Phenotypic similarity-based approach for variant prioritization for unsolved rare disease: a preliminary methodological report

Rare diseases (RD) have a prevalence of not more than 1/2000 persons in the European population, and are characterised by the difficulty experienced in obtaining a correct and timely diagnosis. According to Orphanet, 72.5% of RD have a genetic origin although 35% of them do not yet have an identified causative gene. A significant proportion of patients suspected to have a genetic RD receive an inconclusive exome/genome sequencing. Working towards the International Rare Diseases Research Consortium (IRDiRC)'s goal for 2027 to ensure that all people living with a RD receive a diagnosis within one year of coming to medical attention, the Solve-RD project aims to identify the molecular causes underlying undiagnosed RD. As part of this strategy, we developed a phenotypic similarity-based variant prioritization methodology comparing submitted cases with other submitted cases and with known RD in Orphanet. Three complementary approaches based on phenotypic similarity calculations using the Human Phenotype Ontology (HPO), the Orphanet Rare Diseases Ontology (ORDO) and the HPO-ORDO Ontological Module (HOOM) were developed; genomic data reanalysis was performed by the RD-Connect Genome-Phenome Analysis Platform (GPAP). The methodology was tested in 4 exemplary cases discussed with experts from European Reference Networks. Variants of interest (pathogenic or likely pathogenic) were detected in 8.8% of the 725 cases clustered by similarity calculations. Diagnostic hypotheses were validated in 42.1% of them and needed further exploration in another 10.9%. Based on the promising results, we are devising an automated standardized phenotypic-based re-analysis pipeline to be applied to the entire unsolved cases cohort.

The Human Phenotype Ontology in 2024: phenotypes around the world

The Human Phenotype Ontology (HPO) is a widely used resource that comprehensively organizes and defines the phenotypic features of human disease, enabling computational inference and supporting genomic and phenotypic analyses through semantic similarity and machine learning algorithms. The HPO has widespread applications in clinical diagnostics and translational research, including genomic diagnostics, gene-disease discovery, and cohort analytics. In recent years, groups around the world have developed translations of the HPO from English to other languages, and the HPO browser has been internationalized, allowing users to view HPO term labels and in many cases synonyms and definitions in ten languages in addition to English. Since our last report, a total of 2239 new HPO terms and 49235 new HPO annotations were developed, many in collaboration with external groups in the fields of psychiatry, arthrogryposis, immunology and cardiology. The Medical Action Ontology (MAxO) is a new effort to model treatments and other measures taken for clinical management. Finally, the HPO consortium is contributing to efforts to integrate the HPO and the GA4GH Phenopacket Schema into electronic health records (EHRs) with the goal of more standardized and computable integration of rare disease data in EHRs.

The Human Phenotype Ontology in 2021

The Human Phenotype Ontology (HPO, https://hpo.jax.org) was launched in 2008 to provide a comprehensive logical standard to describe and computationally analyze phenotypic abnormalities found in human disease. The HPO is now a worldwide standard for phenotype exchange. The HPO has grown steadily since its inception due to considerable contributions from clinical experts and researchers from a diverse range of disciplines. Here, we present recent major extensions of the HPO for neurology, nephrology, immunology, pulmonology, newborn screening, and other areas. For example, the seizure subontology now reflects the International League Against Epilepsy (ILAE) guidelines and these enhancements have already shown clinical validity. We present new efforts to harmonize computational definitions of phenotypic abnormalities across the HPO and multiple phenotype ontologies used for animal models of disease. These efforts will benefit software such as Exomiser by improving the accuracy and scope of cross-species phenotype matching. The computational modeling strategy used by the HPO to define disease entities and phenotypic features and distinguish between them is explained in detail.We also report on recent efforts to translate the HPO into indigenous languages. Finally, we summarize recent advances in the use of HPO in electronic health record systems.

Fr-PPIChem: An Academic Compound Library Dedicated to Protein-Protein Interactions

Protein-protein interactions (PPIs) mediate nearly every cellular process and represent attractive targets for modulating disease states but are challenging to target with small molecules. Despite this, several PPI inhibitors (iPPIs) have entered clinical trials, and a growing number of PPIs have become validated drug targets. However, high-throughput screening efforts still endure low hit rates mainly because of the use of unsuitable screening libraries. Here, we describe the collective effort of a French consortium to build, select, and store in plates a unique chemical library dedicated to the inhibition of PPIs. Using two independent predictive models and two updated databases of experimentally confirmed PPI inhibitors developed by members of the consortium, we built models based on different training sets, molecular descriptors, and machine learning methods. Independent statistical models were used to select putative PPI inhibitors from large commercial compound collections showing great complementarity. Medicinal chemistry filters were applied to remove undesirable structures from this set (such as PAINS, frequent hitters, and toxic compounds) and to improve drug likeness. The remaining compounds were subjected to a clustering procedure to reduce the final size of the library while maintaining its chemical diversity. In practice, the library showed a 46-fold activity rate enhancement when compared to a non-iPPI-enriched diversity library in high-throughput screening against the CD47-SIRPα PPI. The Fr-PPIChem library is plated in 384-well plates and will be distributed on demand to the scientific community as a powerful tool for discovering new chemical probes and early hits for the development of potential therapeutic drugs.

FAF-Drugs4: free ADME-tox filtering computations for chemical biology and early stages drug discovery

Motivation

Identification of small molecules that could be interesting starting points for drug discovery or to investigate a biological system as in chemical biology endeavours is both time consuming and costly. In silico approaches that assist the design of quality compound collections or help to prioritize molecules before synthesis or purchase are therefore valuable. Here quality refers to the selection of molecules that pass one or several selected filters that can be tuned by the users according to the project and the stage of the project. These filters can involve prediction of physicochemical properties, search for toxicophores or other unwanted chemical groups.

Results

FAF-Drugs4 is a novel version of our online server dedicated to the preparation and annotation of compound collections. The tool is now faster and several parameters have been optimized. In addition, a new service referred to as FAF-QED, an implementation of the quantitative estimate of drug-likeness method, is now available.

Availability and implementation

The server is available at http://fafdrugs4.mti.univ-paris-diderot.fr.

Contact

Bruno.Villoutreix@inserm.fr.

Supplementary information

Supplementary data are available at Bioinformatics online.

In silico model of the human ClC-Kb chloride channel: pore mapping, biostructural pathology and drug screening

The human ClC-Kb channel plays a key role in exporting chloride ions from the cytosol and is known to be involved in Bartter syndrome type 3 when its permeation capacity is decreased. The ClC-Kb channel has been recently proposed as a potential therapeutic target to treat hypertension. In order to gain new insights into the sequence-structure-function relationships of this channel, to investigate possible impacts of amino-acid substitutions, and to design novel inhibitors, we first built a structural model of the human ClC-Kb channel using comparative modeling strategies. We combined in silico and in vitro techniques to analyze amino acids involved in the chloride ion pathway as well as to rationalize the possible role of several clinically observed mutations leading to the Bartter syndrome type 3. Virtual screening and drug repositioning computations were then carried out. We identified six novel molecules, including 2 approved drugs, diflusinal and loperamide, with Kd values in the low micromolar range, that block the human ClC-Kb channel and that could be used as starting point to design novel chemical probes for this potential therapeutic target.

Computational analysis of calculated physicochemical and ADMET properties of protein-protein interaction inhibitors

The modulation of PPIs by low molecular weight chemical compounds, particularly by orally bioavailable molecules, would be very valuable in numerous disease indications. However, it is known that PPI inhibitors (iPPIs) tend to have properties that are linked to poor Absorption, Distribution, Metabolism, Excretion and Toxicity (ADMET) and in some cases to poor clinical outcomes. Previously reported in silico analyses of iPPIs have essentially focused on physicochemical properties but several other ADMET parameters would be important to assess. In order to gain new insights into the ADMET properties of iPPIs, computations were carried out on eight datasets collected from several databases. These datasets involve compounds targeting enzymes, GPCRs, ion channels, nuclear receptors, allosteric modulators, oral marketed drugs, oral natural product-derived marketed drugs and iPPIs. Several trends are reported that should assist the design and optimization of future PPI inhibitors, either for drug discovery endeavors or for chemical biology projects.

iPPI-DB: an online database of modulators of protein-protein interactions

In order to boost the identification of low-molecular-weight drugs on protein–protein interactions (PPI), it is essential to properly collect and annotate experimental data about successful examples. This provides the scientific community with the necessary information to derive trends about privileged physicochemical properties and chemotypes that maximize the likelihood of promoting a given chemical probe to the most advanced stages of development. To this end we have developed iPPI-DB (freely accessible at http://www.ippidb.cdithem.fr), a database that contains the structure, some physicochemical characteristics, the pharmacological data and the profile of the PPI targets of several hundreds modulators of protein–protein interactions. iPPI-DB is accessible through a web application and can be queried according to two general approaches: using physicochemical/pharmacological criteria; or by chemical similarity to a user-defined structure input. In both cases the results are displayed as a sortable and exportable datasheet with links to external databases such as Uniprot, PubMed. Furthermore each compound in the table has a link to an individual ID card that contains its physicochemical and pharmacological profile derived from iPPI-DB data. This includes information about its binding data, ligand and lipophilic efficiencies, location in the PPI chemical space, and importantly similarity with known drugs, and links to external databases like PubChem, and ChEMBL.

FAF-Drugs3: a web server for compound property calculation and chemical library design

Drug attrition late in preclinical or clinical development is a serious economic problem in the field of drug discovery. These problems can be linked, in part, to the quality of the compound collections used during the hit generation stage and to the selection of compounds undergoing optimization. Here, we present FAF-Drugs3, a web server that can be used for drug discovery and chemical biology projects to help in preparing compound libraries and to assist decision-making during the hit selection/lead optimization phase. Since it was first described in 2006, FAF-Drugs has been significantly modified. The tool now applies an enhanced structure curation procedure, can filter or analyze molecules with user-defined or eight predefined physicochemical filters as well as with several simple ADMET (absorption, distribution, metabolism, excretion and toxicity) rules. In addition, compounds can be filtered using an updated list of 154 hand-curated structural alerts while Pan Assay Interference compounds (PAINS) and other, generally unwanted groups are also investigated. FAF-Drugs3 offers access to user-friendly html result pages and the possibility to download all computed data. The server requires as input an SDF file of the compounds; it is open to all users and can be accessed without registration at http://fafdrugs3.mti.univ-paris-diderot.fr.

MTiOpenScreen: a web server for structure-based virtual screening

Open screening endeavors play and will play a key role to facilitate the identification of new bioactive compounds in order to foster innovation and to improve the effectiveness of chemical biology and drug discovery processes. In this line, we developed the new web server MTiOpenScreen dedicated to small molecule docking and virtual screening. It includes two services, MTiAutoDock and MTiOpenScreen, allowing performing docking into a user-defined binding site or blind docking using AutoDock 4.2 and automated virtual screening with AutoDock Vina. MTiOpenScreen provides valuable starting collections for screening, two in-house prepared drug-like chemical libraries containing 150 000 PubChem compounds: the Diverse-lib containing diverse molecules and the iPPI-lib enriched in molecules likely to inhibit protein–protein interactions. In addition, MTiOpenScreen offers users the possibility to screen up to 5000 small molecules selected outside our two libraries. The predicted binding poses and energies of up to 1000 top ranked ligands can be downloaded. In this way, MTiOpenScreen enables researchers to apply virtual screening using different chemical libraries on traditional or more challenging protein targets such as protein–protein interactions. The MTiOpenScreen web server is free and open to all users at http://bioserv.rpbs.univ-paris-diderot.fr/services/MTiOpenScreen/.

In silico design of low molecular weight protein-protein interaction inhibitors: Overall concept and recent advances

Protein-protein interactions (PPIs) are carrying out diverse functions in living systems and are playing a major role in the health and disease states. Low molecular weight (LMW) "drug-like" inhibitors of PPIs would be very valuable not only to enhance our understanding over physiological processes but also for drug discovery endeavors. However, PPIs were deemed intractable by LMW chemicals during many years. But today, with the new experimental and in silico technologies that have been developed, about 50 PPIs have already been inhibited by LMW molecules. Here, we first focus on general concepts about protein-protein interactions, present a consensual view about ligandable pockets at the protein interfaces and the possibilities of using fast and cost effective structure-based virtual screening methods to identify PPI hits. We then discuss the design of compound collections dedicated to PPIs. Recent financial analyses of the field suggest that LMW PPI modulators could be gaining momentum over biologics in the coming years supporting further research in this area.

Drug-Like Protein-Protein Interaction Modulators: Challenges and Opportunities for Drug Discovery and Chemical Biology

[Formula: see text] Fundamental processes in living cells are largely controlled by macromolecular interactions and among them, protein-protein interactions (PPIs) have a critical role while their dysregulations can contribute to the pathogenesis of numerous diseases. Although PPIs were considered as attractive pharmaceutical targets already some years ago, they have been thus far largely unexploited for therapeutic interventions with low molecular weight compounds. Several limiting factors, from technological hurdles to conceptual barriers, are known, which, taken together, explain why research in this area has been relatively slow. However, this last decade, the scientific community has challenged the dogma and became more enthusiastic about the modulation of PPIs with small drug-like molecules. In fact, several success stories were reported both, at the preclinical and clinical stages. In this review article, written for the 2014 International Summer School in Chemoinformatics (Strasbourg, France), we discuss in silico tools (essentially post 2012) and databases that can assist the design of low molecular weight PPI modulators (these tools can be found at www.vls3d.com). We first introduce the field of protein-protein interaction research, discuss key challenges and comment recently reported in silico packages, protocols and databases dedicated to PPIs. Then, we illustrate how in silico methods can be used and combined with experimental work to identify PPI modulators.

One hundred thousand mouse clicks down the road: selected online resources supporting drug discovery collected over a decade

Online resources enabling and supporting drug discovery have blossomed during the past ten years. However, drug hunters commonly find themselves overwhelmed by the proliferation of these computer-based resources. Ten years ago, we, the authors of this review, felt that a comprehensive list of in silico resources relating to drug discovery was needed. Especially because the internet provides a wealth of inspiring tools that, if fully exploited, could greatly assist the process. We present here a compilation of online tools and databases collected over the past decade. The tools were essentially found through literature and internet searches and, currently, our list contains over 1500 URLs. We also briefly highlight some recently reported services and comment about ongoing and future efforts in the field.

A leap into the chemical space of protein-protein interaction inhibitors

Protein-protein interactions (PPI) are involved in vital cellular processes and are therefore associated to a growing number of diseases. But working with them as therapeutic targets comes with some major hurdles that require substantial mutations from our way to design drugs on historical targets such as enzymes and G-Protein Coupled Receptor (GPCR). Among the numerous ways we could improve our methodologies to maximize the potential of developing new chemical entities on PPI targets, is the fundamental question of what type of compounds should we use to identify the first hits and among which chemical space should we navigate to optimize them to the drug candidate stage. In this review article, we cover different aspects on PPI but with the aim to gain some insights into the specific nature of the chemical space of PPI inhibitors. We describe the work of different groups to highlight such properties and discuss their respective approach. We finally discuss a case study in which we describe the properties of a set of 115 PPI inhibitors that we compare to a reference set of 1730 enzyme inhibitors. This case study highlights interesting properties such as the unfortunate price that still needs to be paid by PPI inhibitors in terms of molecular weight, hydrophobicity, and aromaticity in order to reach a critical level of activity. But it also shows that not all PPI targets are equivalent, and that some PPI targets can demonstrate a better druggability by illustrating the better drug likeness of their associated inhibitors.

In silico prediction of aqueous solubility: a multimodel protocol based on chemical similarity

Aqueous solubility is one of the most important ADMET properties to assess and to optimize during the drug discovery process. At present, accurate prediction of solubility remains very challenging and there is an important need of independent benchmarking of the existing in silico models such as to suggest solutions for their improvement. In this study, we developed a new protocol for improved solubility prediction by combining several existing models available in commercial or free software packages. We first performed an evaluation of ten in silico models for aqueous solubility prediction on several data sets in order to assess the reliability of the methods, and we proposed a new diverse data set of 150 molecules as relevant test set, SolDiv150. We developed a random forest protocol to evaluate the performance of different fingerprints for aqueous solubility prediction based on molecular structure similarity. Our protocol, called a "multimodel protocol", allows selecting the most accurate model for a compound of interest among the employed models or software packages, achieving r(2) of 0.84 when applied to SolDiv150. We also found that all models assessed here performed better on druglike molecules than on real drugs, thus additional improvement is needed in this direction. Overall, our approach enlarges the applicability domain as demonstrated by the more accurate results for solubility prediction obtained using our protocol in comparison to using individual models.

AMMOS software: method and application

Recent advances in computational sciences enabled extensive use of in silico methods in projects at the interface between chemistry and biology. Among them virtual ligand screening, a modern set of approaches, facilitates hit identification and lead optimization in drug discovery programs. Most of these approaches require the preparation of the libraries containing small organic molecules to be screened or a refinement of the virtual screening results. Here we present an overview of the open source AMMOS software, which is a platform performing an automatic procedure that allows for a structural generation and optimization of drug-like molecules in compound collections, as well as a structural refinement of protein-ligand complexes to assist in silico screening exercises.

Tyrosine kinase syk non-enzymatic inhibitors and potential anti-allergic drug-like compounds discovered by virtual and in vitro screening

In the past decade, the spleen tyrosine kinase (Syk) has shown a high potential for the discovery of new treatments for inflammatory and autoimmune disorders. Pharmacological inhibitors of Syk catalytic site bearing therapeutic potential have been developed, with however limited specificity towards Syk. To address this topic, we opted for the design of drug-like compounds that could impede the interaction of Syk with its cellular partners while maintaining an active kinase protein. To achieve this challenging task, we used the powerful potential of intracellular antibodies for the modulation of cellular functions in vivo, combined to structure-based in silico screening. In our previous studies, we reported the anti-allergic properties of the intracellular antibody G4G11. With the aim of finding functional mimics of G4G11, we developed an Antibody Displacement Assay and we isolated the drug-like compound C-13, with promising in vivo anti-allergic activity. The likely binding cavity of this compound is located at the close vicinity of G4G11 epitope, far away from the catalytic site of Syk. Here we report the virtual screen of a collection of 500,000 molecules against this new cavity, which led to the isolation of 1000 compounds subsequently evaluated for their in vitro inhibitory effects using the Antibody Displacement Assay. Eighty five compounds were selected and evaluated for their ability to inhibit the liberation of allergic mediators from mast cells. Among them, 10 compounds inhibited degranulation with IC₅₀ values ≤ 10 µM. The most bioactive compounds combine biological activity, significant inhibition of antibody binding and strong affinity for Syk. Moreover, these molecules show a good potential for oral bioavailability and are not kinase catalytic site inhibitors. These bioactive compounds could be used as starting points for the development of new classes of non-enzymatic inhibitors of Syk and for drug discovery endeavour in the field of inflammation related disorders.

The FAF-Drugs2 server: a multistep engine to prepare electronic chemical compound collections

SUMMARY

The FAF-Drugs2 server is a web application that prepares chemical compound libraries prior to virtual screening or that assists hit selection/lead optimization before chemical synthesis or ordering. The FAF-Drugs2 web server is an enhanced version of the FAF-Drugs2 package that now includes Pan Assay Interference Compounds detection. This online toolkit has been designed through a user-centered approach with emphasis on user-friendliness. This is a unique online tool allowing to prepare large compound libraries with in house or user-defined filtering parameters.

AVAILABILITY

The FAF-Drugs2 server is freely available at http://bioserv.rpbs.univ-paris-diderot.fr/FAF-Drugs/.

DG-AMMOS: a new tool to generate 3d conformation of small molecules using distance geometry and automated molecular mechanics optimization for in silico screening

BACKGROUND

Discovery of new bioactive molecules that could enter drug discovery programs or that could serve as chemical probes is a very complex and costly endeavor. Structure-based and ligand-based in silico screening approaches are nowadays extensively used to complement experimental screening approaches in order to increase the effectiveness of the process and facilitating the screening of thousands or millions of small molecules against a biomolecular target. Both in silico screening methods require as input a suitable chemical compound collection and most often the 3D structure of the small molecules has to be generated since compounds are usually delivered in 1D SMILES, CANSMILES or in 2D SDF formats.

RESULTS

Here, we describe the new open source program DG-AMMOS which allows the generation of the 3D conformation of small molecules using Distance Geometry and their energy minimization via Automated Molecular Mechanics Optimization. The program is validated on the Astex dataset, the ChemBridge Diversity database and on a number of small molecules with known crystal structures extracted from the Cambridge Structural Database. A comparison with the free program Balloon and the well-known commercial program Omega generating the 3D of small molecules is carried out. The results show that the new free program DG-AMMOS is a very efficient 3D structure generator engine.

CONCLUSION

DG-AMMOS provides fast, automated and reliable access to the generation of 3D conformation of small molecules and facilitates the preparation of a compound collection prior to high-throughput virtual screening computations. The validation of DG-AMMOS on several different datasets proves that generated structures are generally of equal quality or sometimes better than structures obtained by other tested methods.

FAF-Drugs2: free ADME/tox filtering tool to assist drug discovery and chemical biology projects

BACKGROUND

Drug discovery and chemical biology are exceedingly complex and demanding enterprises. In recent years there are been increasing awareness about the importance of predicting/optimizing the absorption, distribution, metabolism, excretion and toxicity (ADMET) properties of small chemical compounds along the search process rather than at the final stages. Fast methods for evaluating ADMET properties of small molecules often involve applying a set of simple empirical rules (educated guesses) and as such, compound collections' property profiling can be performed in silico. Clearly, these rules cannot assess the full complexity of the human body but can provide valuable information and assist decision-making.

RESULTS

This paper presents FAF-Drugs2, a free adaptable tool for ADMET filtering of electronic compound collections. FAF-Drugs2 is a command line utility program (e.g., written in Python) based on the open source chemistry toolkit OpenBabel, which performs various physicochemical calculations, identifies key functional groups, some toxic and unstable molecules/functional groups. In addition to filtered collections, FAF-Drugs2 can provide, via Gnuplot, several distribution diagrams of major physicochemical properties of the screened compound libraries.

CONCLUSION

We have developed FAF-Drugs2 to facilitate compound collection preparation, prior to (or after) experimental screening or virtual screening computations. Users can select to apply various filtering thresholds and add rules as needed for a given project. As it stands, FAF-Drugs2 implements numerous filtering rules (23 physicochemical rules and 204 substructure searching rules) that can be easily tuned.

MS-DOCK: accurate multiple conformation generator and rigid docking protocol for multi-step virtual ligand screening

Background

The number of protein targets with a known or predicted tri-dimensional structure and of drug-like chemical compounds is growing rapidly and so is the need for new therapeutic compounds or chemical probes. Performing flexible structure-based virtual screening computations on thousands of targets with millions of molecules is intractable to most laboratories nor indeed desirable. Since shape complementarity is of primary importance for most protein-ligand interactions, we have developed a tool/protocol based on rigid-body docking to select compounds that fit well into binding sites.

Results

Here we present an efficient multiple conformation rigid-body docking approach, MS-DOCK, which is based on the program DOCK. This approach can be used as the first step of a multi-stage docking/scoring protocol. First, we developed and validated the Multiconf-DOCK tool that generates several conformers per input ligand. Then, each generated conformer (bioactives and 37970 decoys) was docked rigidly using DOCK6 with our optimized protocol into seven different receptor-binding sites. MS-DOCK was able to significantly reduce the size of the initial input library for all seven targets, thereby facilitating subsequent more CPU demanding flexible docking procedures.

Conclusion

MS-DOCK can be easily used for the generation of multi-conformer libraries and for shape-based filtering within a multi-step structure-based screening protocol in order to shorten computation times.

Free resources to assist structure-based virtual ligand screening experiments

In today's research environment, a wealth of experimental/theoretical structural data is available and the number of therapeutically relevant macromolecular structures is growing rapidly. This, coupled with the huge number of small non-peptide potential drug candidates easily available (over 7 million compounds), highlight the need of using computer-aided techniques for the efficient identification and optimization of novel hit compounds. Virtual (or in silico) ligand screening based on the three-dimensional structure of macromolecular targets (SB-VLS) is firmly established as an important approach to identify chemical entities that have a high likelihood of binding to a target molecule to elicit desired biological responses. A myriad of free applications and services facilitating the drug discovery process have been posted on the Web. In this review, we cite over 350 URLs that are useful for SB-VLS projects and essentially free for academic groups. We attempt to provide links for in silico ADME/tox prediction tools, compound collections, some ligand-based methods, characterization/simulation of 3D targets and homology modeling tools, druggable pocket predictions, active site comparisons, analysis of macromolecular interfaces, protein docking tools to help identify binding pockets and protein-ligand docking/scoring methods. As such, we aim at providing both, methods pertaining to the field of Structural Bioinformatics (defined here as tools to study macromolecules) and methods pertaining to the field of Chemoinformatics (defined here as tools to make better decisions faster in the arena of drug/lead identification and optimization). We also report several recent success stories using these free computer methods. This review should help readers finding free computer tools useful for their projects. Overall, we are confident that these tools will facilitate rapid and cost-effective identification of new hit compounds. The URLs presented in this review will be updated regularly at www.vls3d.com in the coming months, "Links" section.

Hepatitis C virus core triggers apoptosis in liver cells by inducing ER stress and ER calcium depletion

Hepatitis C virus (HCV) core, known to be involved in liver carcinogenesis, is processed in the endoplasmic reticulum (ER). We thus investigated the impact of three HCV core isolates on ER stress, ER calcium signalling and apoptosis. We show that HCV core constructs trigger hyperexpression of Grp78/BiP, Grp 94, calreticulin and sarco/endoplasmic reticulum calcium ATPase, inducing ER stress. By using the ER-targeted aequorin calcium probe, we found that ER calcium depletion follows ER stress in core-expressing cells. HCV core induces apoptosis through overexpression of the CHOP/GADD153 proapoptotic factor, Bax translocation to mitochondria, mitochondrial membrane depolarization, cytochrome c release, caspase-3 and PARP cleavage. Furthermore, reversion of HCV core-induced ER calcium depletion (by transfection of SERCA2) completely abolished mitochondrial membrane depolarization, suggesting that both ER stress (through CHOP overexpression) and calcium signalling play a major role in the HCV core-mediated control of apoptosis. ER stress and apoptosis were also found in a proportion of HCV-full-length replicon-expressing cells and in the liver of HCV core transgenic mice. In conclusion, our data demonstrate that HCV core deregulates the control of apoptosis by inducing ER stress and ER calcium depletion providing new elements to understand the mechanisms involved in HCV-related liver chronic diseases.

Hepatitis B virus-related insertional mutagenesis occurs frequently in human liver cancers and recurrently targets human telomerase gene

Integration of Hepatitis B Virus (HBV) DNA into liver cell DNA has been well established, but its implication in liver carcinogenesis is still being debated. In particular, insertion of the viral genome into cellular genes has been viewed as a rare event. By using HBV-Alu PCR, we have now isolated, from nine hepatocellular carcinomas, nine HBV-DNA integration sites showing that the viral genome mutates key regulatory cellular genes: neurotropic tyrosin receptor kinase 2 (NTRK2) gene, IL-1R-associated kinase 2 (IRAK2) gene, p42 mitogen-activated protein kinase 1 (p42MAPK1) gene, inositol 1,4,5-triphosphate receptor type 2 (IP3R2) gene, inositol 1,4,5-triphosphate receptor (IP3R) type 1 (IP3R1) gene, alpha 2,3 sialyltransferase (ST3GAL VI or SITA) gene, thyroid hormone uncoupling protein (TRUP) gene, EMX2-like gene, and human telomerase reverse transcriptase (hTERT) gene. This result brings to 15 the total number of genes targeted by HBV in a study of 22 human liver cancers. Overall, we found that both the inositol 1,4,5-triphosphate receptor gene and the telomerase gene were targeted by HBV in two different tumors. Thus, HBV frequently targets cellular genes involved in cell signalling and some of them may be preferential targets of the viral integration.

Identification and functional characterization of a new member of the human Mcm protein family: hMcm8

The six minichromosome maintenance proteins (Mcm2-7) are required for both the initiation and elongation of chromosomal DNA, ensuring that DNA replication takes place once, and only once, during the S phase. Here we report on the cloning of a new human Mcm gene (hMcm8) and on characterisation of its protein product. The hMcm8 gene contains the central Mcm domain conserved in the Mcm2-7 gene family, and is expressed in a range of cell lines and human tissues. hMcm8 mRNA accumulates during G(1)/S phase, while hMcm8 protein is detectable throughout the cell cycle. Immunoprecipitation-based studies did not reveal any participation of hMcm8 in the Mcm3/5 and Mcm2/4/6/7 subcomplexes. hMcm8 localises to the nucleus, although it is devoid of a nuclear localisation signal, suggesting that it binds to a nuclear protein. In the nucleus, the hMcm8 structure-bound fraction is detectable in S, but not in G(2)/M, phase, as for hMcm3. However, unlike hMcm3, the hMcm8 structure-bound fraction is not detectable in G(1) phase. Overall, our data identify a new Mcm protein, which does not form part of the Mcm2-7 complex and which is only structure-bound during S phase, thus suggesting its specific role in DNA replication.

Identification of human cancer-related genes by naturally occurring Hepatitis B Virus DNA tagging

Proviral tagging has been used in animals as a powerful tool for cancer genetics. We show that a similar approach is possible in patients with hepatocellular carcinoma (HCC) infected by Hepatitis B Virus (HBV), a human pararetrovirus which may act by insertional mutagenesis. In this work, the HBV genome is used as a probe to identify cancer-related genes. By using HBV-Alu-PCR, we obtained 21 HBV/cellular DNA junctions from 18 different patients. In six of 21, we found the HBV DNA integrated into a cellular gene: (1) Sarco/Endoplasmic Reticulum Calcium ATPase1 Gene; (2) Thyroid Hormone Receptor Associated Protein 150 alpha Gene; (3) Human Telomerase Reverse Transcriptase Gene; (4) Minichromosome Maintenance Protein (MCM)-Related Gene; (5) FR7, a new gene expressed in human liver and cancer tissues; and (6) Nuclear Matrix Protein p84 Gene. Seven junctions contained unique cellular sequences. In the remaining eight, the HBV DNA was next to repetitive sequences, five of them of LINE1 type. The cellular genes targeted by HBV are key regulators of cell proliferation and viability. Our results show that studies on HBV-related HCCs allow to identify cellular genes involved in cancer. We therefore propose this approach as a valuable tool for functional cancer genomic studies in humans.

SERCA1 truncated proteins unable to pump calcium reduce the endoplasmic reticulum calcium concentration and induce apoptosis

By pumping calcium from the cytosol to the ER, sarco/endoplasmic reticulum calcium ATPases (SERCAs) play a major role in the control of calcium signaling. We describe two SERCA1 splice variants (S1Ts) characterized by exon 4 and/or exon 11 splicing, encoding COOH terminally truncated proteins, having only one of the seven calcium-binding residues, and thus unable to pump calcium. As shown by semiquantitative RT-PCR, S1T transcripts are differentially expressed in several adult and fetal human tissues, but not in skeletal muscle and heart. S1T proteins expression was detected by Western blot in nontransfected cell lines. In transiently transfected cells, S1T homodimers were revealed by Western blot using mildly denaturing conditions. S1T proteins were shown, by confocal scanning microscopy, to colocalize with endogenous SERCA2b into the ER membrane. Using ER-targeted aequorin (erAEQ), we have found that S1T proteins reduce ER calcium and reverse elevation of ER calcium loading induced by SERCA1 and SERCA2b. Our results also show that SERCA1 variants increase ER calcium leakage and are consistent with the hypothesis of a cation channel formed by S1T homodimers. Finally, when overexpressed in liver-derived cells, S1T proteins significantly induce apoptosis. These data reveal a further mechanism modulating Ca(2+) accumulation into the ER of nonmuscle cells and highlight the relevance of S1T proteins to the control of apoptosis.

Significance of repeatedly normal aminotransferase activities in HCV-infected patients

The significance of repeatedly normal serum aminotransferase activities in antihepatitis C virus (anti-HCV)-positive patients is not clear. To address this issue, the authors analyzed clinical, virologic, histopathologic, and biological characteristics of such subjects. Among their active file of 1,200 anti-HCV-positive immunocompetent patients, they identified 36 subjects (3%) with repeatedly normal aminotransferase activities, as defined by at least four normal values of aminotransferase over a minimum period of 6 months without any abnormal value (mean of this period, 31 +/- 21 months). The 36 patients included 11 men and 25 women with a mean age of 45 +/- 15 years. Twenty-three of these 36 subjects (64%) had detectable HCV viremia by polymerase chain reaction. Their genotype distribution was as follows: genotype 1a or 1b, 57%; genotype 2, 26%; and genotype 3, 17%. Of the HCV ribonucleic acid (RNA)-positive and HCV RNA-negative subjects, 17 and 5 had a liver biopsy respectively. In the former, the mean Knodell score was 5.6 +/- 3.5 (range, 1 to 14), and was < 5 in 9 patients (53%) and > or = 5 in 8 (47%), including extensive fibrosis (n = 2) or cirrhosis (n = 2). In the HCV RNA-negative subjects, one patient had a Knodell score > or = 5. Comparing the 23 immunocompetent viremic subjects with repeatedly normal serum aminotransferase activities with our group (n = 564) of immunocompetent viremic patients with abnormal aminotransferase activities, there was a significant predominance of women (70% versus 44%, p < 0.05) and of genotype 2 in the former (26% versus 7%, p < 0.05), but no differences according to quantitative viremia, alcohol consumption, or distribution of risk factor were observed. Most of viremic HCV-infected patients with long-term and repeatedly normal aminotransferase values have indeed chronic active hepatitis, including extensive fibrosis or cirrhosis in as many as 20% of patients. This emphasizes the need for serum HCV RNA determination in anti-HCV-positive patients with normal aminotransferase activities. In these patients liver biopsy may be necessary and should be discussed.

Epidemiological and virological analysis of couples infected with hepatitis C virus

BACKGROUND

If transmission of hepatitis C virus (HCV) infection through parenteral exposure is well documented, sexual transmission of HCV is still debated.

AIMS

To perform extensive epidemiological and virological analysis in 24 couples in which each spouse was anti-HCV positive in order to delineate more precisely potential sexual transmission of HCV.

PATIENTS

Twenty four couples in which each partner was anti-HCV positive. These 48 spouses were recruited in a liver unit by regular screening of spouses of index patients.

METHODS

All 48 spouses completed an epidemiological questionnaire on risk factors for HCV. Qualitative detection of serum HCV RNA and determination of HCV type by genotyping and serotyping were performed. Sequence analysis of HCV strains by phylogenetic analysis was carried out in seven couples with concordant genotypes.

RESULTS

The mean (SD) partnership duration was 12 (10) years. Serum HCV RNA was detected in both partners in 18 of the couples (75%) and in only one partner in six of the couples (25%). HCV typing showed concordant genotypes in 12 couples (50%), discordant genotypes in seven (29%), and in the other five couples (21%) only one spouse could be genotyped. Of the 48 spouses, 33 had a major risk factor for HCV transmission such as transfusion (n = 6) and intravenous drug use (n = 27). Eleven of the 12 couples infected with the same HCV genotype had at least one parenteral risk factor for viral transmission in both spouses. Whatever the genotype concordance, in most couples (75%), both spouses showed parenteral risk factors for viral transmission. Sequence analysis of HCV strains was possible in seven of 12 couples with identical genotype and showed different and identical isolates in four and three couples respectively.

CONCLUSION

The study emphasises the risk of overestimating the importance of a very low sexual HCV transmission risk as against other, mainly parenteral, risk factors.

Permissiveness of human biliary epithelial cells to infection by hepatitis C virus

The cellular tropism of hepatitis C virus (HCV) is an important but much debated issue. Permissivity to HCV of biliary cells has never been demonstrated. In this context, we used gallbladder epithelial cells (GBEC) as a model of the more proximal biliary epithelium. These cells were isolated from HCV-positive and -negative individuals and cultured for up to 40 days. Biliary cells from HCV-negative subjects were infected in vitro with various inocula. The retention of GBEC functional characteristics was assessed by the expression of cystic fibrosis transmembrane conductance regulator (CFTR). All 12 GBEC tested from HCV-negative patients were successfully infected by HCV. This was assessed by: 1) the detection of HCV-RNA positive and negative strands; 2) the detection of the viral capsid by immunofluorescence; and 3) the combination of single-strand conformation polymorphism (SSCP) and HVR1 sequence analysis demonstrating the distinct majoritary HCV genomes in serum and in GBEC. The level of HCV RNA in cell extracts and supernatants was low, but HCV infection was highly reproducible. Our results expand those showing the cellular tropism of HCV, and demonstrate the sensitivity of biliary cells to HCV infection. This might have an important impact in terms of pathogenesis and pathological features of HCV infection. In addition, given the easy access to these cells and the high reproducibility of in vitro infection, they should constitute an important tool for studies aimed at analyzing the issue of HCV penetration and neutralizing antibodies.

Impact of HBV, HCV and GBV-C/HGV on hepatocellular carcinomas in Europe: results of a European concerted action

BACKGROUND/AIMS

To investigate the impact of hepatitis B (HBV) and C (HCV) infections on hepatocellular carcinoma (HCC) in Europe.

METHODS

Five hundred and three patients with HCC, from six liver centers, were included. All 503 sera and 80 liver samples were tested for HBV DNA and HCV RNA by polymerase chain reaction. GBV-C/HGV RNA was also tested in 57 sera.

RESULTS

HBsAg and anti-HCV were detected in 19% and 40.1% of the patients, respectively. Serum and liver HBV DNA were detected in 82% and 91% of the HBsAg positive subjects. HBV DNA was also detected in the serum and liver of 33% and 47% of HBsAg negative patients. In this group, serum HBV DNA was more prevalent in anti-HBs and/or anti-HBc patients (47.9%), compared to those without any HBV marker (25.1%). HCV RNA was detected in 89% and 7% of anti-HCV positive and negative cases, respectively, HCV 1b being the most prevalent genotype (80%). Coinfection with HBV and HCV was shown in 20.4% of patients, while only 29% had neither HBV nor HCV GBV-C/HGV RNA was detected in only 4/57 sera.

CONCLUSIONS

This study offers the first large analysis of HCC in Europe, based on both serology and molecular tests. It demonstrates the major impact of HBV and HCV, but not of GBV-C/HGV, in liver carcinogenesis in Northern as well as Southern Europe. It also stresses the need to use viral genome detection in epidemiological studies when serological tests are negative.