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PubMed2001

Theoretical calculation and prediction of drug transport processes using simple parameters and partial least squares projections to latent structures (PLS) statistics. The use of electrotopological state indices.

A method of modeling and predicting drug transport processes using simple, theoretically computed molecular descriptors and multivariate statistics has been investigated in four data sets related to Caco-2 cell permeability, human intestinal absorption, brain-blood partitioning, and immobilized artificial membrane (IAM) chromatography. The program Molconn-Z was used to compute theoretical molecular descriptors related to electrotopological state indices. Additional parameters related to size and lipophilicity [i.e., calculated molar refraction (CMR) and octanol-water partition coefficient (CLOGP)] were also used in the statistical modeling. Good statistical models were derived (r(2) and Q(2) values ranged from 0.75 to 0.93 and 0.70 to 0.89, respectively) that permit fast computational (electronic) screening and prioritization of virtual libraries.

Blood-Brain Barrier↗
PubMed1998

Faecal immunoreactive lipase: a simple diagnostic test for cystic fibrosis.

UNLABELLED: The study evaluates faecal immunoreactive lipase (IRL) measurement in spot stool samples as an index of exocrine pancreatic function in patients with cystic fibrosis (CF). Stool samples (211) from 183 healthy volunteers (age range: 2 days-14.2 years) showed a normal log distribution of IRL values with a median concentration of 71.4 micrograms/g (range: 0.53-4160 micrograms/g). In 156 stool samples from 58 patients with proven CF, the median IRL concentration of 0.4 microgram/g (range: 0.003-107 micrograms/g) was significantly lower (P < 0.001) than that of normal controls. In healthy controls, IRL levels were age related with significantly higher levels (P < 0.001) shortly after birth compared to older children. Stimulation of the exocrine pancreas by oral milk feeding resulted in a significant (P < 0.001) increase in a faecal IRL concentration. Faecal IRL concentrations in meconium were very low and of the same magnitude as in patients with CF. CONCLUSION: Faecal IRL determination had a high diagnostic sensitivity (87%) and excellent diagnostic specificity (97%) in patients with CF. A negative test result (PVneg. 99%) virtually excluded CF under screening conditions.

Adolescent↗
PubMed2004

ProPose: a docking engine based on a fully configurable protein-ligand interaction model.

Virtual high-throughput screening of molecular databases and in particular high-throughput protein-ligand docking are both common methodologies that identify and enrich hits in the early stages of the drug design process. Current protein-ligand docking algorithms often implement a program-specific model for protein-ligand interaction geometries. However, in order to create a platform for arbitrary queries in molecular databases, a new program is desirable that allows more manual control of the modeling of molecular interactions. For that reason, ProPose, an advanced incremental construction docking engine, is presented here that implements a fast and fully configurable molecular interaction and scoring model. This program uses user-defined, discrete, pharmacophore-like representations of molecular interactions that are transformed on-the-fly into a continuous potential energy surface, allowing for the incorporation of target specific interaction mechanisms into docking protocols in a straightforward manner. A torsion angle library, based on semi-empirical quantum chemistry calculations, is used to provide minimum energy torsion angles for the incremental construction algorithm. Docking results of a diverse set of protein-ligand complexes from the Protein Data Bank demonstrate the feasibility of this new approach. As a result, the seamless integration of pharmacophore-like interaction types into the docking and scoring scheme implemented in ProPose opens new opportunities for efficient, receptor-specific screening protocols. [figure: see text]. ProPose--a fully configurable protein-ligand docking program--transforms pharmacophores into a smooth potential energy surface.

Binding Sites↗
PubMed2004

Automatic path searching for interactive navigation support within virtual medical 3-dimensional objects.

RATIONALE AND OBJECTIVES: This article proposes the use of a disembodied autonomous actor for navigation support within complex virtual medical objects reconstructed from Computed Tomography or Magnetic Resonance Imaging. Such objects are often maze-like, and users risk getting lost within them during Virtual Reality sessions. Therefore, users need paths for guided fly-throughs when performing non-invasive diagnostic tasks. MATERIALS AND METHODS: We present a synthetic vision-based actor capable of finding collision-free paths from a given position to a goal point in environments containing loops and impasses. When navigating, the actor voxelizes the virtual environment and searches for collision-free paths in voxel space by using a back tracking search algorithm. Automata and rules control its search behaviour. The resulting paths can be used in dedicated virtual endoscopy applications. RESULTS: Our path search method has been tested within a variety of tubular virtual anatomical structures in 3D such as aortas, colons, or blood vessels of the brain. The actor finds paths within reasonable time limits, even when considering complex anatomical surface models. CONCLUSION: The method may be used as a valuable tool for assisting virtual endoscopic diagnostic and screening activities in the near future.

Algorithms↗
PubMed2006

In silico identification of novel EGFR inhibitors with antiproliferative activity against cancer cells.

Inhibition of the epidermal growth factor receptor (EGFR) tyrosine kinase activity by small molecules has proved effective for the treatment of cancer. To the best of our knowledge, the crystal structure of EGFR has been used for the first time to identify novel inhibitor chemotypes by docking-based in silico screening of a large virtual chemical library followed up by experimental validation. We identified several compounds with antiproliferative effects on cancer cells. Amongst them, a C(4)-N(1)-substituted pyrazolo[3,4-d]pyrimidine MSK-039 (39) was discovered as a low-micromolar inhibitor of EGFR tyrosine kinase activity. The predicted binding mode of 39 opens a new avenue toward the optimization of novel chemical entities to develop potent and selective inhibitors of EGFR signaling.

Antineoplastic Agents↗
PubMed2006

Synthesis and SAR study of acridine, 2-methylquinoline and 2-phenylquinazoline analogues as anti-prion agents.

Transmissible spongiform encephalopathies (TSEs) are thought to arise from aggregation of a protease resistant protein denoted PrP(Sc), which is a misfolded isoform of the normal cellular prion protein PrP(C). Using virtual high-throughput screening we have selected structures analogous to acridine, 2-methyquinoline and 2-phenylquinazoline as potential therapeutic candidates for the treatment of TSEs. From the synthesis and screening of constructed libraries we have shown that an electron-rich aromatic ring attached through an amine linker to the position para to the ring nitrogen is beneficial to both binding to PrP(C) and the suppression of PrP(Sc) accumulation for acridine and 2-methylquinoline analogues. 2-Phenylquinazoline analogues appear to utilise a different mode of action by binding at a different location and/or pose. We report IC50s in the nanomolar range.

Acridines↗
PubMed2001

Identification and analysis of unsatisfactory psychosocial work situations: a participatory approach employing video-computer interaction.

A method for psychosocial evaluation of potentially stressful or unsatisfactory situations in manual work was developed. It focuses on subjective responses regarding specific situations and is based on interactive worker assessment when viewing video recordings of oneself. The worker is first video-recorded during work. The video is then displayed on the computer terminal, and the filmed worker clicks on virtual controls on the screen whenever an unsatisfactory psychosocial situation appears; a window of questions regarding psychological demands, mental strain and job control is then opened. A library with pictorial information and comments on the selected situations is formed in the computer. The evaluation system, called PSIDAR, was applied in two case studies, one of manual materials handling in an automotive workshop and one of a group of workers producing and testing instrument panels. The findings indicate that PSIDAR can provide data that are useful in a participatory ergonomic process of change.

Computers↗
PubMed2002

Consensus scoring for ligand/protein interactions.

Several different functions have been put forward for evaluating the energetics of ligand binding to proteins. Those employed in the DOCK, GOLD and FlexX docking programs have been especially widely used, particularly in connection with virtual high-throughput screening (vHTS) projects. Until recently, such evaluation functions were usually considered only in conjunction with the docking programs that relied on them. In such studies, the evaluation function in question actually fills two distinct roles: it serves as the objective function being optimized (fitness function), but is also the scoring function used to compare the candidate docking configurations generated by the program. We have used descriptions available in the open literature to create free-standing scoring functions based on those used in DOCK and GOLD, and have implemented the more recently formulated PMF [J. Med. Chem. 42 (1999) 791] scoring function as well. The performance of these functions was examined individually for each of several data sets for which both crystal structures and affinities are available, as was the performance of the FlexX scoring function. Various ways of combining individual scores into a consensus score (CScore) were also considered. The individual and consensus scores were also used to try to pick out configurations most similar to those found in crystal structures from among a set of candidate configurations produced by FlexX docking runs. We find that the reliability and interpretability of results can be improved by combining results from all four functions into a CScore.

Crystallography, X-Ray↗
PubMedDate not supplied

OptiDock: virtual HTS of combinatorial libraries by efficient sampling of binding modes in product space.

Products from combinatorial libraries generally share a common core structure that can be exploited to improve the efficiency of virtual high-throughput screening (vHTS). In general, it is more efficient to find a method that scales with the total number of reagents (Sigma growth) rather with the number of products (Pi growth). The OptiDock methodology described herein entails selecting a diverse but representative subset of compounds that span the structural space encompassed by the full library. These compounds are docked individually using the FlexX program (Rarey, M.; Kramer, B.; Lengauer, T.; Klebe, G. J. Mol. Biol. 1995, 251, 470-489) to define distinct docking modes in terms of reference placements for combinatorial core atoms. Thereafter, substituents in R-cores (consisting of the core structure substituted at a single variation site) are docked, keeping the core atoms fixed at the coordinates dictated by each reference placement. Interaction energies are calculated for each docked R-core with respect to the target protein, and energies for whole compounds are calculated by finding the reference core placement for which the sum of corresponding R-core energies is most negative. The use of diverse whole compounds to define binding modes is a key advantage of the protocol over other combinatorial docking programs. As a result, OptiDock returns better-scoring conformers than does serially applied FlexX. OptiDock is also better able to find a viable docked pose for each library member than are other combinatorial approaches.

Binding Sites↗
PubMedDate not supplied

Drug-like index: a new approach to measure drug-like compounds and their diversity.

Combinatorial organic synthesis (combinatorial chemistry or CC) and ultrahigh-throughput screening (UHTS) are speeding up drug discovery by increasing capacity for making and screening large numbers of compounds. However, a key problem is to select the smaller set of "representative" compounds from a virtual library to make or screen. Our approach is to select drug-like as well as structurally diverse compounds. The compounds, which are not very drug-like, are less taken into account or excluded even if they contribute to the diversity of the collection. Hence, the first step in the compound selection is to rank compounds in drug-like "degree". To quantify the drug-like "degree", drug-like index (DLI) is introduced in this paper. A compound's DLI is calculated based upon the knowledge derived from known drugs selected from Comprehensive Medicinal Chemistry (CMC) database. The paper describes the way of this knowledge base is formed and the procedure for selecting drug-like compounds.

Algorithms↗
PubMedDate not supplied

Prediction of polar surface area and drug transport processes using simple parameters and PLS statistics.

Modeling of the calculated polar surface area of drugs with rapidly derived descriptors (i.e., the number of hydrogen bonds accepting oxygen and nitrogen atoms and the number of hydrogen atoms bonded to these) using partial least squares projection to latent structures (PLS) analysis is described. The statistical analysis showed strong relationships between the hydrogen-bonding descriptors and the calculated polar surface area of five chemically diverse sets of drugs (R2>0.93 and Q2>0.69, n = 11, 20, 45, 70, and 74, respectively). The statistical models (using H-bonding descriptors and log P) of transport across Caco-2 cells (n = 11), brain-blood partitioning (two data sets, n = 45 and 70) and percent intestinal absorption (n = 20) showed R2 = 0.92, 0.72, 0.76, and 0.81 and Q2 = 0.74, 0.75, 0.71, and 0.73, respectively. The inclusion of log P improved two models, had no effect on one model, and had a slightly negative impact on one model. The combination of H-bonding descriptors with log P is similar to the Lipinski "rule-of-five" mnemonic. However, by using a multivariate statistical method (e.g., PLS), the prediction becomes quantitative instead of qualitative. Good statistical models were derived which permit fast computational screening and prioritization of virtual compound libraries.

Blood-Brain Barrier↗
PubMedDate not supplied

Prediction of protein retention times in anion-exchange chromatography systems using support vector regression.

Quantitative Structure-Retention Relationship (QSRR) models are developed for the prediction of protein retention times in anion-exchange chromatography systems. Topological, subdivided surface area, and TAE (Transferable Atom Equivalent) electron-density-based descriptors are computed directly for a set of proteins using molecular connectivity patterns and crystal structure geometries. A novel algorithm based on Support Vector Machine (SVM) regression has been employed to obtain predictive QSRR models using a two-step computational strategy. In the first step, a sparse linear SVM was utilized as a feature selection procedure to remove irrelevant or redundant information. Subsequently, the selected features were used to produce an ensemble of nonlinear SVM regression models that were combined using bootstrap aggregation (bagging) techniques, where various combinations of training and validation data sets were selected from the pool of available data. A visualization scheme (star plots) was used to display the relative importance of each selected descriptor in the final set of "bagged" models. Once these predictive models have been validated, they can be used as an automated prediction tool for virtual high-throughput screening (VHTS).

Anion Exchange Resins↗
PubMedDate not supplied

Comparison of support vector machine and artificial neural network systems for drug/nondrug classification.

Support vector machine (SVM) and artificial neural network (ANN) systems were applied to a drug/nondrug classification problem as an example of binary decision problems in early-phase virtual compound filtering and screening. The results indicate that solutions obtained by SVM training seem to be more robust with a smaller standard error compared to ANN training. Generally, the SVM classifier yielded slightly higher prediction accuracy than ANN, irrespective of the type of descriptors used for molecule encoding, the size of the training data sets, and the algorithm employed for neural network training. The performance was compared using various different descriptor sets and descriptor combinations based on the 120 standard Ghose-Crippen fragment descriptors, a wide range of 180 different properties and physicochemical descriptors from the Molecular Operating Environment (MOE) package, and 225 topological pharmacophore (CATS) descriptors. For the complete set of 525 descriptors cross-validated classification by SVM yielded 82% correct predictions (Matthews cc = 0.63), whereas ANN reached 80% correct predictions (Matthews cc = 0.58). Although SVM outperformed the ANN classifiers with regard to overall prediction accuracy, both methods were shown to complement each other, as the sets of true positives, false positives (overprediction), true negatives, and false negatives (underprediction) produced by the two classifiers were not identical. The theory of SVM and ANN training is briefly reviewed.

Algorithms↗
PubMedDate not supplied

4D-fingerprints, universal QSAR and QSPR descriptors.

An elusive goal in the field of chemoinformatics and molecular modeling has been the generation of a set of descriptors that, once calculated for a molecule, may be used in a wide variety of applications. Since such universal descriptors are generated free from external constraints, they are inherently independent of the data set in which they are employed. The realization of a set of universal descriptors would significantly streamline such chemoinformatics tasks as virtual high-throughout screening (VHTS) and toxicity profiling. The current study reports the derivation and validation of a potential set of universal descriptors, referred to as the 4D-fingerprints. The 4D-fingerprints are derived from the 4D-molecular similarity analysis. To evaluate the applicability of the 4D-fingerprints as universal descriptors, they are used to generate descriptive QSAR models for 5 independent training sets. Each of the training sets has been analyzed previously by several varying QSAR methods, and the results of the models generated using the 4D-fingerprints are compared to the results of the previous QSAR analyses. It was found that the models generated using the 4D-fingerprints are comparable in quality, based on statistical measures of fit and test set prediction, to the previously reported models for the other QSAR methods. This finding is particularly significant considering the 4D-fingerprints are generated independent of external constraints such as alignment, while the QSAR methods used for comparison all require an alignment analysis.

Anesthetics, General↗
PubMed2002

A computational ensemble pharmacophore model for identifying substrates of P-glycoprotein.

P-glycoprotein (P-gp) functions as a drug efflux pump, mediating multidrug resistance and limiting the efficacy of many drugs. Clearly, identification of potential P-gp substrate liability early in the drug discovery process would be advantageous. We describe a multiple-pharmacophore model that can discriminate between substrates and nonsubstrates of P-gp with an accuracy of 63%. The application of this filter allows large virtual libraries to be screened efficiently for compounds less likely to be transported by P-gp.

ATP Binding Cassette Transporter, Subfamily B, Mem↗
PubMedDate not supplied

Rational selection of training and test sets for the development of validated QSAR models.

Quantitative Structure-Activity Relationship (QSAR) models are used increasingly to screen chemical databases and/or virtual chemical libraries for potentially bioactive molecules. These developments emphasize the importance of rigorous model validation to ensure that the models have acceptable predictive power. Using k nearest neighbors (kNN) variable selection QSAR method for the analysis of several datasets, we have demonstrated recently that the widely accepted leave-one-out (LOO) cross-validated R2 (q2) is an inadequate characteristic to assess the predictive ability of the models [Golbraikh, A., Tropsha, A. Beware of q2! J. Mol. Graphics Mod. 20, 269-276, (2002)]. Herein, we provide additional evidence that there exists no correlation between the values of q2 for the training set and accuracy of prediction (R2) for the test set and argue that this observation is a general property of any QSAR model developed with LOO cross-validation. We suggest that external validation using rationally selected training and test sets provides a means to establish a reliable QSAR model. We propose several approaches to the division of experimental datasets into training and test sets and apply them in QSAR studies of 48 functionalized amino acid anticonvulsants and a series of 157 epipodophyllotoxin derivatives with antitumor activity. We formulate a set of general criteria for the evaluation of predictive power of QSAR models.

Algorithms↗
PubMedDate not supplied

Colorectal cancer screening issues: a role for CT colonography?

Colorectal cancer is the third most common cancer in the United States and will cause 56,700 deaths in 2001, despite the availability of screening tests capable of detecting the disease at earlier stages and reducing mortality. This article reviews the natural history of colorectal cancer, common risk factors and prevention strategies, and the strengths, limitations, and cost effectiveness of available screening tests. Although reminders to undergo colorectal cancer screening have become commonplace in the popular media, compliance with screening guidelines remains poor. Although still an unproven technology for widespread screening, computed tomographic (CT) colonography has several attractive characteristics for a screening test. For example, CT scanners are widely available, in contrast to limited numbers of gastroenterologists and radiologists' declining skill and interest in barium enema examinations. Also, patients may be less reluctant to undergo CT colonography than screening colonoscopy. Development of virtual bowel cleansing could further increase compliance and thereby reduce mortality from colorectal cancer. Other articles in this Feature Section discuss technical details of CT colonography and its methodologic challenges.

Adenomatous Polyps↗
PubMed2006

Bioinformatic analysis of an unusual gene-enzyme relationship in the arginine biosynthetic pathway among marine gamma proteobacteria: implications concerning the formation of N-acetylated intermediates in prokaryotes.

BACKGROUND: The N-acetylation of L-glutamate is regarded as a universal metabolic strategy to commit glutamate towards arginine biosynthesis. Until recently, this reaction was thought to be catalyzed by either of two enzymes: (i) the classical N-acetylglutamate synthase (NAGS, gene argA) first characterized in Escherichia coli and Pseudomonas aeruginosa several decades ago and also present in vertebrates, or (ii) the bifunctional version of ornithine acetyltransferase (OAT, gene argJ) present in Bacteria, Archaea and many Eukaryotes. This paper focuses on a new and surprising aspect of glutamate acetylation. We recently showed that in Moritella abyssi and M. profunda, two marine gamma proteobacteria, the gene for the last enzyme in arginine biosynthesis (argH) is fused to a short sequence that corresponds to the C-terminal, N-acetyltransferase-encoding domain of NAGS and is able to complement an argA mutant of E. coli. Very recently, other authors identified in Mycobacterium tuberculosis an independent gene corresponding to this short C-terminal domain and coding for a new type of NAGS. We have investigated the two prokaryotic Domains for patterns of gene-enzyme relationships in the first committed step of arginine biosynthesis. RESULTS: The argH-A fusion, designated argH(A), and discovered in Moritella was found to be present in (and confined to) marine gamma proteobacteria of the Alteromonas- and Vibrio-like group. Most of them have a classical NAGS with the exception of Idiomarina loihiensis and Pseudoalteromonas haloplanktis which nevertheless can grow in the absence of arginine and therefore appear to rely on the arg(A) sequence for arginine biosynthesis. Screening prokaryotic genomes for virtual argH-X 'fusions' where X stands for a homologue of arg(A), we retrieved a large number of Bacteria and several Archaea, all of them devoid of a classical NAGS. In the case of Thermus thermophilus and Deinococcus radiodurans, the arg(A)-like sequence clusters with argH in an operon-like fashion. In this group of sequences, we find the short novel NAGS of the type identified in M. tuberculosis. Among these organisms, at least Thermus, Mycobacterium and Streptomyces species appear to rely on this short NAGS version for arginine biosynthesis. CONCLUSION: The gene-enzyme relationship for the first committed step of arginine biosynthesis should now be considered in a new perspective. In addition to bifunctional OAT, nature appears to implement at least three alternatives for the acetylation of glutamate. It is possible to propose evolutionary relationships between them starting from the same ancestral N-acetyltransferase domain. In M. tuberculosis and many other bacteria, this domain evolved as an independent enzyme, whereas it fused either with a carbamate kinase fold to give the classical NAGS (as in E. coli) or with argH as in marine gamma proteobacteria. Moreover, there is an urgent need to clarify the current nomenclature since the same gene name argA has been used to designate structurally different entities. Clarifying the confusion would help to prevent erroneous genomic annotation.

Acetylation↗