InfarctSizer: computing infarct volume from brain images of a stroke animal model

Many computational methods for determining the infarct volume from the image of 2,3,5-triphenyltetrazolium chloride-stained brain slices rely on the discretion of the user to determine the infarct region by visual inspection. Once the user determines the infarct boundary by visual inspection, the methods compute the area within the boundary with the assumption that all the spots within the boundary have been infarcted at the same level. However, in the same brain image, partially infarcted spots often tend to appear pinkish whereas fully or severely infarcted spots appear white. We developed a program called InfarctSizer, which automatically detects the infarct region and computes the infarct volume proportional to infarction levels. Comparison of InfarctSizer with other methods shows that InfarctSizer computes the infarct volume more accurately and efficiently than other methods. InfarctSizer and sample brain images are available at http://wilab.inha.ac.kr/brainimage.     

Visualization and analysis of protein interactions

SUMMARY: We have developed a new program called InterViewer for drawing large-scale protein interaction networks in three-dimensional space. Unique features of InterViewer include (1) it is much faster than other recent implementations of drawing algorithms; (2) it can be used not only for visualizing protein interactions but also for analyzing them interactively; and (3) it provides an integrated framework for querying protein interaction databases and directly visualizes the query results. AVAILABILITY: http://wilab.inha.ac.kr/protein/     

Protein-RNA interactions: structural analysis and functional classes

A data set of 89 protein-RNA complexes has been extracted from the Protein Data Bank, and the nucleic acid recognition sites characterized through direct contacts, accessible surface area, and secondary structure motifs. The differences between RNA recognition sites that bind to RNAs in functional classes has also been analyzed. Analysis of the complete data set revealed that van der Waals interactions are more numerous than hydrogen bonds and the contacts made to the nucleic acid backbone occur more frequently than specific contacts to nucleotide bases. Of the base-specific contacts that were observed, contacts to guanine and adenine occurred most frequently. The most favored amino acid-nucleotide pairings observed were lysine-phosphate, tyrosine-uracil, arginine-phosphate, phenylalanine-adenine and tryptophan-guanine. The amino acid propensities showed that positively charged and polar residues were favored as expected, but also so were tryptophan and glycine. The propensities calculated for the functional classes showed trends similar to those observed for the complete data set. However, the analysis of hydrogen bond and van der Waal contacts showed that in general proteins complexed with messenger RNA, transfer RNA and viral RNA have more base specific contacts and less backbone contacts than expected, while proteins complexed with ribosomal RNA have less base-specific contacts than the expected. Hence, whilst the types of amino acids involved in the interfaces are similar, the distribution of specific contacts is dependent upon the functional class of the RNA bound.     

Protein-RNA interactions: a structural analysis

A detailed computational analysis of 32 protein–RNA complexes is presented. A number of physical and chemical properties of the intermolecular interfaces are calculated and compared with those observed in protein–double-stranded DNA and protein–single-stranded DNA complexes. The interface properties of the protein–RNA complexes reveal the diverse nature of the binding sites. van der Waals contacts played a more prevalent role than hydrogen bond contacts, and preferential binding to guanine and uracil was observed. The positively charged residue, arginine, and the single aromatic residues, phenylalanine and tyrosine, all played key roles in the RNA binding sites. A comparison between protein–RNA and protein–DNA complexes showed that whilst base and backbone contacts (both hydrogen bonding and van der Waals) were observed with equal frequency in the protein–RNA complexes, backbone contacts were more dominant in the protein–DNA complexes. Although similar modes of secondary structure interactions have been observed in RNA and DNA binding proteins, the current analysis emphasises the differences that exist between the two types of nucleic acid binding protein at the atomic contact level.     

Protein-nucleic acid recognition: statistical analysis of atomic interactions and influence of DNA structure

We analyzed structural features of 11,038 direct atomic contacts (either electrostatic, H-bonds, hydrophobic, or other van der Waals interactions) extracted from 139 protein-DNA and 49 protein-RNA nonhomologous complexes from the Protein Data Bank (PDB). Globally, H-bonds are the most frequent interactions (approximately 50%), followed by van der Waals, hydrophobic, and electrostatic interactions. From the protein viewpoint, hydrophilic amino acids are over-represented in the interaction databases: Positively charged amino acids mainly contact nucleic acid phosphate groups but can also interact with base edges. From the nucleotide point of view, DNA and RNA behave differently: Most protein-DNA interactions involve phosphate atoms, while protein-RNA interactions involve more frequently base edge and ribose atoms. The increased participation of DNA phosphate involves H-bonds rather than salt bridges. A statistical analysis was performed to find the occurrence of amino acid-nucleotide pairs most different from chance. These pairs were analyzed individually. Finally, we studied the conformation of DNA in the interaction sites. Despite the prevalence of B-DNA in the database, our results suggest that A-DNA is favored in the interaction sites.     

A fast layout algorithm for protein interaction networks

MOTIVATION: Graph drawing algorithms are often used for visualizing relational information, but a naive implementation of a graph drawing algorithm encounters real difficulties when drawing large-scale graphs such as protein interaction networks. RESULTS: We have developed a new, extremely fast layout algorithm for visualizing large-scale protein interaction networks in the three-dimensional space. The algorithm (1) first finds a layout of connected components of an entire network, (2) finds a global layout of nodes with respect to pivot nodes within a connected component and (3) refines the local layout of each connected component by first relocating midnodes with respect to their cutvertices and direct neighbors of the cutvertices and then by relocating all nodes with respect to their neighbors within distance 2. Advantages of this algorithm over classical graph drawing methods include: (1) it is an order of magnitude faster, (2) it can directly visualize data from protein interaction databases and (3) it provides several abstraction and comparison operations for effectively analyzing large-scale protein interaction networks. AVAILABILITY: http://wilab.inha.ac.kr/interviewer/     

ModuleSearch: finding functional modules in a protein–protein interaction network

Many biological processes are performed by a group of proteins rather than by individual proteins. Proteins involved in the same biological process often form a densely connected sub-graph in a protein–protein interaction network. Therefore, finding a dense sub-graph provides useful information to predict the function or protein complex of uncharacterised proteins in the sub-graph. We developed a heuristic algorithm that finds functional modules in a protein–protein interaction network and visualises the modules. The algorithm has been implemented in a platform-independent, standalone program called ModuleSearch. In an interaction network of yeast proteins, ModuleSearch found 366 overlapping modules. Of the modules, 71% have a function shared by more than half the proteins in the module and 58% have a function shared by all proteins in the module. Comparison of ModuleSearch with other programs shows that ModuleSearch finds more sub-graphs than most other programs, yet a higher proportion of the sub-graphs correspond to known functional modules. ModuleSearch and sample data are freely available to academics at http://bclab.inha.ac.kr/ModuleSearch.     

Discovering the interaction propensities of amino acids and nucleotides from protein-RNA complexes

With the availability of many genome sequences, the mining of biological data is attracting much attention, most of it limited to the sequences of macromolecules. Sequence data are easy to analyze as they can be treated as strings of characters, whereas the structure of a macromolecule is much more complex. We developed a set of algorithms to analyze the structures of protein-RNA complexes at the atomic level and used them to analyze protein-RNA interactions using structural data on 51 protein-RNA complexes. The analysis revealed, among other things, that: (1) polar and charged amino acids have a strong tendency to interact with nucleotides, (2) arginine and asparagine tend to hydrogen bond with uracil, and (3) histidine favors uracil in water-mediated bonding with RNA. We analyzed a large set of structural data of protein-RNA complexes involving water-mediated hydrogen bonds as well as direct hydrogen bonds. The interaction patterns discovered from the analysis provide useful information for predicting the structure of RNA that binds proteins, and of proteins that bind RNA.     

Structure-based analysis of protein-RNA interactions using the program ENTANGLE

Until recently, drawing general conclusions about RNA recognition by proteins has been hindered by the paucity of high-resolution structures. We have analyzed 45 PDB entries of protein-RNA complexes to explore the underlying chemical principles governing both specific and non-sequence specific binding. To facilitate the analysis, we have constructed a database of interactions using ENTANGLE, a JAVA-based program that uses available structural models in their PDB format and searches for appropriate hydrogen bonding, stacking, electrostatic, hydrophobic and van der Waals interactions. The resulting database of interactions reveals correlations that suggest the basis for the discrimination of RNA from DNA and for base-specific recognition. The data illustrate both major and minor interaction strategies employed by families of proteins such as tRNA synthetases, ribosomal proteins, or RNA recognition motifs with their RNA targets. Perhaps most surprisingly, specific RNA recognition appears to be mediated largely by interactions of amide and carbonyl groups in the protein backbone with the edge of the RNA base. In cases where a base accepts a proton, the dominant amino acid donor is arginine, whereas in cases where the base donates a proton, the predominant acceptor is the backbone carbonyl group, not a side-chain group. This is in marked contrast to DNA-protein interactions, which are governed predominantly by amino acid side-chain interactions with functional groups that are presented in the accessible major groove. RNA recognition often proceeds through loops, bulges, kinks and other irregular structures that permit use of all the RNA functional groups and this is seen throughout the protein-RNA interaction database.     

Resolution of sertraline with (R)-mandelic acid: chiral discrimination mechanism study

The chiral discrimination mechanism in the resolution of sertraline with mandelic acid was investigated by examining the weak intermolecular interactions (such as hydrogen bond, CH/π, and van der Waals interactions) and molecular packing difference in crystal structures of the resulting diastereomeric salts. A new one-dimensional chain-like hydrogen-bonding network and unique supramolecular packing mode are disclosed. The investigation demonstrated that stable hydrogen-bonding pattern, herringbone-like arrangement of aromatic rings, and planar boundary surface in the hydrophobic region are the three most important structural characteristics expected in less soluble diastereomeric salts. The existence and magnitude of hydrogen bond, CH/π interaction, and van der Waals interaction related to three characteristic structures, determine the stability of diastereomeric salt. The hydrogen bond is not necessarily the dominant factor while the synergy and optimization of all weak intermolecular interactions attribute to the chiral recognition.     

Protein-RNA interactions: exploring binding patterns with a three-dimensional superposition analysis of high resolution structures

MOTIVATION: The recognition of specific RNA sequences and structures by proteins is critical to our understanding of RNA processing, gene expression and viral replication. The diversity of RNA structures suggests that RNA recognition is substantially different than that of DNA. RESULTS: The atomic coordinates of 41 protein-RNA complexes have been used to probe composite nucleoside binding pockets that form the structural and chemical underpinnings of base recognition. Composite nucleoside binding pockets were constructed using three-dimensional superpositions of each RNA nucleoside. Unlike protein-DNA interactions which are dominated by accessibility, RNA recognition frequently occurs in non-canonical and single-strand-like structures that allow interactions to occur from a much wider set of geometries and make fuller use of unique base shapes and hydrogen-bonding ability. By constructing composites that include all van der Waals, hydrogen-bonding, stacking and general non-polar interactions made to a particular nucleoside, the strategies employed are made readily visible. Protein-RNA interactions can result in the formation of a glove-like tight binding pocket around RNA bases, but the size, shape and non-polar binding patterns differ between specific RNA bases. We show that adenine can be distinguished from guanine based on the size and shape of the binding pocket and steric exclusion of the guanine N2 exocyclic amino group. The unique shape and hydrogen-bonding pattern for each RNA base allow proteins to make specific interactions through a very small number of contacts, as few as two in some cases. AVAILABILITY: The program ENTANGLE is available from http://www.bioc.rice.edu/~shamoo     

Scoring a diverse set of high-quality docked conformations: a metascore based on electrostatic and desolvation interactions

Predicting protein-protein interactions involves sampling and scoring docked conformations. Barring some large structural rearrangement, rapidly sampling the space of docked conformations is now a real possibility, and the limiting step for the successful prediction of protein interactions is the scoring function used to reduce the space of conformations from billions to a few, and eventually one high affinity complex. An atomic level free-energy scoring function that estimates in units of kcal/mol both electrostatic and desolvation interactions (plus van der Waals if appropriate) of protein-protein docked conformations is used to rerank the blind predictions (860 in total) submitted for six targets to the community-wide Critical Assessment of PRediction of Interactions (CAPRI; http://capri.ebi.ac.uk). We found that native-like models often have varying intermolecular contacts and atom clashes, making unlikely that one can construct a universal function that would rank all these models as native-like. Nevertheless, our scoring function is able to consistently identify the native-like complexes as those with the lowest free energy for the individual models of 16 (out of 17) human predictors for five of the targets, while at the same time the modelers failed to do so in more than half of the cases. The scoring of high-quality models developed by a wide variety of methods and force fields confirms that electrostatic and desolvation forces are the dominant interactions determining the bound structure. The CAPRI experiment has shown that modelers can predict valuable models of protein-protein complexes, and improvements in scoring functions should soon solve the docking problem for complexes whose backbones do not change much upon binding. A scoring server and programs are available at http://structure.pitt.edu.     

Dissecting the protein-RNA interface: the role of protein surface shapes and RNA secondary structures in protein-RNA recognition

Protein-RNA interactions are essential for many biological processes. However, the structural mechanisms underlying these interactions are not fully understood. Here, we analyzed the protein surface shape (dented, intermediate or protruded) and the RNA base pairing properties (paired or unpaired nucleotides) at the interfaces of 91 protein-RNA complexes derived from the Protein Data Bank. Dented protein surfaces prefer unpaired nucleotides to paired ones at the interface, and hydrogen bonds frequently occur between the protein backbone and RNA bases. In contrast, protruded protein surfaces do not show such a preference, rather, electrostatic interactions initiate the formation of hydrogen bonds between positively charged amino acids and RNA phosphate groups. Interestingly, in many protein-RNA complexes that interact via an RNA loop, an aspartic acid is favored at the interface. Moreover, in most of these complexes, nucleotide bases in the RNA loop are flipped out and form hydrogen bonds with the protein, which suggests that aspartic acid is important for RNA loop recognition through a base-flipping process. This study provides fundamental insights into the role of the shape of the protein surface and RNA secondary structures in mediating protein-RNA interactions.     

A vector-based method for drawing RNA secondary structure.

MOTIVATION: To produce a polygonal display of RNA secondary structure with minimal overlap and distortion of structural elements, with minimal search for positioning them, and with minimal user intervention. RESULTS: A new algorithm for automatically drawing RNA secondary structure has been developed. The algorithm represents the direction and space for a structural element using vector and vector space. Two heuristics are used. The first heuristic is concerned with ordering structural elements to be positioned and the second with positioning them in space. The algorithm and a graphical user interface have been implemented in a working program called VizQFolder on IBM PC compatibles. Experimental results demonstrate that VizQFolder is capable of automatically generating nearly overlap-free polygonal displays for long RNA molecules. The only distortion performed to avoid overlap is the rotation of helices, leading to efficient generation of a polygonal display without sacrificing its readability. VizQFolder is not coupled to a specific prediction program of RNA secondary structure, and thus can be used for visualizing secondary structure models obtained by any means. AVAILABILITY: The executable code of VizQFolder is available at http://automation.inha.ac.kr/khan. It can also be obtained from the authors upon request.     

Molecular mechanical perspective on halogen bonding

The nature and strength of halogen bonding in halo molecule-Lewis base complexes were studied in terms of molecular mechanics using our recently developed positive extra-point (PEP) approach, in which the σ-hole on the halogen atom is represented by an extra point of positive charge. The contributions of the σ-hole (i.e., positively charged extra point) and the halogen atom to the strength of this noncovalent interaction were clarified using the atomic parameter contribution to the molecular interaction (APCtMI) approach. The molecular mechanical results revealed that the halogen bond is electrostatic and van der Waals in nature, and its strength depends on three types of interaction: (1) the attractive electrostatic interaction between the σ-hole and the Lewis base, (2) the repulsive electrostatic interaction between the negative halogen atom and the Lewis base, and (3) the repulsive/attractive van der Waals interactions between the halogen atom and the Lewis base. The strength of the halogen bond increases with increasing σ-hole size (i.e., magnitude of the extra-point charge) and increasing halogen atom size. The van der Waals interaction's contribution to the halogen bond strength is most favorable in chloro complexes, whereas the electrostatic interaction is dominant in iodo complexes. The idea that the chloromethane molecule can form a halogen bond with a Lewis base was revisited in terms of quantum mechanics and molecular mechanics. Although chloromethane does produce a positive region along the C-Cl axis, basis set superposition error corrected second-order M?ller-Plesset calculations showed that chloromethane-Lewis base complexes are unstable, producing halogen-Lewis base contacts longer than the sum of the van der Waals radii of the halogen and O/N atoms. Molecular mechanics using the APCtMI approach showed that electrostatic interactions between chloromethane and a Lewis base are unfavorable owing to the high negative charge on the chlorine atom, which overcomes the corresponding favorable van der Waals interactions.     

Predicting genes expressed via -1 and +1 frameshifts

Computational identification of ribosomal frameshift sites in genomic sequences is difficult due to their diverse nature, yet it provides useful information for understanding the underlying mechanisms and discovering new genes. We have developed an algorithm that searches entire genomic or mRNA sequences for frameshifting sites, and implements the algorithm as a web-based program called FSFinder (Frameshift Signal Finder). The current version of FSFinder is capable of finding -1 frameshift sites on heptamer sequences X XXY YYZ, and +1 frameshift sites for two genes: protein chain release factor B (prfB) and ornithine decarboxylase antizyme (oaz). We tested FSFinder on approximately 190 genomic and partial DNA sequences from a number of organisms and found that it predicted frameshift sites efficiently and with greater sensitivity and specificity than existing approaches. It has improved sensitivity because it considers many known components of a frameshifting cassette and searches these components on both + and - strands, and its specificity is increased because it focuses on overlapping regions of open reading frames and prioritizes candidate frameshift sites. FSFinder is useful for discovering unknown genes that utilize alternative decoding, as well as for analyzing frameshift sites. It is freely accessible at http://wilab.inha.ac.kr/FSFinder/.     

PSEUDOVIEWER2: Visualization of RNA pseudoknots of any type

Visualizing RNA pseudoknot structures is computationally more difficult than depicting RNA secondary structures, because a drawing of a pseudoknot structure is a graph (and possibly a nonplanar graph) with inner cycles within the pseudoknot, and possibly outer cycles formed between the pseudoknot and other structural elements. We previously developed PSEUDOVIEWER for visualizing H-type pseudoknots. PSEUDOVIEWER2 improves on the first version in many ways: (i) PSEUDOVIEWER2 is more general because it can visualize a pseudoknot of any type, including H-type pseudoknots, as a planar graph; (ii) PSEUDOVIEWER2 computes a drawing of RNA structures much more efficiently and is an order of magnitude faster in actual running time; and (iii) PSEUDOVIEWER2 is a web-based application program. Experimental results demonstrate that PSEUDOVIEWER2 generates an aesthetically pleasing drawing of pseudoknots of any type and that the new representation offered by PSEUDOVIEWER2 ensures uniform and clear drawings, with no edge crossing, for all types of pseudoknots. The PSEUDOVIEWER2 algorithm is the first developed for the automatic drawing of RNA secondary structures, including pseudoknots of any type. PSEUDOVIEWER2 is accessible at http://wilab.inha.ac.kr/pseudoviewer2/.     

Investigation of Atomic Level Patterns in Protein—Small Ligand Interactions

Background

Shape complementarity and non-covalent interactions are believed to drive protein-ligand interaction. To date protein-protein, protein-DNA, and protein-RNA interactions were systematically investigated, which is in contrast to interactions with small ligands. We investigate the role of covalent and non-covalent bonds in protein-small ligand interactions using a comprehensive dataset of 2,320 complexes.

Methodology and Principal Findings

We show that protein-ligand interactions are governed by different forces for different ligand types, i.e., protein-organic compound interactions are governed by hydrogen bonds, van der Waals contacts, and covalent bonds; protein-metal ion interactions are dominated by electrostatic force and coordination bonds; protein-anion interactions are established with electrostatic force, hydrogen bonds, and van der Waals contacts; and protein-inorganic cluster interactions are driven by coordination bonds. We extracted several frequently occurring atomic-level patterns concerning these interactions. For instance, 73% of investigated covalent bonds were summarized with just three patterns in which bonds are formed between thiol of Cys and carbon or sulfur atoms of ligands, and nitrogen of Lys and carbon of ligands. Similar patterns were found for the coordination bonds. Hydrogen bonds occur in 67% of protein-organic compound complexes and 66% of them are formed between NH- group of protein residues and oxygen atom of ligands. We quantify relative abundance of specific interaction types and discuss their characteristic features. The extracted protein-organic compound patterns are shown to complement and improve a geometric approach for prediction of binding sites.

Conclusions and Significance

We show that for a given type (group) of ligands and type of the interaction force, majority of protein-ligand interactions are repetitive and could be summarized with several simple atomic-level patterns. We summarize and analyze 10 frequently occurring interaction patterns that cover 56% of all considered complexes and we show a practical application for the patterns that concerns interactions with organic compounds.     

The structures of solvated methylmercury(II) chlolade,bromide and iodide in pyridine solution; Implications for aqueous solution

The structures of solvated methylmercury(II) halides in pyridine solution were determined by a large angle X-ray scattering technique. Near-linear CH₃HgX (X = Cl, Br and I) species solvated by two weakly-coordinated pyridine molecules are indirectly interpreted. Additional mercury-pyridine interactions, through van der Waals forces, are found at the sum of the van der Waals radii. The HgX bond distances in the methylmercury(II) halides are found to be 2.325(8), 2.480(3) and 2.649(3) Å for chloride, bromide and iodide, respectively. The HgC bond distances are assumed to be ∼2.08 Å. This interaction is indicated in the radial distribution functions. The bond distance between mercury and the two solvating pyridine molecules is ∼2.8 Å, e.g., 2.84(2) Å in methylmercury(II) bromide. The additional mercury interactions with roughly two pyridine molecules at the sum of van der Waals radii are revealed at around 3.15 Å. Comparison between Raman stretching vibrations and the solvated structures of methylmercury(II) complexes found in various solvents indicates a lower limit in solvent donor property for the formation of solvate bonds to mercury for the methylmercury(II) halides.     

Protein-RNA contacts at crystal packing surfaces

The crystal packing surfaces comprising protein-RNA interactions were analyzed for 50 RNA-protein crystal structures in the Protein Data Bank database. Protein-RNA crystal contacts, which represent nonspecific protein-RNA interfaces, were investigated for their amino acid propensities, hydrogen bond patterns, and backbone and side chain interactions. When compared to biologically relevant interactions, the protein-RNA crystal contacts exhibit similarities as well as differences with respect to the principles of protein-RNA interactions. Similar to what was observed at cognate protein-RNA interfaces, positively charged amino acids have high propensities at noncognate protein-RNA interfaces and preferentially form hydrogen bonds with RNA phosphate groups. In contrast, nonpolar residues are less frequently associated with noncognate interactions. These results highlight the important roles of both electrostatic and hydrogen bonding interactions, facilitated by positively charged amino acids, in mediating both specific and nonspecific protein-RNA interactions.