NLDB: a database for 3D protein–ligand interactions in enzymatic reactions

NLDB (Natural Ligand DataBase; URL: http://nldb.hgc.jp) is a database of automatically collected and predicted 3D protein–ligand interactions for the enzymatic reactions of metabolic pathways registered in KEGG. Structural information about these reactions is important for studying the molecular functions of enzymes, however a large number of the 3D interactions are still unknown. Therefore, in order to complement such missing information, we predicted protein–ligand complex structures, and constructed a database of the 3D interactions in reactions. NLDB provides three different types of data resources; the natural complexes are experimentally determined protein–ligand complex structures in PDB, the analog complexes are predicted based on known protein structures in a complex with a similar ligand, and the ab initio complexes are predicted by docking simulations. In addition, NLDB shows the known polymorphisms found in human genome on protein structures. The database has a flexible search function based on various types of keywords, and an enrichment analysis function based on a set of KEGG compound IDs. NLDB will be a valuable resource for experimental biologists studying protein–ligand interactions in specific reactions, and for theoretical researchers wishing to undertake more precise simulations of interactions.     

Advances in the study of protein–DNA interaction

Protein-DNA interaction plays an important role in many biological processes. The classical methods and the novel technologies advanced have been developed for the interaction of protein-DNA. Recent developments of these methods and research achievements have been reviewed in this paper.     

212 Shifting interfaces: changes in protein–protein and protein–DNA interfaces probed via molecular dynamics

Over the past decade, there has been a growing interest in studying the binding of DNA to the MutSalpha protein complex. This heterodimeric protein complex, the Msh2/Msh6 complex in humans, is the initial complex that binds mismatched DNA and other DNA defects that occur during replication. This complex has also been shown to bind at least some types of damaged DNA, such as the cross-linked adducts due to the chemotherapeutics cisplatin and carboplatin, or the incorporation of the chemotherapeutic, FdU. As a result of this interest, multiple studies have contrasted the interactions of MutSalpha with its normal mismatched substrate and with the interactions of MutsSalpha with the DNA damaged by chemotherapeutic cisplatin. To complement these studies, we examine the interaction between MutSalpha and the DNA damaged by carboplatin via all-atom molecular dynamics simulations. These simulations provide evidence for subtle changes in the protein–DNA and protein–protein interfaces. The interfaces shifts found are broadly similar to those found in binding with adduct from cis-platin, but have distinct differences. These subtle differences may play a role in the way of the different damages and mismatched DNA are signaled by MutSalpha, and suggest a signaling mechanism for DNA damage that chiefly involves shifts in protein–protein interactions as opposed to changes in protein conformation.     

An information-theoretic classification of amino acids for the assessment of interfaces in protein–protein docking

Docking represents a versatile and powerful method to predict the geometry of protein–protein complexes. However, despite significant methodical advances, the identification of good docking solutions among a large number of false solutions still remains a difficult task. We have previously demonstrated that the formalism of mutual information (MI) from information theory can be adapted to protein docking, and we have now extended this approach to enhance its robustness and applicability. A large dataset consisting of 22,934 docking decoys derived from 203 different protein–protein complexes was used for an MI-based optimization of reduced amino acid alphabets representing the protein–protein interfaces. This optimization relied on a clustering analysis that allows one to estimate the mutual information of whole amino acid alphabets by considering all structural features simultaneously, rather than by treating them individually. This clustering approach is fast and can be applied in a similar fashion to the generation of reduced alphabets for other biological problems like fold recognition, sequence data mining, or secondary structure prediction. The reduced alphabets derived from the present work were converted into a scoring function for the evaluation of docking solutions, which is available for public use via the web service score-MI: http://score-MI.biochem.uni-erlangen.de     

A simple method for monitoring protein–DNA interactions

A simple, efficient and cheap method is reported for monitoring interactions between single stranded desoxyribonucleic acids and proteins, using fluorescence spectroscopy and complexes of 5′-dye–DNA conjugates with bovine serum albumin as probes. In the presence of a single stranded DNA-binding protein the complexes with bovine serum albumin are disrupted, which results in a reduction of fluorescence intensity.     

Role for protein–protein interaction databases in human genetics

Proteomics and the study of protein–protein interactions are becoming increasingly important in our effort to understand human diseases on a system-wide level. Thanks to the development and curation of protein-interaction databases, up-to-date information on these interaction networks is accessible and publicly available to the scientific community. As our knowledge of protein–protein interactions increases, it is important to give thought to the different ways that these resources can impact biomedical research. In this article, we highlight the importance of protein–protein interactions in human genetics and genetic epidemiology. Since protein–protein interactions demonstrate one of the strongest functional relationships between genes, combining genomic data with available proteomic data may provide us with a more in-depth understanding of common human diseases. In this review, we will discuss some of the fundamentals of protein interactions, the databases that are publicly available and how information from these databases can be used to facilitate genome-wide genetic studies.     

High-throughput single-molecule studies of protein–DNA interactions

Fluorescence and force-based single-molecule studies of protein–nucleic acid interactions continue to shed critical insights into many aspects of DNA and RNA processing. As single-molecule assays are inherently low-throughput, obtaining statistically relevant datasets remains a major challenge. Additionally, most fluorescence-based single-molecule particle-tracking assays are limited to observing fluorescent proteins that are in the low-nanomolar range, as spurious background signals predominate at higher fluorophore concentrations. These technical limitations have traditionally limited the types of questions that could be addressed via single-molecule methods. In this review, we describe new approaches for high-throughput and high-concentration single-molecule biochemical studies. We conclude with a discussion of outstanding challenges for the single-molecule biologist and how these challenges can be tackled to further approach the biochemical complexity of the cell.     

Composition of Woody Species in a Dynamicforest–woodland–savannah Mosaic in Uganda: Implications for Conservation and Management

Forest–woodland–savannah mosaics are a common feature in the East African landscape. For the conservation of the woody species that occur in such landscapes, the species patterns and the factors that maintain it need to be understood. We studied the woody species distribution in a forest–woodland–savannah mosaic in Budongo Forest Reserve, Uganda. The existing vegetation gradients were analyzed using data from a total of 591 plots of 400 or 500 m² each. Remotely sensed data was used to explore current vegetation cover and the gradients there in for the whole area. A clear species gradient exists in the study area ranging from forest, where there is least disturbance, to wooded grassland, where frequent fire disturbance occurs. Most species are not limited to a specific part of the gradient although many show a maximum abundance at some point along the gradient. Fire and accessibility to the protected area were closely related to variation in species composition along the ordination axis with species like Cynometra alexandri and Uvariopsis congensis occurring at one end of the gradient and Combretum guenzi and Lonchocarpus laxiflorus at the other. The vegetation cover classes identified in the area differed in diversity, density and, especially, basal area. All vegetation cover classes, except open woodland, had indicator species. Diospyros abyssinica, Uvariopsis congensis, Holoptelea grandis and all Celtis species were the indicator species for the forest class, Terminalia velutina and Albizia grandbracteata for closed woodland, Grewia mollis and Combretum mole for very open woodland and Lonchocarpus laxiflorus, Grewia bicolor and Combretum guenzi for the wooded grassland class. Eleven of the species occurred in all cover classes and most of the species that occurred in more than one vegetation cover class showed peak abundance in a specific cover class. Species composition in the study area changes gradually from forest to savannah. Along the gradient, the cover classes are distinguishable in terms of species composition and vegetation structure. These classes are, however, interrelated in species composition. For conservation of the full range of the species within this East African landscape, the mosaic has to be managed as an integrated whole. Burning should be varied over the area with the forest not being burnt at all and the wooded grassland burnt regularly. The different vegetation types that occur between these two extremes should be maintained using a varied fire regime.     

Evolution of Mhc–DRB Introns: Implications for the Origin of Primates

Introns are generally believed to evolve too rapidly and too erratically to be of much use in phylogenetic reconstructions. Few phylogenetically informative intron sequences are available, however, to ascertain the validity of this supposition. In the present study the supposition was tested on the example of the mammalian class II major histocompatibility complex (Mhc) genes of the DRB family. Since the Mhc genes evolve under balancing selection and are believed to recombine or rearrange frequently, the evolution of their introns could be expected to be particularly rapid and subject to scrambling. Sequences of intron 4 and 5 DRB genes were obtained from polymerase chain reaction-amplified fragments of genomic DNA from representatives of six eutherian orders—Primates, Scandentia, Chiroptera, Dermoptera, Lagomorpha, and Insectivora. Although short stretches of the introns have indeed proved to be unalignable, the bulk of the intron sequences from all six orders, spanning >85 million years (my) of evolution, could be aligned and used in a study of the tempo and mode of intron evolution. The analysis has revealed the Mhc introns to evolve at a rate similar to that of other genes and of synonymous sites of non-Mhc genes. No evidence of homogenization or large-scale scrambling of the intron sequences could be found. The Mhc introns apparently evolve largely by point mutations and insertions/deletions. The phylogenetic signals contained in the intron sequences could be used to identify Scandentia as the sister group of Primates, to support the existence of the Archonta superorder, and to confirm the monophyly of the Chiroptera. Received: 26 October 1998 / Accepted: 21 December 1998     

Data mining for protein–protein interactions in invertebrate model organisms

Well-annotated genome databases are available for many invertebrate species, notably the fruitfly, Drosophila melanogaster, and the nematode, Caenorhabditis elegans. An adequate interpretation of this information at the biological level requires the exploration of the interactions between the gene products. Knowledge of protein interactions and the components of cell signalling pathways in the fly and worm are particularly valuable as hypotheses can be rapidly tested using the powerful genetic toolkits available. Invertebrates offer additional experimental advantages when attempting to characterise protein–protein interactions (PPIs). Their relatively small genome size compared to mammals helps to reduce missed interactions due to redundancy, and their function can be addressed using forward (mutants) and reverse (RNA interference) genetics. However, the researcher looking for evidence of PPIs for a protein of interest is faced with the challenge of extracting interaction data from sources that are highly varied, such as the results of microarray experiments in the unstructured text of research papers. This challenge is greatly reduced by a range of public databases of curated information, as well as publicly available, enhanced search engines, which can provide either direct experimental evidence for a PPI, or valuable clues for generating new hypotheses.     

Implications of Tourist–Macaque Interactions for Disease Transmission

During wildlife tourism, proximity or actual contact between people and animals may lead to a significant risk of anthropozoonotic disease transmission. In this paper, we use social network analysis, disease simulation modelling and data on animal health and behaviour to investigate such risks at a site in Morocco, where tourists come to see wild Barbary macaques (Macaca sylvanus). Measures of individual macaques’ network centrality—an index of the strength and distribution of their social relationships and thus potentially their ability to spread disease—did not show clear and consistent relationships with their time spent in close proximity to, or rate of interacting with, tourists. Disease simulation modelling indicated that while higher-ranked animals had a significantly greater ability to spread disease within the group, in absolute terms there was little difference in the size of outbreaks that different individuals were predicted to cause. We observed a high rate of physical contact and close proximity between humans and macaques, including during three periods when the macaques were coughing and sneezing heavily, highlighting the potential risk of disease transmission. We recommend that general disease prevention strategies, such as those aimed at reducing opportunities for contact between tourists and macaques, should be adopted.     

Hot spot-based design of small-molecule inhibitors for protein–protein interactions

Protein–protein interactions (PPIs) are important targets for the development of chemical probes and therapeutic agents. From the initial discovery of the existence of hot spots at PPI interfaces, it has been proposed that hot spots might provide the key for developing small-molecule PPI inhibitors. However, there has been no review on the ways in which the knowledge of hot spots can be used to achieve inhibitor design, nor critical examination of successful examples. This Digest discusses the characteristics of hot spots and the identification of druggable hot spot pockets. An analysis of four examples of hot spot-based design reveals the importance of this strategy in discovering potent and selective PPI inhibitors. A general procedure for hot spot-based design of PPI inhibitors is outlined.