PSI-DOCK: towards highly efficient and accurate flexible ligand docking

We have developed a new docking method, Pose-Sensitive Inclined (PSI)-DOCK, for flexible ligand docking. An improved SCORE function has been developed and used in PSI-DOCK for binding free energy evaluation. The improved SCORE function was able to reproduce the absolute binding free energies of a training set of 200 protein-ligand complexes with a correlation coefficient of 0.788 and a standard error of 8.13 kJ/mol. For ligand binding pose exploration, a unique searching strategy was designed in PSI-DOCK. In the first step, a tabu-enhanced genetic algorithm with a rapid shape-complementary scoring function is used to roughly explore and store potential binding poses of the ligand. Then, these predicted binding poses are optimized and compete against each other by using a genetic algorithm with the accurate SCORE function to determine the binding pose with the lowest docking energy. The PSI-DOCK 1.0 program is highly efficient in identifying the experimental binding pose. For a test dataset of 194 complexes, PSI-DOCK 1.0 achieved a 67% success rate (RMSD < 2.0 A) for only one run and a 74% success rate for 10 runs. PSI-DOCK can also predict the docking binding free energy with high accuracy. For a test set of 64 complexes, the correlation between the experimentally observed binding free energies and the docking binding free energies for 64 complexes is r = 0.777 with a standard deviation of 7.96 kJ/mol. Moreover, compared with other docking methods, PSI-DOCK 1.0 is extremely easy to use and requires minimum docking preparations. There is no requirement for the users to add hydrogen atoms to proteins because all protein hydrogen atoms and the flexibility of the terminal protein atoms are intrinsically taken into account in PSI-DOCK. There is also no requirement for the users to calculate partial atomic charges because PSI-DOCK does not calculate an electrostatic energy term. These features are not only convenient for the users but also help to avoid the influence of different preparation methods.     

SCORE: A New Empirical Method for Estimating the Binding Affinity of a Protein-Ligand Complex

A new method is presented to estimate the binding affinity of a protein-ligand complex with known three-dimensional structure. The method, SCORE, uses an empirical scoring function to describe the binding free energy, which includes terms to account for van der Waals contact, metal-ligand bonding, hydrogen bonding, desolvation effect, and deformation penalty upon the binding process. The coefficients of each term are obtained by multivariate regressional analysis of a diverse training set of 170 protein-ligand complexes. The final scoring function reproduces the binding free energies of the whole training set with a cross-validated deviation of 6.3 kJ/mol. The predictive ability of the function is further tested by a set of 11 endothiapepsin complexes and the internal consistency of the function is demonstrated in a stepwise procedure named Evolutionary Test. A major innovation of this method is the introduction of an atomic binding score which allows the researcher to inspect and optimize the lead compound rationally in a structure-based drug design scheme.     

A computerized system for scoring primate behavior using standard keyboards

A scoring system has been developed for primate behavior which uses standard keyboards and minicomputers or microcomputers. The mnemonic, alphanumeric code used is easily learned, highly flexible, and can be recorded in longhand for later entry into a computer if a keyboard is not immediately available. The software consists of two programs, both of which can be written in BASIC. SCORE is used for data acquisition and appends the test time to each behavioral sequence. DATSUM decodes and summarizes the test data using table-driven logic. The minimum hardware required is a 16K microcomputer, an alphanumeric keyboard, a display, and cassette storage.     

Speech Perception and Localisation with SCORE Bimodal: A Loudness Normalisation Strategy for Combined Cochlear Implant and Hearing Aid Stimulation

A significant fraction of newly implanted cochlear implant recipients use a hearing aid in their non-implanted ear. SCORE bimodal is a sound processing strategy developed for this configuration, aimed at normalising loudness perception and improving binaural loudness balance. Speech perception performance in quiet and noise and sound localisation ability of six bimodal listeners were measured with and without application of SCORE. Speech perception in quiet was measured either with only acoustic, only electric, or bimodal stimulation, at soft and normal conversational levels. For speech in quiet there was a significant improvement with application of SCORE. Speech perception in noise was measured for either steady-state noise, fluctuating noise, or a competing talker, at conversational levels with bimodal stimulation. For speech in noise there was no significant effect of application of SCORE. Modelling of interaural loudness differences in a long-term-average-speech-spectrum-weighted click train indicated that left-right discrimination of sound sources can improve with application of SCORE. As SCORE was found to leave speech perception unaffected or to improve it, it seems suitable for implementation in clinical devices.     

Robust and Reproducible Quantification of the Extent of Chest Radiographic Abnormalities (And It’s Free!)

RationaleObjective, reproducible quantification of the extent of abnormalities seen on a chest radiograph would improve the user-friendliness of a previously proposed severity scoring system for pulmonary tuberculosis and could be helpful in monitoring response to therapy, including in clinical trials.MethodsIn this study we report the development and evaluation of a simple tool using free image editing software (GIMP) to accurately and reproducibly quantify the area of affected lung on the chest radiograph of tuberculosis patients. As part of a pharmacokinetic study in Lima, Peru, a chest radiograph was performed on patients with pulmonary tuberculosis and this was subsequently photographed using a digital camera. The GIMP software was used by two independent and trained readers to estimate the extent of affected lung (expressed as a percentage of total lung area) in each radiograph and the resulting radiographic SCORE.Results56 chest radiographs were included in the reading analysis. The Intraclass correlation coefficient (ICC) between the 2 observers was 0.977 (p<0.001) for the area of lung affected and was 0.955 (p<0.001) for the final score; and the kappa coefficient of Interobserver agreement for both the area of lung affected and the score were 0.9 (p<0.001) and 0.86 (p<0.001) respectively.ConclusionsThis high level of between-observer agreement suggests that this freely available software could constitute a simple and useful tool for robust evaluation of individual and serial chest radiographs.     

Cooperation through indirect reciprocity: image scoring or standing strategy?

Theorists have only recently shown that cooperation through indirect reciprocity can evolve. The first modelling approach favoured a mechanism called image scoring. Helping someone increases one's image score, whereas refusing to help reduces it. The evolutionary outcome was a discriminator image scoring strategy that helps everybody who has, for example, a positive image score. Two experimental studies with humans found results that were compatible with discriminator image scoring. However, a new analysis of other theorists, based on another population structure, has cast doubts on the evolutionary stability of strategies using the recipient's score as a sole basis for decision. The new theoretical study confirmed that a strategy aiming at "good standing" has superior properties and easily beats image scoring. An individual loses good standing by failing to help a recipient in good standing, whereas failing to help recipients who lack good standing does not damage the standing of a potential donor (but would reduce his image score). The present empirical study with 23 groups of seven human subjects each was designed for distinguishing between the two proposed mechanisms experimentally. The results differed strongly from standing strategies, which might demand too much working memory capacity, but were compatible with image scoring or a similar strategy to a large extent. Furthermore, donors of constant "NO players" compensated for their refusing to help these players by being more generous to others.     

A comparison of two methods for evaluating drug-induced chromosome alterations.

Evaluating the technique and procedure for mutagenicity testing in mammals is a prerequisite to the development of a broad spectrum mutagenic assessment program. Two techniques, chromosome examination and micronucleus scoring, show promise but their applicability for mass screening is uncertain. We determined the slide observation time for these two techniques in mice treated orally, subcutaneously, intravenously, and intraperitoneally with cyclophosphamide (CY). In each instance, we detected a dose-response in less observation time by counting micronuclei in polychromatophilic erythrocytes. The simplicity of the scoring method, the ease of micronucleus identification and the rapidity of scoring all suggest the micronucleus test may be favorably integrated into a mutagenicity screening program.     

SCORE: predicting the core of protein models

MOTIVATION: The prediction of the regions of homology models that can be 'restrained by' or 'copied from' the basis structures is a vital step in correct model generation, because these regions are the models most accurate part. However, there is no ideal method for the identification of their limits. In most algorithms their length depends on the number of family members and definitions of secondary structure. RESULTS: The algorithm SCORE steps away from the conventional definitions of the core to identify from large numbers of basis structures those regions that can be considered structurally related to a target sequence. The use of phi, psi constraints to accurately pinpoint the regions that are conserved across a family and environmentally constrained substitution tables to extend these regions allows SCORE to rapidly (generally in under 1 s, an order of magnitude faster than methods such as MODELLER) identify and build the core of homology models from the alignments of the target sequence to the basis structures. The SCORE algorithm was used to build 114 model cores. In only two cases was the core size less than 50% of the structure and all the cores built had an RMSD of 3.7 A or less to the target structure.     

The 3D-QSAR analysis of 4(3H)-quinazolinone derivatives with dithiocarbamate side chains on thymidylate synthase

Thymidylate synthase (TS) is a critical enzyme for DNA biosynthesis and many nonclassical lipophilic antifolates targeting this enzyme are quite efficient and encouraging as antitumor drug. In this paper, the binding model of 14 antifolates of 4(3H)-quinazolinone derivatives with dithiocarbamate side chains was examined using molecular simulation methods--FlexiDock and SCORE2.0. The resulted conformation and orientation of these antifolates were directly applied to CoMFA study. A good correlation between the calculated binding energies of these antifolates complexed with TS and their inhibitory activities was derived. The robust QSAR model, its three-dimensional contour map, and binding score for these antifolates derived from SCORE2.0 provided guidelines for structural optimization of current antifolates.     

Partner Choice Drives the Evolution of Cooperation via Indirect Reciprocity

Indirect reciprocity potentially provides an important means for generating cooperation based on helping those who help others. However, the use of ‘image scores’ to summarize individuals’ past behaviour presents a dilemma: individuals withholding help from those of low image score harm their own reputation, yet giving to defectors erodes cooperation. Explaining how indirect reciprocity could evolve has therefore remained problematic. In all previous treatments of indirect reciprocity, individuals are assigned potential recipients and decide whether to cooperate or defect based on their reputation. A second way of achieving discrimination is through partner choice, which should enable individuals to avoid defectors. Here, I develop a model in which individuals choose to donate to anyone within their group, or to none. Whereas image scoring with random pairing produces cycles of cooperation and defection, with partner choice there is almost maximal cooperation. In contrast to image scoring with random pairing, partner choice results in almost perfect contingency, producing the correlation between giving and receiving required for cooperation. In this way, partner choice facilitates much higher and more stable levels of cooperation through image scoring than previously reported and provides a simple mechanism through which systems of helping those who help others can work.     

Tailoring the Implementation of New Biomarkers Based on Their Added Predictive Value in Subgroups of Individuals

Background

The value of new biomarkers or imaging tests, when added to a prediction model, is currently evaluated using reclassification measures, such as the net reclassification improvement (NRI). However, these measures only provide an estimate of improved reclassification at population level. We present a straightforward approach to characterize subgroups of reclassified individuals in order to tailor implementation of a new prediction model to individuals expected to benefit from it.

Methods

In a large Dutch population cohort (n = 21,992) we classified individuals to low (<5%) and high (≥5%) fatal cardiovascular disease risk by the Framingham risk score (FRS) and reclassified them based on the systematic coronary risk evaluation (SCORE). Subsequently, we characterized the reclassified individuals and, in case of heterogeneity, applied cluster analysis to identify and characterize subgroups. These characterizations were used to select individuals expected to benefit from implementation of SCORE.

Results

Reclassification after applying SCORE in all individuals resulted in an NRI of 5.00% (95% CI [-0.53%; 11.50%]) within the events, 0.06% (95% CI [-0.08%; 0.22%]) within the nonevents, and a total NRI of 0.051 (95% CI [-0.004; 0.116]). Among the correctly downward reclassified individuals cluster analysis identified three subgroups. Using the characterizations of the typically correctly reclassified individuals, implementing SCORE only in individuals expected to benefit (n = 2,707,12.3%) improved the NRI to 5.32% (95% CI [-0.13%; 12.06%]) within the events, 0.24% (95% CI [0.10%; 0.36%]) within the nonevents, and a total NRI of 0.055 (95% CI [0.001; 0.123]). Overall, the risk levels for individuals reclassified by tailored implementation of SCORE were more accurate.

Discussion

In our empirical example the presented approach successfully characterized subgroups of reclassified individuals that could be used to improve reclassification and reduce implementation burden. In particular when newly added biomarkers or imaging tests are costly or burdensome such a tailored implementation strategy may save resources and improve (cost-)effectiveness.     

Web-based scoring of the dicentric assay,a collaborative biodosimetric scoring strategy for population triage in large scale radiation accidents

In the case of a large scale radiation accident high throughput methods of biological dosimetry for population triage are needed to identify individuals requiring clinical treatment. The dicentric assay performed in web-based scoring mode may be a very suitable technique. Within the MULTIBIODOSE EU FP7 project a network is being established of 8 laboratories with expertise in dose estimations based on the dicentric assay. Here, the manual dicentric assay was tested in a web-based scoring mode. More than 23,000 high resolution images of metaphase spreads (only first mitosis) were captured by four laboratories and established as image galleries on the internet (cloud). The galleries included images of a complete dose effect curve (0–5.0 Gy) and three types of irradiation scenarios simulating acute whole body, partial body and protracted exposure. The blood samples had been irradiated in vitro with gamma rays at the University of Ghent, Belgium. Two laboratories provided image galleries from Fluorescence plus Giemsa stained slides (3 h colcemid) and the image galleries from the other two laboratories contained images from Giemsa stained preparations (24 h colcemid). Each of the 8 participating laboratories analysed 3 dose points of the dose effect curve (scoring 100 cells for each point) and 3 unknown dose points (50 cells) for each of the 3 simulated irradiation scenarios. At first all analyses were performed in a QuickScan Mode without scoring individual chromosomes, followed by conventional scoring (only complete cells, 46 centromeres). The calibration curves obtained using these two scoring methods were very similar, with no significant difference in the linear-quadratic curve coefficients. Analysis of variance showed a significant effect of dose on the yield of dicentrics, but no significant effect of the laboratories, different methods of slide preparation or different incubation times used for colcemid. The results obtained to date within the MULTIBIODOSE project by a network of 8 collaborating laboratories throughout Europe are very promising. The dicentric assay in the web based scoring mode as a high throughput scoring strategy is a useful application for biodosimetry in the case of a large scale radiation accident.     

Predicting flexible loop regions that interact with ligands: the challenge of accurate scoring

Flexible loop regions play a critical role in the biological function of many proteins and have been shown to be involved in ligand binding. In the context of structure-based drug design, using or predicting an incorrect loop configuration can be detrimental to the study if the loop is capable of interacting with the ligand. Three protein systems, each with at least one flexible loop region in close proximity to the known binding site, were selected for loop prediction using the CorLps program; a six residue loop region from phosphoribosylglycinamide formyltransferase (GART), two nine residue loop regions from cytochrome P450 (CYP) 119, and an 11 residue loop region from enolase were selected for loop prediction. The results of this study indicate that the statistically based DFIRE scoring function implemented in the CorLps program did not accurately rank native-like predicted loop configurations in any protein system. In an attempt to improve the ranking of the native-like predicted loop configurations, the MM/GBSA and the optimized MM/GBSA-dsr scoring functions were used to re-rank the predicted loops with and without bound ligand. In general, single snapshot MM/GBSA scoring provided the best ranking of native-like loop configurations. Based on the scoring function analyses presented, the optimal ranking of native-like loop configurations is still a difficult challenge and the choice of the "best" scoring function appears to be system dependent.     

Evaluation of Geometric Complementarity between Molecular Surfaces Using Compactly Supported Radial Basis Functions

One of the challenges faced by all molecular docking algorithms is that of being able to discriminate between correct results and false positives obtained in the simulations. The scoring or energetic function is the one that must fulfill this task. Several scoring functions have been developed and new methodologies are still under development. In this paper, we have employed the Compactly Supported Radial Basis Functions (CSRBF) to create analytical representations of molecular surfaces, which are then included as key components of a new scoring function for molecular docking. The method proposed here achieves a better ranking of the solutions produced by the program DOCK, as compared with the ranking done by its native contact scoring function. Our new analytical scoring function based on CSRBF can be easily included in different available docking programs as a reliable and quick filter in large-scale docking simulations.     

Prediction of phosphotyrosine signaling networks using a scoring matrix-assisted ligand identification approach

Systematic identification of binding partners for modular domains such as Src homology 2 (SH2) is important for understanding the biological function of the corresponding SH2 proteins. We have developed a worldwide web-accessible computer program dubbed SMALI for scoring matrix-assisted ligand identification for SH2 domains and other signaling modules. The current version of SMALI harbors 76 unique scoring matrices for SH2 domains derived from screening oriented peptide array libraries. These scoring matrices are used to search a protein database for short peptides preferred by an SH2 domain. An experimentally determined cut-off value is used to normalize an SMALI score, therefore allowing for direct comparison in peptide-binding potential for different SH2 domains. SMALI employs distinct scoring matrices from Scansite, a popular motif-scanning program. Moreover, SMALI contains built-in filters for phosphoproteins, Gene Ontology (GO) correlation and colocalization of subject and query proteins. Compared to Scansite, SMALI exhibited improved accuracy in identifying binding peptides for SH2 domains. Applying SMALI to a group of SH2 domains identified hundreds of interactions that overlap significantly with known networks mediated by the corresponding SH2 proteins, suggesting SMALI is a useful tool for facile identification of signaling networks mediated by modular domains that recognize short linear peptide motifs.     

Evaluating scoring functions for docking and designing beta-secretase inhibitors

Several simple scoring methods were examined for 2 series of beta-secretase (BACE-1) inhibitors to identify a docking/scoring protocol which could be used to design BACE-1 inhibitors in a drug discovery program. Both the PLP1 score and MMFFs interaction energy (E(inter)) performed as well or better than more computationally intensive methods for a set of substrate-based inhibitors, while the latter performed well for both sets of inhibitors.     

OLAV: towards high-throughput tandem mass spectrometry data identification

Mass spectrometry combined with database searching has become the preferred method for identifying proteins in proteomics projects. Proteins are digested by one or several enzymes to obtain peptides, which are analyzed by mass spectrometry. We introduce a new family of scoring schemes, named OLAV, aimed at identifying peptides in a database from their tandem mass spectra. OLAV scoring schemes are based on signal detection theory, and exploit mass spectrometry information more extensively than previously existing schemes. We also introduce a new concept of structural matching that uses pattern detection methods to better separate true from false positives. We show the superiority of OLAV scoring schemes compared to MASCOT, a widely used identification program. We believe that this work introduces a new way of designing scoring schemes that are especially adapted to high-throughput projects such as GeneProt large-scale human plasma project, where it is impractical to check all identifications manually.     

SMOOTH: a statistical method for successful removal of genotyping errors from high-density genetic linkage data

High-density genetic linkage maps can be used for purposes such as fine-scale targeted gene cloning and anchoring of physical maps. However, their construction is significantly complicated by even relatively small amounts of scoring errors. Currently available software is not able to solve the ordering ambiguities in marker clusters, which inhibits the application of high-density maps. A statistical method named SMOOTH was developed to remove genotyping errors from genetic linkage data during the mapping process. The program SMOOTH calculates the difference between the observed and predicted values of data points based on data points of neighbouring loci in a given marker order. Highly improbable data points are removed by the program in an iterative process with a mapping algorithm that recalculates the map after cleaning. SMOOTH has been tested with simulated data and experimental mapping data from potato. The simulations prove that this method is able to detect a high amount of scoring errors and demonstrates that the program enables mapping software to successfully construct a very accurate high-density map. In potato the application of the program resulted in a reliable placement of nearly 1,000 markers in one linkage group.     

Evolution of cooperation through indirect reciprocity

How can cooperation through indirect reciprocity evolve and what would it be like? This problem has previously been studied by simulating evolution in a small group of interacting individuals, assuming no gene flow between groups. In these simulations, certain ''image scoring'' strategies were found to be the most successful. However, analytical arguments show that it would not be in an individual''s interest to use these strategies. Starting with this puzzle, we investigate indirect reciprocity in simulations based on an island model. This has an advantage in that the role of genetic drift can be examined. Our results show that the image scoring strategies depend on very strong drift or a very small cost of giving help. As soon as these factors are absent, selection eliminates image scoring. We also consider other possibilities for the evolution of indirect reciprocity. In particular, we find that the strategy of aiming for ''good standing'' has superior properties. It can be an evolutionarily stable strategy and, even if not, it usually beats image scoring. Furthermore, by introducing quality variation among individuals into the model, we show that the standing strategy can be quality revealing, adding a new dimension to indirect reciprocity. Finally, we discuss general problems with currently popular modelling styles.     

RootScan: Software for high-throughput analysis of root anatomical traits

Background and aims

RootScan is a program for semi-automated image analysis of anatomical traits in root cross-sections.

Methods

RootScan uses pixel thresholds to separate the cross-section from its background and to divide it into tissue regions. Area measurements and object counts are performed within various regions of interest. A graphical user interface permits the user to see which regions are selected, to edit those selections, and to rate and comment on the data. The structure of the program allows for organized workflow and increased data collection efficiency.

Results

The program collects data on more than 20 variables per image including areas of the cross-section, stele, cortex, aerenchyma lacunae, xylem vessels, and counts of cortical cells and cell files. An increased rate of data collection allows collection of four times more variables in less time than is possible with current methods. Correlation analysis shows that RootScan data is equal or greater in accuracy than data collected with Photoshop.

Conclusions

Compared with currently available tools, this software offers considerable improvements in the amount and quality of data, ease of use, and time needed for data collection. RootScan permits phenotypic scoring of physiologically and agronomically important traits on a large number of genotypes.