Matthieu Montes

Genomewide association study of an AIDS-nonprogression cohort emphasizes the role played by HLA genes (ANRS genomewide association study 02)

To elucidate the genetic factors predisposing to AIDS progression, we analyzed a unique cohort of 275 human immunodeficiency virus (HIV) type 1-seropositive nonprogressor patients in relation to a control group of 1352 seronegative individuals in a genomewide association study (GWAS). The strongest association was obtained for HCP5 rs2395029 (P=6.79x10(-10); odds ratio, 3.47) and was possibly linked to an effect of sex. Interestingly, this single-nucleotide polymorphism (SNP) was in high linkage disequilibrium with HLA-B, MICB, TNF, and several other HLA locus SNPs and haplotypes. A meta-analysis of our genomic data combined with data from the previously conducted Euro-CHAVI (Center for HIV/AIDS Vaccine Immunology) GWAS confirmed the HCP5 signal (P=3.02x10(-19)) and identified several new associations, all of them involving HLA genes: MICB, TNF, RDBP, BAT1-5, PSORS1C1, and HLA-C. Finally, stratification by HCP5 rs2395029 genotypes emphasized an independent role for ZNRD1, also in the HLA locus, and this finding was confirmed by experimental data. The present study, the first GWAS of HIV-1 nonprogressors, underscores the potential for some HLA genes to control disease progression soon after infection.

Genomewide Association Study of a Rapid Progression Cohort Identifies New Susceptibility Alleles for AIDS (ANRS Genomewide Association Study 03)

BACKGROUND Previous genomewide association studies (GWASs) of AIDS have targeted end points based on the control of viral load and disease nonprogression. The discovery of genetic factors that predispose individuals to rapid progression to AIDS should also reveal new insights into the molecular etiology of the pathology. METHODS We undertook a case-control GWAS of a unique cohort of 85 human immunodeficiency virus type 1 (HIV-1)-infected patients who experienced rapid disease progression, using Illumina HumanHap300 BeadChips. The case group was compared with a control group of 1352 individuals for the 291,119 autosomal single-nucleotide polymorphisms (SNPs) passing the quality control tests, using the false-discovery rate (FDR) statistical method for multitest correction. RESULTS Novel associations with rapid progression (FDR, < or = 25%) were identified for PRMT6 (P = 6.1 x 10(-7); odds ratio [OR], 0.24), SOX5 (P = 1.8 x 10(-6); OR, 0.45), RXRG (P = 3.9 x 10(-6); OR, 3.29), and TGFBRAP1 (P = 7 x 10(-6); OR, 0.34). The haplotype analysis identified exonic and promoter SNPs potentially important for PRMT6 and TGFBRAP1 function. CONCLUSIONS The statistical and biological relevance of these associations and their high ORs underscore the power of extreme phenotypes for GWASs, even with a modest sample size. These genetic results emphasize the role of the transforming growth factor beta pathway in the pathogenesis of HIV-1 disease. Finally, the wealth of information provided by this study should help unravel new diagnostic and therapeutic targets.

Structure‐based virtual ligand screening with LigandFit: Pose prediction and enrichment of compound collections

Virtual ligand screening methods based on the structure of the receptor are extensively used to facilitate the discovery of lead compounds. In the present study, we investigated the LigandFit package on four different proteins (coagulation factor VIIa, estrogen receptor, thymidine kinase, and neuraminidase), a relatively large compound collection of 65,560 unique “drug‐like” molecules and four focused libraries (1950 molecules each). We performed virtual screening experiments with the large database and evaluated six scoring functions available in the package (DockScore, LigScore1, LigScore2, PLP1, PLP2, and PMF). The results showed that LigandFit is an efficient program, especially when used with LigScore1. Similar computations were carried out using focused libraries. In this situation the LigScore1 scoring function outperformed the other ones on three out of the four proteins tested. Even for the difficult neuraminidase case, the LigandFit/LigScore1 combination was still reasonably successful. Assessment of docking accuracy was also performed and again, we found that LigandFit (with DockScore and the CFF parameters) was performing well. On the basis of these results and observed increased enrichments after LigandFit/Ligscore1 screening on focused libraries, we suggest that using this program as a final step of a hierarchical protocol can be very beneficial to assist lead finding. Proteins 2007.

Novel organic proteasome inhibitors identified by virtual and in vitro screening.

Proteasome inhibition is a promising strategy for treating cancers. Herein, we report the discovery of novel drug-like inhibitors of mammalian proteasome 20S using a multistep structure-based virtual ligand screening strategy. Sulfone- or piperazine-containing hits essentially belong to the under-represented class of noncovalent and nonpeptidic proteasome inhibitors. Several of our compounds act in the micromolar range and are cytotoxic on human tumoral cell lines. Optimization of these molecules could lead to better anticancer therapy.

Benchmarking Data Sets for the Evaluation of Virtual Ligand Screening Methods: Review and Perspectives.

Virtual screening methods are commonly used nowadays in drug discovery processes. However, to ensure their reliability, they have to be carefully evaluated. The evaluation of these methods is often realized in a retrospective way, notably by studying the enrichment of benchmarking data sets. To this purpose, numerous benchmarking data sets were developed over the years, and the resulting improvements led to the availability of high quality benchmarking data sets. However, some points still have to be considered in the selection of the active compounds, decoys, and protein structures to obtain optimal benchmarking data sets.

Targeting IL-6 by both passive or active immunization strategies prevents bleomycin-induced skin fibrosis

IntroductionInterleukin-6 (IL-6) is a pleiotropic cytokine for which preliminary data have suggested that it might contribute to systemic sclerosis (SSc). Our aims were to investigate, firstly, IL-6 expression in patients with SSc and, secondly, the efficacy of both passive and active immunization against IL-6 to reduce skin fibrosis in complementary mouse models of SSc.MethodsHuman serum levels and skin expression of IL-6 were determined by enzyme-linked immunosorbent assay and immunohistochemistry, respectively. We first evaluated the antifibrotic properties of the monoclonal anti-IL-6R antibody, MR16-1, in the bleomycin-induced dermal fibrosis mouse model, reflecting early and inflammatory stages of SSc. Then, we assessed the efficacy of MR16-1 in tight skin-1 (Tsk-1) mice, an inflammation-independent model of skin fibrosis. Additionally, we have developed an innovative strategy using an anti-IL-6 peptide-based active immunization. Infiltrating leukocytes, T cells, and B cells were quantified, and IL-6 levels were measured in the serum and lesional skin of mice after passive or active immunization.ResultsSerum and skin levels of IL-6 were significantly increased in patients with early SSc. Treatment with MR16-1 led in the bleomycin mouse model to a 25% (P = 0.02) and 30% (P = 0.007) reduction of dermal thickness and hydroxyproline content, respectively. MR16-1 demonstrated no efficacy in Tsk-1 mice. Thereafter, mice were immunized against a small peptide derived from murine IL-6 and this strategy led in the bleomycin model to a 20% (P = 0.02) and 25% (P = 0.005) decrease of dermal thickness and hydroxyproline content, respectively. Passive and active immunization led to decreased T-cell infiltration in the lesional skin of mice challenged with bleomycin. Upon bleomycin injections, serum and skin IL-6 levels were increased after treatment with MR16-1 and were significantly reduced after anti-IL-6 active immunization.ConclusionsOur results support the relevance of targeting IL-6 in patients with early SSc since IL-6 is overexpressed in early stages of the disease. Targeting IL-6 by both passive and active immunization strategies prevented the development of bleomycin-induced dermal fibrosis in mice. Our results highlight the therapeutic potential of active immunization against IL-6, which is a seductive alternative to passive immunization.

SCREENING LOW FREQUENCY SNPS FROM GENOME WIDE ASSOCIATION STUDY REVEALS A NEW RISK ALLELE FOR PROGRESSION TO AIDS

Background: Seven genome-wide association studies (GWAS) have been published in AIDS, and only associations in the HLA region on chromosome 6 and CXCR6 have passed genome-wide significance. Methods: We reanalyzed the data from 3 previously published GWAS, targeting specifically low-frequency SNPs (minor allele frequency <5%). Two groups composed of 365 slow progressors and 147 rapid progressors from Europe and the United States were compared with a control group of 1394 seronegative individuals using Eigenstrat corrections. Results: Of the 8584 SNPs with minor allele frequency <5% in cases and controls (Bonferroni threshold = 5.8 × 10−6), 4 SNPs showed statistical evidence of association with the slow progressor phenotype. The best result was for HCP5 rs2395029 [P = 8.54 × 10−15, odds ratio (OR) = 3.41] in the HLA locus, in partial linkage disequilibrium with 2 additional chromosome 6 associations in C6orf48 (P = 3.03 × 10−10, OR = 2.9) and NOTCH4 (9.08 × 10−07, OR = 2.32). The fourth association corresponded to rs2072255 located in RICH2 (P = 3.30 × 10−06, OR = 0.43) in chromosome 17. Using HCP5 rs2395029 as a covariate, the C6orf48 and NOTCH4 signals disappeared, but the RICH2 signal still remained significant. Conclusions: Besides the already known chromosome 6 associations, the analysis of low-frequency SNPs brought up a new association in the RICH2 gene. Interestingly, RICH2 interacts with BST-2 known to be a major restriction factor for HIV-1 infection. Our study has thus identified a new candidate gene for AIDS molecular etiology and confirms the interest of singling out low-frequency SNPs to exploit GWAS data.

Multicohort Genomewide Association Study Reveals a New Signal of Protection Against HIV-1 Acquisition

BACKGROUND To date, only mutations in CCR5 have been shown to confer resistance to human immunodeficiency virus type 1 (HIV-1) infection, and these explain only a small fraction of the observed variability in HIV susceptibility. METHODS We performed a meta-analysis between 2 independent European genomewide association studies, each comparing HIV-1 seropositive cases with normal population controls known to be HIV uninfected, to identify single-nucleotide polymorphisms (SNPs) associated with the HIV-1 acquisition phenotype. SNPs exhibiting P < 10(-5) in this first stage underwent second-stage analysis in 2 independent US cohorts of European descent. RESULTS After the first stage, a single highly significant association was revealed for the chromosome 8 rs6996198 with HIV-1 acquisition and was replicated in both second-stage cohorts. Across the 4 groups, the rs6996198-T allele was consistently associated with a significant reduced risk of HIV-1 infection, and the global meta-analysis reached genomewide significance: P(combined) = 7.76 × 10(-8). CONCLUSIONS We provide strong evidence of association for a common variant with HIV-1 acquisition in populations of European ancestry. This protective signal against HIV-1 infection is the first identified outside the CCR5 nexus. First clues point to a potential functional role for a nearby candidate gene, CYP7B1, but this locus warrants further investigation.

Structure-based discovery of a small non-peptidic Neuropilins antagonist exerting in vitro and in vivo anti-tumor activity on breast cancer model

Neuropilin-1/-2 (+33 NRPs), VEGF-A165 co-receptors, are over-expressed during cancer progression. Thus, NRPs targeted drug development is challenged using a multistep in silico/in vitro screening procedure. The first fully non-peptidic VEGF-A165/NRPs protein-protein interaction antagonist (IC50=34 μM) without effect on pro-angiogenic kinases has been identified (compound-1). This hit showed breast cancer cells anti-proliferative activity (IC50=0.60 μM). Compound-1 treated NOG-xenografted mice significantly exerted tumor growth inhibition, which is correlated with Ki-67(low) expression and apoptosis. Furthermore, CD31(+)/CD34(+) vessels are reduced in accordance with HUVEC-tube formation inhibition (IC50=0.20 μM). Taking together, compound-1 is the first fully organic inhibitor targeting NRPs.

Predictiveness curves in virtual screening

BackgroundIn the present work, we aim to transfer to the field of virtual screening the predictiveness curve, a metric that has been advocated in clinical epidemiology. The literature describes the use of predictiveness curves to evaluate the performances of biological markers to formulate diagnoses, prognoses and assess disease risks, assess the fit of risk models, and estimate the clinical utility of a model when applied to a population. Similarly, we use logistic regression models to calculate activity probabilities related to the scores that the compounds obtained in virtual screening experiments. The predictiveness curve can provide an intuitive and graphical tool to compare the predictive power of virtual screening methods.ResultsSimilarly to ROC curves, predictiveness curves are functions of the distribution of the scores and provide a common scale for the evaluation of virtual screening methods. Contrarily to ROC curves, the dispersion of the scores is well described by predictiveness curves. This property allows the quantification of the predictive performance of virtual screening methods on a fraction of a given molecular dataset and makes the predictiveness curve an efficient tool to address the early recognition problem. To this last end, we introduce the use of the total gain and partial total gain to quantify recognition and early recognition of active compounds attributed to the variations of the scores obtained with virtual screening methods. Additionally to its usefulness in the evaluation of virtual screening methods, predictiveness curves can be used to define optimal score thresholds for the selection of compounds to be tested experimentally in a drug discovery program. We illustrate the use of predictiveness curves as a complement to ROC on the results of a virtual screening of the Directory of Useful Decoys datasets using three different methods (Surflex-dock, ICM, Autodock Vina).ConclusionThe predictiveness curves cover different aspects of the predictive power of the scores, allowing a detailed evaluation of the performance of virtual screening methods. We believe predictiveness curves efficiently complete the set of tools available for the analysis of virtual screening results.