Active-Site Monovalent Cations Revealed in a 1.55-Å-Resolution Hammerhead Ribozyme Structure

We have obtained a 1.55-Å crystal structure of a hammerhead ribozyme derived from Schistosoma mansoni under conditions that permit detailed observations of Na⁺ ion binding in the ribozyme's active site. At least two such Na⁺ ions are observed. The first Na⁺ ion binds to the N7 of G10.1 and the adjacent A9 phosphate in a manner identical with that previously observed for divalent cations. A second Na⁺ ion binds to the Hoogsteen face of G12, the general base in the hammerhead cleavage reaction, thereby potentially dissipating the negative charge of the catalytically active enolate form of the nucleotide base. A potential but more ambiguous third site bridges the A9 and scissile phosphates in a manner consistent with that of previous predictions. Hammerhead ribozymes have been observed to be active in the presence of high concentrations of monovalent cations, including Na⁺, but the mechanism by which monovalent cations substitute for divalent cations in hammerhead catalysis remains unclear. Our results enable us to suggest that Na⁺ directly and specifically substitutes for divalent cations in the hammerhead active site. The detailed geometry of the pre-catalytic active-site complex is also revealed with a new level of precision, thanks to the quality of the electron density maps obtained from what is currently the highest-resolution ribozyme structure in the Protein Data Bank.     

Travel depth, a new shape descriptor for macromolecules: application to ligand binding

Depth is a term frequently applied to the shape and surface of macromolecules, describing for example the grooves in DNA, the shape of an enzyme active site, or the binding site for a small molecule in a protein. Yet depth is a difficult property to define rigorously in a macromolecule, and few computational tools exist to quantify this notion, to visualize it, or analyze the results. We present our notion of travel depth, simply put the physical distance a solvent molecule would have to travel from a surface point to a suitably defined reference surface. To define the reference surface, we use the limiting form of the molecular surface with increasing probe size: the convex hull. We then present a fast, robust approximation algorithm to compute travel depth to every surface point. The travel depth is useful because it works for pockets of any size and complexity. It also works for two interesting special cases. First, it works on the grooves in DNA, which are unbounded in one direction. Second, it works on the case of tunnels, that is pockets that have no "bottom", but go through the entire macromolecule. Our algorithm makes it straightforward to quantify discussions of depth when analyzing structures. High-throughput analysis of macromolecule depth is also enabled by our algorithm. This is demonstrated by analyzing a database of protein-small molecule binding pockets, and the distribution of bound magnesium ions in RNA structures. These analyses show significant, but subtle effects of depth on ligand binding localization and strength.     

Disordered domains and high surface charge confer hubs with the ability to interact with multiple proteins in interaction networks

We investigate the structural properties of hubs that enable them to interact with several partners in protein-protein interaction networks. We find that hubs have more observed and predicted disordered residues with fewer loops/coils, and more charged residues on the surface as compared to non-hubs. Smaller hubs have fewer disordered residues and more charged residues on the surface than larger hubs. We conclude that the global flexibility provided by disordered domains, and high surface charge are complementary factors that play a significant role in the binding ability of hubs.     

Computational protein design and large-scale assessment by I-TASSER structure assembly simulations

Protein design aims at designing new protein molecules of desired structure and functionality. One of the major obstacles to large-scale protein design are the extensive time and manpower requirements for experimental validation of designed sequences. Recent advances in protein structure prediction have provided potentials for an automated assessment of the designed sequences via folding simulations. We present a new protocol for protein design and validation. The sequence space is initially searched by Monte Carlo sampling guided by a public atomic potential, with candidate sequences selected by the clustering of sequence decoys. The designed sequences are then assessed by I-TASSER folding simulations, which generate full-length atomic structural models by the iterative assembly of threading fragments. The protocol is tested on 52 nonhomologous single-domain proteins, with an average sequence identity of 24% between the designed sequences and the native sequences. Despite this low sequence identity, three-dimensional models predicted for the first designed sequence have an RMSD of < 2 Å to the target structure in 62% of cases. This percentage increases to 77% if we consider the three-dimensional models from the top 10 designed sequences. Such a striking consistency between the target structure and the structural prediction from nonhomologous sequences, despite the fact that the design and folding algorithms adopt completely different force fields, indicates that the design algorithm captures the features essential to the global fold of the target. On average, the designed sequences have a free energy that is 0.39 kcal/(mol residue) lower than in the native sequences, potentially affording a greater stability to synthesized target folds.     

A Structural Portrait of the PDZ Domain Family

PDZ (PSD-95/Discs-large/ZO1) domains are interaction modules that typically bind to specific C-terminal sequences of partner proteins and assemble signaling complexes in multicellular organisms. We have analyzed the existing database of PDZ domain structures in the context of a specificity tree based on binding specificities defined by peptide-phage binding selections. We have identified 16 structures of PDZ domains in complex with high-affinity ligands and have elucidated four additional structures to assemble a structural database that covers most of the branches of the PDZ specificity tree. A detailed comparison of the structures reveals features that are responsible for the diverse specificities across the PDZ domain family. Specificity differences can be explained by differences in PDZ residues that are in contact with the peptide ligands, but these contacts involve both side-chain and main-chain interactions. Most PDZ domains bind peptides in a canonical conformation in which the ligand main chain adopts an extended β-strand conformation by interacting in an antiparallel fashion with a PDZ β-strand. However, a subset of PDZ domains bind peptides with a bent main-chain conformation and the specificities of these non-canonical domains could not be explained based on canonical structures. Our analysis provides a structural portrait of the PDZ domain family, which serves as a guide in understanding the structural basis for the diverse specificities across the family.     

Four spatial points that define enzyme families

The catalytic properties of enzymes, containing the Asp-His-Ser triads are deeply investigated for a long time. Serine endopeptidases, cutinases, acetylcholinesterases, cellulases, among other enzymes, contain these triads. We found that solely the geometric properties of just four points in the spatial structure of these enzymes are characteristic to their family (Fig. 3).     

Signal transduction network motifs and biological memory

Memory is a ubiquitous phenomenon in biological systems, yet the mechanisms responsible for memory, and how to manipulate it at the subcellular level, remain poorly understood. Subjected to transient stimuli, biological systems can exhibit short early responses and/or prolonged (or permanent) late responses. Experimental evidence suggests that early responses (short-term memory) involve post-translational modification of existing proteins and/or their intracellular relocalization, whereas late responses (long-term memory) depend on new protein synthesis. Although this provides an intuitive explanation at the basic molecular level, it does little to clarify the important dynamics that actually maintain memory at the systems level. In this study, we use mathematical modeling to study dynamical mechanisms of biological memory. We first examined the response of four fundamental motifs (positive/negative feedforward and feedback) to external stimuli. Because motifs do not exist in isolation within the cell, we then combined these motifs to form signaling modules to understand how they confer biological memory. These motifs, and different combinations thereof, displayed distinct behavior in response to external stimuli. The principles described in this study have important implications for experimental approaches to identify the mechanisms for biological memory and for the development of therapeutic strategies to modulate signaling network responses in the setting of human disease.     

Enhanced validation of small-molecule ligands and carbohydrates in the Protein Data Bank

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CARON – Average RMSD of NMR structure ensembles

The NMR protein structures are often deposited in the Protein Data Bank as ensembles of models that agree with the experimental restraints.Information about stereochemical variability and the molecular flexibility can be obtained by systematic comparison of all models. Here wedescribe CARON, a software that allows the computation of the root-mean-square-distances between equivalent atoms and residues in all modelsand introduces these values into the occupancy and the B-factor fields of PDB-formatted files. This tool allows the user to both get a quantitativeestimation of the conformational homogeneity of the models and to exploit this information in common computer graphics programs.     

Nucleotide correlation based measure for identifying origin of replication in genomic sequences

Computational prediction of the origin of replication is a challenging problem and of immense interest to biologists. Several methods have been proposed for identifying the replicon site for various classes of organisms. However, these methods have limited applicability since the replication mechanism is different in different organisms. We propose a correlation measure and show that it is correctly able to predict the origin of replication in most of the bacterial genomes. When applied to Methanocaldococcus jannaschii, Plasmodium falciparum apicoplast and Nicotiana tabacum plastid, this correlation based method is able to correctly predict the origin of replication whereas the generally used GC skew measure fails. Thus, this correlation based measure is a novel and promising tool for predicting the origin of replication in a wide class of organisms. This could have important implications in not only gaining a deeper understanding of the replication machinery in higher organisms, but also for drug discovery.     

Recent Advances in Computational Methods for Nuclear Magnetic Resonance Data Processing

Although three-dimensional protein structure determination using nuclear magnetic resonance (NMR) spectroscopy is a computationally costly and tedious process that would benefit from advanced computational techniques, it has not garnered much research attention from specialists in bioinformatics and computational biology. In this paper, we review recent advances in computational methods for NMR protein structure determination. We summarize the advantages of and bottlenecks in the existing methods and outline some open problems in the field. We also discuss current trends in NMR technology development and suggest directions for research on future computational methods for NMR.     

MACBenAbim: A Multi-platform Mobile Application for searching keyterms in Computational Biology and Bioinformatics

Computational biology and bioinformatics are gradually gaining grounds in Africa and other developing nations of the world. However, in these countries, some of the challenges of computational biology and bioinformatics education are inadequate infrastructures, and lack of readily-available complementary and motivational tools to support learning as well as research. This has lowered the morale of many promising undergraduates, postgraduates and researchers from aspiring to undertake future study in these fields. In this paper, we developed and described MACBenAbim (Multi-platform Mobile Application for Computational Biology and Bioinformatics), a flexible user-friendly tool to search for, define and describe the meanings of keyterms in computational biology and bioinformatics, thus expanding the frontiers of knowledge of the users. This tool also has the capability of achieving visualization of results on a mobile multi-platform context.

Availability

MACBenAbim is available from the authors for non-commercial purposes.     

Certain heptapeptide and large sequences representing an entire helix, strand or coil conformation in proteins are associated as chameleon sequences

Helices, strands and coils in proteins of known three-dimensional structure, corresponding to heptapeptide and large sequences (‘probe’ peptides), were scanned against peptide sequences of variable length, comprising seven or more residues that correspond to a different conformation (‘target’ peptides) in protein crystal structures available from the Protein Data Bank (PDB). Where the ‘probe’ and ‘target’ peptide sequences exactly match, they correspond to ‘chameleon’ sequences in protein structures. We observed ∼548 heptapeptide and large chameleon sequences that included peptides in the coil conformation from 53,794 PDB files that were analyzed. However, after excluding several chameleon peptides based on the quality of protein structure data, redundancy and peptides associated with cloning artifacts, such as, histidine-tags, we observed only ten chameleon peptides in structurally different proteins and the maximum length comprised seven amino acid residues. Our analysis suggests that the quality of protein structure data is important for identifying possibly, the ‘true chameleons’ in PDB. Majority of the chameleon sequences correspond to an entire strand in one protein that is observed as part of helix sequence in another protein. The heptapeptide chameleons are characterized with a high propensity of alanine, leucine and valine amino acid residues. The total hydropathy values range between −11.2 and 22.9, the difference in solvent accessibility between 2.0 Å² and 373 Å² units and the difference in total number of residue neighbor contacts between 0 and 7 residues. Our work identifies for the first time heptapeptide and large sequences that correspond to a single complete helix, strand or coil, which adopt entirely different secondary structures in another protein.     

The role of RNA sequence and structure in RNA--protein interactions

We investigate the sequence and structural properties of RNA-protein interaction sites in 211 RNA-protein chain pairs, the largest set of RNA-protein complexes analyzed to date. Statistical analysis confirms and extends earlier analyses made on smaller data sets. There are 24.6% of hydrogen bonds between RNA and protein that are nucleobase specific, indicating the importance of both nucleobase-specific and -nonspecific interactions. While there is no significant difference between RNA base frequencies in protein-binding and non-binding regions, distinct preferences for RNA bases, RNA structural states, protein residues, and protein secondary structure emerge when nucleobase-specific and -nonspecific interactions are considered separately. Guanine nucleobase and unpaired RNA structural states are significantly preferred in nucleobase-specific interactions; however, nonspecific interactions disfavor guanine, while still favoring unpaired RNA structural states. The opposite preferences of nucleobase-specific and -nonspecific interactions for guanine may explain discrepancies between earlier studies with regard to base preferences in RNA-protein interaction regions. Preferences for amino acid residues differ significantly between nucleobase-specific and -nonspecific interactions, with nonspecific interactions showing the expected bias towards positively charged residues. Irregular protein structures are strongly favored in interactions with the protein backbone, whereas there is little preference for specific protein secondary structure in either nucleobase-specific interaction or -nonspecific interaction. Overall, this study shows strong preferences for both RNA bases and RNA structural states in protein-RNA interactions, indicating their mutual importance in protein recognition.     

Mapping of protein-protein interaction sites by the 'absence of interference' approach

Protein-protein interactions are critical to most biological processes, and locating protein-protein interfaces on protein structures is an important task in molecular biology. We developed a new experimental strategy called the ‘absence of interference’ approach to determine surface residues involved in protein-protein interaction of established yeast two-hybrid pairs of interacting proteins. One of the proteins is subjected to high-level randomization by error-prone PCR. The resulting library is selected by yeast two-hybrid system for interacting clones that are isolated and sequenced. The interaction region can be identified by an absence or depletion of mutations. For data analysis and presentation, we developed a Web interface that analyzes the mutational spectrum and displays the mutational frequency on the surface of the structure (or a structural model) of the randomized protein†. Additionally, this interface might be of use for the display of mutational distributions determined by other types of random mutagenesis experiments. We applied the approach to map the interface of the catalytic domain of the DNA methyltransferase Dnmt3a with its regulatory factor Dnmt3L. Dnmt3a was randomized with high mutational load. A total of 76 interacting clones were isolated and sequenced, and 648 mutations were identified. The mutational pattern allowed to identify a unique interaction region on the surface of Dnmt3a, which comprises about 500-600 Å². The results were confirmed by site-directed mutagenesis and structural analysis. The absence-of-interference approach will allow high-throughput mapping of protein interaction sites suitable for functional studies and protein docking.     

Structural Analysis of Peroxide-Soaked MnSOD Crystals Reveals Side-On Binding of Peroxide to Active-Site Manganese

The superoxide dismutase (SOD) enzymes are important antioxidant agents that protect cells from reactive oxygen species. The SOD family is responsible for catalyzing the disproportionation of superoxide radical to oxygen and hydrogen peroxide. Manganese- and iron-containing SOD exhibit product inhibition whereas Cu/ZnSOD does not. Here, we report the crystal structure of Escherichia coli MnSOD with hydrogen peroxide cryotrapped in the active site. Crystallographic refinement to 1.55 Å and close inspection revealed electron density for hydrogen peroxide in three of the four active sites in the asymmetric unit. The hydrogen peroxide molecules are in the position opposite His26 that is normally assumed by water in the trigonal bipyramidal resting state of the enzyme. Hydrogen peroxide is present in active sites B, C, and D and is side-on coordinated to the active-site manganese. In chains B and D, the peroxide is oriented in the plane formed by manganese and ligands Asp167 and His26. In chain C, the peroxide is bound, making a 70° angle to the plane. Comparison of the peroxide-bound active site with the hydroxide-bound octahedral form shows a shifting of residue Tyr34 towards the active site when peroxide is bound. Comparison with peroxide-soaked Cu/ZnSOD indicates end-on binding of peroxide when the SOD does not exhibit inhibition by peroxide and side-on binding of peroxide in the product-inhibited state of MnSOD.