This report documents the implementation of drug discovery pipeline in the D4Science platform realised in the context of the EOSC-Pillar project. In particular, it documents the pipeline and its constituents. Moreover, it describes how this pipeline has been integrated into the D4Science platform and exploited to create a dedicated Virtual Research Environment facilitating its exploitation and promoting a collaborative oriented approach for screening activities.

Chronic pain is a widespread disorder affecting millions of people and is insufficiently addressed by current classes of analgesics due to significant long-term or high dosage side effects. A promising approach that was recently proposed involves the systemic inhibition of the voltage-gated sodium channel Nav1.7, capable of cancelling pain perception completely. Notwithstanding numerous attempts, currently no drugs have been approved for the inhibition of Nav1.7. The task is complicated by the difficulty of creating a selective drug for Nav1.7, and avoiding binding to the many human paralogs performing fundamental physiological functions. In our work, we obtained a promising set of ligands with up to 5-40-fold selectivity and reaching 5.2 nanomolar binding affinity by employing a proper treatment of the problem and an innovative differential in silico screening procedure to discriminate for affinity and selectivity against the Nav paralogs. The absorption, distribution, metabolism, and excretion (ADME) properties of our top-scoring ligands were also evaluated, with good to excellent results. Additionally, our study revealed that the top-scoring ligand is a stereoisomer of an already-approved drug. These facts could reduce the time required to bring a new effective and selective Nav1.7 inhibitor to the market.

The HIV-1 matrix protein p17 (p17) is a pleiotropic molecule impacting on different cell types. Its interaction with many cellular proteins underlines the importance of the viral protein as a major determinant of human specific adaptation. We previously showed the proangiogenic capability of p17. Here, by integrating functional analysis and receptor binding, we identify a functional epitope that displays molecular mimicry with human erythropoietin (EPO) and promotes angiogenesis through common beta chain receptor (?CR) activation. The functional EPO-like epitope was found to be present in the matrix protein of HIV-1 ancestors SIV originated in chimpanzees (SIVcpz) and gorillas (SIVgor) but not in that of HIV-2 and its ancestor SIVsmm from sooty mangabeys. According to biological data, evolution of the EPO-like epitope showed a clear differentiation between HIV-1/SIVcpz-gor and HIV-2/SIVsmm branches, thus highlighting this epitope on p17 as a divergent signature discriminating HIV-1 and HIV-2 ancestors. P17 is known to enhance HIV-1 replication. Similarly to other ?CR ligands, p17 is capable of attracting and activating HIV-1 target cells and promoting a proinflammatory microenvironment. Thus, it is tempting to speculate that acquisition of an epitope on the matrix proteins of HIV-1 ancestors capable of triggering ?CR may have represented a critical step to enhance viral aggressiveness and early human-to-human SIVcpz/gor dissemination. The hypothesis that the p17/?CR interaction and ?CR abnormal stimulation may also play a role in sustaining chronic activation and inflammation, thus marking the difference between HIV-1 and HIV-2 in term of pathogenicity, needs further investigation.

Computational drug repositioning is of growing interest to academia and industry, for its ability to rapidly screen a huge number of candidates in silico (exploiting comprehensive drug datasets) together with reduced development cost and time. The potential of drug repositioning has not been fully evaluated yet for cystic fibrosis (CF), a disease mainly caused by deletion of Phe 508 (F508del) of the cystic fibrosis transmembrane conductance regulator (CFTR) protein. F508del-CFTR is thus withheld in the endoplasmic reticulum and rapidly degraded by the ubiquitin/proteasome system. CF is still a fatal disease. Nowadays, it is treatable by some CFTR-rescuing drugs, but new-generation drugs with stronger therapeutic benefits and fewer side effects are still awaited. In this manuscript we report about the results of a pilot computational drug repositioning screening in search of F508del-CFTR-targeted drugs performed on AIFA library by means of a dedicated computational pipeline and surface plasmon resonance binding assay to experimentally validate the computational findings.

Combined antiretroviral therapy (cART) for HIV-1 dramatically slows disease progression among HIV individuals. Currently, lymphoma represents the main cause of death among HIV-1-infected patients. Detection of p17 variants (vp17s) endowed with B-cell clonogenic activity in HIV-1-seropositive patients with lymphoma suggests their possible role in lymphomagenesis. Here, we demonstrate that the clonogenic activity of vp17s is mediated by their binding to PAR1 and to PAR1-mediated EGFR transactivation through Gq protein. The entire vp17s-triggered clonogenic process is MMPs dependent. Moreover, phosphoproteomic and bioinformatic analysis highlighted the crucial role of EGFR/PI3K/Akt pathway in modulating several molecules promoting cancer progression, including RAC1, ABL1, p53, CDK1, NPM, Rb, PTP-1B, and STAT1. Finally, we show that a peptide (F1) corresponding to the vp17s functional epitope is sufficient to trigger the PAR1/EGFR/PI3K/Akt pathway and bind PAR1. Our findings suggest novel potential therapeutic targets to counteract vp17-driven lymphomagenesis in HIV patients.

Cystic fibrosis transmembrane conductance regulator (CFTR)-rescuing drugs have already transformed cystic fibrosis (CF) from a fatal disease to a treatable chronic condition. However, new-generation drugs able to bind CFTR with higher specificity/affinity and to exert stronger therapeutic benefits and fewer side effects are still awaited. Computational methods and biosensors have become indispensable tools in the process of drug discovery for many important human pathologies. Instead, they have been used only piecemeal in CF so far, calling for their appropriate integration with well-tried CF biochemical and cell-based models to speed up the discovery of new CFTR-rescuing drugs. This review will give an overview of the available structures and computational models of CFTR and of the biosensors, biochemical and cell-based assays already used in CF-oriented studies. It will also give the reader some insights about how to integrate these tools as to improve the efficiency of the drug discovery process targeted to CFTR.

Recent studies have raised concerns about e-cigarette liquid inhalation toxicity by reporting the presence of chemicals with European Union CLP toxicity classification. In this scenario, the regulatory context is still developing and is not yet up to date with vaping current reality. Due to the paucity of toxicological studies, robust data regarding which components in e-liquids exhibit potential toxicities, are still inconsistent. In this study we applied computational methods for estimating the toxicity of poorly studied chemicals as a useful tool for predicting the acute toxicity of chemicals contained in e-liquids. The purpose of this study was 3-fold: (a) to provide a lower tier assessment of the potential health concerns associated with e-liquid ingredients, (b) to prioritize e-liquid ingredients by calculating the e-tox index, and (c) to estimate acute toxicity of e-liquid mixtures. QSAR models were generated using QSARINS software to fill the acute toxicity data gap of 264 e-liquid ingredients. As a second step, the potential acute toxicity of e-liquids mixtures was evaluated. Our preliminary data suggest that a computational approach may serve as a roadmap to enable regulatory bodies to better regulate e-liquid composition and to contribute to consumer health protection.

Xylenes are considered one of the most common hazardous sources of environmental contamination. The biodegradation of these compounds has been often reported, rarer the ability to oxidize theortho-isomer. Among fewo-xylene-degrading bacteria,Rhodococcus opacusR7 is well known for its capability to degrade diverse aromatic hydrocarbons and toxic compounds, includingo-xylene as only carbon and energy source. This work shows for the first time the RNA-seq approach to elucidate the genetic determinants involved in theo-xylene degradation pathway inR. opacusR7. Transcriptomic data showed 542 differentially expressed genes that are associated with the oxidation of aromatic hydrocarbons and stress response, osmotic regulation and central metabolism. Gene ontology (GO) enrichment and KEGG pathway analysis confirmed significant changes in aromatic compound catabolic processes, fatty acid metabolism,beta-oxidation, TCA cycle enzymes, and biosynthesis of metabolites when cells are cultured in the presence ofo-xylene. Interestingly, the most up-regulated genes belong to theakbgene cluster encoding for the ethylbenzene (Akb) dioxygenase system. Moreover, the transcriptomic approach allowed identifying candidate enzymes involved in R7o-xylene degradation for their likely participation in the formation of the metabolites that have been previously identified. Overall, this approach supports the identification of several oxidative systems likely involved ino-xylene metabolism confirming thatR. opacusR7 possesses a redundancy of sequences that converge ino-xylene degradation through R7 peculiar degradation pathway. This work advances our understanding ofo-xylene metabolism in bacteria belonging toRhodococcusgenus and provides a framework of useful enzymes (molecular tools) that can be fruitfully targeted for optimizedo-xylene consumption.

Stroke, one of the common neurological diseases, is a leading cause of long-term disability. About 17 million people suffer a stroke each year with an incidence of about 250/100000/year worldwide. The number of survivors doubled between 1990 and 2010, and will reach 77 million by 2030 according to epidemiological projections [1, 2]. Stroke is a main cause of long-term disability often causing permanent disability in the upper and/or lower limbs. More than 75% of individuals lose their ability to walk after stroke [3,4] and intense rehabilitation treatments are required to reduce disability effects and to recover most of the lost functionalities.

Electronic cigarettes (e-cigs) are designed to heat and aerosolized mixtures of propylene glycol, glycerol, flavorings, humectants and, optionally, nicotine. Unlike cigarettes, the process involves no tobacco and no combustion; however, the inhalation and exhalation of vapour is reminiscent of smoking. In this context, the use of these devices, might play an important role in smoking cessation and reduction; however, there is still a lack of international consensus over the public health role of the e-cig. Despite the large use of e-cigs, still few toxicological studies are available on the potential long term effects of inhaled of many characterizing flavors used in e-cig products. For instance, the FDA GRAS (Generally Recognized As Safe) designation for some flavorings compounds and for propylene glycol, does not apply to inhalation, and currently, there are no controlled long-term studies of the effects of inhaling heated aerosolized mixture in humans. Thus, there is legitimate concern over the health effects of chronically inhaling these substances and the lack of toxicological studies. In this respect, the aim of this study was to determine potential Cancerogenic, Mutagenic and Reprotoxic (CMR) properties of several e-liquid ingredients by means of in silico methods. With reference to our e-liquid ingredients and CMR effects, we first conducted an in depth screening, through the literature reviews; and we found experimental data gap for all the three categories. Specifically, for the investigated e-liquid ingredients, we observed 35%, 85% and 70% of experimental data gap for Cancerogenicity, Mutagenicity and Reprotoxicity effects, respectively. By following a battery approach, almost all data gaps were successfully filled using Quantitative Structure-Activity Relationship (Q) SAR methods. The predictions were performed using several open source software (VEGA, Toxtree, ToxRead and T.E.S.T.) and the results were combined to obtain the highest possible prediction accuracy (consensus approach). This in silico study is a part of a broader integrated approach (literature research, in chemico, in vitro and computational analysis) specifically designed to assess the potential risk associated with characterizing lavors and e-liquid ingredients.

p17 matrix protein released by HIV+ cells interacts with leukocytes heparan sulfate proteoglycans (HSPGs), CXCR1 and CXCR2 exerting different cytokine-like activities that contribute to AIDS pathogenesis. Since the bioactive form of several cytokines is represented by dimers/oligomers and oligomerization is promoted by binding to heparin or HSPGs, here we evaluated if heparin/HSPGs also promote p17 oligomerization. Heparin favours p17 dimer, trimer and tetramer assembly, in a time- and biphasic dose-dependent way. Heparin-induced p17 oligomerization is of electrostatic nature, being it prevented by NaCl, by removing negative sulfated groups of heparin and by neutralizing positive lysine residues in the p17 N-terminus. A new computational protocol has been implemented to study heparin chains up to 24-mer accommodating a p17 dimer. Molecular dynamics show that, in the presence of heparin, two p17 molecules undergo conformational modifications creating a continuous "electropositive channel" in which heparin sulfated groups interact with p17 basic amino acids, promoting its dimerization. At the cell surface, HSPGs induce p17 oligomerization, as demonstrated by using B-lymphoblastoid Namalwa cells overexpressing the HSPG Syndecan-1. Also, HSPGs on the surface of BJAB and Raji human B-lymphoblastoid cells are required to p17 to induce ERK activation, suggesting that HS-induced oligomerization plays a role in p17-induced lymphoid dysregulation during AIDS.

Cystic fibrosis (CF) is mainly caused by the mutation F508del of the cystic fibrosis transmembrane conductance regulator (CFTR) that is thus retained in the endoplasmic reticulum and degraded. New drugs able to rescue F508del-CFTR trafficking and activity are eagerly awaited, a goal that requires the availability of computational and experimental models closely resembling the F508del-CFTR structure and environment in vivo. Here we describe the development of a biosensor based on F508del-CFTR in a lipid environment that proved to be endowed with a wider analytical potential in respect to the previous CFTR-based biosensors. Integrated with an appropriate computational model of the whole human F508del-CFTR in lipid environment and CFTR stability and functional assays, the new biosensor allowed the identification and characterization at the molecular level of the binding modes of some known F508del-CFTR-rescuing drugs and of a new aminoarylthiazole-Lumacaftor/Tezacaftor hybrid derivative endowed with promising F508del-CFTR-binding and rescuing activity.

The incidence of cancer and Alzheimer's disease (AD) increases exponentially with age. A growing body of epidemiological evidence and molecular investigations inspired the hypothesis of an inverse relationship between these two pathologies. It has been proposed that the two diseases might utilize the same proteins and pathways that are, however, modulated differently and sometimes in opposite directions. Investigation of the common processes underlying these diseases may enhance the understanding of their pathogenesis and may also guide novel therapeutic strategies. Starting from a text-mining approach, our in silico study integrated the dispersed biological evidence by combining data mining, gene set enrichment, and protein-protein interaction (PPI) analyses while searching for common biological hallmarks linked to AD and cancer. We retrieved 138 genes (ALZCAN gene set), computed a significant number of enriched gene ontology clusters, and identified four PPI modules. The investigation confirmed the relevance of autophagy, ubiquitin proteasome system, and cell death as common biological hallmarks shared by cancer and AD. Then, from a closer investigation of the PPI modules and of the miRNAs enrichment data, several genes (SQSTM1, UCHL1, STUB1, BECN1, CDKN2A, TP53, EGFR, GSK3B, and HSPA9) and miRNAs (miR-146a-5p, MiR-34a-5p, miR-21-5p, miR-9-5p, and miR-16-5p) emerged as promising candidates. The integrative approach uncovered novel miRNA-gene networks (e.g., miR-146 and miR-34 regulating p62 and Beclin1 in autophagy) that might give new insights into the complex regulatory mechanisms of gene expression in AD and cancer.

The identification of multilocus imprinting disturbances (MLID) appears fundamental to uncover molecular pathways underlying imprinting disorders (IDs) and to complete clinical diagnosis of patients. However, MLID genetic associated mechanisms remain largely unknown. To characterize MLID in Beckwith-Wiedemann (BWS) and Silver-Russell (SRS) syndromes, we profiled by MassARRAY the methylation of 12 imprinted differentially methylated regions (iDMRs) in 21 BWS and 7 SRS patients with chromosome 11p15.5 epimutations. MLID was identified in 50% of BWS and 29% of SRS patients as a maternal hypomethylation syndrome. By next-generation sequencing, we searched for putative MLID-causative mutations in genes involved in methylation establishment/maintenance and found two novel missense mutations possibly causative of MLID: one in NLRP2, affecting ADP binding and protein activity, and one in ZFP42, likely leading to loss of DNA binding specificity. Both variants were paternally inherited. In silico protein modelling allowed to define the functional effect of these mutations. We found that MLID is very frequent in BWS/SRS. In addition, since MLID-BWS patients in our cohort show a peculiar pattern of BWS-associated clinical signs, MLID test could be important for a comprehensive clinical assessment. Finally, we highlighted the possible involvement of ZFP42 variants in MLID development and confirmed NLRP2 as causative locus in BWS-MLID.D

The inverse relationship of occurrence of Alzheimer's disease (AD) and cancer has been reported in several population based studies and meta-analysis. The different distribution of exposures to known risk factors in people with cancer or AD was found insufficient to explain, in our previous cohort study, the lower than expected co-occurrence. Aim of this study was to investigate the genetic basis underlying the inverse relationship by analysing common genetic variants differently expressed in the two diseases and their potential role in molecular pathways. A comparative analysis explored the distribution of 545,982 known Single Nucleotide Polymorphisms (SNPs) in the genome of large populations of cancers (N=4409) and AD (N=1292) patients from NIH dbGaP datasets. GWAS, PCA methods, SNPnexus, STRING, and ToppGene tools were employed to compare the datasets and distinguish molecular processes associated with AD and cancer. The GWAS analyses identified 300 SNPs (p< 10-5) associated with 213 unique genes (SNPnexus functional annotation) lying within 1 Mb from each SNPs' position. The gene set enrichment analysis (GSE) in ToppGene identified 11 out of 213 genes as significantly (p<10-5) enriching phospholipid binding (GO:0005543): ABCA1, CADPS, GBF1, KCNQ1, MARCKS, NF1, PLD1, PXK, SNX29, TIAM1, ZFYVE26. The protein-protein interaction analysis (STRING) and exploration of activity of proteins produced by the 11 genes, indicated enrichment for molecular pathways associated to carcinogenesis (RAS) and apoptosis. Furthermore we tested the SNPs ability of discriminating AD form cancer by calculating a composite numeric score based on the 40 most significant ones (p<10-12) from the GWAS analysis. For each of these SNPs we assigned value 1 if an allele with minor frequency was observed, and 0 otherwise. In a Receiver Operating Characteristic analysis the score performance resulted high, with AUC=83.1 [95% CI 82.0-84.2]. The adopted combination of epidemiological and in silico approaches indicates potential explanatory capabilities. The biological soundness of our finding is consistent with the existing studies identifying the cell membrane damage and metabolic processes as underlying initiation and progression of both AD and cancer. These preliminary results show that genes, identified by SNPs significantly different in the two diseases, are involved in shared biological pathways that, if deregulated, may explain the divergent trajectories towards AD or cancer. Further investigations using other independent genetic datasets are required to confirm these findings that, if successfully replicated in silico, can form the basis for specific in vitro and in vivo future studies on the inverse occurrence of the two diseases.

The inverse relationship of occurrence of Alzheimer's disease (AD) and cancer has been reported in several population based studies and meta-analysis. The different distribution of exposures to known risk factors in people with cancer or AD was found insufficient to explain, in our previous cohort study, the lower than expected co-occurrence. Therefore, we investigate the genetic basis underlying the inverse relationship by analysing common genetic variants differently expressed in the two diseases. The study explores and identifies the genotypic 'red flags' that could distinguish and classify a priori the AD and cancer cases. A comparative analysis explored the distribution of 545,982 known Single Nucleotide Polymorphisms (SNPs) in the genome of large populations of cancers (N=4409) and AD (N=1292) patients from NIH dbGaP datasets. GWAS, PCA methods, SNPnexus, and ToppGene tools were employed to compare the datasets, to distinguish molecular processes associated with AD and cancer, and to select a set of SNPs differentially distributed in the two diseases. The GWAS analyses identified 300 SNPs (p< 10-5) associated with 213 unique genes (SNPnexus functional annotation). The gene set enrichment analysis (GSE) in ToppGene identified 11 out of 213 genes as significantly (p<10-5) enriched for phospholipid binding (GO:0005543): ABCA1, CADPS, GBF1, KCNQ1, MARCKS, NF1, PLD1, PXK, SNX29, TIAM1, ZFYVE26. Furthermore we tested the SNPs ability to discriminate AD form cancer cases by means of contingency tables and a Receiver Operating Characteristic (ROC) analysis. ROC score performance resulted high (AUC=72.9) for 11 most significant SNPS from the GWAS analysis, while 11 SNPs associated with the phospholipid binding classified even better AD vs. cancer cases (AUC=78.1). The adopted combination of top-down and bottom-up approaches indicates its potential explanatory capabilities. These preliminary results show that genes, identified by SNPs significantly different in the two diseases, are involved in shared biological pathways that, if deregulated, may explain the divergent trajectories towards AD or cancer. The differentially distributed SNPs might have potential clinical applications that could direct future research. Further investigations using other independent genetic datasets are required to confirm these findings that, if successfully replicated in silico, can form the basis for specific in vitro and in vivo studies on the inverse occurrence of the two diseases.

BACKGROUND: Bacteria belonging to the Rhodococcus genus play an important role in the degradation of many contaminants, including methylbenzenes. These bacteria, widely distributed in the environment, are known to be a powerhouse of numerous degradation functions, due to their ability to metabolize a wide range of organic molecules including aliphatic, aromatic, polycyclic aromatic compounds (PAHs), phenols, and nitriles. In accordance with their immense catabolic diversity, Rhodococcus spp. possess large and complex genomes, which contain a multiplicity of catabolic genes, a high genetic redundancy of biosynthetic pathways and a sophisticated regulatory network. The present study aimed to identify genes involved in the o-xylene degradation in R. opacus strain R7 through a genome-based approach. RESULTS: Using genome-based analysis we identified all the sequences in the R7 genome annotated as dioxygenases or monooxygenases/hydroxylases and clustered them into two different trees. The akb, phe and prm sequences were selected as genes encoding respectively for dioxygenases, phenol hydroxylases and monooxygenases and their putative involvement in o-xylene oxidation was evaluated. The involvement of the akb genes in o-xylene oxidation was demonstrated by RT-PCR/qPCR experiments after growth on o-xylene and by the selection of the R7-50 leaky mutant. Although the akb genes are specifically activated for o-xylene degradation, metabolic intermediates of the pathway suggested potential alternative oxidation steps, possibly through monooxygenation. This led us to further investigate the role of the prm and the phe genes. Results showed that these genes were transcribed in a constitutive manner, and that the activity of the Prm monooxygenase was able to transform o-xylene slowly in intermediates as 3,4-dimethylphenol and 2-methylbenzylalcohol. Moreover, the expression level of phe genes, homologous to the phe genes of Rhodococcus spp. 1CP and UPV-1 with a 90% identity, could explain their role in the further oxidation of o-xylene and R7 growth on dimethylphenols. CONCLUSIONS: These results suggest that R7 strain is able to degrade o-xylene by the Akb dioxygenase system leading to the production of the corresponding dihydrodiol. Likewise, the redundancy of sequences encoding for several monooxygenases/phenol hydroxylases, supports the involvement of other oxygenases converging in the o-xylene degradation pathway in R7 strain

The identification of multi-locus imprinting disturbances (MLID) appears fundamental to uncover molecular pathways underlying imprinting disorders (IDs) and to complete clinical diagnosis of patients. However, MLID genetic associated mechanisms remain largely unknown. To characterize MLID in Beckwith-Wiedemann (BWS) and Silver-Russell (SRS) syndromes, we profiled by MassARRAY the methylation of 12 imprinted differentially methylated regions (iDMRs) in 21 BWS and 7 SRS patients with chromosome 11p15.5 epimutations. MLID was identified in 50% of BWS and 29% of SRS patients as a maternal hypomethylation syndrome. By next-generation sequencing, we searched for putative MLID-causative mutations in genes involved in methylation establishment/maintenance and found two novel missense mutations possibly causative of MLID: one in NLRP2, affecting ADP binding and protein activity, and one in ZFP42, likely leading to loss of DNA binding specificity. Both variants were paternally inherited. In silico protein modelling allowed to define the functional effect of these mutations. We found that MLID is very frequent in BWS/SRS. In addition, since MLID-BWS patients in our cohort show a peculiar pattern of BWS-associated clinical signs, MLID test could be important for a comprehensive clinical assessment. Finally, we highlighted the possible involvement of ZFP42 variants in MLID development and confirmed NLRP2 as causative locus in BWS-MLID.

Cystic fibrosis (CF) is mainly caused by the deletion of Phe 508 (DeltaF508) in the cystic fibrosis transmembrane conductance regulator (CFTR) protein that is thus withheld in the endoplasmic reticulum and rapidly degraded by the ubiquitin/proteasome system. New drugs able to rescue DeltaF508-CFTR trafficking are eagerly awaited. An integrated bioinformatics and surface plasmon resonance (SPR) approach was here applied to investigate the rescue mechanism(s) of a series of CFTR-ligands including VX809, VX770 and some aminoarylthiazole derivatives (AAT). Computational studies tentatively identified a large binding pocket in the DeltaF508-CFTR nucleotide binding domain-1 (NBD1) and predicted all the tested compounds to bind to three sub-regions of this main pocket. Noticeably, the known CFTR chaperone keratin-8 (K8) seems to interact with some residues located in one of these sub-pockets, potentially interfering with the binding of some ligands. SPR results corroborated all these computational findings. Moreover, for all the considered ligands, a statistically significant correlation was determined between their binding capability to DeltaF508-NBD1 measured by SPR and the pockets availability measured by computational studies. Taken together, these results demonstrate a strong agreement between the in silico prediction and the SPR-generated binding data, suggesting a path to speed up the identification of new drugs for the treatment of cystic fibrosis.