Sulconazole inhibits PD-1 expression in immune cells and cancer cells malignant phenotype through NF-κB and calcium activity repression

The overexpression of the immunoinhibitory receptor programmed death-1 (PD1) on T-cells is involved in immune evasion in cancer. The use of anti-PD-1/PDL-1 strategy has deeply changed the therapies of cancers and patient survival. However, their efficacy diverges greatly along with tumor type and patient populations. Thereby, novel treatments are needed to interfere with the anti-tumoral immune responses and propose an adjunct therapy. In the current study, we found that the antifungal drug Sulconazole (SCZ) inhibits PD-1 expression on activated PBMCs and T cells at the RNA and protein levels. SCZ repressed NF-κB and calcium signaling, both, involved in the induction of PD-1. Further analysis revealed cancer cells treatment with SCZ inhibited their proliferation, and migration and ability to mediate tumor growth in zebrafish embryos. SCZ found also to inhibit calcium mobilization in cancer cells. These results suggest the SCZ therapeutic potential used alone or as adjunct strategy to prevent T-cell exhaustion and promotes cancer cell malignant phenotype repression in order to improve tumor eradication.

Discovery, Structure-Activity Relationships, and In Vivo Activity of Dihydropyridone Agonists of the Bile Acid Receptor TGR5

A novel series of potent agonists of the bile acid receptor TGR5 bearing a dihydropyridone scaffold was developed from a high-throughput screen. Starting from a micromolar hit compound, we implemented an extensive structure-activity-relationship (SAR) study with the synthesis and biological evaluation of 83 analogues. The project culminated with the identification of the potent nanomolar TGR5 agonist 77A. We report the GLP-1 secretagogue effect of our lead compound ex vivo in mouse colonoids and in vivo. In addition, to identify specific features favorable for TGR5 activation, we generated and optimized a three-dimensional quantitative SAR model that contributed to our understanding of our activity profile and could guide further development of this dihydropyridone series.

Targeting protein-protein interactions with low molecular weight and short peptide modulators: insights on disease pathways and starting points for drug discovery

INTRODUCTION

Protein-protein interactions (PPIs) have been often considered undruggable targets although they are attractive for the discovery of new therapeutics. The spread of artificial intelligence and machine learning complemented with experimental methods is likely to change the perspectives of protein-protein modulator research. Noteworthy, some novel low molecular weight (LMW) and short peptide modulators of PPIs are already in clinical trials for the treatment of relevant diseases.

AREAS COVERED

This review focuses on the main molecular properties of protein-protein interfaces and on key concepts pertaining to the modulation of PPIs. The authors survey recently reported state-of-the-art methods dealing with the rational design of PPI modulators and highlight the role of several computer-based approaches.

EXPERT OPINION

Interfering specifically with large protein interfaces is still an open challenge. The initial concerns about the unfavorable physicochemical properties of many of these modulators are nowadays less acute with several molecules lying beyond the rule of 5, orally available and successful in clinical trials. As the cost of biologics interfering with PPIs is very high, it would seem reasonable to put more effort, both in academia and the private sectors, on actively developing novel low molecular weight compounds and short peptides to perform this task.

Biallelic variants in NOS3 and GUCY1A3, the two major genes of the nitric oxide pathway, cause moyamoya cerebral angiopathy

BACKGROUND

Moyamoya angiopathy (MMA) is a rare cerebrovascular condition leading to stroke. Mutations in 15 genes have been identified in Mendelian forms of MMA, but they explain only a very small proportion of cases. Our aim was to investigate the genetic basis of MMA in consanguineous patients having unaffected parents in order to identify genes involved in autosomal recessive MMA.

METHODS

Exome sequencing (ES) was performed in 6 consecutive consanguineous probands having MMA of unknown etiology. Functional consequences of variants were assessed using western blot and protein 3D structure analyses.

RESULTS

Causative homozygous variants of NOS3, the gene encoding the endothelial nitric oxide synthase (eNOS), and GUCY1A3, the gene encoding the alpha1 subunit of the soluble guanylate cyclase (sGC) which is the major nitric oxide (NO) receptor in the vascular wall, were identified in 3 of the 6 probands. One NOS3 variant (c.1502 + 1G > C) involves a splice donor site causing a premature termination codon and leads to a total lack of eNOS in endothelial progenitor cells of the affected proband. The other NOS3 variant (c.1942 T > C) is a missense variant located into the flavodoxine reductase domain; it is predicted to be destabilizing and shown to be associated with a reduction of eNOS expression. The GUCY1A3 missense variant (c.1778G > A), located in the catalytic domain of the sGC, is predicted to disrupt the tridimensional structure of this domain and to lead to a loss of function of the enzyme. Both NOS3 mutated probands suffered from an infant-onset and severe MMA associated with posterior cerebral artery steno-occlusive lesions. The GUCY1A3 mutated proband presented an adult-onset MMA associated with an early-onset arterial hypertension and a stenosis of the superior mesenteric artery. None of the 3 probands had achalasia.

CONCLUSIONS

We show for the first time that biallelic loss of function variants in NOS3 is responsible for MMA and that mutations in NOS3 and GUCY1A3 are causing fifty per cent of MMA in consanguineous patients. These data pinpoint the essential role of the NO pathway in MMA pathophysiology.

A Hybrid Docking and Machine Learning Approach to Enhance the Performance of Virtual Screening Carried out on Protein-Protein Interfaces

The modulation of protein-protein interactions (PPIs) by small chemical compounds is challenging. PPIs play a critical role in most cellular processes and are involved in numerous disease pathways. As such, novel strategies that assist the design of PPI inhibitors are of major importance. We previously reported that the knowledge-based DLIGAND2 scoring tool was the best-rescoring function for improving receptor-based virtual screening (VS) performed with the Surflex docking engine applied to several PPI targets with experimentally known active and inactive compounds. Here, we extend our investigation by assessing the vs. potential of other types of scoring functions with an emphasis on docking-pose derived solvent accessible surface area (SASA) descriptors, with or without the use of machine learning (ML) classifiers. First, we explored rescoring strategies of Surflex-generated docking poses with five GOLD scoring functions (GoldScore, ChemScore, ASP, ChemPLP, ChemScore with Receptor Depth Scaling) and with consensus scoring. The top-ranked poses were post-processed to derive a set of protein and ligand SASA descriptors in the bound and unbound states, which were combined to derive descriptors of the docked protein-ligand complexes. Further, eight ML models (tree, bagged forest, random forest, Bayesian, support vector machine, logistic regression, neural network, and neural network with bagging) were trained using the derivatized SASA descriptors and validated on test sets. The results show that many SASA descriptors are better than Surflex and GOLD scoring functions in terms of overall performance and early recovery success on the used dataset. The ML models were superior to all scoring functions and rescoring approaches for most targets yielding up to a seven-fold increase in enrichment factors at 1% of the screened collections. In particular, the neural networks and random forest-based ML emerged as the best techniques for this PPI dataset, making them robust and attractive vs. tools for hit-finding efforts. The presented results suggest that exploring further docking-pose derived SASA descriptors could be valuable for structure-based virtual screening projects, and in the present case, to assist the rational design of small-molecule PPI inhibitors.

A new ChEMBL dataset for the similarity-based target fishing engine FastTargetPred: Annotation of an exhaustive list of linear tetrapeptides

Drug discovery often requires the identification of off-targets as the binding of a compound to targets other than the intended target(s) can be beneficial in some cases or detrimental in other situations (e.g., binding to anti-targets). Such investigations are also of importance during the early stage of a project, for example when the target is not known (e.g., phenotypic screening). Target identification can be performed in-vitro, but various in-silico methods have also been developed in recent years to facilitate target identification and help generate ideas. FastTargetPred is one such approach, it is a freely available Python/C program that attempts to predict putative macromolecular targets (i.e., target fishing) for a single input small molecule query or an entire compound collection using established chemical similarity search approaches. Indeed, the putative macromolecular target(s) of a small chemical compound can be predicted by identifying ligands that are known experimentally to bind to some targets and that are structurally similar to the input query chemical compound. Therefore, this type of target fishing approach relies on a large collection of experimentally validated macromolecule-chemical compound binding data. The small chemical compounds can be described as molecular fingerprints encoding their structural characteristics as a vector. The published version of FastTargetPred used ligand-target binding data extracted from the release 25 (2019) of the ChEMBL database. Here we provide a new dataset for FastTargetPred extracted from the last ChEMBL release, namely, at the time of writing, ChEMBL29 (2021). Four fingerprints were computed (ECFP4, ECFP6, MACCS and PL) for the extracted compound dataset (714,780 unique ChEMBL29 compounds while the entire ChEMBL29 database contained about 2.1 million compounds). However, it was not possible to compute fingerprints for 19 molecules because of their unusual chemistry (complex macrocycles). These data files were then prepared so as to be compatible with FastTargetPred requirements. The 714,761 ChEMBL chemical compounds with computed fingerprints hit 6,477 macromolecular targets based on the selected criteria. For these ChEMBL compounds a ChEMBL target ID is reported and these target IDs were matched with the corresponding UniProt IDs. Thus, when available, the UniProt ID is provided, the protein UniProt name, the gene name, the organism as well as annotated involvement in diseases, gene ontology data, and cross-references to the Reactome pathway database. As short peptides can be of interest for drug discovery and chemical biology endeavours, we were interested in attempting to predict putative macromolecular targets for a previously reported exhaustive combination of peptides containing four natural amino acids (i.e., 20 × 20 × 20 × 20 = 160,000 linear tetrapeptides) using FastTargetPred and the presently generated ChEMBL29 dataset. With the parameters used, putative targets are reported for 63,944 unique query peptides. These target predictions are provided in two different searchable files with hyperlinks to the ChEMBL, UniProt and Reactome databases.

Dominant negative mutation in oxalate transporter SLC26A6 associated with enteric hyperoxaluria and nephrolithiasis

Background

Nephrolithiasis (NL) is a complex multifactorial disease affecting up to 10%–20% of the human population and causing a significant burden on public health systems worldwide. It results from a combination of environmental and genetic factors. Hyperoxaluria is a major risk factor for NL.

Methods

We used a whole exome-based approach in a patient with calcium oxalate NL. The effects of the mutation were characterised using cell culture and in silico analyses.

Results

We identified a rare heterozygous missense mutation (c.1519C>T/p.R507W) in the SLC26A6 gene that encodes a secretory oxalate transporter. This mutation cosegregated with hyperoxaluria in the family. In vitro characterisation of mutant SLC26A6 demonstrated that Cl⁻-dependent oxalate transport was dramatically reduced because the mutation affects both SLC26A6 transport activity and membrane surface expression. Cotransfection studies demonstrated strong dominant-negative effects of the mutant on the wild-type protein indicating that the phenotype of patients heterozygous for this mutation may be more severe than predicted by haploinsufficiency alone.

Conclusion

Our study is in line with previous observations made in the mouse showing that SLC26A6 inactivation can cause inherited enteric hyperoxaluria with calcium oxalate NL. Consistent with an enteric form of hyperoxaluria, we observed a beneficial effect of increasing calcium in the patient’s diet to reduce urinary oxalate excretion.

Machine learning-driven identification of drugs inhibiting cytochrome P450 2C9

Cytochrome P450 2C9 (CYP2C9) is a major drug-metabolizing enzyme that represents 20% of the hepatic CYPs and is responsible for the metabolism of 15% of drugs. A general concern in drug discovery is to avoid the inhibition of CYP leading to toxic drug accumulation and adverse drug-drug interactions. However, the prediction of CYP inhibition remains challenging due to its complexity. We developed an original machine learning approach for the prediction of drug-like molecules inhibiting CYP2C9. We created new predictive models by integrating CYP2C9 protein structure and dynamics knowledge, an original selection of physicochemical properties of CYP2C9 inhibitors, and machine learning modeling. We tested the machine learning models on publicly available data and demonstrated that our models successfully predicted CYP2C9 inhibitors with an accuracy, sensitivity and specificity of approximately 80%. We experimentally validated the developed approach and provided the first identification of the drugs vatalanib, piriqualone, ticagrelor and cloperidone as strong inhibitors of CYP2C9 with IC values <18 μM and sertindole, asapiprant, duvelisib and dasatinib as moderate inhibitors with IC50 values between 40 and 85 μM. Vatalanib was identified as the strongest inhibitor with an IC50 value of 0.067 μM. Metabolism assays allowed the characterization of specific metabolites of abemaciclib, cloperidone, vatalanib and tarafenacin produced by CYP2C9. The obtained results demonstrate that such a strategy could improve the prediction of drug-drug interactions in clinical practice and could be utilized to prioritize drug candidates in drug discovery pipelines.

Computational Analysis of Chemical Space of Natural Compounds Interacting with Sulfotransferases

The aim of this study was to investigate the chemical space and interactions of natural compounds with sulfotransferases (SULTs) using ligand- and structure-based in silico methods. An in-house library of natural ligands (hormones, neurotransmitters, plant-derived compounds and their metabolites) reported to interact with SULTs was created. Their chemical structures and properties were compared to those of compounds of non-natural (synthetic) origin, known to interact with SULTs. The natural ligands interacting with SULTs were further compared to other natural products for which interactions with SULTs were not known. Various descriptors of the molecular structures were calculated and analyzed. Statistical methods (ANOVA, PCA, and clustering) were used to explore the chemical space of the studied compounds. Similarity search between the compounds in the different groups was performed with the ROCS software. The interactions with SULTs were additionally analyzed by docking into different experimental and modeled conformations of SULT1A1. Natural products with potentially strong interactions with SULTs were outlined. Our results contribute to a better understanding of chemical space and interactions of natural compounds with SULT enzymes and help to outline new potential ligands of these enzymes.

Antithrombin Resistance Rescues Clotting Defect of Homozygous Prothrombin-Y510N Dysprothrombinemia

A patient with hematuria in our clinic was diagnosed with urolithiasis. Analysis of the patient's plasma clotting time indicated that both activated partial thromboplastin time (52.6 seconds) and prothrombin time (19.4 seconds) are prolonged and prothrombin activity is reduced to 12.4% of normal, though the patient exhibited no abnormal bleeding phenotype and a prothrombin antigen level of 87.9%. Genetic analysis revealed the patient is homozygous for prothrombin Y510N mutation. We expressed and characterized the prothrombin-Y510N variant in appropriate coagulation assays and found that the specificity constant for activation of the mutant zymogen by factor Xa is impaired approximately fivefold. Thrombin generation assay using patient's plasma and prothrombin-deficient plasma supplemented with either wild-type or prothrombin-Y510N revealed that both peak height and time to peak for the prothrombin mutant are decreased; however, the endogenous thrombin generation potential is increased. Further analysis indicated that the thrombin mutant exhibits resistance to antithrombin and is inhibited by the serpin with approximately 12-fold slower rate constant. Protein C activation by thrombin-Y510N was also decreased by approximately 10-fold; however, thrombomodulin overcame the catalytic defect. The Na⁺-concentration-dependence of the amidolytic activities revealed that the dissociation constant for the interaction of Na⁺ with the mutant has been elevated approximately 20-fold. These results suggest that Y510 (Y184a in chymotrypsin numbering) belongs to network of residues involved in binding Na⁺. A normal protein C activation by thrombin-Y510N suggests that thrombomodulin modulates the conformation of the Na⁺-binding loop of thrombin. The clotting defect of thrombin-Y510N appears to be compensated by its markedly lower reactivity with antithrombin, explaining patient's normal hemostatic phenotype.

Resources and computational strategies to advance small molecule SARS-CoV-2 discovery: Lessons from the pandemic and preparing for future health crises

There is an urgent need to identify new therapies that prevent SARS-CoV-2 infection and improve the outcome of COVID-19 patients. This pandemic has thus spurred intensive research in most scientific areas and in a short period of time, several vaccines have been developed. But, while the race to find vaccines for COVID-19 has dominated the headlines, other types of therapeutic agents are being developed. In this mini-review, we report several databases and online tools that could assist the discovery of anti-SARS-CoV-2 small chemical compounds and peptides. We then give examples of studies that combined in silico and in vitro screening, either for drug repositioning purposes or to search for novel bioactive compounds. Finally, we question the overall lack of discussion and plan observed in academic research in many countries during this crisis and suggest that there is room for improvement.

Chemoinformatic Analysis of Psychotropic and Antihistaminic Drugs in the Light of Experimental Anti-SARS-CoV-2 Activities

Introduction

There is an urgent need to identify therapies that prevent SARS-CoV-2 infection and improve the outcome of COVID-19 patients.

Objective

Based upon clinical observations, we proposed that some psychotropic and antihistaminic drugs could protect psychiatric patients from SARS-CoV-2 infection. This observation is investigated in the light of experimental in vitro data on SARS-CoV-2.

Methods

SARS-CoV-2 high-throughput screening results are available at the NCATS COVID-19 portal. We investigated the in vitro anti-viral activity of many psychotropic and antihistaminic drugs using chemoinformatics approaches.

Results and Discussion

We analyze our clinical observations in the light of SARS-CoV-2 experimental screening results and propose that several cationic amphiphilic psychotropic and antihistaminic drugs could protect people from SARS-CoV-2 infection; some of these molecules have very limited adverse effects and could be used as prophylactic drugs. Other cationic amphiphilic drugs used in other disease areas are also highlighted. Recent analyses of patient electronic health records reported by several research groups indicate that some of these molecules could be of interest at different stages of the disease progression. In addition, recently reported drug combination studies further suggest that it might be valuable to associate several cationic amphiphilic drugs. Taken together, these observations underline the need for clinical trials to fully evaluate the potentials of these molecules, some fitting in the so-called category of broad-spectrum antiviral agents. Repositioning orally available drugs that have moderate side effects and should act on molecular mechanisms less prone to drug resistance would indeed be of utmost importance to deal with COVID-19.

PAK1-Dependent Antitumor Effect of AAC-11‒Derived Peptides on Sézary Syndrome Malignant CD4+ T Lymphocytes

Sézary syndrome is an aggressive form of cutaneous T-cell lymphoma characterized by the presence of a malignant CD4⁺ T-cell clone in both blood and skin. Its pathophysiology is still poorly understood, and the development of targeted therapies is hampered by the absence of specific target proteins. AAC-11 plays important roles in cancer cell progression and survival and thus has been considered as an anticancer therapeutic target. In this study, we show that a peptide called RT39, comprising a portion of AAC-11‒binding site to its protein partners coupled to the penetratin sequence, induces the specific elimination of the malignant T-cell clone both ex vivo on the circulating cells of patients with Sézary syndrome and in vivo in a subcutaneous xenograft mouse model. RT39 acts by direct binding to PAK1 that is overexpressed, located in the plasma membrane, and constitutively activated in Sézary cells, resulting in their selective depletion by membranolysis. Along with the absence of toxicity, our preclinical efficacy evidence suggests that RT39 might represent a promising alternative therapeutic tool for Sézary syndrome because it spares the nonmalignant immune cells and, contrary to antibody-based immunotherapies, does not require the mobilization of the cellular immunity that shows heavy deficiencies at advanced stages of the disease.

Role of Gly197 in the structure and function of protein C

We previously demonstrated that heterozygous Gly197 to Arg mutation in PROC is associated with venous thrombosis due to the mutation abrogating both zymogenic and enzymatic activities of protein C and activated protein C (APC). In this study, we investigated the role of Gly197 on the structure and function of protein C by replacing it with Ala, Lys and Glu in separate constructs. Characterization of protein C mutants indicated their activation by thrombin is improved ~5-20-fold with the order of PC-G197K > PC-G197E > PC-G197A > PC-WT. Interestingly, the cofactor function of thrombomodulin (TM) in promoting the activation of zymogens by thrombin followed the reverse order of PC-WT > PC-G197A > PC-G197E > PC-G197K. The thrombin-generation inhibitory profiles of zymogens in a tissue factor-mediated thrombin generation assay using protein C-deficient plasma with or without supplementation with TM followed the same order of zymogen activation in the purified system. Evaluation of anticoagulant activities of APC derivatives by prothrombinase and aPTT assays revealed a normal activity for APC-G197A but dramatically impaired activity for the other two mutants. In the endothelial cell permeability assay, APC-G197A exhibited normal antiinflammatory activity, but the other two mutants were nearly inactive. These results suggest that Gly197 plays a key role in TM cofactor-dependent protein C activation by thrombin. It facilitates the recognition of protein C by thrombin in the presence of TM but impedes it in the absence of the cofactor. In APC, a small residue at this position is required for the proper folding/reactivity of the active-site pocket of the protease, a hypothesis supported by structural modeling.

In Silico Investigation of the New UK (B.1.1.7) and South African (501Y.V2) SARS-CoV-2 Variants with a Focus at the ACE2-Spike RBD Interface

SARS-CoV-2 exploits angiotensin-converting enzyme 2 (ACE2) as a receptor to invade cells. It has been reported that the UK and South African strains may have higher transmission capabilities, eventually in part due to amino acid substitutions on the SARS-CoV-2 Spike protein. The pathogenicity seems modified but is still under investigation. Here we used the experimental structure of the Spike RBD domain co-crystallized with part of the ACE2 receptor, several in silico methods and numerous experimental data reported recently to analyze the possible impacts of three amino acid replacements (Spike K417N, E484K, N501Y) with regard to ACE2 binding. We found that the N501Y replacement in this region of the interface (present in both the UK and South African strains) should be favorable for the interaction with ACE2, while the K417N and E484K substitutions (South African strain) would seem neutral or even unfavorable. It is unclear if the N501Y substitution in the South African strain could counterbalance the K417N and E484K Spike replacements with regard to ACE2 binding. Our finding suggests that the UK strain should have higher affinity toward ACE2 and therefore likely increased transmissibility and possibly pathogenicity. If indeed the South African strain has a high transmission level, this could be due to the N501Y replacement and/or to substitutions in regions located outside the direct Spike-ACE2 interface but not so much to the K417N and E484K replacements. Yet, it should be noted that amino acid changes at Spike position 484 can lead to viral escape from neutralizing antibodies. Further, these amino acid substitutions do not seem to induce major structural changes in this region of the Spike protein. This structure-function study allows us to rationalize some observations made for the UK strain but raises questions for the South African strain.

Demystifying the Molecular Basis of Pyrazoloquinolinones Recognition at the Extracellular α1+/β3- Interface of the GABAA Receptor by Molecular Modeling

GABA_A receptors are pentameric ligand-gated ion channels that serve as major inhibitory neurotransmitter receptors in the mammalian brain and the target of numerous clinically relevant drugs interacting with different ligand binding sites. Here, we report an in silico approach to investigate the binding of pyrazoloquinolinones (PQs) that mediate allosteric effects through the extracellular α+/β- interface of GABA_A receptors. First, we docked a potent prototype of PQs into the α1+/β3- site of a homology model of the human α1β3γ2 subtype of the GABA_A receptor. Next, for each docking pose, we computationally derived protein-ligand complexes for 18 PQ analogs with known experimental potency. Subsequently, binding energy was calculated for all complexes using the molecular mechanics-generalized Born surface area method. Finally, docking poses were quantitatively assessed in the light of experimental data to derive a binding hypothesis. Collectively, the results indicate that PQs at the α1+/β3- site likely exhibit a common binding mode that can be characterized by a hydrogen bond interaction with β3Q64 and hydrophobic interactions involving residues α1F99, β3Y62, β3M115, α1Y159, and α1Y209. Importantly, our results are in good agreement with the recently resolved cryo-Electron Microscopy structures of the human α1β3γ2 and α1β2γ2 subtypes of GABA_A receptors.

FastTargetPred: a program enabling the fast prediction of putative protein targets for input chemical databases

SUMMARY

Several web-based tools predict the putative targets of a small molecule query compound by similarity to molecules with known bioactivity data using molecular fingerprints. In numerous situations, it would however be valuable to be able to run such computations on a local computer. We present FastTargetPred, a new program for the prediction of protein targets for small molecule queries. Structural similarity computations rely on a large collection of confirmed protein-ligand activities extracted from the curated ChEMBL 25 database. The program allows to annotate an input chemical library of ∼100k compounds within a few hours on a simple personal computer.

AVAILABILITY AND IMPLEMENTATION

FastTargetPred is written in Python 3 (≥3.7) and C languages. Python code depends only on the Python Standard Library. The program can be run on Linux, MacOS and Windows operating systems. Pre-compiled versions are available at https://github.com/ludovicchaput/FastTargetPred. FastTargetPred is licensed under the GNU GPLv3. The program calls some scripts from the free chemistry toolkit MayaChemTools.

CONTACT

bruno.villoutreix@inserm.fr.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Fast Rescoring Protocols to Improve the Performance of Structure-Based Virtual Screening Performed on Protein-Protein Interfaces

Protein-protein interactions (PPIs) are attractive targets for drug design because of their essential role in numerous cellular processes and disease pathways. However, in general, PPIs display exposed binding pockets at the interface, and as such, have been largely unexploited for therapeutic interventions with low-molecular weight compounds. Here, we used docking and various rescoring strategies in an attempt to recover PPI inhibitors from a set of active and inactive molecules for 11 targets collected in ChEMBL and PubChem. Our focus is on the screening power of the various developed protocols and on using fast approaches so as to be able to apply such a strategy to the screening of ultralarge libraries in the future. First, we docked compounds into each target using the fast "pscreen" mode of the structure-based virtual screening (VS) package Surflex. Subsequently, the docking poses were postprocessed to derive a set of 3D topological descriptors: (i) shape similarity and (ii) interaction fingerprint similarity with a co-crystallized inhibitor, (iii) solvent-accessible surface area, and (iv) extent of deviation from the geometric center of a reference inhibitor. The derivatized descriptors, together with descriptor-scaled scoring functions, were utilized to investigate possible impacts on VS performance metrics. Moreover, four standalone scoring functions, RF-Score-VS (machine-learning), DLIGAND2 (knowledge-based), Vinardo (empirical), and X-SCORE (empirical), were employed to rescore the PPI compounds. Collectively, the results indicate that the topological scoring algorithms could be valuable both at a global level, with up to 79% increase in areas under the receiver operating characteristic curve for some targets, and in early stages, with up to a 4-fold increase in enrichment factors at 1% of the screened collections. Outstandingly, DLIGAND2 emerged as the best scoring function on this data set, outperforming all rescoring techniques in terms of VS metrics. The described methodology could help in the rational design of small-molecule PPI inhibitors and has direct applications in many therapeutic areas, including cancer, CNS, and infectious diseases such as COVID-19.

Structure-based drug repositioning over the human TMPRSS2 protease domain: search for chemical probes able to repress SARS-CoV-2 Spike protein cleavages

In December 2019, a new coronavirus was identified in the Hubei province of central china and named SARS-CoV-2. This new virus induces COVID-19, a severe respiratory disease with high death rate. A putative target to interfere with the virus is the host transmembrane serine protease family member II (TMPRSS2). This enzyme is critical for the entry of coronaviruses into human cells by cleaving and activating the spike protein (S) of SARS-CoV-2. Repositioning approved, investigational and experimental drugs on the serine protease domain of TMPRSS2 could thus be valuable. There is no experimental structure for TMPRSS2 but it is possible to develop quality structural models for the serine protease domain using comparative modeling strategies as such domains are highly structurally conserved. Beside the TMPRSS2 catalytic site, we predicted on our structural models a main exosite that could be important for the binding of protein partners and/or substrates. To block the catalytic site or the exosite of TMPRSS2 we used structure-based virtual screening computations and two different collections of approved, investigational and experimental drugs. We propose a list of 156 molecules that could bind to the catalytic site and 100 compounds that may interact with the exosite. These small molecules should now be tested in vitro to gain novel insights over the roles of TMPRSS2 or as starting point for the development of second generation analogs.

ELA/APELA precursor cleaved by furin displays tumor suppressor function in renal cell carcinoma through mTORC1 activation

Apelin is a well-established mediator of survival and mitogenic signaling through the apelin receptor (Aplnr) and has been implicated in various cancers; however, little is known regarding Elabela (ELA/APELA) signaling, also mediated by Aplnr, and its role and the role of the conversion of its precursor proELA into mature ELA in cancer are unknown. Here, we identified a function of mTORC1 signaling as an essential mediator of ELA that repressed kidney tumor cell growth, migration, and survival. Moreover, sunitinib and ELA showed a synergistic effect in repressing tumor growth and angiogenesis in mice. The use of site-directed mutagenesis and pharmacological experiments provided evidence that the alteration of the cleavage site of proELA by furin induced improved ELA antitumorigenic activity. Finally, a cohort of tumors and public data sets revealed that ELA was only repressed in the main human kidney cancer subtypes, namely clear cell, papillary, and chromophobe renal cell carcinoma. Aplnr was expressed by various kidney cells, whereas ELA was generally expressed by epithelial cells. Collectively, these results showed the tumor-suppressive role of mTORC1 signaling mediated by ELA and established the potential use of ELA or derivatives in kidney cancer treatment.

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.

Thr90Ser Mutation in Antithrombin is Associated with Recurrent Thrombosis in a Heterozygous Carrier

Antithrombin (AT) is a serine protease inhibitor that regulates the activity of coagulation proteases of both intrinsic and extrinsic pathways. We identified an AT-deficient patient with a heterozygous Thr90Ser (T90S) mutation who experiences recurrent venous thrombosis. To understand the molecular basis of the clotting defect, we expressed AT-T90S in mammalian cells, purified it to homogeneity, and characterized its properties in established kinetics, binding, and coagulation assays. The possible effect of mutation on the AT structure was also evaluated by molecular modeling. Results demonstrate the inhibitory activity of AT-T90S toward thrombin and factor Xa has been impaired three- to fivefold in both the absence and presence of heparin. The affinity of heparin for AT-T90S has been decreased by four- to fivefold. Kinetic analysis revealed the stoichiometry of AT-T90S inhibition of both thrombin and factor Xa has been elevated by three- to fourfold in both the absence and presence of heparin, suggesting that the reactivity of coagulation proteases with AT-T90S has been elevated in the substrate pathway. The anticoagulant activity of AT-T90S has been significantly impaired as analyzed in the AT-deficient plasma supplemented with AT-T90S. The anti-inflammatory effect of AT-T90S was also decreased. Structural analysis predicts the shorter side-chain of Ser in AT-T90S has a destabilizing effect on the structure of AT and/or the AT-protease complex, possibly increasing the size of an internal cavity and altering a hydrogen-bonding network that modulates conformations of the allosterically linked heparin-binding site and reactive center loop of the serpin. This mutational effect increases the reactivity of AT-T90S with coagulation proteases in the substrate pathway.

Gly197Arg mutation in protein C causes recurrent thrombosis in a heterozygous carrier

BACKGROUND

Activated protein C (APC) downregulates thrombin generation by inactivating procoagulant cofactors Va and VIIIa by limited proteolysis. We identified two protein C-deficient patients both of whom carry a heterozygous Gly197 to Arg (G197R) mutation in PROC and experience venous thrombosis.

OBJECTIVE

The objective of this study was to determine the molecular basis of the clotting defect in patients carrying the G197R mutation.

METHODS

We expressed protein C-G197R in mammalian cells and characterized its properties in established coagulation and anti-inflammatory assay systems.

RESULTS

The activation of protein C-G197R by thrombin was improved ~10-fold; however, its activation by thrombin was not promoted by thrombomodulin (TM). In a tissue factor-mediated thrombin generation assay, the addition of soluble TM to protein C-deficient plasma, supplemented with protein C-G197R, did not have a significant inhibitory effect on thrombin generation parameters. APC-G197R did not exhibit a significant anticoagulant activity in either purified or plasma-based assay systems. APC-G197R was essentially inactive because it showed no activity in an aPTT assay. Anti-inflammatory activity of APC-G197R was also dramatically impaired as determined by an endothelial cell permeability assay. Structural modeling predicted that the side-chain of Arg cannot be accommodated at this site of APC without a major distortion of the local structure that appears to propagate and adversely affect the reactivity/folding of the catalytic pocket.

CONCLUSION

The G197R mutation in patients appears to be functionally equivalent to a heterozygous protein C knockout with half of the protein having no significant activity and thus causing thrombosis.

Analysis of protein missense alterations by combining sequence- and structure-based methods

BACKGROUND

Different types of in silico approaches can be used to predict the phenotypic consequence of missense variants. Such algorithms are often categorized as sequence based or structure based, when they necessitate 3D structural information. In addition, many other in silico tools, not dedicated to the analysis of variants, can be used to gain additional insights about the possible mechanisms at play.

METHODS

Here we applied different computational approaches to a set of 20 known missense variants present on different proteins (CYP, complement factor B, antithrombin and blood coagulation factor VIII). The tools that were used include fast computational approaches and web servers such as PolyPhen-2, PopMusic, DUET, MaestroWeb, SAAFEC, Missense3D, VarSite, FlexPred, PredyFlexy, Clustal Omega, meta-PPISP, FTMap, ClusPro, pyDock, PPM, RING, Cytoscape, and ChannelsDB.

RESULTS

We observe some conflicting results among the methods but, most of the time, the combination of several engines helped to clarify the potential impacts of the amino acid substitutions.

CONCLUSION

Combining different computational approaches including some that were not developed to investigate missense variants help to predict the possible impact of the amino acid substitutions. Yet, when the modified residues are involved in a salt-bridge, the tools tend to fail, even when the analysis is performed in 3D. Thus, interactive structural analysis with molecular graphics packages such as Chimera or PyMol or others are still needed to clarify automatic prediction.

Virtual screening web servers: designing chemical probes and drug candidates in the cyberspace

The interplay between life sciences and advancing technology drives a continuous cycle of chemical data growth; these data are most often stored in open or partially open databases. In parallel, many different types of algorithms are being developed to manipulate these chemical objects and associated bioactivity data. Virtual screening methods are among the most popular computational approaches in pharmaceutical research. Today, user-friendly web-based tools are available to help scientists perform virtual screening experiments. This article provides an overview of internet resources enabling and supporting chemical biology and early drug discovery with a main emphasis on web servers dedicated to virtual ligand screening and small-molecule docking. This survey first introduces some key concepts and then presents recent and easily accessible virtual screening and related target-fishing tools as well as briefly discusses case studies enabled by some of these web services. Notwithstanding further improvements, already available web-based tools not only contribute to the design of bioactive molecules and assist drug repositioning but also help to generate new ideas and explore different hypotheses in a timely fashion while contributing to teaching in the field of drug development.

Anti-Factor B Antibodies and Acute Postinfectious GN in Children

BACKGROUND

The pathophysiology of the leading cause of pediatric acute nephritis, acute postinfectious GN, including mechanisms of the pathognomonic transient complement activation, remains uncertain. It shares clinicopathologic features with C3 glomerulopathy, a complement-mediated glomerulopathy that, unlike acute postinfectious GN, has a poor prognosis.

METHODS

This retrospective study investigated mechanisms of complement activation in 34 children with acute postinfectious GN and low C3 level at onset. We screened a panel of anticomplement protein autoantibodies, carried out related functional characterization, and compared results with those of 60 children from the National French Registry who had C3 glomerulopathy and persistent hypocomplementemia.

RESULTS

All children with acute postinfectious GN had activation of the alternative pathway of the complement system. At onset, autoantibodies targeting factor B (a component of the alternative pathway C3 convertase) were found in a significantly higher proportion of children with the disorder versus children with hypocomplementemic C3 glomerulopathy (31 of 34 [91%] versus 4 of 28 [14%], respectively). In acute postinfectious GN, anti-factor B autoantibodies were transient and correlated with plasma C3 and soluble C5b-9 levels. We demonstrated that anti-factor B antibodies enhance alternative pathway convertase activity in vitro, confirming their pathogenic effect. We also identified crucial antibody binding sites on factor B, including one correlated to disease severity.

CONCLUSIONS

These findings elucidate the pathophysiologic mechanisms underlying acute postinfectious GN by identifying anti-factor B autoantibodies as contributing factors in alternative complement pathway activation. At onset of a nephritic syndrome with low C3 level, screening for anti-factor B antibodies might help guide indications for kidney biopsy to avoid misdiagnosed chronic glomerulopathy, such as C3 glomerulopathy, and to help determine therapy.

Ile73Asn mutation in protein C introduces a new N-linked glycosylation site on the first EGF-domain of protein C and causes thrombosis

Activated protein C exerts its anticoagulant activity by protein S-dependent inactivation of factors Va and VIIIa by limited proteolysis. We identified a venous thrombosis patient who has plasma protein C antigen level of 63% and activity levels of 44% and 23%, as monitored by chromogenic and clotting assays. Genetic analysis revealed the proband carries compound heterozygous mutations (c.344T>A, p.I73N and c.1181G>A, p.R352Q) in PROC. We individually expressed protein C mutations and discovered that thrombin-thrombomodulin activates both variants normally and the resulting activated protein C mutants exhibit normal amidolytic and proteolytic activities. However, while protein S-dependent catalytic activity of activated protein C-R352Q toward factor Va was normal, it was significantly impaired for activated protein C-I73N. These results suggest that the Ile to Asn substitution impairs interaction of activated protein C-I73N with protein S. This conclusion was supported by a normal anticoagulant activity for activated protein C-I73N in protein S-deficient but not in normal plasma. Further analysis revealed Ile to Asn substitution introduces a new glycosylation site on first EGF-like domain of protein C, thereby adversely affecting interaction of activated protein C with protein S. Activated protein C-R352Q only exhibited reduced activity in sub-physiological concentrations of Na⁺ and Ca²⁺, suggesting that this residue contributes to metal ion-binding affinity of the protease, with no apparent adverse effect on its function in the presence of physiological levels of metal ions. These results provide insight into the mechanism by which I73N/R352Q mutations in activated protein C cause thrombosis in proband carrying this compound heterozygous mutation.

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.

Online structure-based screening of purchasable approved drugs and natural compounds: retrospective examples of drug repositioning on cancer targets

Drug discovery is a long and difficult process that benefits from the integration of virtual screening methods in experimental screening campaigns such as to generate testable hypotheses, accelerate and/or reduce the cost of drug development. Current drug attrition rate is still a major issue in all therapeutic areas and especially in the field of cancer. Drug repositioning as well as the screening of natural compounds constitute promising approaches to accelerate and improve the success rate of drug discovery. We developed three compounds libraries of purchasable compounds: Drugs-lib, FOOD-lib and NP-lib that contain approved drugs, food constituents and natural products, respectively, that are optimized for structure-based virtual screening studies. The three compounds libraries are implemented in the MTiOpenScreen web server that allows users to perform structure-based virtual screening computations on their selected protein targets. The server outputs a list of 1,500 molecules with predicted binding scores that can then be processed further by the users and purchased for experimental validation. To illustrate the potential of our service for drug repositioning endeavours, we selected five recently published drugs that have been repositioned in vitro and/or in vivo on cancer targets. For each drug, we used the MTiOpenScreen service to screen the Drugs-lib collection against the corresponding anti-cancer target and we show that our protocol is able to rank these drugs within the top ranked compounds. This web server should assist the discovery of promising molecules that could benefit patients, with faster development times, and reduced costs and risk.

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.

A Two-Allele Polymorphism in Protein C Inhibitor with Varying Frequencies in Different Ethnic Populations

cDNAs for protein C inhibitor (PCI), prepared from human liver RNA, contained two forms of PCI, designated PCI*A and PCPB 1 . While PCI*A is identical to the published PCI sequence, PCPB differs in 4 of 1221 bp and two amino acids, A36V and K86E. Frequencies for the PCI*B allele, determined from genomic DNA, differed among ethnic groups. Frequency distribution and historical migration of modem man suggest that PCI*A arose from the PCI*B allele. Antigen levels in plasma homozygous for PCI*A or PCI*B equalled that of pooled normal plasma. K86E in PCI*B causes a charge alteration in helix D which is likely involved in heparin binding in antithrombin III but not likely involved in glycosaminoglycan binding in PCI. Kinetic studies showed that plasmas homozygous for PCI*A and PCPB are similar in their APC inhibiting properties and in their heparin sensitivity, consistent with the idea that helix D in PCI is not involved in heparin binding

Characterization of a cDNA for Rhesus Monkey Protein C Inhibitor – Evidence for N-Terminal Involvement in Heparin Stimulation

cDNAs for protein C inhibitor (PCI) were cloned from human and rhesus monkey 1 liver RNAs by reverse transcription and polymerase chain reaction (PCR) amplification. Sequencing showed that rhesus monkey and human PCI cDNAs were 93% identical. Predicted amino acid sequences differed at 26 of 387 residues. Pour of these differences (T352M, N359S, R362K, L3631) were in the reactive center loop that is important for inhibitory specificity, and two were in the N-terminal helix (M8T, E13K) that is implicated in glycosaminoglycan binding. PCI in human or rhesus monkey plasma showed comparable inhibitory activity towards human activated protein C in the presence of 10 U/ml heparin. However, maximal acceleration of the inhibition of activated protein C required 5-fold lower heparin concentration for rhesus monkey than for human plasma, consistent with the interpretation that the additional positive charge (E13K) in a putative-heparin binding region increased the affinity for heparin.

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 β 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.

Blockade of the malignant phenotype by β-subunit selective noncovalent inhibition of immuno- and constitutive proteasomes

A structure-based virtual screening of over 400,000 small molecules against the constitutive proteasome activity followed by in vitro assays led to the discovery of a family of proteasome inhibitors with a sulfonyl piperazine scaffold. Some members of this family of small non-peptidic inhibitors were found to act selectively on the β2 trypsin-like catalytic site with a preference for the immunoproteasome β2i over the constitutive proteasome β2c, while some act on the β5 site and post-acid site β1 of both, the immunoproteasome and the constitutive proteasome. Anti-proliferative and anti-invasive effects on tumor cells were investigated and observed for two compounds. We report novel chemical inhibitors able to interfere with the three types of active centers of both, the immuno- and constitutive proteasomes. Identifying and analyzing a novel scaffold with decorations able to shift the binders’ active site selectivity is essential to design a future generation of proteasome inhibitors able to distinguish the immunoproteasome from the constitutive proteasome.

Expression and functional characterization of two natural heparin-binding site variants of antithrombin

Essentials Heparin-binding site (HBS) variants of antithrombin (AT) are associated with thrombosis risk. HSB variants have, in general, normal progressive inhibitory activity but reduced heparin affinity. Thrombosis in HSB carriers has been primarily attributed to the loss of heparin cofactor activity. Results here demonstrate that HSB variants of AT also lack anti-inflammatory signaling functions.

SUMMARY

Background Several heparin-binding site (HBS) variants of antithrombin (AT) have been identified that predispose carriers to a higher incidence of thrombosis. Thrombosis in carriers of HBS variants has been primarily attributed to a loss in their heparin-dependent anticoagulant function. Objective The objective of this study was to determine whether HSB mutations affect the anti-inflammatory functions of variants. Methods Two HBS variants of AT (AT-I7N and AT-L99F), which are known to be associated with a higher incidence of thrombosis, were expressed in mammalian cells and purified to homogeneity. These variants were characterized by kinetic assays followed by analysis of their activities in established cellular and/or in vivo inflammatory models. The possible effects of mutations on AT structure were also evaluated by molecular modeling. Results The results indicated that, whereas progressive inhibitory activities of variants were minimally affected, their heparin affinity and inhibitory activity in the presence of heparin were markedly decreased. Unlike wild-type AT, neither AT variant was capable of inhibiting activation of nuclear factor-κB or downregulation of expression of cell adhesion molecules in response to lipopolysaccharide (LPS). Similarly, neither variant elicited barrier protective activity in response to LPS. Structural analysis suggested that the L99F substitution locally destabilizes AT structure. Conclusions It is concluded that the L99F mutation of AT is associated with destabilization of the serpin structure, and that the loss of anti-inflammatory signaling function of the HBS variants may also contribute to enhanced thrombosis in carriers of HBS mutations.

Breast Cancer Targeting through Inhibition of the Endoplasmic Reticulum-Based Apoptosis Regulator Nrh/BCL2L10

Drug resistance and metastatic relapse remain a top challenge in breast cancer treatment. In this study, we present preclinical evidence for a strategy to eradicate advanced breast cancers by targeting the BCL-2 homolog Nrh/BCL2L10, which we discovered to be overexpressed in >45% of a large cohort of breast invasive carcinomas. Nrh expression in these tumors correlated with reduced metastasis-free survival, and we determined it to be an independent marker of poor prognosis. Nrh protein localized to the endoplasmic reticulum. Mechanistic investigations showed that Nrh made BH4 domain-dependent interactions with the ligand-binding domain of the inositol-1,4,5-triphosphate receptor (IP3R), a type 1/3 Ca2⁺ channel, allowing Nrh to negatively regulate ER-Ca2⁺ release and to mediate antiapoptosis. Notably, disrupting Nrh/IP3R complexes by BH4 mimetic peptides was sufficient to inhibit the growth of breast cancer cells in vitro and in vivo Taken together, our results highlighted Nrh as a novel prognostic marker and a candidate therapeutic target for late stage breast cancers that may be addicted to Nrh.Significance: These findings offer a comprehensive molecular model for the activity of Nrh/BCL2L10, a little studied antiapoptotic molecule, prognostic marker, and candidate drug target in breast cancer. Cancer Res; 78(6); 1404-17. ©2018 AACR.

Identification of insulin-sensitizing molecules acting by disrupting the interaction between the Insulin Receptor and Grb14

Metabolic diseases are characterized by a decreased action of insulin. During the course of the disease, usual treatments frequently fail and patients are finally submitted to insulinotherapy. There is thus a need for innovative therapeutic strategies to improve insulin action. Growth factor receptor-bound protein 14 (Grb14) is a molecular adapter that specifically binds to the activated insulin receptor (IR) and inhibits its tyrosine kinase activity. Molecules disrupting Grb14-IR binding are therefore potential insulin-sensitizing agents. We used Structure-Based Virtual Ligand Screening to generate a list of 1000 molecules predicted to hinder Grb14-IR binding. Using an acellular bioluminescence resonance energy transfer (BRET) assay, we identified, out of these 1000 molecules, 3 compounds that inhibited Grb14-IR interaction. Their inhibitory effect on insulin-induced Grb14-IR interaction was confirmed in co-immunoprecipitation experiments. The more efficient molecule (C8) was further characterized. C8 increased downstream Ras-Raf and PI3-kinase insulin signaling, as shown by BRET experiments in living cells. Moreover, C8 regulated the expression of insulin target genes in mouse primary hepatocytes. These results indicate that C8, by reducing Grb14-IR interaction, increases insulin signalling. The use of C8 as a lead compound should allow for the development of new molecules of potential therapeutic interest for the treatment of diabetes.

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.

Gly74Ser mutation in protein C causes thrombosis due to a defect in protein S-dependent anticoagulant function

Protein C is a vitamin K-dependent serine protease zymogen in plasma which upon activation by thrombin in complex with thrombomodulin (TM) down-regulates the clotting cascade by a feedback loop inhibition mechanism. Activated protein C (APC) exerts its anticoagulant function through protein S-dependent degradation of factors Va and VIIIa. We recently identified a venous thrombosis patient whose plasma level of protein C antigen is normal, but its anticoagulant activity is only 34 % of the normal level. Genetic analysis revealed that the proband and her younger brother carry a novel heterozygous mutation c.346G>A, p.Gly74Ser (G74S) in PROC. Thrombin generation assay indicated that the TM-dependent anticoagulant activity of the proband's plasma has been significantly impaired. We expressed protein C-G74S in mammalian cells and characterised its properties in established coagulation assays. We demonstrate that the protein C variant can be normally activated by the thrombin-TM complex and the resulting APC mutant also exhibits normal amidolytic and proteolytic activities toward both FVa and FVIIIa. However, it was discovered the protein S-dependent catalytic activity of APC variant toward both procoagulant cofactors has been significantly impaired. Protein S concentration-dependence of FVa degradation revealed that the capacity of APC variant to interact with the cofactor has been markedly impaired. The same results were obtained for inactivation of FVa-Leiden suggesting that the protein S-dependent activity of APC variant toward cleavage of Arg-306 site has been adversely affected. These results provide insight into the mechanism through which G74S substitution in APC causes thrombosis in the proband carrying this mutation.

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.

Genetic polymorphisms associated with increased risk of developing chronic myelogenous leukemia

Little is known about inherited factors associated with the risk of developing chronic myelogenous leukemia (CML). We used a dedicated DNA chip containing 16 561 single nucleotide polymorphisms (SNPs) covering 1 916 candidate genes to analyze 437 CML patients and 1 144 healthy control individuals. Single SNP association analysis identified 139 SNPs that passed multiple comparisons (1% false discovery rate). The HDAC9, AVEN, SEMA3C, IKBKB, GSTA3, RIPK1 and FGF2 genes were each represented by three SNPs, the PSM family by four SNPs and the SLC15A1 gene by six. Haplotype analysis showed that certain combinations of rare alleles of these genes increased the risk of developing CML by more than two or three-fold. A classification tree model identified five SNPs belonging to the genes PSMB10, TNFRSF10D, PSMB2, PPARD and CYP26B1, which were associated with CML predisposition. A CML-risk-allele score was created using these five SNPs. This score was accurate for discriminating CML status (AUC: 0.61, 95%CI: 0.58-0.64). Interestingly, the score was associated with age at diagnosis and the average number of risk alleles was significantly higher in younger patients. The risk-allele score showed the same distribution in the general population (HapMap CEU samples) as in our control individuals and was associated with differential gene expression patterns of two genes (VAPA and TDRKH). In conclusion, we describe haplotypes and a genetic score that are significantly associated with a predisposition to develop CML. The SNPs identified will also serve to drive fundamental research on the putative role of these genes in CML development.

Pharmacogenomics of the cytochrome P450 2C family: impacts of amino acid variations on drug metabolism

Pharmacogenomics investigates DNA and RNA variations in the human genome related to drug responses. Cytochrome P450 (CYP) is a supergene family of drug-metabolizing enzymes responsible for the metabolism of approximately 90% of human drugs. Among the major CYP isoforms, the CYP2C subfamily is of clinical significance because it metabolizes approximately 20% of clinically administrated drugs and represents several variant alleles leading to adverse drug reactions or altering drug efficacy. Here, we review recent progress on understanding the interindividual variability of the CYP2C members and the functional and clinical impact on drug metabolism. We summarize current advances in the molecular modeling of CYP2C polymorphisms and discuss the structural bases and molecular mechanisms of amino acid variants of CYP2C members that affect drug metabolism.

DNA damage-induced nuclear translocation of Apaf-1 is mediated by nucleoporin Nup107

Beside its central role in the mitochondria-dependent cell death pathway, the apoptotic protease activating factor 1 (Apaf-1) is involved in the DNA damage response through cell-cycle arrest induced by genotoxic stress. This non-apoptotic function requires a nuclear translocation of Apaf-1 during the G1-to-S transition. However, the mechanisms that trigger the nuclear accumulation of Apaf-1 upon DNA damage remain to be investigated. Here we show that the main 4 isoforms of Apaf-1 can undergo nuclear translocation and restore Apaf-1 deficient MEFs cell cycle arrest in the S phase following genotoxic stress through activation of Chk-1. Interestingly, DNA damage-dependent nuclear accumulation of Apaf-1 occurs independently of p53 and the retinoblastoma (pRb) pathway. We demonstrated that Apaf-1 associates with the nucleoporin Nup107 and this association is necessary for Apaf-1 nuclear import. The CED-4 domain of Apaf-1 directly binds to the central domain of Nup107 in an ATR-regulated, phosphorylation-dependent manner. Interestingly, expression of the Apaf-1-interacting domain of Nup107 interfered with Apaf-1 nuclear translocation upon genotoxic stress, resulting in a marked reduction of Chk-1 activation and cell cycle arrest. Thus, our results confirm the crucial role of Apaf-1 nuclear relocalization in mediating cell-cycle arrest induced by genotoxic stress and implicate Nup107 as a critical regulator of the DNA damage-induced intra-S phase checkpoint response.

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.