Predicting common foldings of homologous RNAs.

A new approach is proposed for determining common RNA secondary structures within a set of homologous RNAs. The approach is a combination of phylogenetic and thermodynamic methods which is based on the prediction of optimal and suboptimal secondary structures, topological similarity searches and phylogenetic comparative analysis. The optimal and suboptimal RNA secondary structures are predicted by energy minimization. Structural comparison of the predicted RNA secondary structures is used to find conserved structures that are topologically similar in all these homologous RNAs. The validity of the conserved structural elements found is then checked by phylogenetic comparison of the sequences. This procedure is used to predict common structures of ribonuclease P (RNAase P) RNAs.     

Structural differences of matrix metalloproteinases. Homology modeling and energy minimization of enzyme-substrate complexes

Matrix metalloproteinases are extracellular enzymes taking part in the remodeling of extracellular matrix. The structures of the catalytic domain of MMP1, MMP3, MMP7 and MMP8 are known, but structures of enzymes belonging to this family still remain to be determined. A general approach to the homology modeling of matrix metalloproteinases, exemplified by the modeling of MMP2, MMP9, MMP12 and MMP14 is described. The models were refined using an energy minimization procedure developed for matrix metalloproteinases. This procedure includes incorporation of parameters for zinc and calcium ions in the AMBER 4.1 force field, applying a non-bonded approach and a full ion charge representation. Energy minimization of the apoenzymes yielded structures with distorted active sites, while reliable three-dimensional structures of the enzymes containing a substrate in active site were obtained. The structural differences between the eight enzyme-substrate complexes were studied with particular emphasis on the active site, and possible sites for obtaining selectivity among the MMP's are discussed. Differences in the P1' pocket are well-documented and have been extensively exploited in inhibitor design. The present work indicates that selectivity could be further improved by considering the P2 pocket as well.     

Modelling by Homology of the HSV1-TK Sequence Embedded Structural Alignment

Abstract

Modelling by homology is an approach to the rational design of new drugs based on the construction of ligand protein interaction complexes. Because in most cases the 3D-structure of the target protein is not known from biophysical data, this approach yields a theoretical procedure which establishes at least parts of the protein by comparison with isofunctional proteins, assuming that much of the structural information is embedded in the amino acid sequence. This approach should be of considerable importance for proteins with divergent primary structures but with a high degree of isofunctionality, the latter demanding a similar active site folding pattern.

This study is a pattern recognition approach based on additive secondary structure prediction and surface probabilities from residue variabilities. The comparison of the additive properties yields a sequence alignment of the viral thymidine kinases with the adenylate kinases having a closely related functionality. X-ray structures of adenylate kinases can then be used as templates to derive a 3D-structure prediction of the thymidine kinase active site.     

Bi-Directional X-Ray Phase-Contrast Mammography

Phase-contrast x-ray imaging is a promising improvement of conventional absorption-based mammography for early tumor detection. This potential has been demonstrated recently, utilizing structured gratings to obtain differential phase and dark-field scattering images. However, the inherently anisotropic imaging sensitivity of the proposed mono-directional approach yields only insufficient diagnostic information, and has low diagnostic sensitivity to highly oriented structures. To overcome these limitations, we present a two-directional x-ray phase-contrast mammography approach and demonstrate its advantages by applying it to a freshly dissected, cancerous mastectomy breast specimen. We illustrate that the two-directional scanning procedure overcomes the insufficient diagnostic value of a single scan, and reliably detects tumor structures, independently from their orientation within the breast. Our results indicate the indispensable diagnostic necessity and benefit of a multi-directional approach for x-ray phase-contrast mammography.     

Multistate Mark–Recapture Model Selection Using Score Tests

Summary Although multistate mark–recapture models are recognized as important, they lack a simple model‐selection procedure. This article proposes and evaluates a step‐up approach to select appropriate models for multistate mark–recapture data using score tests. Only models supported by the data require fitting, so that over‐complicated model structures with too many parameters do not need to be considered. Typically only a small number of models are fitted, and the procedure is also able to identify parameter‐redundant and near‐redundant models. The good performance of the technique is demonstrated using simulation, and the approach is illustrated on a three‐region Canada goose data set. In this case, it identifies a new model that is much simpler than the best model previously considered for this application.     

Guiding protein docking with geometric and evolutionary information

Structural modeling of molecular assemblies promises to improve our understanding of molecular interactions and biological function. Even when focusing on modeling structures of protein dimers from knowledge of monomeric native structure, docking two rigid structures onto one another entails exploring a large configurational space. This paper presents a novel approach for docking protein molecules and elucidating native-like configurations of protein dimers. The approach makes use of geometric hashing to focus the docking of monomeric units on geometrically complementary regions through rigid-body transformations. This geometry-based approach improves the feasibility of searching the combined configurational space. The search space is narrowed even further by focusing the sought rigid-body transformations around molecular surface regions composed of amino acids with high evolutionary conservation. This condition is based on recent findings, where analysis of protein assemblies reveals that many functional interfaces are significantly conserved throughout evolution. Different search procedures are employed in this work to search the resulting narrowed configurational space. A proof-of-concept energy-guided probabilistic search procedure is also presented. Results are shown on a broad list of 18 protein dimers and additionally compared with data reported by other labs. Our analysis shows that focusing the search around evolutionary-conserved interfaces results in lower lRMSDs.     

A new method for building protein conformations from sequence alignments with homologues of known structure

We describe a largely automatic procedure for building protein structures from sequence alignments with homologues of known structure. This procedure uses simple rules by which multiple sequence alignments can be translated into distance and chirality constraints, which are then used as input for distance geometry calculations. By this means one obtains an ensemble of conformations for the unknown structure that are compatible with the rules employed, and the differences among these conformations provide an indication of the reliability of the structure prediction. The overall approach is demonstrated here by applying it to several Kazal-type trypsin inhibitors, for which experimentally determined structures are available. On the basis of our experience with these test problems, we have further predicted the conformation of the human pancreatic secretory trypsin inhibitor, for which no experimentally determined structure is presently available.     

Molecular anatomy: Phyletic relationships derived from three-dimensional structures of proteins

Summary A distance measure that reflects the dissimilarity among structures has been developed on the basis of the three-dimensional structures of similar proteins, this being totally independent of sequence in the sense that only the relative spatial positions of mainchain alpha-carbon atoms need be known. This procedure leads to phyletic relationships that are in general correlated with the sequence phylogenies based on residue type. Such relationships among known protein three-dimensional structures are also a useful aid to their classification and selection in knowledge-based modeling using homologous structures. We have applied this approach to six homologous sets of proteins: immunoglobulin fragments, globins, cytochromesc, serine proteinases, eye-lens gamma crystallins, and dinucleotide-binding domains.     

An efficient Monte Carlo approach to assessing statistical significance in genomic studies

MOTIVATION: Multiple hypothesis testing is a common problem in genome research, particularly in microarray experiments and genomewide association studies. Failure to account for the effects of multiple comparisons would result in an abundance of false positive results. The Bonferroni correction and Holm's step-down procedure are overly conservative, whereas the permutation test is time-consuming and is restricted to simple problems. RESULTS: We developed an efficient Monte Carlo approach to approximating the joint distribution of the test statistics along the genome. We then used the Monte Carlo distribution to evaluate the commonly used criteria for error control, such as familywise error rates and positive false discovery rates. This approach is applicable to any data structures and test statistics. Applications to simulated and real data demonstrate that the proposed approach provides accurate error control, and can be substantially more powerful than the Bonferroni and Holm methods, especially when the test statistics are highly correlated.     

Protein-protein docking by simulating the process of association subject to biochemical constraints

We present a computational procedure for modeling protein-protein association and predicting the structures of protein-protein complexes. The initial sampling stage is based on an efficient Brownian dynamics algorithm that mimics the physical process of diffusional association. Relevant biochemical data can be directly incorporated as distance constraints at this stage. The docked configurations are then grouped with a hierarchical clustering algorithm into ensembles that represent potential protein-protein encounter complexes. Flexible refinement of selected representative structures is done by molecular dynamics simulation. The protein-protein docking procedure was thoroughly tested on 10 structurally and functionally diverse protein-protein complexes. Starting from X-ray crystal structures of the unbound proteins, in 9 out of 10 cases it yields structures of protein-protein complexes close to those determined experimentally with the percentage of correct contacts >30% and interface backbone RMSD <4 A. Detailed examination of all the docking cases gives insights into important determinants of the performance of the computational approach in modeling protein-protein association and predicting of protein-protein complex structures.     

Protein docking using surface matching and supervised machine learning

Computational prediction of protein complex structures through docking offers a means to gain a mechanistic understanding of protein interactions that mediate biological processes. This is particularly important as the number of experimentally determined structures of isolated proteins exceeds the number of structures of complexes. A comprehensive docking procedure is described in which efficient sampling of conformations is achieved by matching surface normal vectors, fast filtering for shape complementarity, clustering by RMSD, and scoring the docked conformations using a supervised machine learning approach. Contacting residue pair frequencies, residue propensities, evolutionary conservation, and shape complementarity score for each docking conformation are used as input data to a Random Forest classifier. The performance of the Random Forest approach for selecting correctly docked conformations was assessed by cross-validation using a nonredundant benchmark set of X-ray structures for 93 heterodimer and 733 homodimer complexes. The single highest rank docking solution was the correct (near-native) structure for slightly more than one third of the complexes. Furthermore, the fraction of highly ranked correct structures was significantly higher than the overall fraction of correct structures, for almost all complexes. A detailed analysis of the difficult to predict complexes revealed that the majority of the homodimer cases were explained by incorrect oligomeric state annotation. Evolutionary conservation and shape complementarity score as well as both underrepresented and overrepresented residue types and residue pairs were found to make the largest contributions to the overall prediction accuracy. Finally, the method was also applied to docking unbound subunit structures from a previously published benchmark set.     

All-Atom Monte Carlo Approach to Protein-Peptide Binding

We develop a procedure for exploring the free energy landscape of protein-peptide binding at atomic detail and apply it to PDZ domain-peptide interactions. The procedure involves soft constraints on receptor proteins providing limited chain flexibility, including backbone motions. Peptide chains are left fully flexible and kept in spatial proximity of the protein through periodic boundary conditions. By extensive Monte Carlo simulations, full representative conformational ensembles at temperatures where bound and unbound states coexist are obtained. To make this approach computationally feasible, we develop an effective all-atom energy function centering on hydrophobicity, hydrogen bonding, and electrostatic interactions. Our initial focus is a set of 11 PDZ domain-peptide pairs with experimentally determined complex structures. Minimum-energy conformations are found to be highly similar to the respective native structures in eight of the cases (all-atom peptide RMSDs < 6 Å). Having achieved that, we turn to a more complete characterization of the bound peptide state through a clustering scheme applied on the full ensembles of peptide structures. We find a significant diversity among bound peptide conformations for several PDZ domains, in particular involving the N terminal side of the peptide chains. Our computational model is then tested further on a set of nine PDZ domain-peptide pairs where the peptides are not originally present in the experimentally determined structures. We find a similar success rate in terms of the nativeness of minimum-energy conformations. Finally, we investigate the ability of our approach to capture variations in binding affinities for different peptide sequences. This is done in particular for a set of related sequences binding to the third PDZ domain of PSD-95 with encouraging results.     

Analysis of the structure and composition of individual lipoplex particles by flow fluorometry

A flow fluorometric approach to study cationic lipoid-DNA complexes is presented. The approach uses standard flow cytometry equipment and common fluorescent dyes (BODIPY and ethidium homodimer-2) to detect both lipoid and DNA content in individual particles. In addition, a procedure that allows determination of whether or not liposomes remain intact is described. The procedure is based on monitoring the retention of a polar tracer that has been preloaded into its aqueous compartment. Sample preparation, instrument setup, data analysis, and methodological limitations are described. Applications of the procedure to cationic lipoid-DNA complexes are described, and illustrations are given for the determination of how the lipoid content, composition, and structure of individual lipoplexes in a population evolve over time, starting at about 1 min after DNA and vesicles are mixed. Analogous procedures can be applied to other heterogeneous particles and supramolecular structures.     

A new approach for assigning bone material properties from CT images into finite element models

Generation of subject-specific finite element (FE) models from computed tomography (CT) datasets is of significance for application of the FE analysis to bone structures. A great challenge that remains is the automatic assignment of bone material properties from CT Hounsfield Units into finite element models. This paper proposes a new assignment approach, in which material properties are directly assigned to each integration point. Instead of modifying the dataset of FE models, the proposed approach divides the assignment procedure into two steps: generating the data file of the image intensity of a bone in a MATLAB program and reading the file into ABAQUS via user subroutines. Its accuracy has been validated by assigning the density of a bone phantom into a FE model. The proposed approach has been applied to the FE model of a sheep tibia and its applicability tested on a variety of element types. The proposed assignment approach is simple and illustrative. It can be easily modified to fit users’ situations.     

Refinement of the main chain directed assignment strategy for the analysis of 1H NMR spectra of proteins.

The underlying basis of the main chain directed (MCD) resonance assignment strategy for the analysis of 1H NMR spectra of proteins is reexamined. The criteria used in the construction of the patterns used in the MCD method have been extended to increase the robustness of the approach to the presence of variable protein secondary structure and significant spectral degeneracy. These criteria have led to the development of several dozen patterns exclusively involving the short distance relationships between main chain amide NH-C alpha-H-C beta H (NAB) J-coupled subspin systems of the amino acid residues. The MCD patterns have been examined for fidelity and frequency of occurrence in a database composed of the high resolution crystal structures of 39 proteins. The analysis has identified several extremely robust patterns, suitable for initiating a hierarchical construction of units of secondary structure based upon a systematic analysis of two-dimensional nuclear Overhauser effect spectra. A formal procedure, suitable for the computer assisted application of the MCD strategy, is developed. This procedure, termed MCDPAT, has been applied to the analysis of the crystal structures of human ubiquitin, T4 lysozyme, and ribonuclease A. It has been found that the MCDPAT procedure is conservative producing no significant errors and is globally successful in correctly identifying the appropriate units of secondary structure contained in these three proteins.     

Correlative microscopy: bridging the gap between fluorescence light microscopy and cryo-electron tomography

Cryo-electron tomography of frozen-hydrated biological samples offers a means of studying large and complex cellular structures in three-dimensions and with nanometer-scale resolution. The low contrast of unstained biological material embedded in amorphous ice and the need to minimise the exposure of these radiation-sensitive samples to the electron beam result in a poor signal-to-noise ratio. This poses problems not only in the visualisation and interpretation of such tomograms, it is also a problem in surveying the sample and in finding regions which contain the features of interest and which are suitable for recording tomograms. To address this problem, we have developed a correlative fluorescence light microscopy-electron microscopy approach, which guides the search for the structures of interest and allows electron microscopy to zoom in on them. With our approach, the total dose spent on locating regions of interest is negligible. A newly designed cryo-holder allows imaging of fluorescently labelled samples after vitrification. The absolute coordinates of structures identified and located by cryo-light microscopy are transferred to the electron microscope via a Matlab-based user interface. We have successfully tested the experimental setup and the whole procedure with two types of adherent fluorescently labelled cells, a neuronal cell line and keratinocytes, both grown directly on EM grids.     

Bayesian estimation of NMR restraint potential and weight: a validation on a representative set of protein structures

The classical procedure for nuclear magnetic resonance structure calculation allocates empirical distance ranges and uses historical values for weighting factors. However, Bayesian analysis suggests that there are more optimal choices for potential shape (bounds-free log-harmonic shape) and restraints weights. We compare the classical protocol with the Bayesian approach for more than 300 protein structures. We analyze the conformation similarity to the corresponding X-ray crystal structure, the distribution of the conformations around their average, and independent validation criteria. On average, the log-harmonic potential reduces the difference to the X-ray crystal structure. If the log-harmonic potential is used, the constant weighting tightens the distribution around the average conformation, with respect to the distributions obtained with Bayesian weighting. Conversely, the structure quality is improved by the Bayesian weighting over the classical procedure, whereas constant weighting worsens some criteria. The quality improvement obtained with the log-harmonic potential coupled to Bayesian weighting validates this approach on a representative set of protein structures.     

A rational approach to predict and modulate stereolability of chiral alpha substituted ketones

An effective strategy to assess and modulate the stereolability of chiral alpha substituted ketones (C alpha SKs) is presented. The tendency of C alpha SKs to retain or change their configuration in water is analyzed as a function of thermodynamic proton-release attitude of alpha asymmetric atoms inside the structures by linear Br?nsted correlations. A molecular modeling procedure was developed to analyze and suggest chemical modifications of C alpha SKs in view to obtain the desired grade of stereochemical stability. The approach was employed to predict the tendency to enantiomerize in water of two ketones (1 and 2) endowed with inhibitory activity against monoamine oxidases (MAOs) and the results were confirmed by experimental kinetics measurements performed in organic medium. As a demonstration of practical potentialities of the approach, four new structures, conceived as simple chemical modifications of 1 and 2, were designed to improve/reduce the stereostability grade of the starting anti-MAO ketones. The possibility to extend easily the procedure to other classes of C-H acids appears of interest.     

Automated 3D tree-ring detection and measurement from X-ray computed tomography

Tree ring analysis is essential to reveal the environmental information encoded in the wood structure. It provides quantitative data on the anatomical structure which can be used, for example, to measure the impact of the fluctuating environment on the tree growth, to support global vegetation models and for the dendrochronological analysis of archaeological wooden artefacts. Currently, several imaging-based methods for tree-ring detection and tree-ring feature estimation exist. However, despite advances in computer vision and edge recognition algorithms, detection of tree-rings is mostly limited to two-dimensional (2D) datasets and performed manually in some cases. This paper describes a new approach to estimate the three-dimensional (3D) structure of tree rings and their width automatically from X-ray computed tomography data. This approach relies on a modified Canny edge detection algorithm, which is capable of detecting fully connected tree-ring edges throughout the image stack. Our results show that this approach performs well on six tree species having conifer, ring-porous and diffuse-porous ring boundary structures. In our study, image denoising proved to be a critical step to achieve accurate results. A major advantage of this procedure is that it requires very little to no user interaction rendering it a reproducible procedure for tree-ring width measurements. As it also provides 3D representations of the ring edges, it also may be used in the future for the inspection of anatomical features.     

Application of distance geometry to the proton assignment problem

Assignment of the hydrogen spectrum is the first step in the conventional procedure for the determination of molecular structure by ¹H-nmr. In this paper, we explore the possibility of directly exploiting the distances derived from nuclear Overhauser effect experiments to generate a three-dimensional structure that is then assigned based on knowledge of the connectivity or primary sequence. This effort is analogous to that of the protein crystallographers in tracing electron density of the peptide chain. In particular, we compare structures produced by distance geometry to known peptide secondary structures to see what level of information is required to “trace” the backbone α-carbon and amide hydrogens and the β-carbon hydrogens. We conclude that this approach is only useful with excellent quality stereo-resolved data. © 1993 John Wiley & Sons, Inc.