Search

The Modern Evolutionary Synthesis seemingly fails to explain how a population can survive a large environmental change. That is, the pre-existence of heritable variants adapted to the novel environment is too opportunistic whereas the search for new adaptive mutations after the environmental change is too slow. Plasticity-led evolution, the process of initial environmental induction of a novel adaptive phenotype followed by genetic accommodation, has been proposed to solve this problem. However, the mechanism enabling plasticity-led evolution is unclear. Here, we propose computational models that exhibit behaviors compatible with plasticity-led evolution by extending the Wagner model of gene regulatory networks. The models exhibit adaptive plastic response and uncovering of cryptic mutations under large environmental changes, followed by genetic accommodation. Moreover, these behaviors are consistently observed over distinct novel environments. We further show that environmental cues, developmental process, and hierarchical regulation cooperatively amplify the above behaviors and accelerate evolution. These observations suggest that plasticity-led evolution is a universal property of complex developmental regulation independent of particular mutations.

In the protein sequence space, natural proteins form clusters of families which are characterized by their unique native folds whereas the great majority of random polypeptides are neither clustered nor foldable to unique structures. Since a given polypeptide can be either foldable or unfoldable, a kind of "folding transition" is expected at the boundary of a protein family in the sequence space. By Monte Carlo simulations of a statistical mechanical model of protein sequence alignment that coherently incorporates both short-range and long-range interactions as well as variable-length insertions to reproduce the statistics of the multiple sequence alignment of a given protein family, we demonstrate the existence of such transition between natural-like sequences and random sequences in the sequence subspaces for 15 domain families of various folds. The transition was found to be highly cooperative and two-state-like. Furthermore, enforcing or suppressing consensus residues on a few of the well-conserved sites enhanced or diminished, respectively, the natural-like pattern formation over the entire sequence. In most families, the key sites included ligand binding sites. These results suggest some selective pressure on the key residues, such as ligand binding activity, may cooperatively facilitate the emergence of a protein family during evolution. From a more practical aspect, the present results highlight an essential role of long-range effects in precisely defining protein families, which are absent in conventional sequence models., 13 pages, 7 figures, 2 tables (a new subsection added)

We re-examine a site-binding approach independently proposed by Schellman (Schellman, J.A. (1958) Compt. rend. Lab. Carlsberg Ser. Chim. 30, 439-449) and Aune and Tanford (Aune, K.C. and Tanford, D. (1969) Biochemistry, 8, 4586-4590) for explicitly including the denaturant concentration within the protein unfolding equilibrium. We extend and formalize the approach through development of a multi-dimensional analytical model in which the folding reaction coordinate is defined by the number of denaturant molecules bound to sites located on either the initially folded, or unfolded, states of the protein. We use the developed method to re-examine the mechanistic determinants underlying the sigmoidal shape of the unfolding transition. A natural feature of our method is that it presents a landscape picture of the denaturant induced protein unfolding reaction.

The Protein Data Bank Japan (PDBj), a member of the worldwide Protein Data Bank (wwPDB), accepts and processes the deposited data of experimentally determined biological macromolecular structures. In addition to archiving the PDB data in collaboration with the other wwPDB partners, PDBj also provides a wide range of original and unique services and tools, which are continuously improved and updated. Here, we report the new RDB PDBj Mine 2, the WebGL molecular viewer Molmil, the ProMode-Elastic server for normal mode analysis, a virtual reality system for the eF-site protein electrostatic molecular surfaces, the extensions of the Omokage search for molecular shape similarity, and the integration of PDBj and BMRB searches.

The Protein Data Bank Japan (PDBj, http://pdbj.org), a member of the worldwide Protein Data Bank (wwPDB), accepts and processes the deposited data of experimentally determined macromolecular structures. While maintaining the archive in collaboration with other wwPDB partners, PDBj also provides a wide range of services and tools for analyzing structures and functions of proteins. We herein outline the updated web user interfaces together with RESTful web services and the backend relational database that support the former. To enhance the interoperability of the PDB data, we have previously developed PDB/RDF, PDB data in the Resource Description Framework (RDF) format, which is now a wwPDB standard called wwPDB/RDF. We have enhanced the connectivity of the wwPDB/RDF data by incorporating various external data resources. Services for searching, comparing and analyzing the ever-increasing large structures determined by hybrid methods are also described.

The multiple sequence alignment (MSA) of a protein family provides a wealth of information in terms of the conservation pattern of amino acid residues not only at each alignment site but also between distant sites. In order to statistically model the MSA incorporating both short-range and long-range correlations as well as insertions, I have derived a lattice gas model of the MSA based on the principle of maximum entropy. The partition function, obtained by the transfer matrix method with a mean-field approximation, accounts for all possible alignments with all possible sequences. The model parameters for short-range and long-range interactions were determined by a self-consistent condition and by a Gaussian approximation, respectively. Using this model with and without long-range interactions, I analyzed the globin and V-set domains by increasing the "temperature" and by "mutating" a site. The correlations between residue conservation and various measures of the system's stability indicate that the long-range interactions make the conservation pattern more specific to the structure, and increasingly stabilize better conserved residues., 21 pages (2-column), 13 figures

Conrad H. Waddington discovered the phenomenon of genetic assimilation through a series of experiments on fruit flies. In those experiments, artificially exerted environmental stress induced plastic phe-notypic changes in the fruit flies, but after some generations the same phenotypic variant started to appear without the environmental stress. Both the initial state (where the phenotypic changes were environmentally induced and plastic) and the final state (where the phenotypic changes were genetically fixed and constitutive) are experimental facts. However, it remains unclear how the environmentally induced phenotypic change in the first generation becomes genetically fixed in the central process of genetic assimilation itself. We have argued that the key to understanding the mechanism of genetic assimilation lies in epigenetics, and proposed the “cooperative model” in which the evolutionary process depends on both genetic and epigenetic factors. Evolutionary simulations based on the cooperative model reproduced the process of genetic assimilation. Detailed analysis of the trajectories has revealed genetic assimilation is a process in which epigenetically induced phe-notypic changes are incrementally and statistically replaced with multiple minor genetic mutations through natural selection. In this scenario, epigenetic and genetic changes may be considered as mutually independent but equivalent in terms of their effects on phenotypic changes. This finding rejects the common (and confused) hypothesis that epigenetically induced phe-notypic changes depend on genetic mutations. Furthermore, we argue that transgenerational epigenetic inheritance is not required for evolution by genetic assimilation.

Motivation Biological data and knowledge bases increasingly rely on Semantic Web technologies and the use of knowledge graphs for data integration, retrieval and federated queries. In the past years, feature learning methods that are applicable to graph-structured data are becoming available, but have not yet widely been applied and evaluated on structured biological knowledge. Results: We develop a novel method for feature learning on biological knowledge graphs. Our method combines symbolic methods, in particular knowledge representation using symbolic logic and automated reasoning, with neural networks to generate embeddings of nodes that encode for related information within knowledge graphs. Through the use of symbolic logic, these embeddings contain both explicit and implicit information. We apply these embeddings to the prediction of edges in the knowledge graph representing problems of function prediction, finding candidate genes of diseases, protein-protein interactions, or drug target relations, and demonstrate performance that matches and sometimes outperforms traditional approaches based on manually crafted features. Our method can be applied to any biological knowledge graph, and will thereby open up the increasing amount of Semantic Web based knowledge bases in biology to use in machine learning and data analytics. Availability and implementation https://github.com/bio-ontology-research-group/walking-rdf-and-owl Supplementary information Supplementary data are available at Bioinformatics online.

The Protein Data Bank Japan (PDBj), a member of the worldwide Protein Data Bank (wwPDB), accepts and processes the deposited data of experimentally determined biological macromolecular structures. In addition to archiving the PDB data in collaboration with the other wwPDB partners, PDBj also provides a wide range of original and unique services and tools, which are continuously improved and updated. Here, we report the new RDB PDBj Mine 2, the WebGL molecular viewer Molmil, the ProMode‐Elastic server for normal mode analysis, a virtual reality system for the eF‐site protein electrostatic molecular surfaces, the extensions of the Omokage search for molecular shape similarity, and the integration of PDBj and BMRB searches.

Publishing databases in the Resource Description Framework (RDF) model is becoming widely accepted to maximize the syntactic and semantic interoperability of open data in life sciences. Here we report advancements made in the 6th and 7th annual BioHackathons which were held in Tokyo and Miyagi respectively. This review consists of two major sections covering: 1) improvement and utilization of RDF data in various domains of the life sciences and 2) meta-data about these RDF data, the resources that store them, and the service quality of SPARQL Protocol and RDF Query Language (SPARQL) endpoints. The first section describes how we developed RDF data, ontologies and tools in genomics, proteomics, metabolomics, glycomics and by literature text mining. The second section describes how we defined descriptions of datasets, the provenance of data, and quality assessment of services and service discovery. By enhancing the harmonization of these two layers of machine-readable data and knowledge, we improve the way community wide resources are developed and published. Moreover, we outline best practices for the future, and prepare ourselves for an exciting and unanticipatable variety of real world applications in coming years.

We propose the cooperative model of phenotype-driven evolution, in which natural selection operates on a phenotype caused by both genetic and epigenetic factors. The conventional theory of evolutionary synthesis assumes that a phenotypic value (P) is the sum of genotypic value (G) and environmental deviation (E), P=G+E, where E is the fluctuations of the phenotype among individuals in the absence of environmental changes. In contrast, the cooperative model assumes that an evolution is triggered by an environmental change and individuals respond to the change by phenotypic plasticity (epigenetic changes). The phenotypic plasticity, while essentially qualitative, is denoted by a quantitative value F which is modeled as a normal random variable like E, but with a much larger variance. Thus, the fundamental equation of the cooperative model is given as P=G+F where F includes the effect of E. Computer simulations using a genetic algorithm demonstrated that the cooperative model realized much faster evolution than the evolutionary synthesis. This accelerated evolution was found to be due to the cumulative evolution made possible by a ratchet mechanism due to the epigenetic contribution to the phenotypic value. The cooperative model can well account for the phenomenon of genetic assimilation, which, in turn, suggests the mechanism of cumulative selection. The cooperative model may also serve as a theoretical basis to understand various ideas and phenomena of the phenotype-driven evolution such as genetic assimilation, the theory of facilitated phenotypic variation, and epigenetic inheritance over generations.

The epigenome, i.e. the whole of chromatin modifications, is transferred from mother to daughter cells during cell differentiation. When de novo chromatin modifications (establishment or erasure of, respectively, new or pre-existing DNA methylations and/or histone modifications) are made in a daughter cell, however, it has a different epigenome than its mother cell. Although de novo chromatin modifications are an important event that comprises elementary processes of cell differentiation, its molecular mechanism remains poorly understood. We argue in this Letter that a key to solving this problem lies in understanding the role of long non-coding RNAs (lncRNAs)- a type of RNA that is becoming increasingly prominent in epigenetic studies. Many studies show that lncRNAs form ribonucleo-protein complexes in the nucleus and are involved in chromatin modifications. However, chromatin-modifying enzymes lack the information about genomic positions on which they act. It is known, on the other hand, that a single-stranded RNA in general can bind to a double-stranded DNA to form a triple helix. If each lncRNA forms a ribonucleo-protein complex with chromatin-modifying enzymes on one hand and, at the same time, a triple helix with a genomic region based on its specific nucleotide sequence on the other hand, it can induce de novo chromatin modifications at specific sites. Thus, the great variety of lncRNAs can be explained by the requirement for the diversity of "genomic address codes" specific to their cognate genomic regions where de novo chromatin modifications take place., Comment: 12 pages, 1 figure

Life science research now heavily relies on all sorts of databases for genome sequences, transcription, protein three-dimensional (3D) structures, protein-protein interactions, phenotypes and so forth. The knowledge accumulated by all the omics research is so vast that a computer-aided search of data is now a prerequisite for starting a new study. In addition, a combinatory search throughout these databases has a chance to extract new ideas and new hypotheses that can be examined by wet-lab experiments. By virtually integrating the related databases on the Internet, we have built a new web application that facilitates life science researchers for retrieving experts' knowledge stored in the databases and for building a new hypothesis of the research target. This web application, named VaProS, puts stress on the interconnection between the functional information of genome sequences and protein 3D structures, such as structural effect of the gene mutation. In this manuscript, we present the notion of VaProS, the databases and tools that can be accessed without any knowledge of database locations and data formats, and the power of search exemplified in quest of the molecular mechanisms of lysosomal storage disease. VaProS can be freely accessed at http://p4d-info.nig.ac.jp/vapros/ .

Date hub proteins are a type of proteins that show multispecificity in a time-dependent manner. To understand dynamic aspects of such multispecificity we studied Ubiquitin as a typical example of a date hub protein. Here we analyzed 9 biologically relevant Ubiquitin-protein (ligand) heterodimer structures by using normal mode analysis based on an elastic network model. Our result showed that the self-coupled motion of Ubiquitin in the complex, rather than its ligand-coupled motion, is similar to the motion of Ubiquitin in the unbound condition. The ligand-coupled motions are correlated to the conformational change between the unbound and bound conditions of Ubiquitin. Moreover, ligand-coupled motions favor the formation of the bound states, due to its in-phase movements of the contacting atoms at the interface. The self-coupled motions at the interface indicated loss of conformational entropy due to binding. Therefore, such motions disfavor the formation of the bound state. We observed that the ligand-coupled motions are embedded in the motions of unbound Ubiquitin. In conclusion, multispecificity of Ubiquitin can be characterized by an intricate balance of the ligand- and self-coupled motions, both of which are embedded in the motions of the unbound form.

Cellular functions of an organism are maintained by protein–protein interactions. Those proteins that bind multiple partners asynchronously (date hub proteins) are important to make the interaction network coordinated. It is known that many date hub proteins bind different partners at overlapping (OV) interfaces. To understand how OV interfaces of date hub proteins can recognize multiple partners, we analyzed the difference between OV and non-overlapping (Non-OV) regions of interfaces involved in the binding of different partners. By using the structures of 16 date hub proteins with various interaction partners (ranging from 5 to 33), we compared buried surface area, compositions of amino acid residues and secondary structures, and side-chain orientations. It was found that buried interface residues are important for recognizing multiple partners, while exposed interface residues are important for determining specificity to a particular ligand. In addition, our analyses reveal that residue compositions in OV and Non-OV regions are different and that residues in OV region show diverse side-chain torsion angles to accommodate binding to multiple targets.

To elucidate the structural basis of the diversity and universality in protein-protein interactions, an exhaustive all-against-all structural comparison of all known protein interfaces in the Protein Data Bank was performed at atomic resolution. After similar interfaces were clustered, approximately 20,000 structural motifs with at least two members were identified, out of which 3678 motifs consisted of at least 10 interfaces. Except for some trivial interfaces involving single alpha helices, almost all motifs were found to be confined within single protein families. Furthermore, the interaction partners of each motif were found to be very limited, and, accordingly, the interaction networks of the motifs tend to be small and are much more restricted than the binding sites for small ligand molecules. These findings suggest that, at the level of atomic structures, protein-protein interactions are precisely designed; hence, protein interfaces with multiple interacting partners should involve incompletely overlapping multiple interfaces and/or accommodate structural changes upon binding to their targets.

A thermionic RF gun usually suffers from a rapid decrease of electron beam energy caused by a rapid increase of beam current due to the back-bombardment effect. The authors propose a new method named ldquocavity detuningrdquo to keep the electron beam energy constant. This method detunes the resonant frequency of the gun cavity to a frequency that is lower (by several hundred kilohertz) than the driving frequency. A proof-of-principle experiment was carried out using a 4.5 cell S-band RF gun. The beam energy was successfully kept constant during a macro-pulse duration of 7.5 mus using a cavity detuning of -590 kHz, even with a significant current increase from 240 to 660 mA. A numerical simulation was also conducted to evaluate the cathode temperature, the current density on the cathode surface, and the phase stability of the output beam. All results demonstrated that cavity detuning provides an easy and simple way to compensate for the energy decrease in thermionic RF guns.

Comprehensive knowledge of protein-ligand interactions should provide a useful basis for annotating protein functions, studying protein evolution, engineering enzymatic activity, and designing drugs. To investigate the diversity and universality of ligand binding sites in protein structures, we conducted the all-against-all atomic-level structural comparison of over 180,000 ligand binding sites found in all the known structures in the Protein Data Bank by using a recently developed database search and alignment algorithm. By applying a hybrid top-down-bottom-up clustering analysis to the comparison results, we determined approximately 3000 well-defined structural motifs of ligand binding sites. Apart from a handful of exceptions, most structural motifs were found to be confined within single families or superfamilies, and to be associated with particular ligands. Furthermore, we analyzed the components of the similarity network and enumerated more than 4000 pairs of ligand binding sites that were shared across different protein folds., Comment: 13 pages, 8 figures

The Protein Data Bank Japan (PDBj) curates, edits and distributes protein structural data as a member of the worldwide Protein Data Bank (wwPDB) and currently processes approximately 25-30% of all deposited data in the world. Structural information is enhanced by the addition of biological and biochemical functional data as well as experimental details extracted from the literature and other databases. Several applications have been developed at PDBj for structural biology and biomedical studies: (i) a Java-based molecular graphics viewer, jV; (ii) display of electron density maps for the evaluation of structure quality; (iii) an extensive database of molecular surfaces for functional sites, eF-site, as well as a search service for similar molecular surfaces, eF-seek; (iv) identification of sequence and structural neighbors; (v) a graphical user interface to all known protein folds with links to the above applications, Protein Globe. Recent examples are shown that highlight the utility of these tools in recognizing remote homologies between pairs of protein structures and in assigning putative biochemical functions to newly determined targets from structural genomics projects.

A method to search for local structural similarities in proteins at atomic resolution is presented. It is demonstrated that a huge amount of structural data can be handled within a reasonable CPU time by using a conventional relational database management system with appropriate indexing of geometric data. This method, which we call geometric indexing, can enumerate ligand binding sites that are structurally similar to sub-structures of a query protein among more than 160,000 possible candidates within a few hours of CPU time on an ordinary desktop computer. After detecting a set of high scoring ligand binding sites by the geometric indexing search, structural alignments at atomic resolution are constructed by iteratively applying the Hungarian algorithm, and the statistical significance of the final score is estimated from an empirical model based on a gamma distribution. Applications of this method to several protein structures clearly shows that significant similarities can be detected between local structures of non-homologous as well as homologous proteins., Comment: 29 pages, 8 figures, 3 tables

Background The nuclear magnetic resonance (NMR) spectroscopic data for biological macromolecules archived at the BioMagResBank (BMRB) provide a rich resource of biophysical information at atomic resolution. The NMR data archived in NMR-STAR ASCII format have been implemented in a relational database. However, it is still fairly difficult for users to retrieve data from the NMR-STAR files or the relational database in association with data from other biological databases. Findings To enhance the interoperability of the BMRB database, we present a full conversion of BMRB entries to two standard structured data formats, XML and RDF, as common open representations of the NMR-STAR data. Moreover, a SPARQL endpoint has been deployed. The described case study demonstrates that a simple query of the SPARQL endpoints of the BMRB, UniProt, and Online Mendelian Inheritance in Man (OMIM), can be used in NMR and structure-based analysis of proteins combined with information of single nucleotide polymorphisms (SNPs) and their phenotypes. Conclusions We have developed BMRB/XML and BMRB/RDF and demonstrate their use in performing a federated SPARQL query linking the BMRB to other databases through standard semantic web technologies. This will facilitate data exchange across diverse information resources. Electronic supplementary material The online version of this article (doi:10.1186/s13326-016-0057-1) contains supplementary material, which is available to authorized users.

Human transcriptional regulation factors, such as activators, repressors, and enhancer-binding factors are quite different from their prokaryotic counterparts in two respects: the average sequence in human is more than twice as long as that in prokaryotes, while the fraction of sequence aligned to domains of known structure is 31% in human transcription factors (TFs), less than half of that in bacterial TFs (72%). Intrinsically disordered (ID) regions were identified by a disorder-prediction program, and were found to be in good agreement with available experimental data. Analysis of 401 human TFs with experimental evidence from the Swiss-Prot database showed that as high as 49% of the entire sequence of human TFs is occupied by ID regions. More than half of the human TFs consist of a small DNA binding domain (DBD) and long ID regions frequently sandwiching unassigned regions. The remaining TFs have structural domains in addition to DBDs and ID regions. Experimental studies, particularly those with NMR, revealed that the transactivation domains in unbound TFs are usually unstructured, but become structured upon binding to their partners. The sequences of human and mouse TF orthologues are 90.5% identical despite a high incidence of ID regions, probably reflecting important functional roles played by ID regions. In general ID regions occupy a high fraction in TFs of eukaryotes, but not in prokaryotes. Implications of this dichotomy are discussed in connection with their functional roles in transcriptional regulation and evolution.

Protein one-dimensional (1D) structures such as secondary structure and contact number provide intuitive pictures to understand how the native three-dimensional (3D) structure of a protein is encoded in the amino acid sequence. However, it has not been clear whether a given set of 1D structures contains sufficient information for recovering the underlying 3D structure. Here we show that the 3D structure of a protein can be recovered from a set of three types of 1D structures, namely, secondary structure, contact number and residue-wise contact order which is introduced here for the first time. Using simulated annealing molecular dynamics simulations, the structures satisfying the given native 1D structural restraints were sought for 16 proteins of various structural classes and of sizes ranging from 56 to 146 residues. By selecting the structures best satisfying the restraints, all the proteins showed a coordinate RMS deviation of less than 4\AA{} from the native structure, and for most of them, the deviation was even less than 2\AA{}. The present result opens a new possibility to protein structure prediction and our understanding of the sequence-structure relationship., Comment: Corrected title. No Change In Contents

The living cell is inherently crowded with proteins and macromolecules. To avoid aggregation of denatured proteins in the living cell, molecular chaperones play important roles. Here we introduce a simple model to describe crowded protein solutions with chaperone-like species based on a dynamic density functional theory. As predicted by others, our simulations show that macromolecular crowding enhances the association of proteins and chaperones. However, when the intrinsic folding rate of the protein is slow, it is possible that crowding also enhances aggregation of proteins. The results of simulation suggest that, when the concentration of the crowding agent is as high as that in the cell, the association of the protein and unbound chaperone becomes correlated with the aggregation process, and that the protein-bound chaperones efficiently destroy the potential nuclei of aggregates and thus prevent the aggregation.

The direct-coupling analysis is a powerful method for protein contact prediction, and enables us to extract "direct" correlations between distant sites that are latent in "indirect" correlations observed in a protein multiple-sequence alignment. I show that the direct correlation can be obtained by using a formulation analogous to the Ornstein-Zernike integral equation in liquid theory. This formulation intuitively illustrates how the indirect or apparent correlation arises from an infinite series of direct correlations, and provides interesting insights into protein structure prediction., Comment: 3 pages, 1 figure

We, four independent predictors, organized a team and tackled blind protein structure predictions using fold recognition methods. We tried to assign the homologous or analogous folds in the protein structure database for a number of target sequences that showed no apparent sequence homology to the proteins of known folds. After primary analyses by conventional softwares, these sequences were threaded through the structural library using three different programs developed by ourselves, which employed different compatibility functions. Collecting the results of our individual analyses, and the available biological knowledge about the target, we held meetings and discussed all plausible structures for the target. For 25 target sequences, we submitted 56 models including NONE: This was the first time the fold was determined. At the time of the meeting (CASP3), 19 protein structures (21 domains) categorized as the threading targets were available. We succeeded in predicting eight out of 18 targets (20 domains) that we submitted; however, alignment accuracies were not satisfactory for some of the models. We often obtained correct answers even if some of us missed the right prediction; therefore it would appear that our threaders compensated each other. When all the information is managed effectively, the prediction gains more accuracy. Proteins Suppl 1999;3:126–132. © 1999 Wiley-Liss, Inc.

3D complex structures of proteins and other molecules provide a clue for mechanism of interaction. However, few servers for searching complex structures are available. We are developing an updated server HOMCOS (HOmology Modeling of Complex Structure) with more services than the previous version. It separates component molecules of PDB files of complexes, such as proteins, nucleic acids, small chemical compounds, stores their binding relationships. It searches these molecules by BLAST and our chemical structure comparison program dkcombu. Based on found similar complexes, simple template-based models of the complex can be generated by replacing the template with the query amino acid sequence. The service ‘Modeling Homo Protein Multimer’ searches homologous protein complexes with one query protein sequence, whereas the service ‘Modeling Hetero Protein Multimer’ searches with two sequences. The service ‘Modeling Compound-Protein Complexes’ searches with one sequence and one chemical structure. For modeling a bound conformation of a target compound, our flexible overlay program fkcombu is performed to superimpose the target compound onto the template compound bound to a protein. The program transforms a pose and torsion angles of the target molecule to superimpose atom pairs of the target and template molecule determined by 2D-MCS. The service ‘Searching Contacting Molecules for Query Protein’ searches contacting molecules with homologous proteins to a given query sequence, and provide putative interacting molecules with putative binding sites. It is useful to estimate mutational effects on molecular interactions. The service ‘Searching Contacting Proteins for Query Compound’ searching contacting proteins with similar compounds to a given query chemical compound. It may be useful to predict unintended interacting proteins, which cause side effects of the compound. We hope this server may contribute to the platform for drug discoveries and life sciences.

To understand the dynamic aspects of multispecificity of ubiquitin, we studied nine ubiquitin–ligand (partner protein) complexes by normal mode analysis based on an elastic network model. The coupling between ubiquitin and ligand motions was analyzed by decomposing it into rigid-body (external) and vibrational (internal) motions of each subunit. We observed that in total the external motions in one of the subunits largely dominated the coupling. The combination of external motions of ubiquitin and the ligands showed general trends of rotations and translations. Moreover, we observed that the rotational motions of ubiquitin were correlated to the ligand orientations. We also identified ubiquitin atomic vibrations that differentiated the orientation of the ligand molecule. We observed that the extents of coupling were correlated to the shapes of the ligands, and this trend was more pronounced when the coupling involved vibrational motions of the ligand. In conclusion, an intricate interplay between internal and external motions of ubiquitin and the ligands help understand the dynamics of multispecificity, which is mostly guided by the shapes of the ligands and the complex. Proteins 2014; 82:77–89. © 2013 Wiley Periodicals, Inc.

Many proteins function by interacting with other small molecules (ligands). Identification of ligand-binding sites (LBS) in proteins can therefore help to infer their molecular functions. A comprehensive comparison among local structures of LBSs was previously performed, in order to understand their relationships and to classify their structural motifs. However, similar exhaustive comparison among local surfaces of LBSs (patches) has never been performed, due to computational complexity. To enhance our understanding of LBSs, it is worth performing such comparisons among patches and classifying them based on similarities of their surface configurations and electrostatic potentials. In this study, we first developed a rapid method to compare two patches. We then clustered patches corresponding to the same PDB chemical component identifier for a ligand, and selected a representative patch from each cluster. We subsequently exhaustively as compared the representative patches and clustered them using similarity score, PatSim. Finally, the resultant PatSim scores were compared with similarities of atomic structures of the LBSs and those of the ligand-binding protein sequences and functions. Consequently, we classified the patches into ≈ 2000 well-characterized clusters. We found that about 63% of these clusters are used in identical protein folds, although about 25% of the clusters are conserved in distantly related proteins and even in proteins with cross-fold similarity. Furthermore, we showed that patches with higher PatSim score have potential to be involved in similar biological processes.

Protein functions are mediated by interactions between proteins and other molecules. One useful approach to analyze protein functions is to compare and classify the structures of interaction interfaces of proteins. Here, we describe the procedures for compiling a database of interface structures and efficiently comparing the interface structures. To do so requires a good understanding of the data structures of the Protein Data Bank (PDB). Therefore, we also provide a detailed account of the PDB exchange dictionary necessary for extracting data that are relevant for analyzing interaction interfaces and secondary structures. We identify recurring structural motifs by classifying similar interface structures, and we define a coarse-grained representation of supersecondary structures (SSS) which represents a sequence of two or three secondary structure elements including their relative orientations as a string of four to seven letters. By examining the correspondence between structural motifs and SSS strings, we show that no SSS string has particularly high propensity to be found interaction interfaces in general, indicating any SSS can be used as a binding interface. When individual structural motifs are examined, there are some SSS strings that have high propensity for particular groups of structural motifs. In addition, it is shown that while the SSS strings found in particular structural motifs for nonpolymer and protein interfaces are as abundant as in other structural motifs that belong to the same subunit, structural motifs for nucleic acid interfaces exhibit somewhat stronger preference for SSS strings. In regard to protein folds, many motif-specific SSS strings were found across many folds, suggesting that SSS may be a useful description to investigate the universality of ligand binding modes.

Background BioHackathon 2010 was the third in a series of meetings hosted by the Database Center for Life Sciences (DBCLS) in Tokyo, Japan. The overall goal of the BioHackathon series is to improve the quality and accessibility of life science research data on the Web by bringing together representatives from public databases, analytical tool providers, and cyber-infrastructure researchers to jointly tackle important challenges in the area of in silico biological research. Results The theme of BioHackathon 2010 was the 'Semantic Web', and all attendees gathered with the shared goal of producing Semantic Web data from their respective resources, and/or consuming or interacting those data using their tools and interfaces. We discussed on topics including guidelines for designing semantic data and interoperability of resources. We consequently developed tools and clients for analysis and visualization. Conclusion We provide a meeting report from BioHackathon 2010, in which we describe the discussions, decisions, and breakthroughs made as we moved towards compliance with Semantic Web technologies - from source provider, through middleware, to the end-consumer.

A Mid-infrared Free-Electron Laser (MIR-FEL) facility named as KU-FEL (Kyoto University FEL) has been developed in Institute of Advanced Energy, Kyoto University. The facility aims at utilizing MIR-FEL to various energy related sciences, such as material, biological and chemical sciences. The present status, performance and result of demonstration experiment are reported in this paper.

Start-to-end calculation has been performed to estimate the performance of the THz FEL system using a photocathode RF gun which will be installed to existing MIR-FEL (KU-FEL) system at Institute of Advanced Energy, Kyoto University. The aim of this system is a test bench to realize the table-top THz system. The electron beam properties have been evaluated from the photocathode RF gun to the entrance of undulator by using the simulation code PARMELA. FEL gain was calculated by GENESIS 1.3.

Protein functions are mediated by interactions between proteins and other molecules. One useful approach to analyze protein functions is to compare and classify the structures of interaction interfaces of proteins. Here, we describe the procedures for compiling a database of interface structures and efficiently comparing the interface structures. To do so requires a good understanding of the data structures of the Protein Data Bank (PDB). Therefore, we also provide a detailed account of the PDB exchange dictionary necessary for extracting data that are relevant for analyzing interaction interfaces and secondary structures. We identify recurring structural motifs by classifying similar interface structures, and we define a coarse-grained representation of supersecondary structures (SSS) which represents a sequence of two or three secondary structure elements including their relative orientations as a string of four to seven letters. By examining the correspondence between structural motifs and SSS strings, we show that no SSS string has particularly high propensity to be found interaction interfaces in general, indicating any SSS can be used as a binding interface. When individual structural motifs are examined, there are some SSS strings that have high propensity for particular groups of structural motifs. In addition, it is shown that while the SSS strings found in particular structural motifs for nonpolymer and protein interfaces are as abundant as in other structural motifs that belong to the same subunit, structural motifs for nucleic acid interfaces exhibit somewhat stronger preference for SSS strings. In regard to protein folds, many motif-specific SSS strings were found across many folds, suggesting that SSS may be a useful description to investigate the universality of ligand binding modes.

The ferroelectric soft mode in a SrTiO(3) thin film was impulsively driven to a large amplitude using intense picosecond terahertz pulses. As the terahertz electric field increased, the soft-mode absorption peak exhibited blueshifting and spectral narrowing. A classical anharmonic oscillator model suggests that the induced displacement is comparable to that of the ferroelectric phase transition. The spectral narrowing indicates that the displacement exceeds that induced by any inhomogeneities in the film, demonstrating that the method can be used to explore intrinsic quartic anharmonicity.

Most biological processes are described as a series of interactions between proteins and other molecules, and interactions are in turn described in terms of atomic structures. To annotate protein functions as sets of interaction states at atomic resolution, and thereby to better understand the relation between protein interactions and biological functions, we conducted exhaustive all-against-all atomic structure comparisons of all known binding sites for ligands including small molecules, proteins and nucleic acids, and identified recurring elementary motifs. By integrating the elementary motifs associated with each subunit, we defined composite motifs which represent context-dependent combinations of elementary motifs. It is demonstrated that function similarity can be better inferred from composite motif similarity compared to the similarity of protein sequences or of individual binding sites. By integrating the composite motifs associated with each protein function, we define meta-composite motifs each of which is regarded as a time-independent diagrammatic representation of a biological process. It is shown that meta-composite motifs provide richer annotations of biological processes than sequence clusters. The present results serve as a basis for bridging atomic structures to higher-order biological phenomena by classification and integration of binding site structures., Comment: 34 pages, 7 figures

Background: As the coverage of experimentally determined protein structures increases, fragment-based structural modeling approaches are expected to play an ever more important role in structural modeling. Here we introduce a structural modeling method by which an initial structural template can be extended by the addition of structural fragments to more closely match an aligned query sequence. A database of pro-tein fragments indexed by their internal coordinates was created and a novel methodology for their retrieval was implemented. After fragment selection and assembly, sidechains are replaced and the all-atom model is refined by restrained energy minimization. We implemented the proposed method in the program Span-ner and benchmarked it using a previously published set of 367 immunoglobulin (Ig) loops, 206 historical query-template pairs and alignments from the Critical Assessment of protein Structure Prediction (CASP) experiment, and 217 structural alignments between remotely homologous query-template pairs. The con-straint-based modeling software MODELLER and previously reported results for RosettaAntibody, were used as references. Results: The error in the modeled structures was assessed by root-mean square deviation (RMSD) from the native structure, as a function of the query-template sequence identity. For the Ig benchmark set, for which a single fragment was used to model each loop, the average RMSD for Spanner (3 +/- 1.5 A) was found to lie midway between that of MODELLER (4 +/- 2 A) and RosettaAntibody (2 +/- 1 A). For the CASP and structural alignment benchmarks, for which gaps represent a small fraction of the modeled residues, the difference between Spanner and MODELLER were much smaller then the standard deviations of either program. The Spanner web server and source code are available at http://sysimm.ifrec.osaka-u.ac.jp/Spanner/. Conclusions: For typical homology modeling, Spanner is at least as good, on average as the template-free constraint-driven approach used by MODELLER. The Ig model results suggest that when gap regions represent a significant fraction of the alignment, Spanner’s efficient use of fragment libraries, along with local sequence and secondary structural information, significantly improve model accuracy without a dra-matic increase in computational cost.

A mid‐infrared free electron laser (MIR‐FEL) facility (KU‐FEL: Kyoto University Free Electron Laser) has been constructed for developing energy materials in Institute of Advanced Energy (IAE), Kyoto University. The tunable range of KU‐FEL was estimated as 5–13.2 μm by numerical calculation to design the MIR‐FEL transport line for application purposes. Aiming to increase the number of FEL users with different desires we decided to develop an FEL beam sharing system that is useful for multi‐utilization at different end‐stations. The transport line and the beam sharing system has been designed and constructed to the user stations. Applications of the MIR‐FEL in the renewable energy research at Kyoto University will start as well.

A mid‐infrared free electron laser (MIR‐FEL: 5 μm–20 μm) facility (KU‐FEL: Kyoto University Free Electron Laser) has been constructed in Institute of Advanced Energy Kyoto University, and first laser saturation at 13.2 μm was achieved in May 2008. Currently, we have started to develop the application of MIR‐FEL in the field of energy and material science. This study aimed at investigating the feasibility for the development of new evaluation technique of electron‐phonon interaction in metal oxides by MIR‐FEL. A preliminary result of electrical and optical properties of titanium dioxides was presented.

We propose a novel tabletop THz FEL amplifier consisting of a photocathode RF gun, an undulator, and an is-TPG THz seeding system. In the compact FEL amplifier, tunable and narrowband THz seed light generated by the is-TPG device is amplified through FEL interaction with high brightness electron beam in the undulator. Design study and numerical estimation of the performance of the tabletop THz FEL amplifier have been studied. The sub-watt level THz seed light will be amplified order of 4 in peak power with a 2.5 m long undulator. Total size of the novel THz FEL amplifier is expected to be 2 m × 4 m.

At Institute of Advanced Energy, Kyoto University we have started study of tabletop THz FEL amplifier. Spectral range of FEL is aimed at 150–300µm. The whole length of amplifier was designed to be less than 4m. For conceptual design, start-to-end simulation of FEL was made by simulation code Parmela and GENESIS 1.3. The slippage effect and the diffraction loss were taken into account FEL simulation. The output power of about 5kW was expected from the design scheme.

A statistical model of protein families, called profile conditional random fields (CRFs), is proposed. This model may be regarded as an integration of the profile hidden Markov model (HMM) and the Finkelstein-Reva (FR) theory of protein folding. While the model structure of the profile CRF is almost identical to the profile HMM, it can incorporate arbitrary correlations in the sequences to be aligned to the model. In addition, like in the FR theory, the profile CRF can incorporate long-range pairwise interactions between model states via mean-field-like approximations. We give the detailed formulation of the model, self-consistent approximations for treating long-range interactions, and algorithms for computing partition functions and marginal probabilities. We also outline the methods for the global optimization of model parameters as well as a Bayesian framework for parameter learning and selection of optimal alignments., Comment: 11 pages (two column), 1 figure, 1 table, revised

Background: One-dimensional protein structures such as secondary structures or contact numbers are useful for three-dimensional structure prediction and helpful for intuitive understanding of the sequence-structure relationship. Accurate prediction methods will serve as a basis for these and other purposes. Results: We implemented a program CRNPRED which predicts secondary structures, contact numbers and residue-wise contact orders. This program is based on a novel machine learning scheme called critical random networks. Unlike most conventional one-dimensional structure prediction methods which are based on local windows of an amino acid sequence, CRNPRED takes into account the whole sequence. CRNPRED achieves, on average per chain, Q3 = 81% for secondary structure prediction, and correlation coefficients of 0.75 and 0.61 for contact number and residue-wise contact order predictions, respectively. Conclusion: CRNPRED will be a useful tool for computational as well as experimental biologists who need accurate one-dimensional protein structure predictions., Comment: 10 pages, 1 figure, 2 tables

Prediction of one-dimensional protein structures such as secondary structures and contact numbers is useful for the three-dimensional structure prediction and important for the understanding of sequence-structure relationship. Here we present a new machine-learning method, critical random networks (CRNs), for predicting one-dimensional structures, and apply it, with position-specific scoring matrices, to the prediction of secondary structures (SS), contact numbers (CN), and residue-wise contact orders (RWCO). The present method achieves, on average, $Q_3$ accuracy of 77.8% for SS, correlation coefficients of 0.726 and 0.601 for CN and RWCO, respectively. The accuracy of the SS prediction is comparable to other state-of-the-art methods, and that of the CN prediction is a significant improvement over previous methods. We give a detailed formulation of critical random networks-based prediction scheme, and examine the context-dependence of prediction accuracies. In order to study the nonlinear and multi-body effects, we compare the CRNs-based method with a purely linear method based on position-specific scoring matrices. Although not superior to the CRNs-based method, the surprisingly good accuracy achieved by the linear method highlights the difficulty in extracting structural features of higher order from amino acid sequence beyond that provided by the position-specific scoring matrices., Comment: 20 pages, 1 figure, 5 tables; minor revision; accepted for publication in BIOPHYSICS