Chemodiversity and molecular plasticity: recognition processes as explored by property spaces.

In the last few years, a need to account for molecular flexibility in drug-design methodologies has emerged, even if the dynamic behavior of molecular properties is seldom made explicit. For a flexible molecule, it is indeed possible to compute different values for a given conformation-dependent property and the ensemble of such values defines a property space that can be used to describe its molecular variability; a most representative case is the lipophilicity space. In this review, a number of applications of lipophilicity space and other property spaces are presented, showing that this concept can be fruitfully exploited: to investigate the constraints exerted by media of different levels of structural organization, to examine processes of molecular recognition and binding at an atomic level, to derive informative descriptors to be included in quantitative structure--activity relationships and to analyze protein simulations extracting the relevant information. Much molecular information is neglected in the descriptors used by medicinal chemists, while the concept of property space can fill this gap by accounting for the often-disregarded dynamic behavior of both small ligands and biomacromolecules. Property space also introduces some innovative concepts such as molecular sensitivity and plasticity, which appear best suited to explore the ability of a molecule to adapt itself to the environment variously modulating its property and conformational profiles. Globally, such concepts can enhance our understanding of biological phenomena providing fruitful descriptors in drug-design and pharmaceutical sciences.

iLOGP: A Simple, Robust, and Efficient Description of n-Octanol/Water Partition Coefficient for Drug Design Using the GB/SA Approach.

The n-octanol/water partition coefficient (log Po/w) is a key physicochemical parameter for drug discovery, design, and development. Here, we present a physics-based approach that shows a strong linear correlation between the computed solvation free energy in implicit solvents and the experimental log Po/w on a cleansed data set of more than 17,500 molecules. After internal validation by five-fold cross-validation and data randomization, the predictive power of the most interesting multiple linear model, based on two GB/SA parameters solely, was tested on two different external sets of molecules. On the Martel druglike test set, the predictive power of the best model (N = 706, r = 0.64, MAE = 1.18, and RMSE = 1.40) is similar to six well-established empirical methods. On the 17-drug test set, our model outperformed all compared empirical methodologies (N = 17, r = 0.94, MAE = 0.38, and RMSE = 0.52). The physical basis of our original GB/SA approach together with its predictive capacity, computational efficiency (1 to 2 s per molecule), and tridimensional molecular graphics capability lay the foundations for a promising predictor, the implicit log P method (iLOGP), to complement the portfolio of drug design tools developed and provided by the SIB Swiss Institute of Bioinformatics.

Integrated methodologies to study human transcriptional regulation from functional genomics data

Abstract : The human body is composed of a huge number of cells acting together in a concerted manner. The current understanding is that proteins perform most of the necessary activities in keeping a cell alive. The DNA, on the other hand, stores the information on how to produce the different proteins in the genome. Regulating gene transcription is the first important step that can thus affect the life of a cell, modify its functions and its responses to the environment. Regulation is a complex operation that involves specialized proteins, the transcription factors. Transcription factors (TFs) can bind to DNA and activate the processes leading to the expression of genes into new proteins. Errors in this process may lead to diseases. In particular, some transcription factors have been associated with a lethal pathological state, commonly known as cancer, associated with uncontrolled cellular proliferation, invasiveness of healthy tissues and abnormal responses to stimuli. Understanding cancer-related regulatory programs is a difficult task, often involving several TFs interacting together and influencing each other's activity. This Thesis presents new computational methodologies to study gene regulation. In addition we present applications of our methods to the understanding of cancer-related regulatory programs. The understanding of transcriptional regulation is a major challenge. We address this difficult question combining computational approaches with large collections of heterogeneous experimental data. In detail, we design signal processing tools to recover transcription factors binding sites on the DNA from genome-wide surveys like chromatin immunoprecipitation assays on tiling arrays (ChIP-chip). We then use the localization about the binding of TFs to explain expression levels of regulated genes. In this way we identify a regulatory synergy between two TFs, the oncogene C-MYC and SP1. C-MYC and SP1 bind preferentially at promoters and when SP1 binds next to C-NIYC on the DNA, the nearby gene is strongly expressed. The association between the two TFs at promoters is reflected by the binding sites conservation across mammals, by the permissive underlying chromatin states 'it represents an important control mechanism involved in cellular proliferation, thereby involved in cancer. Secondly, we identify the characteristics of TF estrogen receptor alpha (hERa) target genes and we study the influence of hERa in regulating transcription. hERa, upon hormone estrogen signaling, binds to DNA to regulate transcription of its targets in concert with its co-factors. To overcome the scarce experimental data about the binding sites of other TFs that may interact with hERa, we conduct in silico analysis of the sequences underlying the ChIP sites using the collection of position weight matrices (PWMs) of hERa partners, TFs FOXA1 and SP1. We combine ChIP-chip and ChIP-paired-end-diTags (ChIP-pet) data about hERa binding on DNA with the sequence information to explain gene expression levels in a large collection of cancer tissue samples and also on studies about the response of cells to estrogen. We confirm that hERa binding sites are distributed anywhere on the genome. However, we distinguish between binding sites near promoters and binding sites along the transcripts. The first group shows weak binding of hERa and high occurrence of SP1 motifs, in particular near estrogen responsive genes. The second group shows strong binding of hERa and significant correlation between the number of binding sites along a gene and the strength of gene induction in presence of estrogen. Some binding sites of the second group also show presence of FOXA1, but the role of this TF still needs to be investigated. Different mechanisms have been proposed to explain hERa-mediated induction of gene expression. Our work supports the model of hERa activating gene expression from distal binding sites by interacting with promoter bound TFs, like SP1. hERa has been associated with survival rates of breast cancer patients, though explanatory models are still incomplete: this result is important to better understand how hERa can control gene expression. Thirdly, we address the difficult question of regulatory network inference. We tackle this problem analyzing time-series of biological measurements such as quantification of mRNA levels or protein concentrations. Our approach uses the well-established penalized linear regression models where we impose sparseness on the connectivity of the regulatory network. We extend this method enforcing the coherence of the regulatory dependencies: a TF must coherently behave as an activator, or a repressor on all its targets. This requirement is implemented as constraints on the signs of the regressed coefficients in the penalized linear regression model. Our approach is better at reconstructing meaningful biological networks than previous methods based on penalized regression. The method is tested on the DREAM2 challenge of reconstructing a five-genes/TFs regulatory network obtaining the best performance in the "undirected signed excitatory" category. Thus, these bioinformatics methods, which are reliable, interpretable and fast enough to cover large biological dataset, have enabled us to better understand gene regulation in humans.

Rational design of an organometallic glutathione transferase inhibitor.

Double trouble: A hybrid organic-inorganic (organometallic) inhibitor was designed to target glutathione transferases. The metal center is used to direct protein binding, while the organic moiety acts as the active-site inhibitor (see picture). The mechanism of inhibition was studied using a range of biophysical and biochemical methods.

Using active learning for monitoring networks design: The example of wind power plants sites evaluation

Locating new wind farms is of crucial importance for energy policies of the next decade. To select the new location, an accurate picture of the wind fields is necessary. However, characterizing wind fields is a difficult task, since the phenomenon is highly nonlinear and related to complex topographical features. In this paper, we propose both a nonparametric model to estimate wind speed at different time instants and a procedure to discover underrepresented topographic conditions, where new measuring stations could be added. Compared to space filling techniques, this last approach privileges optimization of the output space, thus locating new potential measuring sites through the uncertainty of the model itself.

Design and evaluation of a solid sampler for the monitoring of airborne 1,6-hexamethylene diisocyanate (HDI) and its prepolymers in 2-component spray painting

An active, solvent-free solid sampler was developed for the collection of 1,6-hexamethylene diisocyanate (HDI) aerosol and prepolymers. The sampler was made of a filter impregnated with 1-(2-methoxyphenyl)piperazine contained in a filter holder. Interferences with HDI were observed when a set of cellulose acetate filters and a polystyrene filter holder were used; a glass fiber filter and polypropylene filter cassette gave better results. The applicability of the sampling and analytical procedure was validated with a test chamber, constructed for the dynamic generation of HDI aerosol and prepolymers in commercial two-component spray paints (Desmodur(R) N75) used in car refinishing. The particle size distribution, temporal stability, and spatial uniformity of the simulated aerosol were established in order to test the sample. The monitoring of aerosol concentrations was conducted with the solid sampler paired to the reference impinger technique (impinger flasks contained 10 mL of 0.5 mg/mL 1-(2-methoxyphenyl)piperazine in toluene) under a controlled atmosphere in the test chamber. Analyses of derivatized HDI and prepolymers were carried out by using high-performance liquid chromatography and ultraviolet detection. The correlation between the solvent-free and the impinger techniques appeared fairly good (Y = 0.979X - 0.161; R = 0.978), when the tests were conducted in the range of 0.1 to 10 times the threshold limit value (TLV) for HDI monomer and up to 60-mu-g/m3 (3 U.K. TLVs) for total -N = C = O groups.

Experimental design for acquiring relevant data to address the issue of comparing consecutively manufactured tools and firearms

The comparison of consecutively manufactured tools and firearms has provided much, but not all, of the basis for the profession of firearm and toolmark examination. The authors accept the fundamental soundness of this approach but appeal to the experimental community to close two minor gaps in the experimental procedure. We suggest that "blinding" and attention to appropriateness of other experimental conditions that would consolidate the foundations of our profession. We do not suggest that previous work is unsound.

New concepts for the design of dermal substitutes

Objectives: Skin can be partially regenerated after full thickness defects by collagen matrices, In this study, we identified the main limitations of induced regeneration aiming to improve the design of dermal matrices. Methods: Single mice received a 1 cm2, full thickness skin wound on the dorsum, which were grafted with collagen-GAG matrices or left ungrafted. The healing modulation induced by the collagen-GAG matrices was compared to spontaneous healing and to custom designed, bioactive, poly-N-Acetyl- Glucosamine (NAG) matrices. Wound staging was based on macroscopic, histological and immunhistochemical analysis on days 3, 7, 10 and 21 post wounding. Results: Cell density was higher in spontaneously granulating wounds compared to grafted wounds. While grafted wounds exhibited increased levels of cell proliferation on days 7 and 10, vascularity was dramatically reduced. NAG scaffolds accelerated both angiogenesis and wound re-epithelialization. Conclusions: Since slow integration and revascularization severely limit the engraftment of clinically used dermal scaffolds, the design of dermal matrices using bioactive materials represent the next step in skin regeneration.

The impact of iron supplementation efficiency in female blood donors with a decreased ferritin level and no anaemia. Rationale and design of a randomised controlled trial: a study protocol.

ABSTRACT: BACKGROUND: There is no recommendation to screen ferritin level in blood donors, even though several studies have noted the high prevalence of iron deficiency after blood donation, particularly among menstruating females. Furthermore, some clinical trials have shown that non-anaemic women with unexplained fatigue may benefit from iron supplementation. Our objective is to determine the clinical effect of iron supplementation on fatigue in female blood donors without anaemia, but with a mean serum ferritin </= 30 ng/ml. METHODS/DESIGN: In a double blind randomised controlled trial, we will measure blood count and ferritin level of women under age 50 yr, who donate blood to the University Hospital of Lausanne Blood Transfusion Department, at the time of the donation and after 1 week. One hundred and forty donors with a ferritin level </= 30 ng/ml and haemoglobin level >/= 120 g/l (non-anaemic) a week after the donation will be included in the study and randomised. A one-month course of oral ferrous sulphate (80 mg/day of elemental iron) will be introduced vs. placebo. Self-reported fatigue will be measured using a visual analogue scale. Secondary outcomes are: score of fatigue (Fatigue Severity Scale), maximal aerobic power (Chester Step Test), quality of life (SF-12), and mood disorders (Prime-MD). Haemoglobin and ferritin concentration will be monitored before and after the intervention. DISCUSSION: Iron deficiency is a potential problem for all blood donors, especially menstruating women. To our knowledge, no other intervention study has yet evaluated the impact of iron supplementation on subjective symptoms after a blood donation. TRIAL REGISTRATION: NCT00689793.

Design and analysis of ChIP-Seq experiments for nuclear factor I DNA-binding proteins

SUMMARY : Eukaryotic DNA interacts with the nuclear proteins using non-covalent ionic interactions. Proteins can recognize specific nucleotide sequences based on the sterical interactions with the DNA and these specific protein-DNA interactions are the basis for many nuclear processes, e.g. gene transcription, chromosomal replication, and recombination. New technology termed ChIP-Seq has been recently developed for the analysis of protein-DNA interactions on a whole genome scale and it is based on immunoprecipitation of chromatin and high-throughput DNA sequencing procedure. ChIP-Seq is a novel technique with a great potential to replace older techniques for mapping of protein-DNA interactions. In this thesis, we bring some new insights into the ChIP-Seq data analysis. First, we point out to some common and so far unknown artifacts of the method. Sequence tag distribution in the genome does not follow uniform distribution and we have found extreme hot-spots of tag accumulation over specific loci in the human and mouse genomes. These artifactual sequence tags accumulations will create false peaks in every ChIP-Seq dataset and we propose different filtering methods to reduce the number of false positives. Next, we propose random sampling as a powerful analytical tool in the ChIP-Seq data analysis that could be used to infer biological knowledge from the massive ChIP-Seq datasets. We created unbiased random sampling algorithm and we used this methodology to reveal some of the important biological properties of Nuclear Factor I DNA binding proteins. Finally, by analyzing the ChIP-Seq data in detail, we revealed that Nuclear Factor I transcription factors mainly act as activators of transcription, and that they are associated with specific chromatin modifications that are markers of open chromatin. We speculate that NFI factors only interact with the DNA wrapped around the nucleosome. We also found multiple loci that indicate possible chromatin barrier activity of NFI proteins, which could suggest the use of NFI binding sequences as chromatin insulators in biotechnology applications. RESUME : L'ADN des eucaryotes interagit avec les protéines nucléaires par des interactions noncovalentes ioniques. Les protéines peuvent reconnaître les séquences nucléotidiques spécifiques basées sur l'interaction stérique avec l'ADN, et des interactions spécifiques contrôlent de nombreux processus nucléaire, p.ex. transcription du gène, la réplication chromosomique, et la recombinaison. Une nouvelle technologie appelée ChIP-Seq a été récemment développée pour l'analyse des interactions protéine-ADN à l'échelle du génome entier et cette approche est basée sur l'immuno-précipitation de la chromatine et sur la procédure de séquençage de l'ADN à haut débit. La nouvelle approche ChIP-Seq a donc un fort potentiel pour remplacer les anciennes techniques de cartographie des interactions protéine-ADN. Dans cette thèse, nous apportons de nouvelles perspectives dans l'analyse des données ChIP-Seq. Tout d'abord, nous avons identifié des artefacts très communs associés à cette méthode qui étaient jusqu'à présent insoupçonnés. La distribution des séquences dans le génome ne suit pas une distribution uniforme et nous avons constaté des positions extrêmes d'accumulation de séquence à des régions spécifiques, des génomes humains et de la souris. Ces accumulations des séquences artéfactuelles créera de faux pics dans toutes les données ChIP-Seq, et nous proposons différentes méthodes de filtrage pour réduire le nombre de faux positifs. Ensuite, nous proposons un nouvel échantillonnage aléatoire comme un outil puissant d'analyse des données ChIP-Seq, ce qui pourraient augmenter l'acquisition de connaissances biologiques à partir des données ChIP-Seq. Nous avons créé un algorithme d'échantillonnage aléatoire et nous avons utilisé cette méthode pour révéler certaines des propriétés biologiques importantes de protéines liant à l'ADN nommés Facteur Nucléaire I (NFI). Enfin, en analysant en détail les données de ChIP-Seq pour la famille de facteurs de transcription nommés Facteur Nucléaire I, nous avons révélé que ces protéines agissent principalement comme des activateurs de transcription, et qu'elles sont associées à des modifications de la chromatine spécifiques qui sont des marqueurs de la chromatine ouverte. Nous pensons que lés facteurs NFI interagir uniquement avec l'ADN enroulé autour du nucléosome. Nous avons également constaté plusieurs régions génomiques qui indiquent une éventuelle activité de barrière chromatinienne des protéines NFI, ce qui pourrait suggérer l'utilisation de séquences de liaison NFI comme séquences isolatrices dans des applications de la biotechnologie.

Study design for technology assessment: critical issues.

The epidemiological methods have become useful tools for the assessment of the effectiveness and safety of health care technologies. The experimental methods, namely the randomized controlled trials (RCT), give the best evidence of the effect of a technology. However, the ethical issues and the very nature of the intervention under study sometimes make it difficult to carry out an RCT. Therefore, quasi-experimental and non-experimental study designs are also applied. The critical issues concerning these designs are discussed. The results of evaluative studies are of importance for decision-makers in health policy. The measurements of the impact of a medical technology should go beyond a statement of its effectiveness, because the essential outcome of an intervention or programme is the health status and quality of life of the individuals and populations concerned.

Docking, virtual high throughput screening and in silico fragment-based drug design.

ABSTRACT The drug discovery process has been profoundly changed recently by the adoption of computational methods helping the design of new drug candidates more rapidly and at lower costs. In silico drug design consists of a collection of tools helping to make rational decisions at the different steps of the drug discovery process, such as the identification of a biomolecular target of therapeutical interest, the selection or the design of new lead compounds and their modification to obtain better affinities, as well as pharmacokinetic and pharmacodynamic properties. Among the different tools available, a particular emphasis is placed in this review on molecular docking, virtual high throughput screening and fragment-based ligand design.

Application of detection probabilities to the design of amphibian monitoring programs in temporary ponds

Failure to detect a species in an area where it is present is a major source of error in biological surveys. We assessed whether it is possible to optimize single-visit biological monitoring surveys of highly dynamic freshwater ecosystems by framing them a priori within a particular period of time. Alternatively, we also searched for the optimal number of visits and when they should be conducted. We developed single-species occupancy models to estimate the monthly probability of detection of pond-breeding amphibians during a four-year monitoring program. Our results revealed that detection probability was species-specific and changed among sampling visits within a breeding season and also among breeding seasons. Thereby, the optimization of biological surveys with minimal survey effort (a single visit) is not feasible as it proves impossible to select a priori an adequate sampling period that remains robust across years. Alternatively, a two-survey combination at the beginning of the sampling season yielded optimal results and constituted an acceptable compromise between sampling efficacy and survey effort. Our study provides evidence of the variability and uncertainty that likely affects the efficacy of monitoring surveys, highlighting the need of repeated sampling in both ecological studies and conservation management.

Nest-box design for the study of diurnal raptors and owls is still an overlooked point in ecological, evolutionary and conservation studies: a review

The use of artificial nest-boxes has led to significant progress in bird conservation and in our understanding of the functional and evolutionary ecology of free-ranging birds that exploit cavities for roosting and reproduction. Nest-boxes and their improved accessibility have made it easier to perform comparative and experimental field investigations. However, concerns about the generality and applicability of scientific studies involving birds breeding in nest-boxes have been raised because the occupants of boxes may differ from conspecifics occupying other nest sites. Here we review the existing evidence demonstrating the importance of nest-box design to individual life-history traits in three falcon (Falconiformes) and seven owl (Strigiformes) species, as well as the extent to which publications on these birds describe the characteristics of exploited artificial nest-boxes in their 'methods' sections. More than 60% of recent publications did not provide any details on nest-box design (e.g. size, shape, material), despite several calls >15 years ago to increase the reporting of such information. We exemplify and discuss how variation in nest-box characteristics can affect or confound conclusions from nest-box studies and conclude that it is of overall importance to present details of nest-box characteristics in scientific publications.