Compartment-specific and ELAVL1-coordinated regulation of intronic polyadenylation isoforms by doxorubicin.

Intronic polyadenylation (IPA) isoforms, which contain alternative last exons, are widely regulated in various biological processes and by many factors. However, little is known about their cytoplasmic regulation and translational status. In this study, we provide the first evidence that the genome-wide patterns of IPA isoform regulation during a biological process can be very distinct between the transcriptome and translatome, and between the nucleus and cytosol. Indeed, by 3'-seq analyses on breast cancer cells, we show that the genotoxic anticancer drug, doxorubicin, preferentially down-regulates the IPA to the last-exon (IPA:LE) isoform ratio in whole cells (as previously reported) but preferentially up-regulates it in polysomes. We further show that in nuclei, doxorubicin almost exclusively down-regulates the IPA:LE ratio, whereas in the cytosol, it preferentially up-regulates the isoform ratio, as in polysomes. Then, focusing on IPA isoforms that are up-regulated by doxorubicin in the cytosol and highly translated (up-regulated and/or abundant in polysomes), we identify several IPA isoforms that promote cell survival to doxorubicin. Mechanistically, by using an original approach of condition- and compartment-specific CLIP-seq (CCS-iCLIP) to analyze ELAVL1-RNA interactions in the nucleus and cytosol in the presence and absence of doxorubicin, as well as 3'-seq analyses upon ELAVL1 depletion, we show that the RNA-binding protein ELAVL1 mediates both nuclear down-regulation and cytosolic up-regulation of the IPA:LE isoform ratio in distinct sets of genes in response to doxorubicin. Altogether, these findings reveal differential regulation of the IPA:LE isoform ratio across subcellular compartments during drug response and its coordination by an RNA-binding protein.

AMMOS2: a web server for protein-ligand-water complexes refinement via molecular mechanics.

AMMOS2 is an interactive web server for efficient computational refinement of protein-small organic molecule complexes. The AMMOS2 protocol employs atomic-level energy minimization of a large number of experimental or modeled protein-ligand complexes. The web server is based on the previously developed standalone software AMMOS (Automatic Molecular Mechanics Optimization for in silico Screening). AMMOS utilizes the physics-based force field AMMP sp4 and performs optimization of protein-ligand interactions at five levels of flexibility of the protein receptor. The new version 2 of AMMOS implemented in the AMMOS2 web server allows the users to include explicit water molecules and individual metal ions in the protein-ligand complexes during minimization. The web server provides comprehensive analysis of computed energies and interactive visualization of refined protein-ligand complexes. The ligands are ranked by the minimized binding energies allowing the users to perform additional analysis for drug discovery or chemical biology projects. The web server has been extensively tested on 21 diverse protein-ligand complexes. AMMOS2 minimization shows consistent improvement over the initial complex structures in terms of minimized protein-ligand binding energies and water positions optimization. The AMMOS2 web server is freely available without any registration requirement at the URL: http://drugmod.rpbs.univ-paris-diderot.fr/ammosHome.php.

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.

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/.

Which three-dimensional characteristics make efficient inhibitors of protein-protein interactions?

The specific properties of protein-protein interactions (PPI) (flat, large and hydrophobic) make them harder to tackle with low-molecular-weight compounds. Learning from the properties of successful examples of PPI interface inhibitors (iPPI) at earlier stages of developments, has been pinpointed as a powerful strategy to circumvent this trend. To this end, we have computationally analyzed the bioactive conformations of iPPI and those of inhibitors of conventional targets (e.g enzymes) to highlight putative iPPI 3D characteristics. Most noticeably, the essential property revealed by this study illustrates how efficiently iPPI manages to bind to the hydrophobic patch often present at the core of protein interfaces. The newly identified properties were further confirmed as characteristics of iPPI using much larger data sets (e.g iPPI-DB, www.ippidb.cdithem.fr ). Interestingly, the absence of correlation of such properties with the hydrophobicity and the size of the compounds opens new ways to design potent iPPI with better pharmacokinetic features.

Differential Effects on the Translation of Immune-Related Alternatively Polyadenylated mRNAs in Melanoma and T Cells by eIF4A Inhibition.

Targeting the translation initiation complex eIF4F, which binds the 5' cap of mRNAs, is a promising anti-cancer approach. Silvestrol, a small molecule inhibitor of eIF4A, the RNA helicase component of eIF4F, inhibits the translation of the mRNA encoding the signal transducer and activator of transcription 1 (STAT1) transcription factor, which, in turn, reduces the transcription of the gene encoding one of the major immune checkpoint proteins, i.e., programmed death ligand-1 (PD-L1) in melanoma cells. A large proportion of human genes produce multiple mRNAs differing in their 3'-ends through the use of alternative polyadenylation (APA) sites, which, when located in alternative last exons, can generate protein isoforms, as in the STAT1 gene. Here, we provide evidence that the STAT1α, but not STAT1ß protein isoform generated by APA, is required for silvestrol-dependent inhibition of PD-L1 expression in interferon-γ-treated melanoma cells. Using polysome profiling in activated T cells we find that, beyond STAT1, eIF4A inhibition downregulates the translation of some important immune-related mRNAs, such as the ones encoding TIM-3, LAG-3, IDO1, CD27 or CD137, but with little effect on the ones for BTLA and ADAR-1 and no effect on the ones encoding CTLA-4, PD-1 and CD40-L. We next apply RT-qPCR and 3'-seq (RNA-seq focused on mRNA 3' ends) on polysomal RNAs to analyze in a high throughput manner the effect of eIF4A inhibition on the translation of APA isoforms. We identify about 150 genes, including TIM-3, LAG-3, AHNAK and SEMA4D, for which silvestrol differentially inhibits the translation of APA isoforms in T cells. It is therefore crucial to consider 3'-end mRNA heterogeneity in the understanding of the anti-tumor activities of eIF4A inhibitors.

Insights into molecular mechanisms of drug metabolism dysfunction of human CYP2C9*30.

Cytochrome P450 2C9 (CYP2C9) metabolizes about 15% of clinically administrated drugs. The allelic variant CYP2C9*30 (A477T) is associated to diminished response to the antihypertensive effects of the prodrug losartan and affected metabolism of other drugs. Here, we investigated molecular mechanisms involved in the functional consequences of this amino-acid substitution. Molecular dynamics (MD) simulations performed for the active species of the enzyme (heme in the Compound I state), in the apo or substrate-bound state, and binding energy analyses gave insights into altered protein structure and dynamics involved in the defective drug metabolism of human CYP2C9.30. Our data revealed an increased rigidity of the key Substrate Recognition Sites SRS1 and SRS5 and shifting of the ß turn 4 of SRS6 toward the helix F in CYP2C9.30. Channel and binding substrate dynamics analyses showed altered substrate channel access and active site accommodation. These conformational and dynamic changes are believed to be involved in the governing mechanism of the reduced catalytic activity. An ensemble of representative conformations of the WT and A477T mutant properly accommodating drug substrates were identified, those structures can be used for prediction of new CYP2C9 and CYP2C9.30 substrates and drug-drug interactions.

Imbalance in chemical space: How to facilitate the identification of protein-protein interaction inhibitors.

Protein-protein interactions (PPIs) play vital roles in life and provide new opportunities for therapeutic interventions. In this large data analysis, 3,300 inhibitors of PPIs (iPPIs) were compared to 17 reference datasets of collectively ~566,000 compounds (including natural compounds, existing drugs, active compounds on conventional targets, etc.) using a chemoinformatics approach. Using this procedure, we showed that comparable classes of PPI targets can be formed using either the similarity of their ligands or the shared properties of their binding cavities, constituting a proof-of-concept that not only can binding pockets be used to group PPI targets, but that these pockets certainly condition the properties of their corresponding ligands. These results demonstrate that matching regions in both chemical space and target space can be found. Such identified classes of targets could lead to the design of PPI-class-specific chemical libraries and therefore facilitate the development of iPPIs to the stage of drug candidates.

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.

iPPI-DB: a manually curated and interactive database of small non-peptide inhibitors of protein-protein interactions.

The development of small molecule drugs targeting protein-protein interactions (PPI) represents a major challenge, in part owing to the misunderstanding of the PPI chemical space. To this end, we have manually collected the structures, the physicochemical and pharmacological profiles of 1650 PPI inhibitors across 13 families of PPI targets in a database named iPPI-DB. To access iPPI-DB, we propose a user-friendly web application (www.ippidb.cdithem.fr) with customizable queries and intuitive visualizing functionalities for associated properties of the compounds. This could assist scientists to design the next generation of PPI drugs. In this review, we describe iPPI-DB in the context of other low molecular weight molecule databases.

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.