Systematic screening identifies ABCG2 as critical factor underlying synergy of kinase inhibitors with transcriptional CDK inhibitors.

BACKGROUND: Triple-negative breast cancer (TNBC) is a subtype of breast cancer with limited treatment options and poor clinical prognosis. Inhibitors of transcriptional CDKs are currently under thorough investigation for application in the treatment of multiple cancer types, including breast cancer. These studies have raised interest in combining these inhibitors, including CDK12/13 inhibitor THZ531, with a variety of other anti-cancer agents. However, the full scope of these potential synergistic interactions of transcriptional CDK inhibitors with kinase inhibitors has not been systematically investigated. Moreover, the mechanisms behind these previously described synergistic interactions remain largely elusive. METHODS: Kinase inhibitor combination screenings were performed to identify kinase inhibitors that synergize with CDK7 inhibitor THZ1 and CDK12/13 inhibitor THZ531 in TNBC cell lines. CRISPR-Cas9 knockout screening and transcriptomic evaluation of resistant versus sensitive cell lines were performed to identify genes critical for THZ531 resistance. RNA sequencing analysis after treatment with individual and combined synergistic treatments was performed to gain further insights into the mechanism of this synergy. Kinase inhibitor screening in combination with visualization of ABCG2-substrate pheophorbide A was used to identify kinase inhibitors that inhibit ABCG2. Multiple transcriptional CDK inhibitors were evaluated to extend the significance of the found mechanism to other transcriptional CDK inhibitors. RESULTS: We show that a very high number of tyrosine kinase inhibitors synergize with the CDK12/13 inhibitor THZ531. Yet, we identified the multidrug transporter ABCG2 as key determinant of THZ531 resistance in TNBC cells. Mechanistically, we demonstrate that most synergistic kinase inhibitors block ABCG2 function, thereby sensitizing cells to transcriptional CDK inhibitors, including THZ531. Accordingly, these kinase inhibitors potentiate the effects of THZ531, disrupting gene expression and increasing intronic polyadenylation. CONCLUSION: Overall, this study demonstrates the critical role of ABCG2 in limiting the efficacy of transcriptional CDK inhibitors and identifies multiple kinase inhibitors that disrupt ABCG2 transporter function and thereby synergize with these CDK inhibitors. These findings therefore further facilitate the development of new (combination) therapies targeting transcriptional CDKs and highlight the importance of evaluating the role of ABC transporters in synergistic drug-drug interactions in general.

Folate receptor alpha in ovarian cancer tissue and patient serum is associated with disease burden and treatment outcomes.

BACKGROUND: Survival rates for ovarian cancer remain poor, and monitoring and prediction of therapeutic response may benefit from additional markers. Ovarian cancers frequently overexpress Folate Receptor alpha (FRα) and the soluble receptor (sFRα) is measurable in blood. Here we investigated sFRα as a potential biomarker. METHODS: We evaluated sFRα longitudinally, before and during neo-adjuvant, adjuvant and palliative therapies, and tumour FRα expression status by immunohistrochemistry. The impact of free FRα on the efficacy of anti-FRα treatments was evaluated by an antibody-dependent cellular cytotoxicity assay. RESULTS: Membrane and/or cytoplasmic FRα staining were observed in 52.7% tumours from 316 ovarian cancer patients with diverse histotypes. Circulating sFRα levels were significantly higher in patients, compared to healthy volunteers, specifically in patients sampled prior to neoadjuvant and palliative treatments. sFRα was associated with FRα cell membrane expression in the tumour. sFRα levels decreased alongside concurrent tumour burden in patients receiving standard therapies. High concentrations of sFRα partly reduced anti-FRα antibody tumour cell killing, an effect overcome by increased antibody doses. CONCLUSIONS: sFRα may present a non-invasive marker for tumour FRα expression, with the potential for monitoring patient response to treatment. Larger, prospective studies should evaluate FRα for assessing disease burden and response to systemic treatments.

Generation and Characterization of Native and Sialic Acid-Deficient IgE.

Efficient characterization of IgE antibodies and their glycan structures is required for understanding their function in allergy and in the emerging AllergoOncology field for antibody immunotherapy. We report the generation, glyco-profiling and functional analysis of native and sialic acid-deficient glyco-engineered human IgE. The antibodies produced from human embryonic kidney cells were purified via a human IgE class-specific affinity matrix and structural integrity was confirmed by SDS-PAGE and size-exclusion chromatography (SEC). Purified IgEs specific for the tumor-associated antigens Chondroitin Sulfate Proteoglycan 4 (CSPG4-IgE) and Human Epidermal Growth Factor Receptor 2 (HER2-IgE) were devoid of by-products such as free light chains. Using neuraminidase-A, we generated sialic acid-deficient CSPG4-IgE as example glyco-engineered antibody. Comparative glycan analyses of native and glyco-engineered IgEs by Hydrophilic interaction liquid chromatography (HILIC)-high performance liquid chromatography (HPLC) indicated loss of sialic acid terminal residues and differential glycan profiles. Native and glyco-engineered CSPG4-IgEs recognized Fc receptors on the surface of human FcεRI-expressing rat basophilic leukemia RBL-SX38 cells, and of CD23/FcεRII-expressing human RPMI-8866 B-lymphocytes and bound to CSPG4-expressing A2058 human melanoma cells, confirming Fab-mediated recognition. When cross-linked on the cell surface, both IgEs triggered RBL-SX38 degranulation. We demonstrate efficient generation and functional competence of recombinant native and sialic acid-deficient IgEs.

Characterisation of a highly potent and near pan-neutralising anti-HIV monoclonal antibody expressed in tobacco plants.

BACKGROUND: HIV remains one of the most important health issues worldwide, with almost 40 million people living with HIV. Although patients develop antibodies against the virus, its high mutation rate allows evasion of immune responses. Some patients, however, produce antibodies that are able to bind to, and neutralise different strains of HIV. One such 'broadly neutralising' antibody is 'N6'. Identified in 2016, N6 can neutralise 98% of HIV-1 isolates with a median IC50 of 0.066 µg/mL. This neutralisation breadth makes N6 a very promising therapeutic candidate. RESULTS: N6 was expressed in a glycoengineered line of N. benthamiana plants (pN6) and compared to the mammalian cell-expressed equivalent (mN6). Expression at 49 mg/kg (fresh leaf tissue) was achieved in plants, although extraction and purification are more challenging than for most plant-expressed antibodies. N-glycoanalysis demonstrated the absence of xylosylation and a reduction in α(1,3)-fucosylation that are typically found in plant glycoproteins. The N6 light chain contains a potential N-glycosylation site, which was modified and displayed more α(1,3)-fucose than the heavy chain. The binding kinetics of pN6 and mN6, measured by surface plasmon resonance, were similar for HIV gp120. pN6 had a tenfold higher affinity for FcγRIIIa, which was reflected in an antibody-dependent cellular cytotoxicity assay, where pN6 induced a more potent response from effector cells than that of mN6. pN6 demonstrated the same potency and breadth of neutralisation as mN6, against a panel of HIV strains. CONCLUSIONS: The successful expression of N6 in tobacco supports the prospect of developing a low-cost, low-tech production platform for a monoclonal antibody cocktail to control HIV in low-to middle income countries.

Engineering the interactions between a plant-produced HIV antibody and human Fc receptors.

Plants can provide a cost-effective and scalable technology for production of therapeutic monoclonal antibodies, with the potential for precise engineering of glycosylation. Glycan structures in the antibody Fc region influence binding properties to Fc receptors, which opens opportunities for modulation of antibody effector functions. To test the impact of glycosylation in detail, on binding to human Fc receptors, different glycovariants of VRC01, a broadly neutralizing HIV monoclonal antibody, were generated in Nicotiana benthamiana and characterized. These include glycovariants lacking plant characteristic α1,3-fucose and ß1,2-xylose residues and glycans extended with terminal ß1,4-galactose. Surface plasmon resonance-based assays were established for kinetic/affinity evaluation of antibody-FcγR interactions, and revealed that antibodies with typical plant glycosylation have a limited capacity to engage FcγRI, FcγRIIa, FcγRIIb and FcγRIIIa; however, the binding characteristics can be restored and even improved with targeted glycoengineering. All plant-made glycovariants had a slightly reduced affinity to the neonatal Fc receptor (FcRn) compared with HEK cell-derived antibody. However, this was independent of plant glycosylation, but related to the oxidation status of two methionine residues in the Fc region. This points towards a need for process optimization to control oxidation levels and improve the quality of plant-produced antibodies.

Structure based classification for bile salt export pump (BSEP) inhibitors using comparative structural modeling of human BSEP.

The bile salt export pump (BSEP) actively transports conjugated monovalent bile acids from the hepatocytes into the bile. This facilitates the formation of micelles and promotes digestion and absorption of dietary fat. Inhibition of BSEP leads to decreased bile flow and accumulation of cytotoxic bile salts in the liver. A number of compounds have been identified to interact with BSEP, which results in drug-induced cholestasis or liver injury. Therefore, in silico approaches for flagging compounds as potential BSEP inhibitors would be of high value in the early stage of the drug discovery pipeline. Up to now, due to the lack of a high-resolution X-ray structure of BSEP, in silico based identification of BSEP inhibitors focused on ligand-based approaches. In this study, we provide a homology model for BSEP, developed using the corrected mouse P-glycoprotein structure (PDB ID: 4M1M). Subsequently, the model was used for docking-based classification of a set of 1212 compounds (405 BSEP inhibitors, 807 non-inhibitors). Using the scoring function ChemScore, a prediction accuracy of 81% on the training set and 73% on two external test sets could be obtained. In addition, the applicability domain of the models was assessed based on Euclidean distance. Further, analysis of the protein-ligand interaction fingerprints revealed certain functional group-amino acid residue interactions that could play a key role for ligand binding. Though ligand-based models, due to their high speed and accuracy, remain the method of choice for classification of BSEP inhibitors, structure-assisted docking models demonstrate reasonably good prediction accuracies while additionally providing information about putative protein-ligand interactions.

Expression and glycoengineering of functionally active heteromultimeric IgM in plants.

IgM antibodies are an important player of the human's innate defense mechanisms and increasingly have gained interest as therapeutics. Although the expression of IgM antibodies in mammalian cell culture is established, this approach remains costly and alternative methods have not been developed yet. Plants have a proven record for the production of therapeutically relevant recombinant proteins. However, whether they are able to express proteins like IgM antibodies, which range among the most complex human proteins, remains unknown so far. Here we report the in planta generation of the functionally active monoclonal antitumor IgM PAT-SM6 (SM6). SM6 efficiently accumulates in plant leaves and assembles correctly into heterooligomers (pentamers and hexamers). Detailed glycosylation analysis exhibited complex and oligomannosidic N-glycans in a site-specific manner on human-serum IgM and on plant- and human-cell-line-produced SM6. Moreover, extensive in planta glycoengineering allowed the generation of SM6 decorated with sialylated human-type oligosaccharides, comparable to plasma-derived IgM. A glycosylated model of pentameric IgM exhibits different accessibility of the glycosylation sites, explaining site-specific glycosylation. Biochemical and biophysical properties and importantly biological activities of plant-derived SM6 glycoforms are comparable to the human-cell-derived counterparts. The in planta generation of one of the most complex human proteins opens new pathways toward the production of difficult-to-express proteins for pharmaceutical applications. Moreover, the generation of IgMs with a controlled glycosylation pattern allows the study of the so far unknown contribution of sugar moieties to the function of IgMs.

Selectivity of cytosolic phospholipase A2 type IV toward arachidonyl phospholipids.

Cytosolic phospholipase A2 (cPLA2 ) is an interesting protein involved in inflammatory processes and various diseases. Its catalytic mechanism as well as its substrate specificity for arachidonyl phospholipids is not typical for other phospolipases. Furthermore, a lid structure, which ensures a hydrophilic surface of the protein without any substrate bound and the movement of this flexible loop to make the hydrophobic active site accessible, is of high interest. Therefore, the focus of this work was to determine the binding mode of cPLA2 with various substrates, such as arachidonic acid, a synthetic inhibitor, a saturated phospholipid, and most importantly an arachidonyl phospholipid. To understand the selectivity of the protein toward the arachidonyl phospholipid and the interaction in a protein-ligand complex, molecular dynamics simulations were performed using the GROMOS suite of simulation programs. The simulations provide insight into the protein and showed that selective binding of arachidonyl phospholipids is because of the shape of the sn-2 tail. The amino acids Asn555 and Ala578 are involved in the strongest interactions observed in the protein-ligand complexes.

Molecular dynamics simulations of the auxin-binding protein 1 in complex with indole-3-acetic acid and naphthalen-1-acetic acid.

Auxin-binding protein 1 (ABP1) is suggested to be an auxin receptor which plays an important role in several processes in green plants. Maize ABP1 was simulated with the natural auxin indole-3-acetic acid (IAA) and the synthetic analog naphthalen-1-acetic acid (NAA), to elucidate the role of the KDEL sequence and the helix at the C-terminus. The KDEL sequence weakens the intermolecular interactions between the monomers but stabilizes the C-terminal helix. Conformational changes at the C-terminus occur within the KDEL sequence and are influenced by the binding of the simulated ligands. This observation helps to explain experimental findings on ABP1 interactions with antibodies that are modulated by the presence of auxin, and supports the hypothesis that ABP1 acts as an auxin receptor. Stable hydrogen bonds between the monomers are formed between Glu40 and Glu62, Arg10 and Thr97, Lys39, and Glu62 in all simulations. The amino acids Ile22, Leu25, Trp44, Pro55, Ile130, and Phe149 are located in the binding pocket and are involved in hydrophobic interactions with the ring system of the ligand. Trp151 is stably involved in a face to end interaction with the ligand. The calculated free energy of binding using the linear interaction energy approach showed a higher binding affinity for NAA as compared to IAA. Our simulations confirm the asymmetric behavior of the two monomers, the stronger interaction of NAA than IAA and offers insight into the possible mechanism of ABP1 as an auxin receptor.

A systematic framework for molecular dynamics simulations of protein post-translational modifications.

By directly affecting structure, dynamics and interaction networks of their targets, post-translational modifications (PTMs) of proteins play a key role in different cellular processes ranging from enzymatic activation to regulation of signal transduction to cell-cycle control. Despite the great importance of understanding how PTMs affect proteins at the atomistic level, a systematic framework for treating post-translationally modified amino acids by molecular dynamics (MD) simulations, a premier high-resolution computational biology tool, has never been developed. Here, we report and validate force field parameters (GROMOS 45a3 and 54a7) required to run and analyze MD simulations of more than 250 different types of enzymatic and non-enzymatic PTMs. The newly developed GROMOS 54a7 parameters in particular exhibit near chemical accuracy in matching experimentally measured hydration free energies (RMSE=4.2 kJ/mol over the validation set). Using this tool, we quantitatively show that the majority of PTMs greatly alter the hydrophobicity and other physico-chemical properties of target amino acids, with the extent of change in many cases being comparable to the complete range spanned by native amino acids.

Calculation of substrate binding affinities for a bacterial GH78 rhamnosidase through molecular dynamics simulations.

Ram2 from Pediococcus acidilactici is a rhamnosidase from the glycoside hydrolase family 78. It shows remarkable selectivity for rutinose rather than para-nitrophenyl-alpha-l-rhamnopyranoside (p-NPR). Molecular dynamics simulations were performed using a homology model of this enzyme, in complex with both substrates. Free energy calculations lead to predicted binding affinities of -34.4 and -30.6 kJ mol-1 respectively, agreeing well with an experimentally estimated relative free energy of 5.4 kJ mol-1. Further, the most relevant binding poses could be determined. While p-NPR preferably orients its rhamnose moiety toward the active site, rutinose interacts most strongly with its glucose moiety. A detailed hydrogen bond analysis confirms previously implicated residues in the active site (Asp217, Asp222, Trp226, Asp229 and Glu488) and quantifies the importance of individual residues for the binding. The most important amino acids are Asp229 and Phe339 which are involved in many interactions during the simulations. While Phe339 was observed in more simulations, Asp229 was involved in more persistent interactions (forming an average of at least 2 hydrogen bonds during the simulation). These analyses directly suggest mutations that could be used in a further experimental characterization of the enzyme. This study shows once more the strength of computer simulations to rationalize and guide experiments at an atomic level.

Ligand- and Structure-based Approaches for Transmembrane Transporter Modeling.

The study of transporter proteins is key to understanding the mechanism behind multi-drug resistance and drug-drug interactions causing severe side effects. While ATP-binding transporters are well-studied, solute carriers illustrate an understudied family with a high number of orphan proteins. To study these transporters, in silico methods can be used to shed light on the basic molecular machinery by studying protein-ligand interactions. Nowadays, computational methods are an integral part of the drug discovery and development process. In this short review, computational approaches, such as machine learning, are discussed, which try to tackle interactions between transport proteins and certain compounds to locate target proteins. Furthermore, a few cases of selected members of the ATP binding transporter and solute carrier family are covered, which are of high interest in clinical drug interaction studies, especially for regulatory agencies. The strengths and limitations of ligand-based and structure-based methods are discussed to highlight their applicability for different studies. Furthermore, the combination of multiple approaches can improve the information obtained to find crucial amino acids that explain important interactions of protein-ligand complexes in more detail. This allows the design of drug candidates with increased activity towards a target protein, which further helps to support future synthetic efforts.

Privacy-preserving techniques for decentralized and secure machine learning in drug discovery.

Data availability, data security, and privacy concerns often hamper optimal performance efficiency of machine learning (ML) techniques. Therefore, novel techniques for the utilization of private/sensitive data in the field of drug discovery have been proposed for ML model-building tasks. Some examples of the different techniques are secure multiparty computation, distributed deep learning, homomorphic encryption, blockchain-based peer-to-peer networking, differential privacy, and federated learning, as well as combinations of such techniques. In this paper, we present an overview of these techniques for decentralized ML to illustrate its benefits and drawbacks in the field of drug discovery.

Improving the efficacy of plant-made anti-HIV monoclonal antibodies for clinical use.

Introduction: Broadly neutralising antibodies are promising candidates for preventing and treating Human Immunodeficiency Virus/Acquired Immunodeficiency Syndrome (HIV/AIDS), as an alternative to or in combination with antiretroviral therapy (ART). These mAbs bind to sites on the virus essential for virus attachment and entry, thereby inhibiting entry into the host cell. However, the cost and availability of monoclonal antibodies, especially combinations of antibodies, hampers implementation of anti-HIV bNAb therapies in low- to middle- income countries (LMICs) where HIV-1 prevalence is highest. Methods: We have produced three HIV broadly neutralizing antibodies (bNAbs), 10-1074, VRC01 and 3BNC117 in the Nicotiana benthamiana transient expression system. The impact of specific modifications to enhance potency and efficacy were assessed. To prolong half-life and increase bioavailability, a M252Y/S254T/T256E (YTE) or M428L/N434S (LS) mutation was introduced. To increase antibody dependent cellular cytotoxicity (ADCC), we expressed an afucosylated version of each antibody using a glycoengineered plant line. Results: The majority of bNAbs and their variants could be expressed at yields of up to 47 mg/kg. Neither the expression system nor the modifications impacted the neutralization potential of the bNAbs. Afucosylated bNAbs exhibit enhanced ability to bind to FcγRIIIa and trigger ADCC, regardless of the presence of Fc amino acid mutations. Lastly, we demonstrated that Fc-modified variants expressed in plants show enhanced binding to FcRn, which results in a favourable in vivo pharmacokinetic profile compared to their unmodified counterparts. Conclusion: Tobacco plants are suitable expression hosts for anti-HIV bNAbs with increased efficacy and an improved pharmacokinetic profile.

Anti-cancer pro-inflammatory effects of an IgE antibody targeting the melanoma-associated antigen chondroitin sulfate proteoglycan 4.

Outcomes for half of patients with melanoma remain poor despite standard-of-care checkpoint inhibitor therapies. The prevalence of the melanoma-associated antigen chondroitin sulfate proteoglycan 4 (CSPG4) expression is ~70%, therefore effective immunotherapies directed at CSPG4 could benefit many patients. Since IgE exerts potent immune-activating functions in tissues, we engineer a monoclonal IgE antibody with human constant domains recognizing CSPG4 to target melanoma. CSPG4 IgE binds to human melanomas including metastases, mediates tumoricidal antibody-dependent cellular cytotoxicity and stimulates human IgE Fc-receptor-expressing monocytes towards pro-inflammatory phenotypes. IgE demonstrates anti-tumor activity in human melanoma xenograft models engrafted with human effector cells and is associated with enhanced macrophage infiltration, enriched monocyte and macrophage gene signatures and pro-inflammatory signaling pathways in the tumor microenvironment. IgE prolongs the survival of patient-derived xenograft-bearing mice reconstituted with autologous immune cells. No ex vivo activation of basophils in patient blood is measured in the presence of CSPG4 IgE. Our findings support a promising IgE-based immunotherapy for melanoma.

Using Jupyter Notebooks for re-training machine learning models.

Machine learning (ML) models require an extensive, user-driven selection of molecular descriptors in order to learn from chemical structures to predict actives and inactives with a high reliability. In addition, privacy concerns often restrict the access to sufficient data, leading to models with a narrow chemical space. Therefore, we propose a framework of re-trainable models that can be transferred from one local instance to another, and further allow a less extensive descriptor selection. The models are shared via a Jupyter Notebook, allowing the evaluation and implementation of a broader chemical space by keeping most of the tunable parameters pre-defined. This enables the models to be updated in a decentralized, facile, and fast manner. Herein, the method was evaluated with six transporter datasets (BCRP, BSEP, OATP1B1, OATP1B3, MRP3, P-gp), which revealed the general applicability of this approach.

Engineering the N-glycosylation pathway of Nicotiana tabacum for molecular pharming using CRISPR/Cas9.

Molecular pharming in plants offers exciting possibilities to address global access to modern biologics. However, differences in the N-glycosylation pathway including the presence of ß(1,2)-xylose and core α(1,3)-fucose can affect activity, potency and immunogenicity of plant-derived proteins. Successful glycoengineering approaches toward human-like structures with no changes in plant phenotype, growth, or recombinant protein expression levels have been reported for Arabidopsis thaliana and Nicotiana benthamiana. Such engineering of N-glycosylation would also be desirable for Nicotiana tabacum, which remains the crop of choice for recombinant protein pharmaceuticals required at massive scale and for manufacturing technology transfer to less developed countries. Here, we generated N. tabacum cv. SR-1 ß(1,2)-xylosyltransferase (XylT) and α(1,3)-fucosyltransferase (FucT) knockout lines using CRISPR/Cas9 multiplex genome editing, targeting three conserved regions of the four FucT and two XylT genes. These two enzymes are responsible for generating non-human N-glycan structures. We confirmed full functional knockout of transformants by immunoblotting of total soluble protein by antibodies recognizing ß(1,2)-xylose and core α(1,3)-fucose, mass spectrometry analysis of recombinantly produced VRC01, a broadly neutralizing anti-HIV-1 hIgG1 antibody, and Sanger sequencing of targeted regions of the putative transformants. These data represent an important step toward establishing Nicotiana tabacum as a biologics platform for Global Health.

Clinical and Translational Significance of Basophils in Patients with Cancer.

Despite comprising a very small proportion of circulating blood leukocytes, basophils are potent immune effector cells. The high-affinity receptor for IgE (FcɛRI) is expressed on the basophil cell surface and powerful inflammatory mediators such as histamine, granzyme B, and cytokines are stored in dense cytoplasmic granules, ready to be secreted in response to a range of immune stimuli. Basophils play key roles in eliciting potent effector functions in allergic diseases and type 1 hypersensitivity. Beyond allergies, basophils can be recruited to tissues in chronic and autoimmune inflammation, and in response to parasitic, bacterial, and viral infections. While their activation states and functions can be influenced by Th2-biased inflammatory signals, which are also known features of several tumor types, basophils have received little attention in cancer. Here, we discuss the presence and functional significance of basophils in the circulation of cancer patients and in the tumor microenvironment (TME). Interrogating publicly available datasets, we conduct gene expression analyses to explore basophil signatures and associations with clinical outcomes in several cancers. Furthermore, we assess how basophils can be harnessed to predict hypersensitivity to cancer treatments and to monitor the desensitization of patients to oncology drugs, using assays such as the basophil activation test (BAT).

The hepatocyte export carrier inhibition assay improves the separation of hepatotoxic from non-hepatotoxic compounds.

An in vitro/in silico method that determines the risk of human drug induced liver injury in relation to oral doses and blood concentrations of drugs was recently introduced. This method utilizes information on the maximal blood concentration (Cmax) for a specific dose of a test compound, which can be estimated using physiologically-based pharmacokinetic modelling, and a cytotoxicity test in cultured human hepatocytes. In the present study, we analyzed if the addition of an assay that measures the inhibition of bile acid export carriers, like BSEP and/or MRP2, to the existing method improves the differentiation of hepatotoxic and non-hepatotoxic compounds. Therefore, an export assay for 5-chloromethylfluorescein diacetate (CMFDA) was established. We tested 36 compounds in a concentration-dependent manner for which the risk of hepatotoxicity for specific oral doses and the capacity to inhibit hepatocyte export carriers are known. Compared to the CTB cytotoxicity test, substantially lower EC10 values were obtained using the CMFDA assay for several known BSEP and/or MRP2 inhibitors. To quantify if the addition of the CMFDA assay to our test system improves the overall separation of hepatotoxic from non-hepatotoxic compounds, the toxicity separation index (TSI) was calculated. We obtained a better TSI using the lower alert concentration from either the CMFDA or the CTB test (TSI: 0.886) compared to considering the CTB test alone (TSI: 0.775). In conclusion, the data show that integration of the CMFDA assay with an in vitro test battery improves the differentiation of hepatotoxic and non-hepatotoxic compounds in a set of compounds that includes bile acid export carrier inhibitors.