Snake cube puzzle and protein folding.

The snake cube puzzle made of a linear array of 27 cubes and its modified and extended versions are used as theoretical models to study the mechanism of folding of proteins into their sequence-specific native three-dimensional structures. Each of the three versions is characterized by the respective set of characteristics attributed to each of its constituent cubes and an array is characterized by its specific sequence of the cube characteristics. The aim of the puzzles is to fold the cube array into a compact 3×3×3 cubic structure. In all three versions, out of all possible sequences, only a limited fraction of sequences are found foldable into the compact cube. Even among foldable sequences, the structures folded into the compact 3×3×3 cube are found often not uniquely determined from the sequence. By comparing the results obtained for the three versions of models, we conclude that the power of the hydrophobic interactions to make the folded structure unique to the sequence is much weaker than the geometrical varieties of constituent cubes as modelled in the original snake cube puzzle. However, when this weak cube attribute is compounded to that of the original snake cube puzzle, the power is enhanced very effectively. This is a strong manifestation of the consistency principle: The sequence-specific native structure of protein is realized as a result of consistency of various types of interactions working in protein.

Ligand-induced protein responses and mechanical signal propagation described by linear response theories.

In this study, a general linear response theory (LRT) is formulated to describe time-dependent and -independent protein conformational changes upon CO binding with myoglobin. Using the theory, we are able to monitor protein relaxation in two stages. The slower relaxation is found to occur from 4.4 to 81.2 picoseconds and the time constants characterized for a couple of aromatic residues agree with those observed by UV Resonance Raman (UVRR) spectrometry and time resolved x-ray crystallography. The faster "early responses", triggered as early as 400 femtoseconds, can be best described by the theory when impulse forces are used. The newly formulated theory describes the mechanical propagation following ligand-binding as a function of time, space and types of the perturbation forces. The "disseminators", defined as the residues that propagate signals throughout the molecule the fastest among all the residues in protein when perturbed, are found evolutionarily conserved and the mutations of which have been shown to largely change the CO rebinding kinetics in myoglobin.

High-speed classification of coherent X-ray diffraction patterns on the K computer for high-resolution single biomolecule imaging.

Single-particle coherent X-ray diffraction imaging using an X-ray free-electron laser has the potential to reveal the three-dimensional structure of a biological supra-molecule at sub-nanometer resolution. In order to realise this method, it is necessary to analyze as many as 1 × 10(6) noisy X-ray diffraction patterns, each for an unknown random target orientation. To cope with the severe quantum noise, patterns need to be classified according to their similarities and average similar patterns to improve the signal-to-noise ratio. A high-speed scalable scheme has been developed to carry out classification on the K computer, a 10PFLOPS supercomputer at RIKEN Advanced Institute for Computational Science. It is designed to work on the real-time basis with the experimental diffraction pattern collection at the X-ray free-electron laser facility SACLA so that the result of classification can be feedback for optimizing experimental parameters during the experiment. The present status of our effort developing the system and also a result of application to a set of simulated diffraction patterns is reported. About 1 × 10(6) diffraction patterns were successfully classificatied by running 255 separate 1 h jobs in 385-node mode.

Classifying and assembling two-dimensional X-ray laser diffraction patterns of a single particle to reconstruct the three-dimensional diffraction intensity function: resolution limit due to the quantum noise.

A new two-step algorithm is developed for reconstructing the three-dimensional diffraction intensity of a globular biological macromolecule from many experimentally measured quantum-noise-limited two-dimensional X-ray laser diffraction patterns, each for an unknown orientation. The first step is classification of the two-dimensional patterns into groups according to the similarity of direction of the incident X-rays with respect to the molecule and an averaging within each group to reduce the noise. The second step is detection of common intersecting circles between the signal-enhanced two-dimensional patterns to identify their mutual location in the three-dimensional wavenumber space. The newly developed algorithm enables one to detect a signal for classification in noisy experimental photon-count data with as low as ~0.1 photons per effective pixel. The wavenumber of such a limiting pixel determines the attainable structural resolution. From this fact, the resolution limit due to the quantum noise attainable by this new method of analysis as well as two important experimental parameters, the number of two-dimensional patterns to be measured (the load for the detector) and the number of pairs of two-dimensional patterns to be analysed (the load for the computer), are derived as a function of the incident X-ray intensity and quantities characterizing the target molecule.

Enhanced resolution of molecular recognition to distinguish structurally similar molecules by different conformational responses of a protein upon ligand binding.

MutT distinguishes substrate 8-oxo-dGTP from dGTP and also 8-oxo-dGMP from dGMP despite small differences of chemical structures between them. In this paper we show by the method of molecular dynamics simulation that the transition between conformational substates of MutT is a key mechanism for a high-resolution molecular recognition of the differences between the very similar chemical compounds. (1) The native state MutT has two conformational substates with similar free energies, each characterized by either open or closed of two loops surrounding the substrate binding active site. Between the two substates, the open substate is more stable in free MutT and in dGMP-MutT complex, and the closed substate is more stable in 8-oxo-dGMP-MutT complex. (2) Conformational fluctuation of the open substate is much larger than that of the closed substate. An estimate of associated entropy difference was found to be consistent with the experimentally found difference of entropy contribution to the binding free energies of the two molecules. (3) A hydrogen bond between H7 atom of 8-oxo-dGMP and the sidechain of Asn119 plays a crucial role for maintaining the closed substate in 8-oxo-dGMP-MutT complex. When this hydrogen bond is absent in the H7-deficient dGMP-MutT complex, the closed substate is no more maintained and transition to the more entropically-favored open substate is induced. (4) Thus, this mechanism of the hydrogen bond controlling the relative stabilities of the drastically different two conformational substates enhances the resolution to recognize the small difference of the chemical structures between the two molecules, dGMP and 8-oxo-dGMP.

Sequence-dependent DNA deformability studied using molecular dynamics simulations.

Proteins recognize specific DNA sequences not only through direct contact between amino acids and bases, but also indirectly based on the sequence-dependent conformation and deformability of the DNA (indirect readout). We used molecular dynamics simulations to analyze the sequence-dependent DNA conformations of all 136 possible tetrameric sequences sandwiched between CGCG sequences. The deformability of dimeric steps obtained by the simulations is consistent with that by the crystal structures. The simulation results further showed that the conformation and deformability of the tetramers can highly depend on the flanking base pairs. The conformations of xATx tetramers show the most rigidity and are not affected by the flanking base pairs and the xYRx show by contrast the greatest flexibility and change their conformations depending on the base pairs at both ends, suggesting tetramers with the same central dimer can show different deformabilities. These results suggest that analysis of dimeric steps alone may overlook some conformational features of DNA and provide insight into the mechanism of indirect readout during protein-DNA recognition. Moreover, the sequence dependence of DNA conformation and deformability may be used to estimate the contribution of indirect readout to the specificity of protein-DNA recognition as well as nucleosome positioning and large-scale behavior of nucleic acids.

BAAQ: an infrastructure for application integration and knowledge discovery in bioinformatics.

The emerging grid computing technologies enable bioinformatics scientists to conduct their researches in a virtual laboratory, in which they share public databases, computational tools as well as their analysis workflows. However, the development of grid applications is still a nightmare for general bioinformatics scientists, due to the lack of grid programming environments, standards and high-level services. Here, we present a system, which we named Bioinformatics: Ask Any Questions (BAAQ), to automate this development procedure as much as possible. BAAQ allows scientists to store and manage remote biological data and programs, to build analysis workflows that integrate these resources seamlessly, and to discover knowledge from available resources. This paper addresses two issues in building grid applications in bioinformatics: how to smoothly compose an analysis workflow using heterogeneous resources and how to efficiently discover and re-use available resources in the grid community. Correspondingly an intelligent grid programming environment and an active solution recommendation service are proposed. Finally, we present a case study applying BAAQ to a bioinformatics problem.

Detection of pockets on protein surfaces using small and large probe spheres to find putative ligand binding sites.

One of the simplest ways to predict ligand binding sites is to identify pocket-shaped regions on the protein surface. Many programs have already been proposed to identify these pocket regions. Examination of their algorithms revealed that a pocket intrinsically has two arbitrary properties, "size" and "depth". We proposed a new definition for pockets using two explicit adjustable parameters that correspond to these two arbitrary properties. A pocket region is defined as a space into which a small probe can enter, but a large probe cannot. The radii of small and large probe spheres are the two parameters that correspond to the "size" and "depth" of the pockets, respectively. These values can be adjusted individual putative ligand molecule. To determine the optimal value of the large probe spheres radius, we generated pockets for thousands of protein structures in the database, using several size of large probe spheres, examined the correspondence of these pockets with known binding site positions. A new measure of shallowness, a minimum inaccessible radius, R(inaccess), indicated that binding sites of coenzymes are very deep, while those for adenine/guanine mononucleotide have only medium shallowness and those for short peptides and oligosaccharides are shallow. The optimal radius of large probe spheres was 3-4 A for the coenzymes, 4 A for adenine/guanine mononucleotides, and 5 A or more for peptides/oligosaccharides. Comparison of our program with two other popular pocket-finding programs showed that our program had a higher performance of detecting binding pockets, although it required more computational time.

Prediction of interacting proteins from homology-modeled complex structures using sequence and structure scores.

Protein-protein interactions support most biological processes, and it is important to find specifically interacting partner proteins among homologous proteins in order to elucidate cellular functions such as signal transduction systems. Various high-throughput experimental methods for identifying these interactions have been invented, and used to generate a huge amount of data. Because these experiments have been applied to only a few organisms, and their accuracy is believed to be limited, it would be valuable to develop computational methods for predicting protein-protein interactions from their amino acid sequences or tertiary structural information. In this study, we describe a prediction method of interacting proteins based on homology-modeled complex structures. We employed the statistical residue-residue contact energy used in a previous study, and two types of new scores, simple electrostatic energy and sequence similarity between target sequences and template structures. The validity of each protein-protein complex model was measured using their single and combined scores. We applied our method to all the protein heterodimers of Saccharomyces cerevisiae. To evaluate the prediction performance of our method, we prepared two types of protein-protein interaction dataset: a complete dataset and high confidence dataset. The complete dataset (10,325 protein dimer models) contains all the yeast protein heterodimers whose complex structures can be modeled. Among them, pairs registered in the DIP database are defined as interacting pairs, and those not registered are defined as non-interacting protein pairs. The high confidence dataset (3,219 protein dimer models) is a more reliable subset of the complete dataset extracted using the criteria of the common subcellular localization. Both datasets show that sequence similarity has a much higher discrimination power than the other structure-based scores, but that the inclusion of contact energy results in significant improvement over predictions using sequence similarity alone. These results suggest that the sequence similarity is indispensable for the prediction, whereas structure scores can play supporting roles.

Amino acid residue doublet propensity in the protein-RNA interface and its application to RNA interface prediction.

Protein-RNA interactions play essential roles in a number of regulatory mechanisms for gene expression such as RNA splicing, transport, translation and post-transcriptional control. As the number of available protein-RNA complex 3D structures has increased, it is now possible to statistically examine protein-RNA interactions based on 3D structures. We performed computational analyses of 86 representative protein-RNA complexes retrieved from the Protein Data Bank. Interface residue propensity, a measure of the relative importance of different amino acid residues in the RNA interface, was calculated for each amino acid residue type (residue singlet interface propensity). In addition to the residue singlet propensity, we introduce a new residue-based propensity, which gives a measure of residue pairing preferences in the RNA interface of a protein (residue doublet interface propensity). The residue doublet interface propensity contains much more information than the sum of two singlet propensities alone. The prediction of the RNA interface using the two types of propensities plus a position-specific multiple sequence profile can achieve a specificity of about 80%. The prediction method was then applied to the 3D structure of two mRNA export factors, TAP (Mex67) and UAP56 (Sub2). The prediction enables us to point out candidate RNA interfaces, part of which are consistent with previous experimental studies and may contribute to elucidation of atomic mechanisms of mRNA export.

Switch interactions control energy frustration and multiple flagellar filament structures.

Bacterial flagellar filament is a macromolecular assembly consisting of a single protein, flagellin. Bacterial swimming is controlled by the conformational transitions of this filament between left- and right-handed supercoils induced by the flagellar motor torque. We present a massive molecular dynamics simulation that was successful in constructing the atomic-level supercoil structures consistent with various experimental data and further in elucidating the detailed underlying molecular mechanisms of the polymorphic supercoiling. We have found that the following three types of interactions are keys to understanding the supercoiling mechanism. "Permanent" interactions are always maintained between subunits in the various supercoil structures. "Sliding" interactions are formed between variable hydrophilic or hydrophobic residue pairs, allowing intersubunit shear without large change in energy. The formation and breakage of "switch" interactions stabilize inter- and intrasubunit interactions, respectively. We conclude that polymorphic supercoiling is due to the energy frustration between them. The transition between supercoils is achieved by a "transform and relax" mechanism: the filament structure is geometrically transformed rapidly and then slowly relaxes to energetically metastable states by rearranging interactions.

Protein boson peak originated from hydration-related multiple minima energy landscape.

The boson peak is a broad peak found in the low-frequency region of inelastic neutron and Raman scattering spectra in many glassy materials, including biopolymers below approximately 200 K. Here, we give a novel insight into the origins of the protein boson peak, which may also be valid for materials other than proteins. Molecular simulation reveals that the structured water molecules around a protein molecule increase the number of local minima in the protein energy landscape, which plays a key role in the origin of the boson peak. The peak appears when the protein dynamics are trapped within a local energy minimum at cryogenic temperatures. This trapping causes very low frequency collective motions to shift to higher frequencies. We demonstrate that the characteristic frequency of such systems shifts higher as the temperature decreases also in model one-dimensional energy surfaces with multiple minima.

Newly sequenced eRF1s from ciliates: the diversity of stop codon usage and the molecular surfaces that are important for stop codon interactions.

The genetic code of nuclear genes in some ciliates was found to differ from that of other organisms in the assignment of UGA, UAG, and UAA codons, which are normally assigned as stop codons. In some ciliate species, the universal stop codons UAA and UAG instead encode glutamine. In some other ciliates, the universal stop codon UGA appears to be translated as cysteine or tryptophan. Eukaryotic release factor 1 (eRF1) is a key protein in stop codon recognition, thus, the protein is believed to play an important role in the stop codon reassignment in ciliates. We have cloned, sequenced, and analyzed the cDNA of eRF1 from four ciliate species of three different classes: Karyorelictea (Loxodes striatus), Heterotrichea (Blepharisma musculus), and Litostomatea (Didinium nasutum, Dileptus margaritifer). Phylogenetic analysis of these eRF1s supports the hypothesis that the genetic code in ciliates has deviated independently several times from the universal genetic code, and that different ciliate eRF1s may have undergone different processes to change the codon specificity. Using computational methods, we have also suggested areas on the surface of eRF1s that are important for stop codon recognition in ciliate eRF1s.

Sequence analysis of the gliding protein Gli349 in Mycoplasma mobile.

The motile mechanism of Mycoplasma mobile remains unknown but is believed to differ from any previously identified mechanism in bacteria. Gli349 of M. mobile is known to be responsible for both adhesion to glass surfaces and mobility. We therefore carried out sequence analyses of Gli349 and its homolog MYPU2110 from M. pulmonis to decipher their structures. We found that the motif "YxxxxxGF" appears 11 times in Gli349 and 16 times in MYPU2110. Further analysis of the sequences revealed that Gli349 contains 18 repeats of about 100 amino acid residues each, and MYPU2110 contains 22. No sequence homologous to any of the repeats was found in the NCBI RefSeq non-redundant sequence database, and no compatible fold structure was found among known protein structures, suggesting that the repeat found in Gli349 and MYPU2110 is novel and takes a new fold structure. Proteolysis of Gli349 using chymotrypsin revealed that cleavage positions were often located between the repeats, implying that regions connecting repeats are unstructured, flexible and exposed to the solvent. Assuming that each repeat folds into a structural domain, we constructed a model of Gli349 that fits well the shape and size of images obtained with electron microscopy.

Electrostatic potential of nucleotide-free protein is sufficient for discrimination between adenine and guanine-specific binding sites.

Despite sharing many common features, adenine-binding and guanine-binding sites in proteins often show a clear preference for the cognate over the non-cognate ligand. We have analyzed electrostatic potential (ESP) patterns at adenine and guanine-binding sites of a large number of non-redundant proteins where each binding site was first annotated as adenine/guanine-specific or non-specific from a survey of primary literature. We show that more than 90% of ESP variance at the binding sites is accounted for by only two principal component ESP vectors, each aligned to molecular dipoles of adenine and guanine. Projected on these principal component vectors, the adenine/guanine-specific and non-specific binding sites, including adenine-containing dinucleotides, show non-overlapping distributions. Adenine or guanine specificities of the binding sites also show high correlation with the corresponding electrostatic replacement (cognate by non-cognate ligand) energies. High correlation coefficients (0.94 for 35 adenine-binding sites and 1.0 for 20 guanine-binding sites) were obtained when adenine/guanine specificities were predicted using the replacement energies. Our results demonstrate that ligand-free protein ESP is an excellent indicator for discrimination between adenine and guanine-specific binding sites and that ESP of ligand-free protein can be used as a tool to annotate known and putative purine-binding sites in proteins as adenine or guanine-specific.

Filtering remote homologues using predicted structural information.

Finding homologues for a given protein plays a major role in predicting the protein's structure and function. However, it is still difficult to find remote homologues with low sequence similarity, even with advanced sequence search methods. We propose a simple filtering method that uses predicted structural information, pertaining to secondary structures and solvent accessibilities. It filters the more promising homologues from the many candidate proteins obtained by PSI-BLAST with a less stringent threshold E-value. The final decision is made by a simple linear discrimination method, considering the E-value of PSI-BLAST and the statistical significance scores of structural matches. An in-house neural network program is used for the prediction of secondary structures and solvent accessibilities for both the query and library proteins. The performance of our filtering method was evaluated by the cross-validation method, using the SCOP superfamily relationship as the correct standard. Coverage-reliability plots show that our filtering method clearly improves the performance of PSI-BLAST. The secondary structure improves PSI-BLAST better than the solvent accessibilities, but the combination of these two features with PSI-BLAST leads to the best result. The advantage of our method is its easy implementation with fewer parameters to be tuned and faster computation. We also discuss its performance with predicted and observed secondary structures.

Highly divergent actins from karyorelictean, heterotrich, and litostome ciliates.

We have cloned, sequenced, and characterized cDNA of actins from five ciliate species of three different classes of the phylum Ciliophora: Karyorelictea (Loxodes striatus), Heterotrichea (Blepharisma japonicum, Blepharisma musculus), and Litostomatea (Didinium nasutum, Dileptus margaritifer). Loxodes striatus uses UGA as the stop codon and has numerous in-frame UAA and UAG, which are translated into glutamine. The other four species use UAA as the stop codon and have no in-frame UAG nor UGA. The putative amino acid sequences of the newly determined actin genes were found to be highly divergent as expected from previous findings of other ciliate actins. These sequences were also highly divergent from other ciliate actins, indicating that actin genes are highly diverse even within the phylum Ciliophora. Phylogenetic analysis showed high evolutionary rate of ciliate actins. Our results suggest that the evolutionary rate was accelerated because of the differences in molecular interactions.

Novel types of two-domain multi-copper oxidases: possible missing links in the evolution.

An analysis of the genome sequence database revealed novel types of two-domain multi-copper oxidases. The two-domain proteins have the conspicuous combination of blue-copper and inter-domain trinuclear copper binding residues, which is common in ceruloplasmin and ascorbate oxidase but not in nitrite reductase, and therefore are considered to retain the characteristics of the plausible ancestral form of ceruloplasmin and ascorbate oxidase. A possible evolutionary relationship of these proteins is proposed.

Finding evolutionary relations beyond superfamilies: fold-based superfamilies.

Superfamily classifications are based variably on similarity of sequences, global folds, local structures, or functions. We have examined the possibility of defining superfamilies purely from the viewpoint of the global fold/function relationship. For this purpose, we first classified protein domains according to the beta-sheet topology. We then introduced the concept of kinship relations among the classified beta-sheet topology by assuming that the major elementary event leading to creation of a new beta-sheet topology is either an addition or deletion of one beta-strand at the edge of an existing beta-sheet during the molecular evolution. Based on this kinship relation, a network of protein domains was constructed so that the distance between a pair of domains represents the number of evolutionary events that lead one from the other domain. We then mapped on it all known domains with a specific core chemical function (here taken, as an example, that involving ATP or its analogs). Careful analyses revealed that the domains are found distributed on the network as >20 mutually disjointed clusters. The proteins in each cluster are defined to form a fold-based superfamily. The results indicate that >20 ATP-binding protein superfamilies have been invented independently in the process of molecular evolution, and the conservative evolutionary diffusion of global folds and functions is the origin of the relationship between them.

Nonlinear temperature dependence of the crystal structure of lysozyme: correlation between coordinate shifts and thermal factors.

The static and dynamic structures of human lysozyme at seven different temperatures ranging from 113 to 178 K were investigated by normal-mode refinement of the cryogenic X-ray diffraction data collected from a single crystal. Normal-mode refinement decomposes the mean-square fluctuations of protein atoms from their average position into the contributions from the internal degrees of freedom, which change the shape of the protein structure, and those from the external degrees of freedom, which generate rigid-body motions in the crystal. While at temperatures below 150 K the temperature dependence of the total mean-square fluctuations shows a small gradient similar to that predicted theoretically by normal-mode analysis, at temperatures above 150 K there is an apparent inflection in the temperature dependence with a higher gradient. The inflection in the temperature dependence at temperatures above 150 K occurs mostly in the external degrees of freedom. Possible causes for the dynamic transition are discussed with respect to the crystal packing and physicochemical properties of crystalline water.