[R74W;R1070W;D1270N]: a new complex allele responsible for cystic fibrosis.

Since the beginning of population screening for CF carriers, it has become apparent that complex CFTR alleles are not uncommon. Deciphering their impact in disease pathogenesis remains a challenge for both clinicians and researchers. We report the observation of a new complex allele p.[R74W+R1070W+D1270N] found in trans with a type 1 mutation and associated with clinical diagnosis of cystic fibrosis in a one year-old Moroccan patient. This case underlines the difficulties in counseling patients with uncommon mutations and the necessity of functional studies to evaluate the structure-function relationships, since the association of several variations in cis can dramatically alter CFTR function.

The use of biodiversity as source of new chemical entities against defined molecular targets for treatment of malaria, tuberculosis, and T-cell mediated diseases: a review

The modern approach to the development of new chemical entities against complex diseases, especially the neglected endemic diseases such as tuberculosis and malaria, is based on the use of defined molecular targets. Among the advantages, this approach allows (i) the search and identification of lead compounds with defined molecular mechanisms against a defined target (e.g. enzymes from defined pathways), (ii) the analysis of a great number of compounds with a favorable cost/benefit ratio, (iii) the development even in the initial stages of compounds with selective toxicity (the fundamental principle of chemotherapy), (iv) the evaluation of plant extracts as well as of pure substances. The current use of such technology, unfortunately, is concentrated in developed countries, especially in the big pharma. This fact contributes in a significant way to hamper the development of innovative new compounds to treat neglected diseases. The large biodiversity within the territory of Brazil puts the country in a strategic position to develop the rational and sustained exploration of new metabolites of therapeutic value. The extension of the country covers a wide range of climates, soil types, and altitudes, providing a unique set of selective pressures for the adaptation of plant life in these scenarios. Chemical diversity is also driven by these forces, in an attempt to best fit the plant communities to the particular abiotic stresses, fauna, and microbes that co-exist with them. Certain areas of vegetation (Amazonian Forest, Atlantic Forest, Araucaria Forest, Cerrado-Brazilian Savanna, and Caatinga) are rich in species and types of environments to be used to search for natural compounds active against tuberculosis, malaria, and chronic-degenerative diseases. The present review describes some strategies to search for natural compounds, whose choice can be based on ethnobotanical and chemotaxonomical studies, and screen for their ability to bind to immobilized drug targets and to inhibit their activities. Molecular cloning, gene knockout, protein expression and purification, N-terminal sequencing, and mass spectrometry are the methods of choice to provide homogeneous drug targets for immobilization by optimized chemical reactions. Plant extract preparations, fractionation of promising plant extracts, propagation protocols and definition of in planta studies to maximize product yield of plant species producing active compounds have to be performed to provide a continuing supply of bioactive materials. Chemical characterization of natural compounds, determination of mode of action by kinetics and other spectroscopic methods (MS, X-ray, NMR), as well as in vitro and in vivo biological assays, chemical derivatization, and structure-activity relationships have to be carried out to provide a thorough knowledge on which to base the search for natural compounds or their derivatives with biological activity.

Relacions estructura-propietat per un conjunt d'hidrocarburs a partir de nous descriptors tridimensionals derivats de la semblança molecular quàntica

En aquest article es defineixen uns nous índexs tridimensionals per a la descripció de les molècules a partir de paràmetres derivats de la Teoria de la Semblança Molecular i de les distàncies euclidianes entre els àtoms i les càrregues atòmiques efectives. Aquests indexs,anomenats 3D, s'han aplicat a l'estudi de les relacions estructura-propietat d'una família d'hidrocarburs, i han demostrat una capacitat de descripció de tres propietats de la família (temperatura d'ebullició, temperatura de fusió i densitat) molt més acurada que quan s'utilitzen els indexs 2D clàssics

Computational drug design strategies applied to the modelling of human immunodeficiency virus-1 reverse transcriptase inhibitors

Reverse transcriptase (RT) is a multifunctional enzyme in the human immunodeficiency virus (HIV)-1 life cycle and represents a primary target for drug discovery efforts against HIV-1 infection. Two classes of RT inhibitors, the nucleoside RT inhibitors (NRTIs) and the nonnucleoside transcriptase inhibitors are prominently used in the highly active antiretroviral therapy in combination with other anti-HIV drugs. However, the rapid emergence of drug-resistant viral strains has limited the successful rate of the anti-HIV agents. Computational methods are a significant part of the drug design process and indispensable to study drug resistance. In this review, recent advances in computer-aided drug design for the rational design of new compounds against HIV-1 RT using methods such as molecular docking, molecular dynamics, free energy calculations, quantitative structure-activity relationships, pharmacophore modelling and absorption, distribution, metabolism, excretion and toxicity prediction are discussed. Successful applications of these methodologies are also highlighted.

Examining the Agreement of Structural Loss Measured With Heidelberg Retinal Tomograhy and Functional Loss With Standard Automated Perimetry (SAP; Octopus), Pulsar Perimetry (PP), and Moorfields Motion Displacement Test (MDT) Perimetry

Purpose: To examine the relationship of functional measurements with structural measures. Methods: 146 eyes of 83 test subjects underwent Heidelberg Retinal Tomography (HRTIII) (disc area<2.43, mphsd<40), and perimetry testing with Octopus (SAP; Dynamic), Pulsar (PP; TOP) and Moorfields MDT (ESTA). Glaucoma was defined as progressive structural or functional loss (20 eyes). Perimetry test points were grouped into 6 sectors based on the estimated optic nerve head angle into which the associated nerve fiber bundle enters (Garway-Heath map). Perimetry summary measures (PSM) (MD SAP/ MD PP/ PTD MDT) were calculated from the average total deviation of each measured threshold from the normal for each sector. We calculated the 95% significance level of the sectorial PSM from the respective normative data. We calculated the percentage agreement with group1 (G1), healthy on HRT and within normal perimetric limits, and group 2 (G2), abnormal on HRT and outside normal perimetric limits. We also examined the relationship of PSM and rim area (RA) in those sectors classified as abnormal by MRA (Moorfields Regression Analysis) of HRT. Results: The mean age was 65 (range= [37, 89]). The global sensitivity versus specificity of each instrument in detecting glaucomatous eyes was: MDT 80% vs. 88%, SAP 80% vs. 80%, PP 70% vs. 89% and HRT 80% vs. 79%. Highest percentage agreement of HRT (respectively G1, G2, sector) with PSM were MDT (89%, 57%, nasal superior), SAP (83%, 74%, temporal superior), PP (74%, 63%, nasal superior). Globally percentage agreement (respectively G1, G2) was MDT (92%, 28%), SAP (87%, 40%) and PP (77%, 49%). Linear regression showed there was no significant trend globally associating RA and PSM. However, sectorally the supero-nasal sector had a statistically significant (p<0.001) trend with each instrument, the associated r2 coefficients are (MDT 0.38 SAP 0.56 and PP 0.39). Conclusions: There were no significant differences in global sensitivity or specificity between instruments. Structure-function relationships varied significantly between instruments and were consistently strongest supero-nasally. Further studies are required to investigate these relationships in detail.

Molecular modeling of peptide-MHC class I complexes : applications to peptide based immunotherapy

Summary The specific CD8+ T cell immune response against tumors relies on the recognition by the T cell receptor (TCR) on cytotoxic T lymphocytes (CTL) of antigenic peptides bound to the class I major histocompatibility complex (MHC) molecule. Such tumor associated antigenic peptides are the focus of tumor immunotherapy with peptide vaccines. The strategy for obtaining an improved immune response often involves the design of modified tumor associated antigenic peptides. Such modifications aim at creating higher affinity and/or degradation resistant peptides and require precise structures of the peptide-MHC class I complex. In addition, the modified peptide must be cross-recognized by CTLs specific for the parental peptide, i.e. preserve the structure of the epitope. Detailed structural information on the modified peptide in complex with MHC is necessary for such predictions. In this thesis, the main focus is the development of theoretical in silico methods for prediction of both structure and cross-reactivity of peptide-MHC class I complexes. Applications of these methods in the context of immunotherapy are also presented. First, a theoretical method for structure prediction of peptide-MHC class I complexes is developed and validated. The approach is based on a molecular dynamics protocol to sample the conformational space of the peptide in its MHC environment. The sampled conformers are evaluated using conformational free energy calculations. The method, which is evaluated for its ability to reproduce 41 X-ray crystallographic structures of different peptide-MHC class I complexes, shows an overall prediction success of 83%. Importantly, in the clinically highly relevant subset of peptide-HLAA*0201 complexes, the prediction success is 100%. Based on these structure predictions, a theoretical approach for prediction of cross-reactivity is developed and validated. This method involves the generation of quantitative structure-activity relationships using three-dimensional molecular descriptors and a genetic neural network. The generated relationships are highly predictive as proved by high cross-validated correlation coefficients (0.78-0.79). Together, the here developed theoretical methods open the door for efficient rational design of improved peptides to be used in immunotherapy. Résumé La réponse immunitaire spécifique contre des tumeurs dépend de la reconnaissance par les récepteurs des cellules T CD8+ de peptides antigéniques présentés par les complexes majeurs d'histocompatibilité (CMH) de classe I. Ces peptides sont utilisés comme cible dans l'immunothérapie par vaccins peptidiques. Afin d'augmenter la réponse immunitaire, les peptides sont modifiés de façon à améliorer l'affinité et/ou la résistance à la dégradation. Ceci nécessite de connaître la structure tridimensionnelle des complexes peptide-CMH. De plus, les peptides modifiés doivent être reconnus par des cellules T spécifiques du peptide natif. La structure de l'épitope doit donc être préservée et des structures détaillées des complexes peptide-CMH sont nécessaires. Dans cette thèse, le thème central est le développement des méthodes computationnelles de prédiction des structures des complexes peptide-CMH classe I et de la reconnaissance croisée. Des applications de ces méthodes de prédiction à l'immunothérapie sont également présentées. Premièrement, une méthode théorique de prédiction des structures des complexes peptide-CMH classe I est développée et validée. Cette méthode est basée sur un échantillonnage de l'espace conformationnel du peptide dans le contexte du récepteur CMH classe I par dynamique moléculaire. Les conformations sont évaluées par leurs énergies libres conformationnelles. La méthode est validée par sa capacité à reproduire 41 structures des complexes peptide-CMH classe I obtenues par cristallographie aux rayons X. Le succès prédictif général est de 83%. Pour le sous-groupe HLA-A*0201 de complexes de grande importance pour l'immunothérapie, ce succès est de 100%. Deuxièmement, à partir de ces structures prédites in silico, une méthode théorique de prédiction de la reconnaissance croisée est développée et validée. Celle-ci consiste à générer des relations structure-activité quantitatives en utilisant des descripteurs moléculaires tridimensionnels et un réseau de neurones couplé à un algorithme génétique. Les relations générées montrent une capacité de prédiction remarquable avec des valeurs de coefficients de corrélation de validation croisée élevées (0.78-0.79). Les méthodes théoriques développées dans le cadre de cette thèse ouvrent la voie du design de vaccins peptidiques améliorés.

Resting-State Functional Connectivity Emerges from Structurally and Dynamically Shaped Slow Linear Fluctuations.

Brain fluctuations at rest are not random but are structured in spatial patterns of correlated activity across different brain areas. The question of how resting-state functional connectivity (FC) emerges from the brain's anatomical connections has motivated several experimental and computational studies to understand structure-function relationships. However, the mechanistic origin of resting state is obscured by large-scale models' complexity, and a close structure-function relation is still an open problem. Thus, a realistic but simple enough description of relevant brain dynamics is needed. Here, we derived a dynamic mean field model that consistently summarizes the realistic dynamics of a detailed spiking and conductance-based synaptic large-scale network, in which connectivity is constrained by diffusion imaging data from human subjects. The dynamic mean field approximates the ensemble dynamics, whose temporal evolution is dominated by the longest time scale of the system. With this reduction, we demonstrated that FC emerges as structured linear fluctuations around a stable low firing activity state close to destabilization. Moreover, the model can be further and crucially simplified into a set of motion equations for statistical moments, providing a direct analytical link between anatomical structure, neural network dynamics, and FC. Our study suggests that FC arises from noise propagation and dynamical slowing down of fluctuations in an anatomically constrained dynamical system. Altogether, the reduction from spiking models to statistical moments presented here provides a new framework to explicitly understand the building up of FC through neuronal dynamics underpinned by anatomical connections and to drive hypotheses in task-evoked studies and for clinical applications.

The permeability P-glycoprotein: a focus on enantioselectivity and brain distribution.

IMPORTANCE OF THE FIELD: The permeability glycoprotein (P-gp) is an important protein transporter involved in the disposition of many drugs with different chemical structures, but few studies have examined a possible stereoselectivity in its activity. P-gp can have a major impact on the distribution of drugs in selected organs, including the brain. Polymorphisms of the ABCB1 gene, which encodes for P-gp, can influence the kinetics of several drugs. AREAS COVERED IN THIS REVIEW: A search including publications from 1990 up to 2009 was performed on P-gp stereoselectivity and on the impact of ABCB1 polymorphisms on enantiomer brain distribution. WHAT THE READER WILL GAIN: Despite stereoselectivity not being expected because of the large variability of chemical structures of P-gp substrates, structure-activity relationships suggest different P-gp-binding sites for enantiomers. Enantioselectivity in the activity of P-gp has been demonstrated by in vitro studies and in animal models (preferential transport of one enantiomer or different inhibitory potencies towards P-gp activity between enantiomers). There is also in vivo evidence of an enantioselective drug transport at the human blood-brain barrier. TAKE HOME MESSAGE: The significant enantioselective activity of P-gp might be clinically relevant and must be taken into account in future studies.

Linker insertion mutagenesis based on IS21 transposition: isolation of an AMP-insensitive variant of catabolic ornithine carbamoyltransferase from Pseudomonas aeruginosa.

The bacterial insertion sequence IS21 when repeated in tandem efficiently promotes non-replicative cointegrate formation in Escherichia coli. An IS21-IS21 junction region which had been engineered to contain unique SalI and BglII sites close to the IS21 termini was not affected in the ability to form cointegrates with target plasmids. Based on this finding, a novel procedure of random linker insertion mutagenesis was devised. Suicide plasmids containing the engineered junction region (pME5 and pME6) formed cointegrates with target plasmids in an E.coli host strain expressing the IS21 transposition proteins in trans. Cointegrates were resolved in vitro by restriction with SalI or BglII and ligation; thus, insertions of four or 11 codons, respectively, were created in the target DNA, practically at random. The cloned Pseudomonas aeruginosa arcB gene encoding catabolic ornithine carbamoyltransferase was used as a target. Of 20 different four-codon insertions in arcB, 11 inactivated the enzyme. Among the remaining nine insertion mutants which retained enzyme activity, three enzyme variants had reduced affinity for the substrate ornithine and one had lost recognition of the allosteric activator AMP. The linker insertions obtained illustrate the usefulness of the method in the analysis of structure-function relationships of proteins.

Identification and characterization of novel classes of macrophage migration inhibitory factor (MIF) inhibitors with distinct mechanisms of action.

Macrophage migration inhibitory factor (MIF), a proinflammatory cytokine, is considered an attractive therapeutic target in multiple inflammatory and autoimmune disorders. In addition to its known biologic activities, MIF can also function as a tautomerase. Several small molecules have been reported to be effective inhibitors of MIF tautomerase activity in vitro. Herein we employed a robust activity-based assay to identify different classes of novel inhibitors of the catalytic and biological activities of MIF. Several novel chemical classes of inhibitors of the catalytic activity of MIF with IC(50) values in the range of 0.2-15.5 microm were identified and validated. The interaction site and mechanism of action of these inhibitors were defined using structure-activity studies and a battery of biochemical and biophysical methods. MIF inhibitors emerging from these studies could be divided into three categories based on their mechanism of action: 1) molecules that covalently modify the catalytic site at the N-terminal proline residue, Pro(1); 2) a novel class of catalytic site inhibitors; and finally 3) molecules that disrupt the trimeric structure of MIF. Importantly, all inhibitors demonstrated total inhibition of MIF-mediated glucocorticoid overriding and AKT phosphorylation, whereas ebselen, a trimer-disrupting inhibitor, additionally acted as a potent hyperagonist in MIF-mediated chemotactic migration. The identification of biologically active compounds with known toxicity, pharmacokinetic properties, and biological activities in vivo should accelerate the development of clinically relevant MIF inhibitors. Furthermore, the diversity of chemical structures and mechanisms of action of our inhibitors makes them ideal mechanistic probes for elucidating the structure-function relationships of MIF and to further determine the role of the oligomerization state and catalytic activity of MIF in regulating the function(s) of MIF in health and disease.

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.

Progress on Lamellarins

This review covers recent literature on the lamellarins, a family of marine natural products, and related analogs, encompassing synthetic strategies for total synthesis, structure-activity relationships (SAR), and studies on mechanisms of biological action, namely in the context of antitumor activity. It reviews work published from January 2008 to December 2010.

Recent advances in lamellarin alkaloids: isolation, synthesis and activity

Lamellarins are a large family of marine alkaloids with potential anticancer activity that have been isolated from diverse marine organisms, mainly ascidians and sponges. All lamellarins feature a 3,4-diarylpyrrole system. Pentacyclic lamellarins, whose polyheterocyclic system has a pyrrole core, are the most active compounds. Some of these alkaloids are potently cytotoxic to various tumor cell lines. To date, Lam-D and Lam-H have been identified as lead compounds for the inhibition of topoisomerase I and HIV-1 integrase, respectively nuclear enzymes which are over-expressed in deregulation disorders. Moreover,these compounds have been reported for their efficacy in treatment of multi-drug resistant (MDR) tumors cells without mediated drug efflux, as well as their immunomodulatory activity and selectivity towards melanoma cell lines. This article is an overview of recent literature on lamellarins, encompassing their isolation, recent synthetic strategies for their total synthesis, the preparation of their analogs, studies on their mechanisms of action, and their structure-activity relationships (SAR).

A web-based tool to aid the identification of chemicals potentially posing a health risk through percutaneous exposure

Occupational hygiene practitioners typically assess the risk posed by occupational exposure by comparing exposure measurements to regulatory occupational exposure limits (OELs). In most jurisdictions, OELs are only available for exposure by the inhalation pathway. Skin notations are used to indicate substances for which dermal exposure may lead to health effects. However, these notations are either present or absent and provide no indication of acceptable levels of exposure. Furthermore, the methodology and framework for assigning skin notation differ widely across jurisdictions resulting in inconsistencies in the substances that carry notations. The UPERCUT tool was developed in response to these limitations. It helps occupational health stakeholders to assess the hazard associated with dermal exposure to chemicals. UPERCUT integrates dermal quantitative structure-activity relationships (QSARs) and toxicological data to provide users with a skin hazard index called the dermal hazard ratio (DHR) for the substance and scenario of interest. The DHR is the ratio between the estimated 'received' dose and the 'acceptable' dose. The 'received' dose is estimated using physico-chemical data and information on the exposure scenario provided by the user (body parts exposure and exposure duration), and the 'acceptable' dose is estimated using inhalation OELs and toxicological data. The uncertainty surrounding the DHR is estimated with Monte Carlo simulation. Additional information on the selected substances includes intrinsic skin permeation potential of the substance and the existence of skin notations. UPERCUT is the only available tool that estimates the absorbed dose and compares this to an acceptable dose. In the absence of dermal OELs it provides a systematic and simple approach for screening dermal exposure scenarios for 1686 substances.

Compostos de platina em quimioterapia do câncer

The vast majority of clinically used antitumor drugs are either synthetic or natural product based organic compounds. In this review we describe different aspects, such as structure-activity relationships, mechanism of action, clinical uses and possible future prospects, of the platinum antitumor complexes, a distinct class of antitumor agents.