RepurposeDrugs: an interactive web-portal and predictive platform for repurposing mono- and combination therapies.

RepurposeDrugs (https://repurposedrugs.org/) is a comprehensive web-portal that combines a unique drug indication database with a machine learning (ML) predictor to discover new drug-indication associations for approved as well as investigational mono and combination therapies. The platform provides detailed information on treatment status, disease indications and clinical trials across 25 indication categories, including neoplasms and cardiovascular conditions. The current version comprises 4314 compounds (approved, terminated or investigational) and 161 drug combinations linked to 1756 indications/conditions, totaling 28 148 drug-disease pairs. By leveraging data on both approved and failed indications, RepurposeDrugs provides ML-based predictions for the approval potential of new drug-disease indications, both for mono- and combinatorial therapies, demonstrating high predictive accuracy in cross-validation. The validity of the ML predictor is validated through a number of real-world case studies, demonstrating its predictive power to accurately identify repurposing candidates with a high likelihood of future approval. To our knowledge, RepurposeDrugs web-portal is the first integrative database and ML-based predictor for interactive exploration and prediction of both single-drug and combination approval likelihood across indications. Given its broad coverage of indication areas and therapeutic options, we expect it accelerates many future drug repurposing projects.

The combination therapy using tyrosine kinase receptors inhibitors and repurposed drugs to target patient-derived glioblastoma stem cells.

The lesson from many studies investigating the efficacy of targeted therapy in glioblastoma (GBM) showed that a future perspective should be focused on combining multiple target treatments. Our research aimed to assess the efficacy of drug combinations against glioblastoma stem cells (GSCs). Patient-derived cells U3042, U3009, and U3039 were obtained from the Human Glioblastoma Cell Culture resource. Additionally, the study was conducted on a GBM commercial U251 cell line. Gene expression analysis related to receptor tyrosine kinases (RTKs), stem cell markers and genes associated with significant molecular targets was performed, and selected proteins encoded by these genes were assessed using the immunofluorescence and flow cytometry methods. The cytotoxicity studies were preceded by analyzing the expression of specific proteins that serve as targets for selected drugs. The cytotoxicity study using the MTS assay was conducted to evaluate the effects of selected drugs/candidates in monotherapy and combinations. The most cytotoxic compounds for U3042 cells were Disulfiram combined with Copper gluconate (DSF/Cu), Dacomitinib, and Foretinib with IC50 values of 52.37 nM, 4.38 µM, and 4.54 µM after 24 h incubation, respectively. Interactions were assessed using SynergyFinder Plus software. The analysis enabled the identification of the most effective drug combinations against patient-derived GSCs. Our findings indicate that the most promising drug combinations are Dacomitinib and Foretinib, Dacomitinib and DSF/Cu, and Foretinib and AZD3759. Since most tested combinations have not been previously examined against glioblastoma stem-like cells, these results can shed new light on designing the therapeutic approach to target the GSC population.

Prolonged Response to Afatinib and Crizotinib in a Rare Case of EGFR-, HER2-, MET- and ROS1-Alterated Lung Adenocarcinoma.

We present the case of a 70-year-old never-smoking female patient with epidermal growth factor receptor (EGFR) p.L858R-mutated metastatic non-small cell lung cancer (NSCLC). After three months of first-line treatment with erlotinib, progression occurred and platinum/pemetrexed was initiated, followed by a response for more than two years. After the progression, the molecular testing of a vertebral metastasis revealed a ROS proto-oncogene 1 (ROS1) translocation and a human epidermal growth factor receptor 2 (HER2) p.S310F mutation, in addition to the known EGFR p.L858R mutation. Crizotinib then led to a durable response of 17 months. The molecular retesting of the tumour cells obtained from the recurrent pleural effusion revealed the absence of the ROS1 translocation, whereas the EGFR and HER2 mutations were still present. Afatinib was added to the crizotinib, and the combination treatment resulted in another durable response of more than two years. The patient died more than 7 years after the initial diagnosis of metastatic NSCLC. This case demonstrates that the repeated molecular testing of metastatic NSCLC may identify new druggable genomic alterations that can impact the patient management and improve the patient outcome.

MathEagle: Accurate prediction of drug-drug interaction events via multi-head attention and heterogeneous attribute graph learning.

BACKGROUND: Drug-drug interaction events influence the effectiveness of drug combinations and can lead to unexpected side effects or exacerbate underlying diseases, jeopardizing patient prognosis. Most existing methods are restricted to predicting whether two drugs interact or the type of drug-drug interactions, while very few studies endeavor to predict the specific risk levels of side effects of drug combinations. METHODS: In this study, we propose MathEagle, a novel approach to predict accurate risk levels of drug combinations based on multi-head attention and heterogeneous attribute graph learning. Initially, we model drugs and three distinct risk levels between drugs as a heterogeneous information graph. Subsequently, behavioral and chemical structure features of drugs are utilized by message passing neural networks and graph embedding algorithms, respectively. Ultimately, MathEagle employs heterogeneous graph convolution and multi-head attention mechanisms to learn efficient latent representations of drug nodes and estimates the risk levels of pairwise drugs in an end-to-end manner. RESULTS: To assess the effectiveness and robustness of the model, five-fold cross-validation, ablation experiments, and case studies were conducted. MathEagle achieved an accuracy of 85.85 % and an AUC of 0.9701 on the drug risk level prediction task and is superior to all comparative models. The MathEagle predictor is freely accessible at http://120.77.11.78/MathEagle/. CONCLUSIONS: The experimental results indicate that MathEagle can function as an effective tool for predicting accurate risk of drug combinations, aiding in guiding clinical medication, and enhancing patient outcomes.

Anticancer drugs: How to select small molecule combinations?

Small molecules are at the forefront of anticancer therapies. Successive treatments with single molecules incur drug resistance, calling for combination. Here, we explore the tough choices oncologists face - not just which drugs to use but also the best treatment plans, based on factors such as target proteins, pathways, and gene expression. We consider the reality of cancer's disruption of normal cellular processes, highlighting why it's crucial to understand the ins and outs of current treatment methods. The discussion on using combination drug therapies to target multiple pathways sheds light on a promising approach while also acknowledging the hurdles that come with it, such as dealing with pathway crosstalk. We review options and provide examples and the mechanistic basis, altogether providing the first comprehensive guide to combinatorial therapy selection.

New drug discovery strategies for the treatment of benznidazole-resistance in Trypanosoma cruzi, the causative agent of Chagas disease.

INTRODUCTION: Benznidazole, the drug of choice for treating Chagas Disease (CD), has significant limitations, such as poor cure efficacy, mainly in the chronic phase of CD, association with side effects, and parasite resistance. Understanding parasite resistance to benznidazole is crucial for developing new drugs to treat CD. AREAS COVERED: Here, the authors review the current understanding of the molecular basis of benznidazole resistance. Furthermore, they discuss the state-of-the-art methods and critical outcomes employed to evaluate the efficacy of potential drugs against T. cruzi, aiming to select better compounds likely to succeed in the clinic. Finally, the authors describe the different strategies employed to overcome resistance to benznidazole and find effective new treatments for CD. EXPERT OPINION: Resistance to benznidazole is a complex phenomenon that occurs naturally among T. cruzi strains. The combination of compounds that inhibit different metabolic pathways of the parasite is an important strategy for developing a new chemotherapeutic protocol.

Associazione Nazionale Medici Cardiologi Ospedalieri (ANMCO) scientific statement on the simplification of the drug regimen for secondary cardiovascular prevention.

The issue of suboptimal drug regimen adherence in secondary cardiovascular prevention presents a significant barrier to improving patient outcomes. To address this, the utilization of drug combinations, specifically single pill combinations (SPCs) and polypills, was proposed as a strategy to simplify treatment regimens. This approach aims to enhance treatment accessibility, affordability, and adherence, thereby reducing healthcare costs and improving patient health. The document is an Associazione Nazionale Medici Cardiologi Ospedalieri (ANMCO) scientific statement on simplifying drug regimens for secondary cardiovascular prevention. It discusses the underuse of treatments despite available, effective, and accessible options, highlighting a significant gap in secondary prevention across different socio-economic statuses and countries. The statement explores barriers to implementing evidence-based treatments, including patient, healthcare provider, and system-related challenges. The paper also reviews international guidelines, the role of SPCs and polypills in clinical practice, and their economic impact, advocating for their use in secondary prevention to improve patient outcomes and adherence.

Defining, identifying and addressing problematic polypharmacy within multimorbidity in primary care: a scoping review.

INTRODUCTION: Polypharmacy and multimorbidity pose escalating challenges. Despite numerous attempts, interventions have yet to show consistent improvements in health outcomes. A key factor may be varied approaches to targeting patients for intervention. OBJECTIVES: To explore how patients are targeted for intervention by examining the literature with respect to: understanding how polypharmacy is defined; identifying problematic polypharmacy in practice; and addressing problematic polypharmacy through interventions. DESIGN: We performed a scoping review as defined by the Joanna Briggs Institute. SETTING: The focus was on primary care settings. DATA SOURCES: Medline, Embase, Cumulative Index to Nursing and Allied Health Literature and Cochrane along with ClinicalTrials.gov, Science.gov and WorldCat.org were searched from January 2004 to February 2024. ELIGIBILITY CRITERIA: We included all articles that had a focus on problematic polypharmacy in multimorbidity and primary care, incorporating multiple types of evidence, such as reviews, quantitative trials, qualitative studies and policy documents. Articles focussing on a single index disease or not written in English were excluded. EXTRACTION AND ANALYSIS: We performed a narrative synthesis, comparing themes and findings across the collective evidence to draw contextualised insights and conclusions. RESULTS: In total, 157 articles were included. Case-finding methods often rely on basic medication counts (often five or more) without considering medical history or whether individual medications are clinically appropriate. Other approaches highlight specific drug indicators and interactions as potentially inappropriate prescribing, failing to capture a proportion of patients not fitting criteria. Different potentially inappropriate prescribing criteria also show significant inconsistencies in determining the appropriateness of medications, often neglecting to consider multimorbidity and underprescribing. This may hinder the identification of the precise population requiring intervention. CONCLUSIONS: Improved strategies are needed to target patients with polypharmacy, which should consider patient perspectives, individual factors and clinical appropriateness. The development of a cross-cutting measure of problematic polypharmacy that consistently incorporates adjustment for multimorbidity may be a valuable next step to address frequent confounding.

Using host-mimicking conditions and a murine cutaneous abscess model to identify synergistic antibiotic combinations effective against Pseudomonas aeruginosa.

Antibiotic drug combination therapy is critical for the successful treatment of infections caused by multidrug resistant pathogens. We investigated the efficacy of ß-lactam and ß-lactam/ß-lactamase inhibitor combinations with other antibiotics, against the hypervirulent, ceftazidime/avibactam resistant Pseudomonas aeruginosa Liverpool epidemic strain (LES) B58. Although minimum inhibitory concentrations in vitro differed by up to eighty-fold between standard and host-mimicking media, combinatorial effects only marginally changed between conditions for some combinations. Effective combinations in vitro were further tested in a chronic, high-density murine infection model. Colistin and azithromycin demonstrated combinatorial effects with ceftazidime and ceftazidime/avibactam both in vitro and in vivo. Conversely, while tobramycin and tigecycline exhibited strong synergy in vitro, this effect was not observed in vivo. Our approach of using host-mimicking conditions and a sophisticated animal model to evaluate drug synergy against bacterial pathogens represents a promising approach. This methodology may offer insights into the prediction of combination therapy outcomes and the identification of potential treatment failures.

DTNPD: A comprehensive database of drugs and targets for neurological and psychiatric disorders.

In response to the shortcomings in data quality and coverage for neurological and psychiatric disorders (NPDs) in existing comprehensive databases, this paper introduces the DTNPD database, specifically designed for NPDs. DTNPD contains detailed information on 30 NPDs types, 1847 drugs, 514 drug targets, 64 drug combinations, and 61 potential target combinations, forming a network with 2389 drug-target associations. The database is user-friendly, offering open access and downloadable data, which is crucial for network pharmacology studies. The key strength of DTNPD lies in its robust networks of drug and target combinations, as well as drug-target networks, facilitating research and development in the field of NPDs. The development of the DTNPD database marks a significant milestone in understanding and treating NPDs. For accessing the DTNPD database, the primary URL is http://dtnpd.cnsdrug.com, complemented by a mirror site available at http://dtnpd.lyhbio.com.

Chlorin Conjugates in Photodynamic Chemotherapy for Triple-Negative Breast Cancer.

Breast cancer (BC) is the most common type of cancer in women and the number of new cases in the US is still increasing each year. Triple-negative breast cancer (TNBC), which comprises 15-20% of all breast cancer, is a heterogeneous disease and is considered the most aggressive type of breast cancer due to the lack of estrogen receptor (ER), progesterone receptor (PR), and human epidermal growth factor receptor 2 (HER2) expressions for treatments. Traditional chemotherapy is the standard protocol for the treatment of TNBC. Toxicity and multidrug resistance are major drawbacks to chemotherapy. The lack of molecular targets and poor prognosis for TNBC prompts an urgent need to discover novel therapeutic strategies to improve clinical outcomes and quality of life for patients. Photodynamic therapy (PDT) or light treatment is a binary anti-cancer procedure that uses a photosensitizer (PS) that, upon light activation, produces cytotoxic oxygen species, destroying tumor cells. PDT is minimally invasive and can be repeated a few times without accumulating significant toxicity in the surrounding tissues. The primary goal of this study was to investigate in vitro photodynamic chemotherapy as a ternary combination therapy using our synthesized photosensitizers (chlorin-vitamin conjugates and their corresponding indium complexes) co-treated with known chemotherapeutic agents (taxol, doxorubicin, cisplatin, fluorouracil, or methotrexate) in the presence of light and determine the optimum conditions as a pre-clinical study of an enhanced tumoricidal effect against TNBC. Our results indicated that the best combination for an effective chemophotodynamic effect involves a ternary treatment of the indium complex of the chlorin-lipoic acid conjugate (InCLA) co-treated with taxol, which exhibited strong synergism at the nanomolar concentration when combined in the presence of visible light irradiation. Other ternary combinations containing taxol with a synergistic anti-tumor effect against TNBC include chlorin-pantothenic acid (CPA) and chlorin-biotin (CBTN) conjugates. Several other ternary combinations containing InCLA, CBTN, and CPA with either cisplatin, fluorouracil, or methotrexate were identified to generate a synergistic or additive effect. The light dosage remained constant, but the dosages of photosensitizers and chemotherapy drugs were varied to obtain the lowest possible concentration for the desired effect. The synergistic, additive or antagonistic effects of the drug combinations were determined based on the Chou-Talalay method, with InCLA-taxol having the lowest combination index (CI) of 0.25. Fluorescence and transmission electron microscopy (TEM) images provided evidence of apoptosis as the preferred mode of cell death. Our study demonstrated the combination of PDT and chemotherapy as a potential treatment option for TNBC patients.

Characterising incident opioid use among incident users of prescription sedative hypnotics: A national cohort study.

OBJECTIVE: To evaluate co-prescribing of sedatives hypnotics and opioids. DESIGN: Retrospective study evaluating the association of patient characteristics and comorbidities with coprescribing. SETTING AND PARTICIPANTS: Using the national Merative MarketScan Database between 2005 and 2018, we identified patients who received an incident sedative prescription with or without subsequent, incident opioid prescriptions within a year of the sedative prescription in the USA. OUTCOME MEASURES: Coprescription of sedative-hypnotics and opioids. RESULTS: A total of 2 632 622 patients (mean (SD) age, 43.2 (12.34) years; 1 297 356 (62.5%) female) received incident prescriptions for sedatives over the course of the study period. The largest proportion of sedative prescribing included benzodiazepines (71.1%); however, z-drugs (19.9%) and barbiturates (9%) were also common. About 557 845 (21.2%) patients with incident sedatives also received incident opioid prescriptions. About 59.2% of these coprescribed patients received opioids coprescription on the same day. Multivariate logistic regression findings showed that individuals with a comorbidity index score of 1, 2 or ≥3 (aOR 1.19 (95% CI 1.17 to 1.21), 1.17 (95% C 1.14 to 1.19) and 1.25 (95% C 1.2 to 1.31)) and substance use disorder (1.21 (95% C 1.19 to 1.23)) were more likely to be coprescribed opioids and sedatives. The likelihood of receiving both opioid and sedative prescriptions was lower for female patients (aOR 0.93; 95% CI 0.92 to 0.94), and those receiving a barbiturate (aOR 0.3; 95% CI 0.29 to 0.31) or z-drugs (aOR 0.67; 95% CI 0.66 to 0.68) prescriptions at the index date. CONCLUSIONS: Coprescription of sedatives with opioids was associated with the presence of comorbidities and substance use disorder, gender and types of sedatives prescribed at the index date. Additionally, more than half of the coprescribing occurred on the same day which warrants further evaluation of current prescribing and dispensing best practice guidelines.

Targeting Intracellular Bacteria with Dual Drug-loaded Lactoferrin Nanoparticles.

Treatment of microbial infections is becoming daunting because of widespread antimicrobial resistance. The treatment challenge is further exacerbated by the fact that certain infectious bacteria invade and localize within host cells, protecting the bacteria from antimicrobial treatments and the host's immune response. To survive in the intracellular niche, such bacteria deploy surface receptors similar to host cell receptors to sequester iron, an essential nutrient for their virulence, from host iron-binding proteins, in particular lactoferrin and transferrin. In this context, we aimed to target lactoferrin receptors expressed by macrophages and bacteria; as such, we prepared and characterized lactoferrin nanoparticles (Lf-NPs) loaded with a dual drug combination of antimicrobial natural alkaloids, berberine or sanguinarine, with vancomycin or imipenem. We observed increased uptake of drug-loaded Lf-NPs by differentiated THP-1 cells with up to 90% proportion of fluorescent cells, which decreased to about 60% in the presence of free lactoferrin, demonstrating the targeting ability of Lf-NPs. The encapsulated antibiotic drug cocktail efficiently cleared intracellular Staphylococcus aureus (Newman strain) compared to the free drug combinations. However, the encapsulated drugs and the free drugs alike exhibited a bacteriostatic effect against the hard-to-treat Mycobacterium abscessus (smooth variant). In conclusion, the results of this study demonstrate the potential of lactoferrin nanoparticles for the targeted delivery of antibiotic drug cocktails for the treatment of intracellular bacteria.

Novel hydrazone compounds with broad-spectrum antiplasmodial activity and synergistic interactions with antimalarial drugs.

The development of novel antiplasmodial compounds with broad-spectrum activity against different stages of Plasmodium parasites is crucial to prevent malaria disease and parasite transmission. This study evaluated the antiplasmodial activity of seven novel hydrazone compounds (referred to as CB compounds: CB-27, CB-41, CB-50, CB-53, CB-58, CB-59, and CB-61) against multiple stages of Plasmodium parasites. All CB compounds inhibited blood stage proliferation of drug-resistant or sensitive strains of Plasmodium falciparum in the low micromolar to nanomolar range. Interestingly, CB-41 exhibited prophylactic activity against hypnozoites and liver schizonts in Plasmodium cynomolgi, a primate model for Plasmodium vivax. Four CB compounds (CB-27, CB-41, CB-53, and CB-61) inhibited P. falciparum oocyst formation in mosquitoes, and five CB compounds (CB-27, CB-41, CB-53, CB-58, and CB-61) hindered the in vitro development of Plasmodium berghei ookinetes. The CB compounds did not inhibit the activation of P. berghei female and male gametocytes in vitro. Isobologram assays demonstrated synergistic interactions between CB-61 and the FDA-approved antimalarial drugs, clindamycin and halofantrine. Testing of six CB compounds showed no inhibition of Plasmodium glutathione S-transferase as a putative target and no cytotoxicity in HepG2 liver cells. CB compounds are promising candidates for further development as antimalarial drugs against multidrug-resistant parasites, which could also prevent malaria transmission.

Two-way pharmacodynamic modeling of drug combinations and its application to pairs of repurposed Ebola and SARS-CoV-2 agents.

Existing pharmacodynamic (PD) mathematical models for drug combinations discriminate antagonistic, additive, multiplicative, and synergistic effects, but fail to consider how concentration-dependent drug interaction effects may vary across an entire dose-response matrix. We developed a two-way pharmacodynamic (TWPD) model to capture the PD of two-drug combinations. TWPD captures interactions between upstream and downstream drugs that act on different stages of viral replication, by quantifying upstream drug efficacy and concentration-dependent effects on downstream drug pharmacodynamic parameters. We applied TWPD to previously published in vitro drug matrixes for repurposed potential anti-Ebola and anti-SARS-CoV-2 drug pairs. Depending on the drug pairing, the model recapitulated combined efficacies as or more accurately than existing models and can be used to infer efficacy at untested drug concentrations. TWPD fits the data slightly better in one direction for all drug pairs, meaning that we can tentatively infer the upstream drug. Based on its high accuracy, TWPD could be used in concert with PK models to estimate the therapeutic effects of drug pairs in vivo.

Recent advances in photodynamic therapy combined with chemotherapy for cervical cancer: a systematic review.

INTRODUCTION: Despite the evidence that photodynamic therapy (PDT) associated with chemotherapy presents great potential to overcome the limitations of monotherapy, little is known about the current status of this combination against cervical cancer. This systematic review aimed to address the currently available advances in combining PDT and chemotherapy in different research models and clinical trials of cervical cancer. METHODS: We conducted a systematic review based on PRISMA Statement and Open Science Framework review protocol using PubMed, Web of Science, Embase, Scopus, LILACS, and Cochrane databases. We selected original articles focusing on 'Uterine Cervical Neoplasms' and 'Photochemotherapy and Chemotherapy' published in the last 10 years. The risk of bias in the studies was assessed using the CONSORT and SYRCLE tools. RESULTS: Twenty-three original articles were included, focusing on HeLa cells, derived from endocervical adenocarcinoma and on combinations of several chemotherapeutics. Most of the combinations used modern drug delivery systems for improved simultaneous delivery and presented promising results with increased cytotoxicity compared to monotherapy. CONCLUSION: Despite the scarcity of animal studies and the absence of clinical studies, the combination of chemotherapy with PDT presents a potential option for cervical cancer therapy requiring additional studies. OSF REGISTRATION: https://doi.org/10.17605/OSF.IO/WPHN5 [Figure: see text].

A Combination of Magnoflorine and Spinosin Improves the Antidepressant effects on CUMS Mouse Model.

BACKGROUND: Depression is a common neuropsychiatric disease. As a famous traditional Chinese medicine with significant anti-depressive and sleep-promoting effects, Ziziphi Spinosae Semen (ZSS) has attracted the attention of many researchers. Although it is well known that Magnoflorine (MAG) and Spinosin (SPI) were the main active components isolated from ZSS, there is a lack of research on the combined treatment of depression with these two ingredients. METHODS: The shaking bottle method was used to simulate the human environment for detecting the changes in oil-water partition coefficient before and after the drug combination. Cell viability was evaluated by the MTT assay. To establish a mouse model of depression and insomnia by CUMS method, and then to explore the effect of combined administration of MAG and SPI on depression in CUMS model by observing behavior and analyzing pharmacokinetics. RESULTS: The change in LogP values affected the lipid solubility of MAG and increased the water solubility of SPI, allowing them to penetrate more easily through the blood-brain barrier into the brain. Compared with the model group, MAG-SPI with a concentration of 60 µM significantly increased cell survival rate. In both the TST and FST experiments, the mice showed a decrease in immobilization time. Pharmacokinetic results showed that the pharmacokinetic parameters, Cmax and AUC of MAG and SPI, were increased in the case of combination, which resulted in enhancement of their relative bioavailability and improvement of in vivo effects. CONCLUSIONS: The present study demonstrated that a combination of MAG and SPI had a synergistic antidepressant effect in CUMS mouse model.

Preclinical development and clinical studies of targeted JAK/STAT combined Anti-PD-1/PD-L1 therapy.

Programmed cell death protein 1 (PD-1) binds to its ligand to help tumours evade the immune system and promote tumour progression. Although anti-PD-1/PD-L1 therapies show powerful effects in some patients, most patients are unable to benefit from this treatment due to treatment resistance. Therefore, it is important to overcome tumour resistance to PD-1/PD-L1 blockade. There is substantial evidence suggesting that the JAK/STAT signalling pathway plays a significant role in PD-1/PD-L1 expression and anti-PD-1/PD-L1 treatment. Herein, we describe the effects of the JAK/STAT signalling pathway on PD-1/PD-L1. Subsequently, the relationship between molecular mutations in the JAK/STAT signalling pathway and immune resistance was analysed. Finally, the latest advancements in drugs targeting the JAK/STAT pathway combined with PD1/PD-L1 inhibitors are summarised.

A promising pipeline of preclinical drug candidates for leishmaniasis and chronic Chagas' disease.

The drug discovery pipeline for leishmaniasis and trypanosomiasis has been filling with novel chemical entities with known mechanisms of action. González et al. and Braillard et al. report a cytochrome bc1 complex inhibitor as another promising preclinical candidate for visceral leishmaniasis (VL) and, in combination with benznidazole, for chronic Chagas' disease (CCD).

Identification of differential biological activity and synergy between the PARP inhibitor rucaparib and its major metabolite.

The (poly)pharmacology of drug metabolites is seldom comprehensively characterized in drug discovery. However, some drug metabolites can reach high plasma concentrations and display in vivo activity. Here, we use computational and experimental methods to comprehensively characterize the kinase polypharmacology of M324, the major metabolite of the PARP1 inhibitor rucaparib. We demonstrate that M324 displays unique PLK2 inhibition at clinical concentrations. This kinase activity could have implications for the efficacy and safety of rucaparib and therefore warrants further clinical investigation. Importantly, we identify synergy between the drug and the metabolite in prostate cancer models and a complete reduction of α-synuclein accumulation in Parkinson's disease models. These activities could be harnessed in the clinic or open new drug discovery opportunities. The study reported here highlights the importance of characterizing the activity of drug metabolites to comprehensively understand drug response in the clinic and exploit our current drug arsenal in precision medicine.