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As a critical issue in drug development and postmarketing safety surveillance, drug-induced liver injury (DILI) leads to failures in clinical trials as well as retractions of on-market approved drugs. Therefore, it is important to identify DILI compounds in the early-stages through in silico and in vivo studies. It is difficult using conventional safety testing methods, since the predictive power of most of the existing frameworks is insufficiently effective to address this pharmacological issue. In our study, we employ a natural language processing (NLP) inspired computational framework using convolutional neural networks and molecular fingerprint-embedded features. Our development set and independent test set have 1597 and 322 compounds, respectively. These samples were collected from previous studies and matched with established chemical databases for structural validity. Our study comes up with an average accuracy of 0.89, Matthews’s correlation coefficient (MCC) of 0.80, and an AUC of 0.96. Our results show a significant improvement in the AUC values compared to the recent best model with a boost of 6.67%, from 0.90 to 0.96. Also, based on our findings, molecular fingerprint-embedded featurizer is an effective molecular representation for future biological and biochemical studies besides the application of classic molecular fingerprints.

IntroductionHIV in Vietnam and Southern China is driven by injection drug use. We have implemented HIV prevention interventions for IDUs since 2002–2003 in Lang Son and Ha Giang Provinces, Vietnam and Ning Ming County (Guangxi), China.MethodsInterventions provide peer education and needle/syringe distribution. Evaluation employed serial cross-sectional surveys of IDUs 26 waves from 2002 to 2011, including interviews and HIV testing. Outcomes were HIV risk behaviors, HIV prevalence and incidence. HIV incidence estimation used two methods: 1) among new injectors from prevalence data; and 2) a capture enzyme immunoassay (BED testing) on all HIV+ samples.ResultsWe found significant declines in drug-related risk behaviors and sharp reductions in HIV prevalence among IDUs (Lang Son from 46% to 23% [p<0.001], Ning Ming: from 17% to 11% [p = 0.003], and Ha Giang: from 51% to 18% [p<0.001]), reductions not experienced in other provinces without such interventions. There were significant declines in HIV incidence to low levels among new injectors through 36–48 months, then some rebound, particularly in Ning Ming, but BED-based estimates revealed significant reductions in incidence through 96 months.DiscussionThis is one of the longest studies of HIV prevention among IDUs in Asia. The rebound in incidence among new injectors may reflect sexual transmission. BED-based estimates may overstate incidence (because of false-recent results in patients with long-term infection or on ARV treatment) but adjustment for false-recent results and survey responses on duration of infection generally confirm BED-based incidence trends. Combined trends from the two estimation methods show sharp declines in incidence to low levels. The significant downward trends in all primary outcome measures indicate that the Cross-Border interventions played an important role in bringing HIV epidemics among IDUs under control. The Cross-Border project offers a model of HIV prevention for IDUs that should be considered for large-scale replication.

ISSN: 1759-9954International audienceA series of bio-based diols containing ester, ester-amide and amide linkages were synthesized from methyl undecenoate (derived from ricin oil) and methyl oleate (derived from sunflower oil). These polymerization grade monomers were thoroughly characterized by FTIR-ATR, NMR spectroscopy and GC. A plethora of thermoplastic polyurethanes (TPUs) with tuned thermo-mechanical properties were prepared by combining the various diols and the diisocyanates, IPDI and MDI. The structural and thermo-mechanical characterizations of PUs were performed by means of FTIR-ATR, SEC, DSC, TGA, DMA, WAXS and tensile-test experiments. As expected, the PUs displayed amorphous to semi-crystalline features with respect to the nature of the diols and diisocyanates. Modulated DSC revealed glass transition temperatures in the range of -27 degrees C to 63 degrees C as well as melt crystallization of metastable phases upon heating. The incorporation of amide functions into the PUs enhanced the Young's modulus from 287 MPa to 775 MPa, while the elongation at break decreased from 269% to 41%. A complex degradation behavior of these PUs was observed by TGA above 280 degrees C

The human cytochrome P450 (CYP) superfamily holds responsibilities for the metabolism of both endogenous and exogenous compounds such as drugs, cellular metabolites, and toxins. The inhibition exerted on the CYP enzymes is closely associated with adverse drug reactions encompassing metabolic failures and induced side effects. In modern drug discovery, identification of potential CYP inhibitors is, therefore, highly essential. Alongside experimental approaches, numerous computational models have been proposed to address this biochemical issue. In this study, we introduce iCYP-MFE, a computational framework for virtual screening on CYP inhibitors toward 1A2, 2C9, 2C19, 2D6, and 3A4 isoforms. iCYP-MFE contains a set of five robust, stable, and effective prediction models developed using multitask learning incorporated with molecular fingerprint-embedded features. The results show that multitask learning can remarkably leverage useful information from related tasks to promote global performance. Comparative analysis indicates that iCYP-MFE achieves three predominant tasks, one equivalent task, and one less effective task compared to state-of-the-art methods. The area under the receiver operating characteristic curve (AUC-ROC) and the area under the precision-recall curve (AUC-PR) were two decisive metrics used for model evaluation. The prediction task for CYP2D6-inhibition achieves the highest AUC-ROC value of 0.93 while the prediction task for CYP1A2-inhibition obtains the highest AUC-PR value of 0.92. The substructural analysis preliminarily explains the nature of the CYP-inhibitory activity of compounds. An online web server for iCYP-MFE with a user-friendly interface was also deployed to support scientific communities in identifying CYP inhibitors.

Vietnam carries a highly diverse practice of traditional medicine in which various combinations of herbs have been widely used as remedies for many types of diseases. Poor hand-written records and current text-based databases, however, perplex the process of conventionalizing and evaluating canonical therapeutic effects. In efforts to reorganize the valuable information, we provide the VIETHERB database (http://vietherb.com.vn/) for herbs documented in Vietnamese traditional medicines. This database is constructed with confidence to provide users with information on herbs and other side information including metabolites, diseases, morphologies, and geographical locations for each individual species. Our data in this release consist of 2,881 species, 10,887 metabolites, 458 geographical locations, and 8,046 therapeutic effects. The numbers of species− metabolite, species−therapeutic effect, species−morphology, and species−distribution binary relationships are 17,602, 2,718, 11,943, and 16,089, respectively. The information on Vietnamese herbal species can be easily accessed or queried using their scientific names. Searching for species sharing side information can be simply done by clicking on the data. The database primarily serves as an open source facilitating users in studies of modernizing traditional medicine, computer-aided drug design, conservation of endangered plants, and other relevant experimental sciences.