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.

A protocol was devised in which FRED, DOCK, and Surflex were combined in a multistep virtual ligand screening (VLS) procedure to screen the pocket of four different proteins. One goal was to evaluate the impact of chaining "freely available packages to academic users" on docking/scoring accuracy and CPU time consumption. A bank of 65 660 compounds including 49 known actives was generated. Our procedure is successful because docking/scoring parameters are tuned according to the nature of the binding pocket and because a shape-based filtering tool is applied prior to flexible docking. The obtained enrichment factors are in line with those reported in recent studies. We suggest that consensus docking/scoring could be valuable to some drug discovery projects. The present protocol could process the entire bank for one receptor in less than a week on one processor, suggesting that VLS experiments could be performed even without large computer resources.

Eur. J. Immunol. 2014Immunol. . 44: 2802Immunol. -2810 Clinical immunology 2803 IntroductionTo date, no effective therapeutic or prophylactic HIV vaccines are yet available. Recent encouraging results from the RV 144 trial showed a modest but statistically significant 31% reduction in the rate of HIV infection in vaccinated healthy volunteers receiving a prophylactic vaccine [1]. However, immune responses that would eradicate or control HIV are likely to be different from those needed to prevent primary infection. Indeed, eradication of HIV infection is likely to depend on the establishment of strong cytotoxic T lymphocytes, while prevention of infection will likely depend on the establishment of antibodies neutralizing the virus [2,3]. In both cases, CD4 + T helper cells are necessary for the establishment of robust and long-lasting immunity. Several candidate vaccines are under evaluation including peptides, inactivated virus, viral vectors, and ex vivo-generated DCs [4]. The latter represents an approach to optimize the induction of immune responses [5]. To date, only two studies, in which DCs have been loaded with chemically inactivated autologous virus, have reported a decrease in viral load [6,7]. Another approach using DCs transfected with RNA isolated from autologous virus yielded immune responses without control of viral replication [8]. However, these very promising data with inactivated autologous virus still need to be reproduced. For large scale use of DC vaccination, it would be advantageous to identify an antigenic cargo that could be used without having to isolate and expand the autologous virus which necessitates antiretroviral treatment interruption. We report here the safety and immunogenicity of a new DC platform loaded with five HIV-1-derived lipopeptides (LP) [9] in HIV-1-infected patients treated with highly active antiretroviral treatment (HAART). The study design included a 6-month analytical treatment interruption (ATI), a period which allowed us to evaluate the effects of vaccine-elicited immune responses on viral replication (Fig. 1). Results Patients and study outcomesTwenty patients were screened and 19 were enrolled within 17 months. Baseline characteristics of patients are reported in Table 1. All patients received the four vaccinations with no changes in vaccine dose. All patients but one completed the trial at 48 weeks.The vaccination was well tolerated. Two patients reached a safety endpoint (CD4 + T-cell counts below 500 cells/μL) during the vaccination phase while no safety endpoints were observed during the ATI phase. Systemic or local adverse events were mild or moderate (grade 1 or 2) and resolved in less than 2 days in the majority of cases. All patients stopped HAART at 24 weeks post inclusion except two of them who stopped at 25 and 26 weeks.Through 48 weeks, eight patients reached the immunology endpoint defining a failure of the strategy: at 28 (two patients), 32 (three patients), 36, 40, and 44 weeks. Three of these patients resumed HAART. No clinical events or pro...

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.Electronic supplementary materialThe online version of this article (doi:10.1186/s13321-015-0100-8) contains supplementary material, which is available to authorized users.

In silico screening based on the structures of the ligands or of the receptors has become an essential tool to facilitate the drug discovery process but compound collections are needed to carry out such in silico experiments. It has been recognized that absorption, distribution, metabolism, excretion and toxicity (ADME/tox) are key properties that need to be considered early on, even during the database preparation stage. FAF-Drugs is an online service based on Frowns (a chemoinformatics toolkit) that allows users to process their own compound collections via simple ADME/Tox filtering rules such as molecular weight, polar surface area, logP or number of rotatable bonds. SMILES (Simplified Molecular Input Line Entry System), CANSMILES (canonical smiles) or SDF (structure data file) files are required as input and molecules that pass or do not pass the filters are sent back in CANSMILES format. This service should thus help scientists engaging in drug discovery campaigns. Other utilities and several compound collections suitable for in silico screening are available at our site. FAF-Drugs can be accessed at .

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.

We provide an unsupervised adaptive sampling strategy capable of producing μs-timescale molecular dynamics (MD) simulations of large biosystems using many-body polarizable force fields (PFF). The global exploration problem is decomposed...

Nuclear receptors (NRs) constitute an important class of drug targets. We created the most exhaustive NR-focused benchmarking database to date, the NRLiSt BDB (NRs ligands and structures benchmarking database). The 9905 compounds and 339 structures of the NRLiSt BDB are ready for structure-based and ligand-based virtual screening. In the present study, we detail the protocol used to generate the NRLiSt BDB and its features. We also give some examples of the errors that we found in ChEMBL that convinced us to manually review all original papers. Since extensive and manually curated experimental data about NR ligands and structures are provided in the NRLiSt BDB, it should become a powerful tool to assess the performance of virtual screening methods on NRs, to assist the understanding of NR's function and modulation, and to support the discovery of new drugs targeting NRs. NRLiSt BDB is freely available online at http://nrlist.drugdesign.fr .