grouped in a protein structure similarity cluster (PSSC). Natural products can be considered as evolutionary pre-validated ligands for multiple proteins and therefore natural products that are known to interact with one of the PSSC member proteins are selected as guiding structures for compound library synthesis. Application of this novel strategy for compound library design provided enhanced hit rates in small compound libraries for structurally similar proteins.

Design of compound libraries based on natural product scaffolds and protein structure similarity clustering (PSSC)

Recent advances in structural biology, bioinformatics and combinatorial chemistry have significantly impacted the discovery of small molecules that modulate protein functions. Natural products which have evolved to bind to proteins may serve as biologically validated starting points for the design of focused libraries that might provide protein ligands with enhanced quality and probability. The combined application of natural product derived scaffolds with a new approach that clusters proteins according to structural similarity of their ligand sensing cores provides a new principle for the design and synthesis of such libraries. This article discusses recent advances in the synthesis of natural product inspired compound collections and the application of protein structure similarity clustering for the development of such libraries.

Modular RNA architecture revealed by computational analysis of existing pseudoknots and ribosomal RNAs

Modular architecture is a hallmark of RNA structures, implying structural, and possibly functional, similarity among existing RNAs. To systematically delineate the existence of smaller topologies within larger structures, we develop and apply an efficient RNA secondary structure comparison algorithm using a newly developed two-dimensional RNA graphical representation. Our survey of similarity among 14 pseudoknots and subtopologies within ribosomal RNAs (rRNAs) uncovers eight pairs of structurally related pseudoknots with non-random sequence matches and reveals modular units in rRNAs. Significantly, three structurally related pseudoknot pairs have functional similarities not previously known: one pair involves the 3′ end of brome mosaic virus genomic RNA (PKB134) and the alternative hammerhead ribozyme pseudoknot (PKB173), both of which are replicase templates for viral RNA replication; the second pair involves structural elements for translation initiation and ribosome recruitment found in the viral internal ribosome entry site (PKB223) and the V4 domain of 18S rRNA (PKB205); the third pair involves 18S rRNA (PKB205) and viral tRNA-like pseudoknot (PKB134), which probably recruits ribosomes via structural mimicry and base complementarity. Additionally, we quantify the modularity of 16S and 23S rRNAs by showing that RNA motifs can be constructed from at least 210 building blocks. Interestingly, we find that the 5S rRNA and two tree modules within 16S and 23S rRNAs have similar topologies and tertiary shapes. These modules can be applied to design novel RNA motifs via build-up-like procedures for constructing sequences and folds.

Structural alignment of proteins by a novel TOPOFIT method, as a superimposition of common volumes at a topomax point

Similarity of protein structures has been analyzed using three-dimensional Delaunay triangulation patterns derived from the backbone representation. It has been found that structurally related proteins have a common spatial invariant part, a set of tetrahedrons, mathematically described as a common spatial subgraph volume of the three-dimensional contact graph derived from Delaunay tessellation (DT). Based on this property of protein structures, we present a novel common volume superimposition (TOPOFIT) method to produce structural alignments. Structural alignments usually evaluated by a number of equivalent (aligned) positions (N(e)) with corresponding root mean square deviation (RMSD). The superimposition of the DT patterns allows one to uniquely identify a maximal common number of equivalent residues in the structural alignment. In other words, TOPOFIT identifies a feature point on the RMSD N(e) curve, a topomax point, until which the topologies of two structures correspond to each other, including backbone and interresidue contacts, whereas the growing number of mismatches between the DT patterns occurs at larger RMSD (N(e)) after the topomax point. It has been found that the topomax point is present in all alignments from different protein structural classes; therefore, the TOPOFIT method identifies common, invariant structural parts between proteins. The alignments produced by the TOPOFIT method have a good correlation with alignments produced by other current methods. This novel method opens new opportunities for the comparative analysis of protein structures and for more detailed studies on understanding the molecular principles of tertiary structure organization and functionality. The TOPOFIT method also helps to detect conformational changes, topological differences in variable parts, which are particularly important for studies of variations in active/ binding sites and protein classification.

Assigning new GO annotations to protein data bank sequences by combining structure and sequence homology

Accompanying the discovery of an increasing number of proteins, there is the need to provide functional annotation that is both highly accurate and consistent. The Gene Ontology (GO) provides consistent annotation in a computer readable and usable form; hence, GO annotation (GOA) has been assigned to a large number of protein sequences based on direct experimental evidence and through inference determined by sequence homology. Here we show that this annotation can be extended and corrected for cases where protein structures are available. Specifically, using the Combinatorial Extension (CE) algorithm for structure comparison, we extend the protein annotation currently provided by GOA at the European Bioinformatics Institute (EBI) to further describe the contents of the Protein Data Bank (PDB). Specific cases of biologically interesting annotations derived by this method are given. Given that the relationship between sequence, structure, and function is complicated, we explore the impact of this relationship on assigning GOA. The effect of superfolds (folds with many functions) is considered and, by comparison to the Structural Classification of Proteins (SCOP), the individual effects of family, superfamily, and fold.

An approach to large scale identification of non-obvious structural similarities between proteins

Background

A new sequence independent bioinformatics approach allowing genome-wide search for proteins with similar three dimensional structures has been developed. By utilizing the numerical output of the sequence threading it establishes putative non-obvious structural similarities between proteins. When applied to the testing set of proteins with known three dimensional structures the developed approach was able to recognize structurally similar proteins with high accuracy.

Results

The method has been developed to identify pathogenic proteins with low sequence identity and high structural similarity to host analogues. Such protein structure relationships would be hypothesized to arise through convergent evolution or through ancient horizontal gene transfer events, now undetectable using current sequence alignment techniques. The pathogen proteins, which could mimic or interfere with host activities, would represent candidate virulence factors.

The developed approach utilizes the numerical outputs from the sequence-structure threading. It identifies the potential structural similarity between a pair of proteins by correlating the threading scores of the corresponding two primary sequences against the library of the standard folds. This approach allowed up to 64% sensitivity and 99.9% specificity in distinguishing protein pairs with high structural similarity.

Conclusion

Preliminary results obtained by comparison of the genomes of Homo sapiens and several strains of Chlamydia trachomatis have demonstrated the potential usefulness of the method in the identification of bacterial proteins with known or potential roles in virulence.