Biomed Pharmacother. 2021 Aug 12;142:112020. doi: 10.1016/j.biopha.2021.112020. Online ahead of print.

ABSTRACT

Chagas disease, caused by Trypanosoma cruzi, is treated with only two drugs; benznidazole and nifurtimox. These drugs have some disadvantages, including their efficacy only in the acute or early infection phases, adverse effects during their use, and the resistance that the parasite has developed to their activity. Therefore, it is necessary to identify new, safe and effective therapeutic alternatives to treat Chagas disease, though governments and the pharmaceutical industry have shown a lack of interest in contributing to this solution. Institutions and research groups on the other hand have worked on some strategies that can help to address the problem. Some of these include the modification of conventional drug dosages, drug repurposing, and combined therapy. Plants and derived compounds with antiparasitic effects have also been studied, taking advantage of traditional medicinal knowledge. Others have studied the parasite to identify essential genes that can be used as therapeutic targets to design new, targeted drugs. Some of these studies have generated promising results, but few reach clinical phase studies. Institutions and research groups should be encouraged to unify efforts and cover all aspects of drug development according to resources and knowledge availability. In the end, this exchange of knowledge would lead to the development of new therapeutic alternatives to treat Chagas disease and benefit the populations it affects.

PMID:34392087 | DOI:10.1016/j.biopha.2021.112020

Int J Pharm. 2021 Aug 11:121002. doi: 10.1016/j.ijpharm.2021.121002. Online ahead of print.

ABSTRACT

3D printing has revolutionized pharmaceutical research, with applications encompassing tissue regeneration and drug delivery. Adopting 3D printing for pharmaceutical drug delivery personalization via nanoparticle-reinforced hydrogel scaffolds promises great regenerative potential. Herein, we engineered novel core/shell, bio-inspired, drug-loaded polymeric hydrogel scaffolds for pharmaceutically personalized drug delivery and superior osteoregeneration. Scaffolds were developed using biopolymeric blends of gelatin, polyvinyl alcohol and hyaluronic acid and integrated with composite doxycycline/hydroxyapatite/polycaprolactone nanoparticles (DX/HAp/PCL) innovatively via 3D printing. The developed scaffolds were optimized for swelling pattern and in-vitro drug release through tailoring the biphasic microstructure and wet/dry state to attain various pharmaceutical personalization platforms. Freeze-dried scaffolds with nanoparticles reinforcing the core phase (DX/HAp/PCL-LCS-FD) demonstrated favorably controlled swelling, preserved structural integrity and controlled drug release over 28 days. DX/HAp/PCL-LCS-FD featured double-ranged pore size (90.4 ± 3.9 and 196.6 ± 38.8 µm for shell and core phases, respectively), interconnected porosity and superior mechanical stiffness (74.5 ± 6.8 kPa) for osteogenic functionality. Cell spreading analysis, computed tomography and histomorphometry in a rabbit tibial model confirmed osteoconduction, bioresorption, immune tolerance and bone regenerative potential of the original scaffolds, affording complete defect healing with bone tissue. Our findings suggest that the developed platforms promise prominent local drug delivery and bone regeneration.

PMID:34390809 | DOI:10.1016/j.ijpharm.2021.121002

Cancer Lett. 2021 Aug 11:S0304-3835(21)00398-0. doi: 10.1016/j.canlet.2021.08.009. Online ahead of print.

ABSTRACT

Multiple myeloma (MM) is incurable and the second most common hematologic malignancy in plasma cells. Multiple myeloma stem-like cells (MMSCs), a rare population of MM cells, are believed to be the major cause of drug resistance and high recurrence rates in patients with MM. Therefore, developing novel strategies to eradicate MMSCs may favor myeloma treatment. In this study, based on the drug repositioning strategy, we found that albendazole (ABZ), a broad-spectrum antiparasitic drug, selectively suppresses the proliferation of multiple myeloma cells in vitro and in vivo and decreases number of aldehyde dehydrogenase (ALDH)-positive MMSCs in MM. Furthermore, RNA-seq of MM cells after ABZ treatment revealed that inhibition of the nuclear factor kappa-B (NF-κB) pathway is a key mediator of ABZ against MM. Moreover, we demonstrated that ABZ can resensitize cells resistant to bortezomib and overcome MMSCs-induced bortezomib resistance by decreasing ALDH1+ MMSCs numbers. Our findings provide preclinical evidence for utilizing the previously known pharmacologically active drug albendazole for the treatment of multiple myeloma.

PMID:34390764 | DOI:10.1016/j.canlet.2021.08.009

Biomed Pharmacother. 2021 Aug 5;142:112015. doi: 10.1016/j.biopha.2021.112015. Online ahead of print.

ABSTRACT

COVID-19, an infectious disease, has emerged as one of the leading causes of death worldwide, making it one of the severe public health issues in recent decades. nCoV, the novel SARS coronavirus that causes COVID-19, has brought together scientists in the quest for possible therapeutic and preventive measures. The development of new drugs to manage COVID-19 effectively is a challenging and time-consuming process, thus encouraging extensive investigation of drug repurposing and repositioning candidates. Several medications, including remdesivir, hydroxychloroquine, chloroquine, lopinavir, favipiravir, ribavirin, ritonavir, interferons, azithromycin, capivasertib and bevacizumab, are currently under clinical trials for COVID-19. In addition, several medicinal plants with considerable antiviral activities are potential therapeutic candidates for COVID-19. Statistical data show that the pandemic is yet to slow down, and authorities are placing their hopes on vaccines. Within a short period, four types of vaccines, namely, whole virus, viral vector, protein subunit, and nucleic acid (RNA/DNA), which can confer protection against COVID-19 in different ways, were already in a clinical trial. SARS-CoV-2 variants spread is associated with antibody escape from the virus Spike epitopes, which has grave concerns for viral re-infection and even compromises the effectiveness of the vaccines. Despite these efforts, COVID-19 treatment is still solely based on clinical management through supportive care. We aim to highlight the recent trends in COVID-19, relevant statistics, and clinical findings, as well as potential therapeutics, including in-line treatment methods, preventive measures, and vaccines to combat the prevalence of COVID-19.

PMID:34388532 | PMC:PMC8339548 | DOI:10.1016/j.biopha.2021.112015

Comput Biol Med. 2021 Aug 8;136:104748. doi: 10.1016/j.compbiomed.2021.104748. Online ahead of print.

ABSTRACT

The outbreak of the triple mutant strain of severe acute respiratory syndrome coronavirus-2 (SARS-COV-2) was more virulent and pathogenic than its original strain. The viral triple mutant strain of SARS-COV-2 is extremely adaptive and increases penetrability into the host. The triple mutant viral strain was first reported in Brazil and South Africa and then communicated to different countries responsible for the second wave of the coronavirus disease (COVID-19) global pandemic with a high mortality rate. The reported genomic mutations are responsible for the alterations in the viral functional and structural proteins, causing the ineffectiveness of the existing antiviral therapy targeting these proteins. Thus, in current research, molecular docking simulation-based virtual screening of a ligand library consisting of FDA-approved existing drugs followed by molecular dynamics simulation-based validation of leads was performed to develop a potent inhibitor molecule for the triple mutant viral strain SARS-CoV-2. Based on the safety profile, tamibarotene was selected as a safe and effective drug candidate for developing therapy against the triple mutant viral spike protein of SARS-CoV-2.

PMID:34388463 | PMC:PMC8349365 | DOI:10.1016/j.compbiomed.2021.104748

J Chem Inf Model. 2021 Aug 13. doi: 10.1021/acs.jcim.1c00683. Online ahead of print.

ABSTRACT

With the rapidly evolving SARS-CoV-2 variants of concern, there is an urgent need for the discovery of further treatments for the coronavirus disease (COVID-19). Drug repurposing is one of the most rapid strategies for addressing this need, and numerous compounds have already been selected for in vitro testing by several groups. These have led to a growing database of molecules with in vitro activity against the virus. Machine learning models can assist drug discovery through prediction of the best compounds based on previously published data. Herein, we have implemented several machine learning methods to develop predictive models from recent SARS-CoV-2 in vitro inhibition data and used them to prioritize additional FDA-approved compounds for in vitro testing selected from our in-house compound library. From the compounds predicted with a Bayesian machine learning model, lumefantrine, an antimalarial was selected for testing and showed limited antiviral activity in cell-based assays while demonstrating binding (Kd 259 nM) to the spike protein using microscale thermophoresis. Several other compounds which we prioritized have since been tested by others and were also found to be active in vitro. This combined machine learning and in vitro testing approach can be expanded to virtually screen available molecules with predicted activity against SARS-CoV-2 reference WIV04 strain and circulating variants of concern. In the process of this work, we have created multiple iterations of machine learning models that can be used as a prioritization tool for SARS-CoV-2 antiviral drug discovery programs. The very latest model for SARS-CoV-2 with over 500 compounds is now freely available at www.assaycentral.org.

PMID:34387990 | DOI:10.1021/acs.jcim.1c00683

Front Microbiol. 2021 Jul 27;12:707629. doi: 10.3389/fmicb.2021.707629. eCollection 2021.

ABSTRACT

It has been demonstrated that some non-steroidal anti-inflammatory drugs (NSAIDs), like acetylsalicylic acid, diclofenac, and ibuprofen, have anti-biofilm activity in concentrations found in human pharmacokinetic studies, which could fuel an interest in repurposing these well tolerated drugs as adjunctive therapies for biofilm-related infections. Here we sought to review the currently available data on the anti-biofilm activity of NSAIDs and its relevance in a clinical context. We performed a systematic literature review to identify the most commonly tested NSAIDs drugs in the last 5 years, the bacterial species that have demonstrated to be responsive to their actions, and the emergence of resistance to these molecules. We found that most studies investigating NSAIDs' activity against biofilms were in vitro, and frequently tested non-clinical bacterial isolates, which may not adequately represent the bacterial populations that cause clinically-relevant biofilm-related infections. Furthermore, studies concerning NSAIDs and antibiotic resistance are scarce, with divergent outcomes. Although the potential to use NSAIDs to control biofilm-related infections seems to be an exciting avenue, there is a paucity of studies that tested these drugs using appropriate in vivo models of biofilm infections or in controlled human clinical trials to support their repurposing as anti-biofilm agents.

PMID:34385992 | PMC:PMC8353384 | DOI:10.3389/fmicb.2021.707629

Nat Genet. 2021 Aug 12. doi: 10.1038/s41588-021-00909-9. Online ahead of print.

ABSTRACT

The functional interpretation of genome-wide association studies (GWAS) is challenging due to the cell-type-dependent influences of genetic variants. Here, we generated comprehensive maps of expression quantitative trait loci (eQTLs) for 659 microdissected human kidney samples and identified cell-type-eQTLs by mapping interactions between cell type abundances and genotypes. By partitioning heritability using stratified linkage disequilibrium score regression to integrate GWAS with single-cell RNA sequencing and single-nucleus assay for transposase-accessible chromatin with high-throughput sequencing data, we prioritized proximal tubules for kidney function and endothelial cells and distal tubule segments for blood pressure pathogenesis. Bayesian colocalization analysis nominated more than 200 genes for kidney function and hypertension. Our study clarifies the mechanism of commonly used antihypertensive and renal-protective drugs and identifies drug repurposing opportunities for kidney disease.

PMID:34385711 | DOI:10.1038/s41588-021-00909-9

Trials. 2021 Aug 11;22(1):530. doi: 10.1186/s13063-021-05475-3.

ABSTRACT

BACKGROUND: Systemic lupus erythematosus (SLE) is an autoimmune disease that can involve multiple organs or systems. Lupus nephritis (LN) is associated with high mortality and morbidity. However, plenty of patients do not respond to present treatment or relapse. Iguratimod (IGU) is a new small molecular, anti-rheumatic drug and has shown the potential for drug repurposing from rheumatoid arthritis (RA) to LN treatment. It has been approved for treating RA in northeast Asia. Beyond expectation in a recent observational study, over 90% of thirteen refractory LN patients responded to iguratimod monotherapy in 24 weeks, with no steroids dose increasing or any other medication add-on during the entire follow-up.

METHODS/DESIGN: This study is a multi-center, randomized, 52-week parallel positive drug-controlled study. The study was designed as a head-to-head comparison between the iguratimod and present first-line therapy on LN patients. A total of 120 patients (60 patients each group) is in the enrolling plan. All enrolled patients are assigned randomly into trial and control groups. The patients will be selected from six study sites in China and will all have biopsy-proven active lupus nephritis. In the first 24 weeks of the trial, IGU is compared with cyclophosphamide as an induction therapy, and in the second 24 weeks, IGU is compared with azathioprine as a maintenance therapy. The primary outcome is renal remission rate including both complete remission and partial remission at week 52, which will be analyzed using a non-inferiority hypothesis test.

DISCUSSION: Most patients diagnosed with SLE will develop LN within 5 years and LN remains a major cause of morbidity and death for SLE patients. Although some medications are proven effective for the treatment of this condition, at least 20-35% LN patients have to suffer from relapse or ineffective treatment and medication intolerance is also frequent. This trial is designed to demonstrate whether iguratimod can be used as an alternative induction or maintenance therapy in subjects who have lupus nephritis. Data from this study will provide an evidence on whether or not iguratimod should be recommended to active LN patients.

TRIAL REGISTRATION: ClinicalTrials.gov NCT02936375 . Registered on October 18, 2016.

PMID:34380536 | DOI:10.1186/s13063-021-05475-3

Microbiol Spectr. 2021 Aug 11:e0047221. doi: 10.1128/Spectrum.00472-21. Online ahead of print.

ABSTRACT

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is a causative agent of the coronavirus disease 2019 (COVID-19) pandemic, and the development of therapeutic interventions is urgently needed. So far, monoclonal antibodies and drug repositioning are the main methods for drug development, and this effort was partially successful. Since the beginning of the COVID-19 pandemic, the emergence of SARS-CoV-2 variants has been reported in many parts of the world, and the main concern is whether the current vaccines and therapeutics are still effective against these variant viruses. Viral entry and viral RNA-dependent RNA polymerase (RdRp) are the main targets of current drug development; therefore, the inhibitory effects of transmembrane serine protease 2 (TMPRSS2) and RdRp inhibitors were compared among the early SARS-CoV-2 isolate (lineage A) and the two recent variants (lineage B.1.1.7 and lineage B.1.351) identified in the United Kingdom and South Africa, respectively. Our in vitro analysis of viral replication showed that the drugs targeting TMPRSS2 and RdRp are equally effective against the two variants of concern. IMPORTANCE The COVID-19 pandemic is causing unprecedented global problems in both public health and human society. While some vaccines and monoclonal antibodies were successfully developed very quickly and are currently being used, numerous variants of the causative SARS-CoV-2 are emerging and threatening the efficacy of vaccines and monoclonal antibodies. In order to respond to this challenge, we assessed antiviral efficacy of small-molecule inhibitors that are being developed for treatment of COVID-19 and found that they are still very effective against the SARS-CoV-2 variants. Since most small-molecule inhibitors target viral or host factors other than the mutated sequence of the viral spike protein, they are expected to be potent control measures against the COVID-19 pandemic.

PMID:34378968 | DOI:10.1128/Spectrum.00472-21

Biomater Sci. 2021 Aug 11. doi: 10.1039/d1bm00486g. Online ahead of print.

ABSTRACT

Duloxetine (DLX) is a selective serotonin and noradrenaline reuptake inhibitor (SNRI) used for the treatment of pain, but it has been reported to show side effects in 10-20% of patients. Its analgesic efficacy in central pain is putatively related to its influence on descending inhibitory neuronal pathways. However, DLX can also affect the activation of microglia. This study was performed to investigate whether PLGA nanoparticles (NPs), which are expected to enhance targeting to microglia, can improve the analgesic efficacy and limit the side effects of DLX. PLGA NPs encapsulating a low dose of DLX (DLX NPs) were synthesized and characterized and their localization was determined. The analgesic and anti-inflammatory effects of DLX NPs were evaluated in a spinal nerve ligation (SNL)-induced neuropathic pain model. The analgesic effect of DLX lasted for only a few hours and disappeared within 1 day. However, DLX NPs alleviated mechanical allodynia, and the effect was maintained for 1 week. DLX NPs were localized to the spinal microglia and suppressed microglial activation, phosphorylation of p38/NF-κB-mediated pathways and the production of inflammatory cytokines in the spinal dorsal horn of SNL rats. We demonstrated that DLX NPs can provide a prolonged analgesic effect by enhanced targeting of microglia. Our observations imply that DLX delivery through nanoparticle encapsulation allows drug repositioning with a prolonged analgesic effect, and reduces the potential side effects of abuse and overdose.

PMID:34378557 | DOI:10.1039/d1bm00486g

Brief Bioinform. 2021 Aug 10:bbab319. doi: 10.1093/bib/bbab319. Online ahead of print.

ABSTRACT

In silico reuse of old drugs (also known as drug repositioning) to treat common and rare diseases is increasingly becoming an attractive proposition because it involves the use of de-risked drugs, with potentially lower overall development costs and shorter development timelines. Therefore, there is a pressing need for computational drug repurposing methodologies to facilitate drug discovery. In this study, we propose a new method, called DRHGCN (Drug Repositioning based on the Heterogeneous information fusion Graph Convolutional Network), to discover potential drugs for a certain disease. To make full use of different topology information in different domains (i.e. drug-drug similarity, disease-disease similarity and drug-disease association networks), we first design inter- and intra-domain feature extraction modules by applying graph convolution operations to the networks to learn the embedding of drugs and diseases, instead of simply integrating the three networks into a heterogeneous network. Afterwards, we parallelly fuse the inter- and intra-domain embeddings to obtain the more representative embeddings of drug and disease. Lastly, we introduce a layer attention mechanism to combine embeddings from multiple graph convolution layers for further improving the prediction performance. We find that DRHGCN achieves high performance (the average AUROC is 0.934 and the average AUPR is 0.539) in four benchmark datasets, outperforming the current approaches. Importantly, we conducted molecular docking experiments on DRHGCN-predicted candidate drugs, providing several novel approved drugs for Alzheimer's disease (e.g. benzatropine) and Parkinson's disease (e.g. trihexyphenidyl and haloperidol).

PMID:34378011 | DOI:10.1093/bib/bbab319

Neurooncol Adv. 2021 Jun 24;3(1):vdab075. doi: 10.1093/noajnl/vdab075. eCollection 2021 Jan-Dec.

ABSTRACT

BACKGROUND: The dismal prognosis of glioblastoma (GBM) may be related to the ability of GBM cells to develop mechanisms of treatment resistance. We designed a protocol called Coordinated Undermining of Survival Paths combining 9 repurposed non-oncological drugs with metronomic temozolomide-version 3-(CUSP9v3) to address this issue. The aim of this phase Ib/IIa trial was to assess the safety of CUSP9v3.

METHODS: Ten adults with histologically confirmed GBM and recurrent or progressive disease were included. Treatment consisted of aprepitant, auranofin, celecoxib, captopril, disulfiram, itraconazole, minocycline, ritonavir, and sertraline added to metronomic low-dose temozolomide. Treatment was continued until toxicity or progression. Primary endpoint was dose-limiting toxicity defined as either any unmanageable grade 3-4 toxicity or inability to receive at least 7 of the 10 drugs at ≥ 50% of the per-protocol doses at the end of the second treatment cycle.

RESULTS: One patient was not evaluable for the primary endpoint (safety). All 9 evaluable patients met the primary endpoint. Ritonavir, temozolomide, captopril, and itraconazole were the drugs most frequently requiring dose modification or pausing. The most common adverse events were nausea, headache, fatigue, diarrhea, and ataxia. Progression-free survival at 12 months was 50%.

CONCLUSIONS: CUSP9v3 can be safely administered in patients with recurrent GBM under careful monitoring. A randomized phase II trial is in preparation to assess the efficacy of the CUSP9v3 regimen in GBM.

PMID:34377985 | PMC:PMC8349180 | DOI:10.1093/noajnl/vdab075

Comput Struct Biotechnol J. 2021 Jul 10;19:3990-4002. doi: 10.1016/j.csbj.2021.07.007. eCollection 2021.

ABSTRACT

Despite the fact that an increased amount of survival-related lncRNAs have been found in cancer, few drugs that target lncRNAs are approved for treatment. Here, we developed a network-based algorithm, LncTx, to repurpose the medications that potentially act on survival-related lncRNAs in lung cancer. We used eight survival-related lncRNAs derived from our previous study to test the efficacy of this method. LncTx calculates the shortest path length (proximity) between the drug targets and the lncRNA-correlated proteins in the protein-protein interaction network (interactome). LncTx contains seven different proximity measures, which are calculated in the unweighted or weighted interactome. First, to test the performance of LncTx in predicting correct indication of drugs, we benchmarked the proximity measures based on the accuracy of differentiating anticancer drugs from non-anticancer drugs. The closest proximity weighted by clustering coefficient (closestCC) has the best performance (AUC around 0.8) compared to other proximity measures across all survival-related lncRNAs. The majority of the other six proximity measures have decent performance as well, with AUC greater than 0.7. Second, to evaluate whether LncTx can repurpose the drugs effectively acting on the lncRNAs, we clustered the drugs according to their proximities by hierarchical clustering. The drugs with smaller proximity (proximal drugs) were proved to be more effective than the drugs with larger proximity (distal drugs). In conclusion, LncTx enables us to accurately identify anticancer drugs and can potentially be an index to repurpose effective agents acting on survival-related lncRNAs in lung cancer.

PMID:34377365 | PMC:PMC8319574 | DOI:10.1016/j.csbj.2021.07.007

Sci Rep. 2021 Aug 10;11(1):16251. doi: 10.1038/s41598-021-95507-4.

ABSTRACT

Drug repurposing is one of the modern techniques used in the drug discovery to find out the new targets for existing drugs. Insilico methods have a major role in this approach. We used 60 FDA approved antiviral drugs reported in the last 50 years to screen against different cancer cell receptors. The thirteen compounds selected after virtual screening are analyzed for their druggability based on ADMET parameters and found the selectivity of guanine derivatives-didanosine, entecavir, acyclovir, valganciclovir, penciclovir, ganciclovir and valacyclovir as suitable candidates. The pharmacophore model, AARR, suggested based on the common feature alignment, shows that the two fused rings as in guanine and two acceptors-one from keto-oxygen (A5) and other from the substituent attached to nitrogen of imidazole ring (A4) give the druggability to the guanine derivatives. The NBO analysis on N9 is indicative of charge distribution from the ring to substituents, which results in delocalization of negative character in most of the ligands. The molecular dynamics simulations also pointed out the importance of guanine scaffold, which stabilizes the ligands inside the binding pocket of the receptor. All these results are indicative of the selectivity of guanine scaffold in anticancer drug development, especially as PARP1 inhibitors in breast, ovarian and prostate cancer. As these seven molecules are already approved by FDA, we can safely go for further preclinical trials.

PMID:34376738 | DOI:10.1038/s41598-021-95507-4

Comput Biol Med. 2021 Jul 29;136:104676. doi: 10.1016/j.compbiomed.2021.104676. Online ahead of print.

ABSTRACT

Analysis and prediction of drug-target interactions (DTIs) play an important role in understanding drug mechanisms, as well as drug repositioning and design. Machine learning (ML)-based methods for DTIs prediction can mitigate the shortcomings of time-consuming and labor-intensive experimental approaches, while providing new ideas and insights for drug design. We propose a novel pipeline for predicting drug-target interactions, called DNN-DTIs. First, the target information is characterized by a number of features, namely, pseudo-amino acid composition, pseudo position-specific scoring matrix, conjoint triad composition, transition and distribution, Moreau-Broto autocorrelation, and structural features. The drug compounds are subsequently encoded using substructure fingerprints. Next, eXtreme gradient boosting (XGBoost) is used to determine the subset of non-redundant features of importance. The optimal balanced set of sample vectors is obtained by applying the synthetic minority oversampling technique (SMOTE). Finally, a DTIs predictor, DNN-DTIs, is developed based on a deep neural network (DNN) via a layer-by-layer learning scheme. Experimental results indicate that DNN-DTIs achieves better performance than other state-of-the-art predictors with ACC values of 98.78%, 98.60%, 97.98%, 98.24% and 98.00% on Enzyme, Ion Channels (IC), GPCR, Nuclear Receptors (NR) and Kuang's datasets. Therefore, the accurate prediction performance of DNN-DTIs makes it a favored choice for contributing to the study of DTIs, especially drug repositioning.

PMID:34375902 | DOI:10.1016/j.compbiomed.2021.104676

IEEE/ACM Trans Comput Biol Bioinform. 2021 Aug 10;PP. doi: 10.1109/TCBB.2021.3103595. Online ahead of print.

ABSTRACT

Drug repositioning/repurposing is a very important approach towards identifying novel treatments for diseases in drug discovery. Recently, large-scale biological datasets are increasingly available for pharmaceutical research and promote the development of drug repositioning, but efficiently utilizing these datasets remains challenging. In this paper, we develop a novel multimodal framework, termed GraphPK(Graph-based Prior Knowledge) for improving in silico drug repositioning via using the prior knowledge from a drug knowledge graph. First, we construct a knowledge graph by integrating relevant bio-entities and associations/interactions among them, and apply the knowledge graph embedding technique to extract prior knowledge of drugs and diseases. Moreover, we make use of the known drug-disease association, and obtain known association-based features from an association bipartite graph through graph embedding, and also take into account biological domain features. Finally, we design a multimodal neural network to combine three types of features and build the prediction model.Massive experiments show that our method outperforms other state-of-the-art methods, and the ablation analysis reveals that prior knowledge from knowledge graphs can not only lift the predictive power of drug repositioning, but also enhance the models robustness to different scenarios. The results of case studies offer support that GraphPK has the potential of actual use.

PMID:34375284 | DOI:10.1109/TCBB.2021.3103595

Assay Drug Dev Technol. 2021 Aug 10. doi: 10.1089/adt.2021.014. Online ahead of print.

ABSTRACT

Recent reports have highlighted the possible role of the antipsychotic chlorpromazine and the antidepressant fluvoxamine as anti-coronavirus disease 2019 (COVID-19) agents. The objective of this narrative review is to explore what is known about the activity of psychotropic medications against viruses in addition to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). PubMed was queried for "drug repurposing, antiviral activity," and for "antiviral activity" with "psychotropic drugs" and individual agents, through November 2020. Of more than 100 psychotropic agents, 37 drugs, including 27 with a history of pediatric use were identified, which had been studied in the preclinical setting and found to have activity against viruses which are human pathogens. Effects were evaluated by type of virus and by category of psychotropic agent. Activity was identified both against viruses known to cause epidemics such as SARS-CoV-2 and Ebola and against those that are the cause of rare disorders such as Human Papillomatosis Virus-related respiratory papillomatosis. Individual drugs and classes of psychotropics often had activity against multiple viruses, with promiscuity explained by shared viral or cellular targets. Safety profiles of psychotropics may be more tolerable in this context than when they are used long-term in the setting of psychiatric illness. Nonetheless, translation of in vitro results to the clinical arena has been slow. Psychotropic medications as a class deserve further study, including in clinical trials for repurposing as antiviral drugs for children and adults.

PMID:34375133 | DOI:10.1089/adt.2021.014

Nat Rev Neurol. 2021 Aug 9. doi: 10.1038/s41582-021-00550-4. Online ahead of print.

NO ABSTRACT

PMID:34373635 | DOI:10.1038/s41582-021-00550-4

mBio. 2021 Aug 10:e0145821. doi: 10.1128/mBio.01458-21. Online ahead of print.

ABSTRACT

Aspergillus fumigatus is an important fungal pathogen and the main etiological agent of aspergillosis, a disease characterized by a noninvasive process that can evolve to a more severe clinical manifestation, called invasive pulmonary aspergillosis (IPA), in immunocompromised patients. The antifungal arsenal to threat aspergillosis is very restricted. Azoles are the main therapeutic approach to control IPA, but the emergence of azole-resistant A. fumigatus isolates has significantly increased over recent decades. Therefore, new strategies are necessary to combat aspergillosis, and drug repurposing has emerged as an efficient and alternative approach for identifying new antifungal drugs. Here, we used a screening approach to analyze A. fumigatus in vitro susceptibility to 1,127 compounds. A. fumigatus was susceptible to 10 compounds, including miltefosine, a drug that displayed fungicidal activity against A. fumigatus. By screening an A. fumigatus transcription factor null library, we identified a single mutant, which has the smiA (sensitive to miltefosine) gene deleted, conferring a phenotype of susceptibility to miltefosine. The transcriptional profiling (RNA-seq) of the wild-type and ΔsmiA strains and chromatin immunoprecipitation coupled to next-generation sequencing (ChIP-Seq) of an SmiA-tagged strain exposed to miltefosine revealed genes of the sphingolipid pathway that are directly or indirectly regulated by SmiA. Sphingolipid analysis demonstrated that the mutant has overall decreased levels of sphingolipids when growing in the presence of miltefosine. The identification of SmiA represents the first genetic element described and characterized that plays a direct role in miltefosine response in fungi. IMPORTANCE The filamentous fungus Aspergillus fumigatus causes a group of diseases named aspergillosis, and their development occurs after the inhalation of conidia dispersed in the environment. Very few classes of antifungal drugs are available for aspergillosis treatment, e.g., azoles, but the emergence of global resistance to azoles in A. fumigatus clinical isolates has increased over recent decades. Repositioning or repurposing drugs already available on the market is an interesting and faster opportunity for the identification of novel antifungal agents. By using a repurposing strategy, we identified 10 different compounds that impact A. fumigatus survival. One of these compounds, miltefosine, demonstrated fungicidal activity against A. fumigatus. The mechanism of action of miltefosine is unknown, and, aiming to get more insights about it, we identified a transcription factor, SmiA (sensitive to miltefosine), important for miltefosine resistance. Our results suggest that miltefosine displays antifungal activity against A. fumigatus, interfering in sphingolipid biosynthesis.

PMID:34372704 | DOI:10.1128/mBio.01458-21