Pomiferin targets SERCA, mTOR, and P-gp to induce autophagic cell death in apoptosis-resistant cancer cells, and reverses the MDR phenotype in cisplatin-resistant tumors in vivo.

Drug resistance in cancer has been classified as innate resistance or acquired resistance, which were characterized by apoptotic defects and ABC transporters overexpression respectively. Therefore, to preclude or reverse these resistance mechanisms could be a promising strategy to improve chemotherapeutic outcomes. In this study, a natural product from Osage Orange, pomiferin, was identified as a novel autophagy activator that circumvents innate resistance by triggering autophagic cell death via SERCA inhibition and activation of the CaMKKß-AMPK-mTOR signaling cascade. In addition, pomiferin also directly inhibited the P-gp (MDR1/ABCB1) efflux and reversed acquired resistance by potentiating the accumulation and efficacy of the chemotherapeutic agent, cisplatin. In vivo study demonstrated that pomiferin triggered calcium-mediated tumor suppression and exhibited an anti-metastatic effect in the LLC-1 lung cancer-bearing mouse model. Moreover, as an adjuvant, pomiferin potentiated the anti-tumor effect of the chemotherapeutic agent, cisplatin, in RM-1 drug-resistant prostate cancer-bearing mouse model by specially attenuating ABCB1-mediated drug efflux, but not ABCC5, thereby promoting the accumulation of cisplatin in tumors. Collectively, pomiferin may serve as a novel effective agent for circumventing drug resistance in clinical applications.

In Silico and In Vitro Identification of P-Glycoprotein Inhibitors from a Library of 375 Phytochemicals.

Cancer therapy with clinically established anticancer drugs is frequently hampered by the development of drug resistance of tumors and severe side effects in normal organs and tissues. The demand for powerful, but less toxic, drugs is high. Phytochemicals represent an important reservoir for drug development and frequently exert less toxicity than synthetic drugs. Bioinformatics can accelerate and simplify the highly complex, time-consuming, and expensive drug development process. Here, we analyzed 375 phytochemicals using virtual screenings, molecular docking, and in silico toxicity predictions. Based on these in silico studies, six candidate compounds were further investigated in vitro. Resazurin assays were performed to determine the growth-inhibitory effects towards wild-type CCRF-CEM leukemia cells and their multidrug-resistant, P-glycoprotein (P-gp)-overexpressing subline, CEM/ADR5000. Flow cytometry was used to measure the potential to measure P-gp-mediated doxorubicin transport. Bidwillon A, neobavaisoflavone, coptisine, and z-guggulsterone all showed growth-inhibitory effects and moderate P-gp inhibition, whereas miltirone and chamazulene strongly inhibited tumor cell growth and strongly increased intracellular doxorubicin uptake. Bidwillon A and miltirone were selected for molecular docking to wildtype and mutated P-gp forms in closed and open conformations. The P-gp homology models harbored clinically relevant mutations, i.e., six single missense mutations (F336Y, A718C, Q725A, F728A, M949C, Y953C), three double mutations (Y310A-F728A; F343C-V982C; Y953A-F978A), or one quadruple mutation (Y307C-F728A-Y953A-F978A). The mutants did not show major differences in binding energies compared to wildtypes. Closed P-gp forms generally showed higher binding affinities than open ones. Closed conformations might stabilize the binding, thereby leading to higher binding affinities, while open conformations may favor the release of compounds into the extracellular space. In conclusion, this study described the capability of selected phytochemicals to overcome multidrug resistance.

Kinome-Wide Profiling Identifies Human WNK3 as a Target of Cajanin Stilbene Acid from Cajanus cajan (L.) Millsp.

Pigeon Pea (Cajanus cajan (L.) Millsp.) is a common food crop used in many parts of the world for nutritional purposes. One of its chemical constituents is cajanin stilbene acid (CSA), which exerts anticancer activity in vitro and in vivo. In an effort to identify molecular targets of CSA, we performed a kinome-wide approach based on the measurement of the enzymatic activities of 252 human kinases. The serine-threonine kinase WNK3 (also known as protein kinase lysine-deficient 3) was identified as the most promising target of CSA with the strongest enzymatic activity inhibition in vitro and the highest binding affinity in molecular docking in silico. The lowest binding affinity and the predicted binding constant pKi of CSA (-9.65 kcal/mol and 0.084 µM) were comparable or even better than those of the known WNK3 inhibitor PP-121 (-9.42 kcal/mol and 0.123 µM). The statistically significant association between WNK3 mRNA expression and cellular responsiveness to several clinically established anticancer drugs in a panel of 60 tumor cell lines and the prognostic value of WNK3 mRNA expression in sarcoma biopsies for the survival time of 230 patients can be taken as clues that CSA-based inhibition of WNK3 may improve treatment outcomes of cancer patients and that CSA may serve as a valuable supplement to the currently used combination therapy protocols in oncology.

In Silico and In Vitro Screening of 50 Curcumin Compounds as EGFR and NF-κB Inhibitors.

The improvement of cancer chemotherapy remains a major challenge, and thus new drugs are urgently required to develop new treatment regimes. Curcumin, a polyphenolic antioxidant derived from the rhizome of turmeric (Curcuma longa L.), has undergone extensive preclinical investigations and, thereby, displayed remarkable efficacy in vitro and in vivo against cancer and other disorders. However, pharmacological limitations of curcumin stimulated the synthesis of numerous novel curcumin analogs, which need to be evaluated for their therapeutic potential. In the present study, we calculated the binding affinities of 50 curcumin derivatives to known cancer-related target proteins of curcumin, i.e., epidermal growth factor receptor (EGFR) and nuclear factor κB (NF-κB) by using a molecular docking approach. The binding energies for EGFR were in a range of −12.12 (±0.21) to −7.34 (±0.07) kcal/mol and those for NF-κB ranged from −12.97 (±0.47) to −6.24 (±0.06) kcal/mol, indicating similar binding affinities of the curcumin compounds for both target proteins. The predicted receptor-ligand binding constants for EGFR and curcumin derivatives were in a range of 0.00013 (±0.00006) to 3.45 (±0.10) µM and for NF-κB in a range of 0.0004 (±0.0003) to 10.05 (±4.03) µM, indicating that the receptor-ligand binding was more stable for EGFR than for NF-κB. Twenty out of 50 curcumin compounds showed binding energies to NF-κB smaller than −10 kcal/mol, while curcumin as a lead compound revealed free binding energies of >−10 kcal/mol. Comparable data were obtained for EGFR: 15 out of 50 curcumin compounds were bound to EGFR with free binding energies of <−10 kcal/mol, while the binding affinity of curcumin itself was >−10 kcal/mol. This indicates that the derivatization of curcumin may indeed be a promising strategy to improve targe specificity and to obtain more effective anticancer drug candidates. The in silico results have been exemplarily validated using microscale thermophoresis. The bioactivity has been further investigated by using resazurin cell viability assay, lactate dehydrogenase assay, flow cytometric measurement of reactive oxygen species, and annexin V/propidium iodide assay. In conclusion, molecular docking represents a valuable approach to facilitate and speed up the identification of novel targeted curcumin-based drugs to treat cancer.

Drug repurposing using transcriptome sequencing and virtual drug screening in a patient with glioblastoma.

Background Precision medicine and drug repurposing are attractive strategies, especially for tumors with worse prognosis. Glioblastoma is a highly malignant brain tumor with limited treatment options and short survival times. We identified novel BRAF (47-438del) and PIK3R1 (G376R) mutations in a glioblastoma patient by RNA-sequencing. Methods The protein expression of BRAF and PIK3R1 as well as the lack of EGFR expression as analyzed by immunohistochemistry corroborated RNA-sequencing data. The expression of additional markers (AKT, SRC, mTOR, NF-κB, Ki-67) emphasized the aggressiveness of the tumor. Then, we screened a chemical library of > 1500 FDA-approved drugs and > 25,000 novel compounds in the ZINC database to find established drugs targeting BRAF47-438del and PIK3R1-G376R mutated proteins. Results Several compounds (including anthracyclines) bound with higher affinities than the control drugs (sorafenib and vemurafenib for BRAF and PI-103 and LY-294,002 for PIK3R1). Subsequent cytotoxicity analyses showed that anthracyclines might be suitable drug candidates. Aclarubicin revealed higher cytotoxicity than both sorafenib and vemurafenib, whereas idarubicin and daunorubicin revealed higher cytotoxicity than LY-294,002. Liposomal formulations of anthracyclines may be suitable to cross the blood brain barrier. Conclusions In conclusion, we identified novel small molecules via a drug repurposing approach that could be effectively used for personalized glioblastoma therapy especially for patients carrying BRAF47-438del and PIK3R1-G376R mutations.

Selection of safe artemisinin derivatives using a machine learning-based cardiotoxicity platform and in vitro and in vivo validation.

The majority of drug candidates fails the approval phase due to unwanted toxicities and side effects. Establishment of an effective toxicity prediction platform is of utmost importance, to increase the efficiency of the drug discovery process. For this purpose, we developed a toxicity prediction platform with machine-learning strategies. Cardiotoxicity prediction was performed by establishing a model with five parameters (arrhythmia, cardiac failure, heart block, hypertension, myocardial infarction) and additional toxicity predictions such as hepatotoxicity, reproductive toxicity, mutagenicity, and tumorigenicity are performed by using Data Warrior and Pro-Tox-II software. As a case study, we selected artemisinin derivatives to evaluate the platform and to provide a list of safe artemisinin derivatives. Artemisinin from Artemisia annua was described first as an anti-malarial compound and later its anticancer properties were discovered. Here, random forest feature selection algorithm was used for the establishment of cardiotoxicity models. High AUC scores above 0.830 were achieved for all five cardiotoxicity indications. Using a chemical library of 374 artemisinin derivatives as a case study, 7 compounds (deoxydihydro-artemisinin, 3-hydroxy-deoxy-dihydroartemisinin, 3-desoxy-dihydroartemisinin, dihydroartemisinin-furano acetate-d3, deoxyartemisinin, artemisinin G, artemisinin B) passed the toxicity filtering process for hepatotoxicity, mutagenicity, tumorigenicity, and reproductive toxicity in addition to cardiotoxicity. Experimental validation with the cardiomyocyte cell line AC16 supported the findings from the in silico cardiotoxicity model predictions. Transcriptomic profiling of AC16 cells upon artemisinin B treatment revealed a similar gene expression profile as that of the control compound, dexrazoxane. In vivo experiments with a Zebrafish model further substantiated the in silico and in vitro data, as only slight cardiotoxicity in picomolar range was observed. In conclusion, our machine-learning approach combined with in vitro and in vivo experimentation represents a suitable method to predict cardiotoxicity of drug candidates.

Identification of potential novel drug resistance mechanisms by genomic and transcriptomic profiling of colon cancer cells with p53 deletion.

TP53 (p53) is a pivotal player in tumor suppression with fifty percent of all invasive tumors displaying mutations in the TP53 gene. In the present study, we characterized colon cancer cells (HCT116 p53 -/-) with TP53 deletion, a sub-line derived from HCT116-p53 +/+ cells. RNA sequencing and network analyses were performed to identify novel drug resistance mechanisms. Chromosomal aberrations were identified by multicolor fluorescence in situ hybridization (mFISH) and array comparative genomic hybridization (aCGH). Numerous genes were overexpressed in HCT116 p53 -/- cells: RND3/RhoE (235.6-fold up-regulated), DCLK1 (60.2-fold up-regulated), LBH (31.9-fold up-regulated), MYB (28.9-fold up-regulated), TACSTD2 (110.1-fold down-regulated), NRIP1 (81.5-fold down-regulated) and HLA-DMB (69.7-fold down-regulated) are among the identified genes with potential influence on multidrug resistance (MDR) and they are associated with cancer progression and tumorigenesis, according to previously published studies. Probably due to TP53 deletion, disturbances in DNA repair and apoptosis are leading to aberrancies in cellular and organismal organization, ultimately increasing tumorigenesis and cancer progression potential. With NFκB, PI3K and HSP70, being at the center of merged protein network, and TH1-2 pathways, being among the influenced pathways, it can be speculated that the inflammatory pathway contributes to a resistance phenotype together with cell cycle regulation and heat-shock response. HCT116-p53 -/- cells have more chromosomal aberrations, gains and losses in copy numbers than HCT116-p53 +/+ cells. In conclusion, numerous genomic aberrations, which might be associated with yet unknown drug resistance mechanisms, were identified. This may have important implications for future treatment strategies.

Synthesis and biological evaluation of a D-ring-contracted analogue of lamellarin D.

A D-ring contracted analogue of the strongly cytotoxic marine pyrrole alkaloid lamellarin D was synthesized and investigated for its antiproliferative action towards a wild type and a multidrug resistant (MDR) cancer cell line. The compound was found to inhibit tumor cell growth at submicromolar concentrations and showed a lower relative resistance in the MDR cell line than the antitumor drug camptothecin to which lamellarin D shows cross resistance and with which lamellarin D shares the same binding site.

Peptide aptamer identified by molecular docking targeting translationally controlled tumor protein in leukemia cells.

Bioinformatics screening and molecular docking analyses were utilized to select high affinity peptides targeting translationally controlled tumor protein (TCTP). Selected peptide aptamers were tested towards cancer cell lines with different levels of TCTP expression. One peptide (WGQWPYHC) revealed specific cytotoxicity according to the TCTP expression in tumor cells without affecting normal cells. Western blot analysis showed peptide-induced down-regulation of TCTP as primary target as well as of cell-cycle related downstream proteins (CDK2, CDK6, Cyclin D3) in MOLT-4 leukemia cells. "WGQWPYHC" deserves further analysis for targeted therapy of TCTP-expressing tumor cells. Graphical abstract Molecular docking on TCTP, cytotoxicity toward MOLT-4 leukemia cell line and downregulation of CDK2, CDK6, CyclinD3 and TCTP proteins.

Modulation of P-glycoprotein activity by novel synthetic curcumin derivatives in sensitive and multidrug-resistant T-cell acute lymphoblastic leukemia cell lines.

BACKGROUND: Multidrug resistance (MDR) and drug transporter P-glycoprotein (P-gp) represent major obstacles in cancer chemotherapy. We investigated 19 synthetic curcumin derivatives in drug-sensitive acute lymphoblastic CCRF-CEM leukemia cells and their multidrug-resistant P-gp-overexpressing subline, CEM/ADR5000. MATERIAL AND METHODS: Cytotoxicity was tested by resazurin assays. Doxorubicin uptake was assessed by flow cytometry. Binding modes of compounds to P-gp were analyzed by molecular docking. Chemical features responsible for bioactivity were studied by quantitative structure activity relationship (QSAR) analyses. A 7-descriptor QSAR model was correlated with doxorubicin uptake values, IC50 values and binding energies. RESULTS: The compounds displayed IC50 values between 0.7±0.03 and 20.2±0.25µM. CEM/ADR5000 cells exhibited cross-resistance to 10 compounds, collateral sensitivity to three compounds and regular sensitivity to the remaining six curcumins. Molecular docking studies at the intra-channel transmembrane domain of human P-gp resulted in lowest binding energies ranging from -9.00±0.10 to -6.20±0.02kcal/mol and pKi values from 0.24±0.04 to 29.17±0.88µM. At the ATP-binding site of P-gp, lowest binding energies ranged from -9.78±0.17 to -6.79±0.01kcal/mol and pKi values from 0.07±0.02 to 0.03±0.03µM. CEM/ADR5000 cells accumulated approximately 4-fold less doxorubicin than CCRF-CEM cells. The control P-gp inhibitor, verapamil, partially increased doxorubicin uptake in CEM/ADR5000 cells. Six curcumins increased doxorubicin uptake in resistant cells or even exceeded uptake levels compared to sensitive one. QSAR yielded good activity prediction (R=0.797 and R=0.794 for training and test sets). CONCLUSION: Selected derivatives may serve to guide future design of novel P-gp inhibitors and collateral sensitive drugs to combat MDR.

Synthetic cajanin stilbene acid derivatives inhibit c-MYC in breast cancer cells.

In the present study, we investigated the activity and modes of action of cajanin stilbene acid (CSA) and its derivatives in terms of cytotoxicity, gene expression profile, and transcription factor activity. XTT assays on MCF7 cells were performed upon treatment with CSA or derivatives. After the determination of IC50 values, gene expression profiling was performed with Agilent microarray experiments. Deregulated genes were determined with Chipster software, pathway and functional analyses were performed with Ingenuity pathway software. In order to identify the potential upstream regulators, MatInspector software was used to perform transcription factor binding motif search in the promoter regions of the deregulated genes. Molecular docking on MYC/MAX complex and reporter cell line experiments were performed to validate the MYC inhibitory activity of CSA and its derivatives. Two known MYC inhibitors: 10058-F4 and 10074-G5 were used as positive control. All compounds showed cytotoxicities in the micromolar range. Microarray analyses pointed to cell cycle, DNA damage, and DNA repair as mainly affected cellular functions. Promoter motif analysis of the deregulated genes further supported the microarray gene expression analysis results emphasizing the relevance of transcription factors regulating cell cycle and proliferation, with MYC as being the most pronounced one. Luciferase-based reporter cell line experiments and molecular docking studies yielded supportive results emphasizing the inhibitory activity of CSA and its derivatives on MYC. CSA and its derivatives are shown to be promising anticancer compounds with low toxicity. They inhibit MYC activity comparable to 10058-F4 and 10074-G5. Further studies are warranted to analyze the therapeutic applicability of these compounds in more detail.

Pharmacogenomics of Scopoletin in Tumor Cells.

Drug resistance and the severe side effects of chemotherapy necessitate the development of novel anticancer drugs. Natural products are a valuable source for drug development. Scopoletin is a coumarin compound, which can be found in several Artemisia species and other plant genera. Microarray-based RNA expression profiling of the NCI cell line panel showed that cellular response of scopoletin did not correlate to the expression of ATP-binding cassette (ABC) transporters as classical drug resistance mechanisms (ABCB1, ABCB5, ABCC1, ABCG2). This was also true for the expression of the oncogene EGFR and the mutational status of the tumor suppressor gene, TP53. However, mutations in the RAS oncogenes and the slow proliferative activity in terms of cell doubling times significantly correlated with scopoletin resistance. COMPARE and hierarchical cluster analyses of transcriptome-wide mRNA expression resulted in a set of 40 genes, which all harbored binding motifs in their promoter sequences for the transcription factor, NF-κB, which is known to be associated with drug resistance. RAS mutations, slow proliferative activity, and NF-κB may hamper its effectiveness. By in silico molecular docking studies, we found that scopoletin bound to NF-κB and its regulator IκB. Scopoletin activated NF-κB in a SEAP-driven NF-κB reporter cell line, indicating that NF-κB might be a resistance factor for scopoletin. In conclusion, scopoletin might serve as lead compound for drug development because of its favorable activity against tumor cells with ABC-transporter expression, although NF-κB activation may be considered as resistance factor for this compound. Further investigations are warranted to explore the full therapeutic potential of this natural product.

Aptamers as a novel tool for diagnostics and therapy.

Aptamers are short single-stranded DNA or RNA oligonucleotides that are capable of binding small molecules, proteins, or nucleotides with high specificity. They show a stable conformation and high binding affinity for their target molecules. There are numerous applications for aptamers in biotechnology, molecular diagnostics and targeted therapy of diseases. Their production is cheap, and they generally display lower immunogenicity than monoclonal antibodies. In the present review, we give an introduction to the preparation of aptamers and provide examples for their use in biotechnology, diagnostics and therapy of diseases.

Pharmacogenomic Characterization of Cytotoxic Compounds from Salvia officinalis in Cancer Cells.

Salvia officinalis is used as a dietary supplement with diverse medicinal activity (e.g. antidiabetic and antiatherosclerotic effects). The plant also exerts profound cytotoxicity toward cancer cells. Here, we investigated possible modes of action to explain its activity toward drug-resistant tumor cells. Log10IC50 values of two constituents of S. officinalis (ursolic acid, pomolic acid) were correlated to the expression of ATP-binding cassette (ABC) transporters (P-glycoprotein/ABCB1/MDR1, MRP1/ABCC1, BCRP/ABCG2) and epidermal growth factor receptor (EGFR) or mutations in RAS oncogenes and the tumor suppressor gene TP53 of the NCI panel of cell lines. Gene expression profiles predicting sensitivity and resistance of tumor cells to these compounds were determined by microarray-based mRNA expressions, COMPARE, and hierarchical cluster analyses. Furthermore, the binding of both plant acids to key molecules of the NF-κB pathway (NF-κB, I-κB, NEMO) was analyzed by molecular docking. Neither expression nor mutation of ABC transporters, oncogenes, or tumor suppressor genes correlated with log10IC50 values for ursolic acid or pomolic acid. In microarray analyses, many genes involved in signal transduction processes correlated with cellular responsiveness to these compounds. Molecular docking indicated that the two plant acids strongly bound to target proteins of the NF-κB pathway with even lower free binding energies than the known NF-κB inhibitor MG-132. They interacted more strongly with DNA-bound NF-κB than free NF-κB, pointing to inhibition of DNA binding by these compounds. In conclusion, the lack of cross-resistance to classical drug resistance mechanisms (ABC-transporters, oncogenes, tumor suppressors) may indicate a promising role of the both plant acids for cancer chemotherapy. Genes involved in signal transduction may contribute to the sensitivity or resistance of tumor cells to ursolic and pomolic acids. Ursolic and pomolic acid may target different steps of the NF-κB pathway to inhibit NF-κB-mediated functions.

Contributions from emerging transcriptomics technologies and computational strategies for drug discovery.

Drug discovery involves various steps and is a long process being even more demanding for complex diseases such as cancer. Tumors are ensembles of subpopulations with different mutations, require very specific and effective strategies. Conventional drug screening technologies may not be adequate and efficient anymore. Drug repositioning is a useful strategy to identify new uses for previously failed drugs. High throughput and deep sequencing technologies provide valuable support by yielding enormous amounts of "-omics" data and contribute to understanding the molecular mechanisms responsible for drug action. Computational methods coupled with systems biology represent a promising step to interpret pharmacogenomic data and establish strong connections with drug discovery. Genomic variations have been found to be linked with differential drug response among individuals. Large genome wide association studies are necessary to identify reliable connections between genomic variations and drug response since personalized medicine has been accepted as an important phenomenon in the drug discovery and development process post approval.

The ability of molecular docking to unravel the controversy and challenges related to P-glycoprotein--a well-known, yet poorly understood drug transporter.

P-glycoprotein is the most crucial membrane transporter implicated in tumor resistance. Intensive efforts were paid to elucidate the complex mechanism of transport and to identify modulators of this transporter. However, the borderline between substrates and modulators is very thin and identification of the binding sites within P-glycoprotein is complex. Herein, we provide an intensive review of those issues and use molecular docking to assess its ability: first, to differentiate between three groups (substrates, modulators and non-substrates) and second to identify the binding sites. After thorough statistical analysis, we conclude despite the various challenges that molecular docking should not be underestimated as differences between the distinct groups were significant. However, when it comes to defining the binding site, care must be taken, since consensus throughout literature could not be reached.

A drug repurposing approach for individualized cancer therapy based on transcriptome sequencing and virtual drug screening.

RNA-sequencing has been proposed as a valuable technique to develop individualized therapy concepts for cancer patients based on their tumor-specific mutational profiles. Here, we aimed to identify drugs and inhibitors in an individualized therapy-based drug repurposing approach focusing on missense mutations for 35 biopsies of cancer patients. The missense mutations belonged to 9 categories (ABC transporter, apoptosis, angiogenesis, cell cycle, DNA damage, kinase, protease, transcription factor, tumor suppressor). The highest percentages of missense mutations were observed in transcription factor genes. The mutational profiles of all 35 tumors were subjected to hierarchical heatmap clustering. All 7 leukemia biopsies clustered together and were separated from solid tumors. Based on these individual mutation profiles, two strategies for the identification of possible drug candidates were applied: Firstly, virtual screening of FDA-approved drugs based on the protein structures carrying particular missense mutations. Secondly, we mined the Drug Gene Interaction (DGI) database (https://www.dgidb.org/) to identify approved or experimental inhibitors for missense mutated proteins in our dataset of 35 tumors. In conclusion, our approach based on virtual drug screening of FDA-approved drugs and DGI-based inhibitor selection may provide new, individual treatment options for patients with otherwise refractory tumors that do not respond anymore to standard chemotherapy.

Identification of Novel Anthracycline Resistance Genes and Their Inhibitors.

Differentially expressed genes have been previously identified by us in multidrug-resistant tumor cells mainly resistant to doxorubicin. In the present study, we exemplarily focused on some of these genes to investigate their causative relationship with drug resistance. HMOX1, NEIL2, and PRKCA were overexpressed by lentiviral-plasmid-based transfection of HEK293 cells. An in silico drug repurposing approach was applied using virtual screening and molecular docking of FDA-approved drugs to identify inhibitors of these new drug-resistant genes. Overexpression of the selected genes conferred resistance to doxorubicin and daunorubicin but not to vincristine, docetaxel, and cisplatin, indicating the involvement of these genes in resistance to anthracyclines but not to a broader MDR phenotype. Using virtual drug screening and molecular docking analyses, we identified FDA-approved compounds (conivaptan, bexarotene, and desloratadine) that were interacting with HMOX1 and PRKCA at even stronger binding affinities than 1-(adamantan-1-yl)-2-(1H-imidazol-1-yl)ethenone and ellagic acid as known inhibitors of HMOX1 and PRKCA, respectively. Conivaptan treatment increased doxorubicin sensitivity of both HMOX1- and PRKCA-transfected cell lines. Bexarotene treatment had a comparable doxorubicin-sensitizing effect in HMOX1-transfected cells and desloratadine in PRKCA-transfected cells. Novel drug resistance mechanisms independent of ABC transporters have been identified that contribute to anthracycline resistance in MDR cells.

Identification of novel compounds against three targets of SARS CoV-2 coronavirus by combined virtual screening and supervised machine learning.

Coronavirus disease 2019 (COVID-19) is a major threat worldwide due to its fast spreading. As yet, there are no established drugs available. Speeding up drug discovery is urgently required. We applied a workflow of combined in silico methods (virtual drug screening, molecular docking and supervised machine learning algorithms) to identify novel drug candidates against COVID-19. We constructed chemical libraries consisting of FDA-approved drugs for drug repositioning and of natural compound datasets from literature mining and the ZINC database to select compounds interacting with SARS-CoV-2 target proteins (spike protein, nucleocapsid protein, and 2'-o-ribose methyltransferase). Supported by the supercomputer MOGON, candidate compounds were predicted as presumable SARS-CoV-2 inhibitors. Interestingly, several approved drugs against hepatitis C virus (HCV), another enveloped (-) ssRNA virus (paritaprevir, simeprevir and velpatasvir) as well as drugs against transmissible diseases, against cancer, or other diseases were identified as candidates against SARS-CoV-2. This result is supported by reports that anti-HCV compounds are also active against Middle East Respiratory Virus Syndrome (MERS) coronavirus. The candidate compounds identified by us may help to speed up the drug development against SARS-CoV-2.