Considering Stage Direction as Building Informed Virtual Environments

This article begins with some recent considerations about real-time music, inspired by the latest contribution of French composer Philippe Manoury. Then, through the case study of the scenic performance La Traversée de la nuit, we analyse some perspectives for designing an Informed Virtual Environment dedicated to live show artistic domain.

Integração das técnicas de triagem virtual e triagem biológica automatizada em alta escala: oportunidades e desafios em P&D de fármacos

High-throughput screening (HTS) and virtual screening (VS) are useful methods employed in drug discovery, allowing the identification of promising hits for lead optimization. The efficiency of these approaches depends on a number of factors, such as the organization of high quality databases of compounds and the parameterization of essential components of the screen process. This brief review presents the basic principles of the HTS and VS methods, as well as a perspective of the utility and integration of these drug design approaches, highlighting current opportunities and future challenges in medicinal chemistry.

Composition d'oeuvres pour hyper-flûtes et traitement audionumérique interactif

La version intégrale de cette thèse est disponible uniquement pour consultation individuelle à la Bibliothèque de musique de l’Université de Montréal (www.bib.umontreal.ca/MU).

Spectroscopic analysis of terrestrial analogues for the interpretation of surface composition of rocky bodies in the solar system. Effects of mineral mixing and particle size. Applications to moon, mars and implications for mercury.

Among the Solar System’s bodies, Moon, Mercury and Mars are at present, or have been in the recent years, object of space missions aimed, among other topics, also at improving our knowledge about surface composition. Between the techniques to detect planet’s mineralogical composition, both from remote and close range platforms, visible and near-infrared reflectance (VNIR) spectroscopy is a powerful tool, because crystal field absorption bands are related to particular transitional metals in well-defined crystal structures, e.g., Fe2+ in M1 and M2 sites of olivine or pyroxene (Burns, 1993). Thanks to the improvements in the spectrometers onboard the recent missions, a more detailed interpretation of the planetary surfaces can now be delineated. However, quantitative interpretation of planetary surface mineralogy could not always be a simple task. In fact, several factors such as the mineral chemistry, the presence of different minerals that absorb in a narrow spectral range, the regolith with a variable particle size range, the space weathering, the atmosphere composition etc., act in unpredictable ways on the reflectance spectra on a planetary surface (Serventi et al., 2014). One method for the interpretation of reflectance spectra of unknown materials involves the study of a number of spectra acquired in the laboratory under different conditions, such as different mineral abundances or different particle sizes, in order to derive empirical trends. This is the methodology that has been followed in this PhD thesis: the single factors previously listed have been analyzed, creating, in the laboratory, a set of terrestrial analogues with well-defined composition and size. The aim of this work is to provide new tools and criteria to improve the knowledge of the composition of planetary surfaces. In particular, mixtures composed with different content and chemistry of plagioclase and mafic minerals have been spectroscopically analyzed at different particle sizes and with different mineral relative percentages. The reflectance spectra of each mixture have been analyzed both qualitatively (using the software ORIGIN®) and quantitatively applying the Modified Gaussian Model (MGM, Sunshine et al., 1990) algorithm. In particular, the spectral parameter variations of each absorption band have been evaluated versus the volumetric FeO% content in the PL phase and versus the PL modal abundance. This delineated calibration curves of composition vs. spectral parameters and allow implementation of spectral libraries. Furthermore, the trends derived from terrestrial analogues here analyzed and from analogues in the literature have been applied for the interpretation of hyperspectral images of both plagioclase-rich (Moon) and plagioclase-poor (Mars) bodies.

Improvement of Virtual Screening Predictions using Computational Intelligence Methods

Virtual Screening (VS) methods can considerably aid clinical research, predicting how ligands interact with drug targets. However, the accuracy of most VS methods is constrained by limitations in the scoring function that describes biomolecular interactions, and even nowadays these uncertainties are not completely understood. In order to improve accuracy of scoring functions used in most VS methods we propose a hybrid novel approach where neural networks (NNET) and support vector machines (SVM) methods are trained with databases of known active (drugs) and inactive compounds, this information being exploited afterwards to improve VS predictions.

Descubrimiento de fármacos basado en cribado virtual refinado con enfoques neuronales paralelos

En el campo de la medicina clínica es crucial poder determinar la seguridad y la eficacia de los fármacos actuales y además acelerar el descubrimiento de nuevos compuestos activos. Para ello se llevan a cabo ensayos de laboratorio, que son métodos muy costosos y que requieren mucho tiempo. Sin embargo, la bioinformática puede facilitar enormemente la investigación clínica para los fines mencionados, ya que proporciona la predicción de la toxicidad de los fármacos y su actividad en enfermedades nuevas, así como la evolución de los compuestos activos descubiertos en ensayos clínicos. Esto se puede lograr gracias a la disponibilidad de herramientas de bioinformática y métodos de cribado virtual por ordenador (CV) que permitan probar todas las hipótesis necesarias antes de realizar los ensayos clínicos, tales como el docking estructural, mediante el programa BINDSURF. Sin embargo, la precisión de la mayoría de los métodos de CV se ve muy restringida a causa de las limitaciones presentes en las funciones de afinidad o scoring que describen las interacciones biomoleculares, e incluso hoy en día estas incertidumbres no se conocen completamente. En este trabajo abordamos este problema, proponiendo un nuevo enfoque en el que las redes neuronales se entrenan con información relativa a bases de datos de compuestos conocidos (proteínas diana y fármacos), y se aprovecha después el método para incrementar la precisión de las predicciones de afinidad del método de CV BINDSURF.

rDock: A Fast, Versatile and Open Source Program for Docking Ligands to Proteins and Nucleic Acids

Identification of chemical compounds with specific biological activities is an important step in both chemical biology and drug discovery. When the structure of the intended target is available, one approach is to use molecular docking programs to assess the chemical complementarity of small molecules with the target; such calculations provide a qualitative measure of affinity that can be used in virtual screening (VS) to rank order a list of compounds according to their potential to be active. rDock is a molecular docking program developed at Vernalis for high-throughput VS (HTVS) applications. Evolved from RiboDock, the program can be used against proteins and nucleic acids, is designed to be computationally very efficient and allows the user to incorporate additional constraints and information as a bias to guide docking. This article provides an overview of the program structure and features and compares rDock to two reference programs, AutoDock Vina (open source) and Schrodinger's Glide (commercial). In terms of computational speed for VS, rDock is faster than Vina and comparable to Glide. For binding mode prediction, rDock and Vina are superior to Glide. The VS performance of rDock is significantly better than Vina, but inferior to Glide for most systems unless pharmacophore constraints are used; in that case rDock and Glide are of equal performance. The program is released under the Lesser General Public License and is freely available for download, together with the manuals, example files and the complete test sets, at http://rdock.sourceforge.net/

Improving drug discovery using hybrid softcomputing methods

Virtual screening (VS) methods can considerably aid clinical research, predicting how ligands interact with drug targets. Most VS methods suppose a unique binding site for the target, but it has been demonstrated that diverse ligands interact with unrelated parts of the target and many VS methods do not take into account this relevant fact. This problem is circumvented by a novel VS methodology named BINDSURF that scans the whole protein surface in order to find new hotspots, where ligands might potentially interact with, and which is implemented in last generation massively parallel GPU hardware, allowing fast processing of large ligand databases. BINDSURF can thus be used in drug discovery, drug design, drug repurposing and therefore helps considerably in clinical research. However, the accuracy of most VS methods and concretely BINDSURF is constrained by limitations in the scoring function that describes biomolecular interactions, and even nowadays these uncertainties are not completely understood. In order to improve accuracy of the scoring functions used in BINDSURF we propose a hybrid novel approach where neural networks (NNET) and support vector machines (SVM) methods are trained with databases of known active (drugs) and inactive compounds, being this information exploited afterwards to improve BINDSURF VS predictions.

Improving drug discovery using a neural networks based parallel scoring function

Virtual Screening (VS) methods can considerably aid clinical research, predicting how ligands interact with drug targets. Most VS methods suppose a unique binding site for the target, but it has been demonstrated that diverse ligands interact with unrelated parts of the target and many VS methods do not take into account this relevant fact. This problem is circumvented by a novel VS methodology named BINDSURF that scans the whole protein surface to find new hotspots, where ligands might potentially interact with, and which is implemented in massively parallel Graphics Processing Units, allowing fast processing of large ligand databases. BINDSURF can thus be used in drug discovery, drug design, drug repurposing and therefore helps considerably in clinical research. However, the accuracy of most VS methods is constrained by limitations in the scoring function that describes biomolecular interactions, and even nowadays these uncertainties are not completely understood. In order to solve this problem, we propose a novel approach where neural networks are trained with databases of known active (drugs) and inactive compounds, and later used to improve VS predictions.

Design and synthesis of E3 ligase RNF5 inhibitors as innovative strategy to trigger mutant CFTR rescue in Cystic Fibrosis

In Cystic Fibrosis (CF) the deletion of phenylalanine 508 (F508del) in the CFTR anion channel is associated to misfolding and defective gating of the mutant protein. Among the known proteins involved in CFTR processing, one of the most promising drug target is the ubiquitin ligase RNF5, which normally promotes F508del-CFTR degradation. In this context, a small molecule RNF5 inhibitor is expected to chemically mimic a condition of RNF5 silencing, thus preventing mutant CFTR degradation and causing its stabilization and plasma membrane trafficking. Hence, by exploiting a virtual screening (VS) campaign, the hit compound inh-2 was discovered as the first-in-class inhibitor of RNF5. Evaluation of inh-2 efficacy on CFTR rescue showed that it efficiently decreases ubiquitination of mutant CFTR and increases chloride current in human primary bronchial epithelia. Based on the promising biological results obtained with inh-2, this thesis reports the structure-based design of potential RNF5 inhibitors having improved potency and efficacy. The optimization of general synthetic strategies gave access to a library of analogues of the 1,2,4-thiadiazol-5-ylidene inh-2 for SAR investigation. The new analogues were tested for their corrector activity in CFBE41o- cells by using the microfluorimetric HS-YFP assay as a primary screen. Then, the effect of putative RNF5 inhibitors on proliferation, apoptosis and the formation of autophagic vacuoles was evaluated. Some of the new analogs significantly increased the basal level of autophagy, reproducing RNF5 silencing effect in cell. Among them, one compound also displayed a greater rescue of the F508del-CFTR trafficking defect than inh-2. Our preliminary results suggest that the 1,2,4-thiadiazolylidene could be a suitable scaffold for the discovery of potential RNF5 inhibitors able to rescue mutant CFTRs. Biological tests are still ongoing to acquire in-depth knowledge about the mechanism of action and therapeutic relevance of this unprecedented pharmacological strategy.

Coronary plaque composition of culprit/target lesions according to the clinical presentation: a virtual histology intravascular ultrasound analysis

AIMS: To evaluate the plaque composition obtained by virtual histology (VH) IVUS according to the clinical presentation and to compare those data to previously published histopathology data. METHODS AND RESULTS: VH was performed on 95 de novo significant lesions (>75% stenosis) in 85 patients [28 acute coronary syndrome (ACS) patients, 30 lesions; 57 stable angina pectoris (SAP) patients, 65 lesions]. There were a higher prevalence of positive remodelling (47 vs. 22%, P=0.013), thrombus (20 vs. 1.5%, P=0.0037), and echo-lucent area (23.3 vs. 7.7%, P=0.047) in ACS patients. At the minimal lumen site, fibrous plaque area was significantly larger in ACS lesions than in SAP lesions (66.0+/-10.7 vs. 61.4+/-8.9%, P=0.034), whereas necrotic core and dense calcium plaque area were smaller in ACS lesions (Necrotic core: 6.8+/-6.0 vs. 11.0+/-8.3%, P=0.02; Dense calcium: 2.6+/-3.0 vs. 4.9+/-5.8%, P=0.03). No differences in rate of thin cap fibroatheroma, thick fibrotheroma, or for the presence of multiple necrotic core layers were observed between both groups. CONCLUSION: Plaque composition obtained by VH-IVUS shows less necrotic core and more fibrous tissue in ACS compared to SAP lesions, which is in contradiction with previously published histopathologic data.

Evaluation of plaque composition by intravascular ultrasound ""virtual histology"": the impact of dense calcium on the measurement of necrotic tissue

Aims: We aimed to evaluate if the co-localisation of calcium and necrosis in intravascular ultrasound virtual histology (IVUS-VH) is due to artefact, and whether this effect can be mathematically estimated. Methods and results: We hypothesised that, in case calcium induces an artefactual coding of necrosis, any addition in calcium content would generate an artificial increment in the necrotic tissue. Stent struts were used to simulate the ""added calcium"". The change in the amount and in the spatial localisation of necrotic tissue was evaluated before and after stenting (n=17 coronary lesions) by means of a especially developed imaging software. The area of ""calcium"" increased from a median of 0.04 mm(2) at baseline to 0.76 mm(2) after stenting (p<0.01). In parallel the median necrotic content increased from 0.19 mm(2) to 0.59 mm(2) (p<0.01). The ""added"" calcium strongly predicted a proportional increase in necrosis-coded tissue in the areas surrounding the calcium-like spots (model R(2)=0.70; p<0.001). Conclusions: Artificial addition of calcium-like elements to the atherosclerotic plaque led to an increase in necrotic tissue in virtual histology that is probably artefactual. The overestimation of necrotic tissue by calcium strictly followed a linear pattern, indicating that it may be amenable to mathematical correction.

Heterogeneity of atherosclerotic plaque phenotypes and composition in four different arterial beds: an intravascular ultrasound virtual histology study

Purpose: The purpose of this study was to compare the plaque morphology between coronary and peripheral arteries using intravascular ultrasound (IVUS). Methods: IVUS was performed in 68 patients with coronary and 93 with peripheral artery lesions (29 carotid, 50 renal, and 14 iliac). Plaques were classified as fibroatheroma (VH-FA) (further subclassified as thin-capped [VH-TCFA] and thick-capped [VH-ThCFA]), fibrocalcific plaque (VH-FC) and pathological intimal thickening (VH-PIT). Results: Plaque rupture (13% of coronary, 7% of carotid, 6% of renal, and 7% of iliac arteries; P=NS) and VH-TCFA (37% of coronary, 24% of carotid, 16% of renal, and 7% of iliac arteries; P=0.02) was observed in all arteries. Compared to coronary arteries, VH-FA was less frequently observed in renal (P<0.001) and iliac arteries (P<0.006), while VH-PIT and VH-FC were prevalent in both of these peripheral arteries. Lesions with positive remodeling demonstrated more characteristics of VH-FA in coronary, carotid, and renal arteries compared to those with intermediate/negative remodeling (all P<0.01). There was positive relationship between RI and percent necrotic core area in all four arteries. Conclusions: Atherosclerotic plaque phenotypes were heterogeneous among four different arteries. In contrast, the associations of remodeling mode with plaque phenotype and composition were similar among the various arterial beds.