Drug repositioning and repurposing: terminology and definitions in literature

GEFA: Early Fusion Approach in Drug-Target Affinity Prediction

Predicting the interaction between a compound and a target is crucial for rapid drug repurposing. Deep learning has been successfully applied in drug-target affinity (DTA)problem. However, previous deep learning-based methods ignore modeling the direct interactions between drug and protein residues. This would lead to inaccurate learning of target representation which may change due to the drug binding effects. In addition, previous DTA methods learn protein representation solely based on a small number of protein sequences in DTA datasets while neglecting the use of proteins outside of the DTA datasets. We propose GEFA (Graph Early Fusion Affinity), a novel graph-in-graph neural network with attention mechanism to address the changes in target representation because of the binding effects. Specifically, a drug is modeled as a graph of atoms, which then serves as a node in a larger graph of residues-drug complex. The resulting model is an expressive deep nested graph neural network. We also use pre-trained protein representation powered by the recent effort of learning contextualized protein representation. The experiments are conducted under different settings to evaluate scenarios such as novel drugs or targets. The results demonstrate the effectiveness of the pre-trained protein embedding and the advantages our GEFA in modeling the nested graph for drug-target interaction.

Repurposing of Medicines in the EU: Launch of a Pilot Framework

Repurposing of authorised medicines has been under discussion for a long time. Drug repurposing is the process of identifying a new use for an existing medicine in an indication outside the scope of the original approved indication. Indeed, the COVID-19 health crisis has brought the concept to the frontline by proving the usefulness of this practise in favour of patients for an early access to treatment. Under the umbrella of the Pharmaceutical Committee and as a result of the discussions at the European Commission Expert Group on Safe and Timely Access to Medicines for Patients (STAMP) a virtual Repurposing Observatory Group (RepOG) was set up in 2019 to define and test the practical aspects of a pilot project thought to provide support to “not-for-profit” stakeholders generating or gathering data for a new therapeutic use for an authorised medicine. The group's initial plan was impacted by the outbreak of the SARS-CoV-2 pandemic and the launch of the pilot needed to be postponed. This article describes the progress and the activities conducted by the group during this past and yet extraordinary 2020–2021 to keep the project alive and explores on the background of this topic together with the obvious opportunities this health crisis has brought up in terms of repurposing of medicines.

Tackling the Behavior of Cancer Cells: Molecular Bases for Repurposing Antipsychotic Drugs in the Treatment of Glioblastoma

Glioblastoma (GBM) is associated with a very dismal prognosis, and current therapeutic options still retain an overall unsatisfactorily efficacy in clinical practice. Therefore, novel therapeutic approaches and effective medications are highly needed. Since the development of new drugs is an extremely long, complex and expensive process, researchers and clinicians are increasingly considering drug repositioning/repurposing as a valid alternative to the standard research process. Drug repurposing is also under active investigation in GBM therapy, since a wide range of noncancer and cancer therapeutics have been proposed or investigated in clinical trials. Among these, a remarkable role is played by the antipsychotic drugs, thanks to some still partially unexplored, interesting features of these agents. Indeed, antipsychotic drugs have been described to interfere at variable incisiveness with most hallmarks of cancer. In this review, we analyze the effects of antipsychotics in oncology and how these drugs can interfere with the hallmarks of cancer in GBM. Overall, according to available evidence, mostly at the preclinical level, it is possible to speculate that repurposing of antipsychotics in GBM therapy might contribute to providing potentially effective and inexpensive therapies for patients with this disease.

Evaluating the performance of drug-repurposing technologies

Drug-repurposing technologies are growing in number and maturing. However, comparisons to each other and to reality are hindered because of a lack of consensus with respect to performance evaluation. Such comparability is necessary to determine scientific merit and to ensure that only meaningful predictions from repurposing technologies carry through to further validation and eventual patient use. Here, we review and compare performance evaluation measures for these technologies using version 2 of our shotgun repurposing Computational Analysis of Novel Drug Opportunities (CANDO) platform to illustrate their benefits, drawbacks, and limitations. Understanding and using different performance evaluation metrics ensures robust cross-platform comparability, enabling us to continue to strive toward optimal repurposing by decreasing the time and cost of drug discovery and development.

Levofloxacin exerts broad-spectrum anticancer activity via regulation of THBS1, LAPTM5, SRD5A3, MFAP5 and P4HA1

One cost-effective way for identifying novel cancer therapeutics is in the repositioning of available drugs for which current therapies are inadequate. Levofloxacin prevents DNA duplication in bacteria by inhibiting the activity of DNA helicase. As eukaryotic cells have similar intracellular biologic characteristics as prokaryotic cells, we speculate that antibiotics inhibiting DNA duplication in bacteria may also affect the survival of cancer cells. Here we report that levofloxacin significantly inhibited the proliferation and clone formation of cancer cells and xenograft tumor growth through cell cycle arrest at G2/M and by enhancing apoptosis. Levofloxacin significantly altered gene expression in a direction favoring anticancer activity. THBS1 and LAPTM5 were dose-dependently upregulated whereas SRD5A3, MFAP5 and P4HA1 were downregulated. Pathway analysis revealed that levofloxacin significantly regulated canonical oncogenic pathways. Specific network enrichment included a MAPK/apoptosis/cytokine-cytokine receptor interaction pathway network that associates with cell growth, differentiation, cell death, angiogenesis and development and repair processes and a bladder cancer/P53 signaling pathway network mediating the inhibition of angiogenesis and metastasis. THBS1 overlapped in 16 of the 22 enriched apoptotic pathways and the 2 pathways in the bladder cancer/P53 signaling pathway network. P4HA1 enriched in 7 of the top 10 molecular functions regulated by differential downregulated genes. Our results indicate that levofloxacin has broad-spectrum anticancer activity with the potential to benefit cancer patients already treated or requiring prophylaxis for an infectious syndrome. The efficacy we find with levofloxacin may provide insight into the discovery and the design of novel less toxic anticancer drugs.

Benzimidazoles induce concurrent apoptosis and pyroptosis of human glioblastoma cells via arresting cell cycle

Glioblastoma multiforme (GBM) is the most malignant and lethal primary brain tumor in adults accounting for about 50% of all gliomas. The only treatment available for GBM is the drug temozolomide, which unfortunately has frequent drug resistance issue. By analyzing the hub genes of GBM via weighted gene co-expression network analysis (WGCNA) of the cancer genome atlas (TCGA) dataset, and using the connectivity map (CMAP) platform for drug repurposing, we found that multiple azole compounds had potential anti-GBM activity. When their anti-GBM activity was examined, however, only three benzimidazole compounds, i.e. flubendazole, mebendazole and fenbendazole, potently and dose-dependently inhibited proliferation of U87 and U251 cells with IC₅₀ values below 0.26 μM. Benzimidazoles (0.125-0.5 μM) dose-dependently suppressed DNA synthesis, cell migration and invasion, and regulated the expression of key epithelial-mesenchymal transition (EMT) markers in U87 and U251 cells. Benzimidazoles treatment also dose-dependently induced the GBM cell cycle arrest at the G₂/M phase via the P53/P21/cyclin B1 pathway. Furthermore, the drugs triggered pyroptosis of GBM cells through the NF-κB/NLRP3/GSDMD pathway, and might also concurrently induced mitochondria-dependent apoptosis. In a nude mouse U87 cell xenograft model, administration of flubendazole (12.5, 25, and 50 mg · kg^-1 · d^-1, i.p, for 3 weeks) dose-dependently suppressed the tumor growth without obvious adverse effects. Taken together, our results demonstrated that benzimidazoles might be promising candidates for the treatment of GBM.

Drug Repurposing: Deferasirox Inhibits the Anti-Apoptotic Activity of Mcl-1

Introduction

With the aim of repositioning commercially available drugs for the inhibition of the anti-apoptotic myeloid cell leukemia protein, Mcl-1, implied in various cancers, five molecules, highlighted from a published theoretical screening, were selected to experimentally validate their affinity toward Mcl-1.

Results

A detailed NMR study revealed that only two of the five tested drugs, Torsemide and Deferasirox, interacted with Mcl-1. NMR data analysis allowed the complete characterization of the binding mode of both drugs to Mcl-1, including the estimation of their affinity for Mcl-1. Biological assays evidenced that the biological activity of Torsemide was lower as compared to the Deferasirox, which was able to efficiently and selectively inhibit the anti-apoptotic activity of Mcl-1. Finally, docking and molecular dynamics led to a 3D model for the Deferasirox:Mcl-1 complex and revealed the positioning of the drug in the Mcl-1 P2/P3 pockets as well as almost all synthetic Mcl-1 inhibitors. Interestingly, contrary to known synthetic Mcl-1 inhibitors which interact through Arg263, Deferasirox, establishes a salt bridge with Lys234.

Conclusion

Deferasirox could be a potential candidate for drug repositioning as Mcl-1 inhibitor.

The extent to which off-patent registered prescription medicines are used for off-label indications in Australia: A scoping review

AIM

The aim of this scoping review was to determine the extent of off-patent prescription medicine use beyond registered indications in various Australian clinical settings.

METHOD

The review followed the Joanna Briggs Institute approach and reported using PRISMA Extension for Scoping Reviews. Online databases were used to identify published literature about off-patent registered prescription medicines used for off-label indications in Australian public hospital, community and primary healthcare settings. In addition, empirical data from the Queensland and the South Australian state-wide medicine formularies were screened for the same medication/off-label indication dyads identified in the literature, and other locally approved uses.

RESULTS

Overall, fourteen studies were included, conducted in public hospitals (n = 11), palliative care units (n = 2) and the community setting (n = 1). There were 213 reports extracted from the literature describing off-patent registered prescription medicines used for off-label indications, representing 128 unique medication/off-label indication dyads and 32 different medicines. Of these, just five medication/off-label indication dyads were approved for use on both the Queensland and South Australian state-wide medicine formularies, with 12 others only approved for use in Queensland and 16 others only approved for use in South Australia. Further examination of these state-wide formularies demonstrated that the use of off-patent registered prescription medicines beyond registered indications is more extensive than has been reported to date in the literature. There were 28 additional medication/off-label indication dyads approved on the Queensland state-wide medicine formulary and 14 such examples approved for use in South Australia. Of these, just two medication/off-label indication dyads were approved for use on both formularies.

CONCLUSION

The extent to which off-patent registered prescription medicines have been repurposed in clinical settings for off-label indications in Australia is greater than previously reported in the literature. Usage and funded availability of certain medication/off-label indication dyads, varies across Australia. These results further expose the two tiered system of medicines regulation in Australia, and its impact on equity of access to medicines. Further research is required to support policy change to encourage submission of registration updates for off-patent prescription medicines.

Neuroinflammation and oxidative stress in schizophrenia: are these opportunities for repurposing?

Purpose: To summarize the main findings on the subject of neuroinflammation and oxidative stress in patients with Schizophrenia (SCZ).Methods: A narrative review of all the relevant papers known to the authors was conducted.Results: SCZ is a chronic, debilitating, neuropsychiatric disorder associated with an immense and adverse impact on both the patient and the caregiver, and impairs the overall quality of life. The current modality of treatment involves the use of antipsychotics to balance the disturbances in the neurotransmitters in the dopaminergic and serotonin pathways in the brain, which have a role to play in SCZ. Contemporary management of SCZ focuses mainly on symptomatic control due to the lack of effective curative treatments.Despite the optimum use of antipsychotics, there is a considerable proportion of the patient population who are poor responders. This has necessitated the exploration of new etiopathologies in order to evolve new modalities of treatment. This narrative review, conducted over a period of 3 months, throws light on the large-scale evidence pointing toward neuroinflammation and oxidative stress as key etiopathological markers that merit further consideration in SCZ, and may even be the basis for devising novel pharmacotherapies for SCZ.Conclusions: This review discusses the various plausible hypotheses, viz., cytokine hypothesis of peripheral inflammation, acute-phase reactants in SCZ, microglial hypothesis of central inflammation, neurogenesis in relation to neuroinflammation, and oxidative stress in SCZ. It also highlights the many opportunities available for repurposing already marketed drugs with anti-inflammatory and antioxidant properties with a view to devising more effective and comprehensive therapies to manage SCZ.

Repurposing drugs in autophagy for the treatment of cancer: From bench to bedside

Autophagy is a multistep degradation pathway involving the lysosome, which supports nutrient reuse and metabolic balance, and has been implicated as a process that regulates cancer genesis and development. Targeting tumors by regulating autophagy has become a therapeutic strategy of interest. Drugs with other indications can have antitumor activity by modulating autophagy, providing a shortcut to developing novel antitumor drugs (i.e., drug repurposing/repositioning), as successfully performed for chloroquine (CQ); an increasing number of repurposed drugs have since advanced into clinical trials. In this review, we describe the application of different drug-repurposing approaches in autophagy for the treatment of cancer and focus on repurposing drugs that target autophagy to treat malignant neoplasms.

Drug Repurposing for Rare Diseases: A Role for Academia

Background: The European Commission highlights in its Pharmaceutical Strategy the role of academic researchers in drug repurposing, especially in the development of orphan medicinal products (OMPs). This study summarizes the contribution of academia over the last 5 years to registered repurposed OMPs and describes barriers to success, based upon three real world cases.

Methods: OMPs granted marketing authorization between January 2016 and December 2020 were reviewed for repurposing and whether the idea originated from academia or industry. Three cases of drug repurposing were selected from different therapeutic areas and stages of development to identify obstacles to success.

Results: Thirteen of the 68 OMPs were the result of drug repurposing. In three OMPs, there were two developments such as both a new indication and a modified application. In total, twelve developments originated from academia and four from industry. The three cases showed as barriers to success: lack of outlook for sufficient return of investments (abatacept), lack of regulatory alignment and timing of interaction between healthcare professionals and regulators (etidronate), failure to register an old drug for a fair price, resulting in commercialization as a high priced orphan drug (mexiletine).

Conclusion: While the majority of repurposed OMPs originates in academia, a gap exists between healthcare professionals, regulators and industry. Future strategies should aim to overcome these hurdles leading to more patient benefit through sustainable access of repurposed drugs. Potential solutions include improved regulatory and reimbursement knowledge by academia and the right for regulators to integrate new effectiveness data into product labels.

Parasitology and One Health-Perspectives on Africa and Beyond

This concept paper reviews issues pertaining to parasitic and vector-borne infections, of humans, animals, or both, of topical relevance to the African continent as well as to neighbouring and interconnected geographies. This analysis is carried out through the "One Health" lens, being mindful of the central role of agriculture and livestock keeping in Africa's sustainable development. The possible agricultural transformation that the continent may undergo to fulfil the rising demand for animal protein of its growing population, coupled with the ongoing climate changes, may lead to potentially enhanced interactions among humans, domesticated and wild animals, in a fast-changing environment. In this view, tackling parasitic conditions of livestock can prove being multidimensionally beneficial by improving animal health as well as communities' food security, livelihood and public health. Accordingly, the value of applying the One Health approach to drug discovery and development in the fight against parasitic neglected tropical diseases and zoonoses, is also underscored. Overall, this article upholds the adoption of a holistic, global, interdisciplinary, multisectoral, harmonised and forward-looking outlook, encompassing both life and social sciences, when dealing with parasitic conditions of humans and animals, in Africa and beyond, in COVID-19 times and further.

Repurposed drugs as adjunctive treatments for mania and bipolar depression: A meta-review and critical appraisal of meta-analyses of randomized placebo-controlled trials

Several drugs previously tested in clinical trials and approved for different indications have been repurposed for bipolar disorder. We carried out a systematic meta-review of meta-analyses of randomized placebo-controlled trials investigating repurposed drugs as adjunctive treatments for mania and bipolar depression. We performed a critical appraisal using 'A MeaSurement Tool to Assess systematic Reviews' Version 2 (AMSTAR 2). We synthesized results on efficacy, tolerability, and safety, assessing evidence quality according to the 'Grading of Recommendations, Assessment, Development and Evaluations' (GRADE) approach. Our systematic search identified nine eligible studies investigating 12 drugs, four for mania and eight for bipolar depression. The quality of reporting was heterogeneous according to AMSTAR 2. In mania, allopurinol (for symptoms reduction and remission at 4-8 weeks) and tamoxifen (for response and symptoms reduction at 4-6 weeks) showed higher efficacy than placebo, with low and very low quality of evidence, respectively. Concerning bipolar depression, modafinil/armodafinil (for response, remission, and symptoms reduction at 6-8 weeks) and pramipexole (for response and symptoms reduction at 6 weeks) were superior to placebo, despite the low quality of evidence. Results on the efficacy of celecoxib and N-acetylcysteine were of low quality and limited to certain outcomes. Overall, the lack of evidence of high and moderate quality does not allow us to draw firm conclusions on the clinical utility of repurposed drugs as adjunctive treatments for mania and bipolar depression, highlighting the need for additional research.

Ethical Tenets of PRN Medicines Management in Healthcare Settings: A Clinical Perspective

Prescription and administration of pro re nata (PRN) medications has remained a poorly discussed area of the international literature regarding ethical tenets influencing this type of medication practice. In this commentary, ethical tenets of PRN medicines management from the clinical perspective based on available international literature and published research have been discussed. Three categories were developed by the authors for summarising review findings as follows: 'benefiting the patient', 'making well-informed decision', and 'follow up assessment' as pre-intervention, through-intervention, and post-intervention aspects, respectively. PRN medicines management is mainly intertwined with the ethical tenets of beneficence, nonmaleficence, dignity, autonomy, justice, informed consent, and error disclosure. It is a dynamic process and needs close collaboration between healthcare professionals especially nurses and patients to prevent unethical practice.

The use of real-world data in drug repurposing

Drug repurposing, or repositioning, is to identify new uses for existing drugs. Significantly reducing the costs and time-to-market of a medication, drug repurposing has been an alternative tool to accelerate drug development process. On the other hand, 'real world data (RWD)' has been also increasingly used to support drug development process owing to its better representing actual pattern of drug treatment and outcome in real world. In the healthcare domain, RWD refers to data collected from sources other than traditional clinical trials; for example, in electronic health records or claims and billing data. With the enactment of the 21st Century Cures Act, which encourages the use of RWD in drug development and repurposing as well, such increasing trend in RWD use will be expedited. In this context, this review provides an overview of recent progresses in the area of drug repurposing where RWD was used by firstly introducing the increasing trend and regulatory change in the use of RWD in drug development, secondly reviewing published works using RWD in drug repurposing, classifying them in the repurposing strategy, and lastly addressing limitations and advantages of RWDs.

Results of the Seventh Scientific Workshop of ECCO: Precision Medicine in IBD-What, Why, and How

Many diseases that affect modern humans fall in the category of complex diseases, thus called because they result from a combination of multiple aetiological and pathogenic factors. Regardless of the organ or system affected, complex diseases present major challenges in diagnosis, classification, and management. Current forms of therapy are usually applied in an indiscriminate fashion based on clinical information, but even the most advanced drugs only benefit a limited number of patients and to a variable and unpredictable degree. This 'one measure does not fit all' situation has spurred the notion that therapy for complex disease should be tailored to individual patients or groups of patients, giving rise to the notion of 'precision medicine' [PM]. Inflammatory bowel disease [IBD] is a prototypical complex disease where the need for PM has become increasingly clear. This prompted the European Crohn's and Colitis Organisation to focus the Seventh Scientific Workshop on this emerging theme. The articles in this special issue of the Journal address the various complementary aspects of PM in IBD, including what PM is; why it is needed and how it can be used; how PM can contribute to prediction and prevention of IBD; how IBD PM can aid in prognosis and improve response to therapy; and the challenges and future directions of PM in IBD. This first article of this series is structured on three simple concepts [what, why, and how] and addresses the definition of PM, discusses the rationale for the need of PM in IBD, and outlines the methodology required to implement PM in IBD in a correct and clinically meaningful way.

SANE: A sequence combined attentive network embedding model for COVID-19 drug repositioning

The COVID-19 has now spread all over the world and causes a huge burden for public health and world economy. Drug repositioning has become a promising treatment strategy in COVID-19 crisis because it can shorten drug development process, reduce pharmaceutical costs and reposition approval drugs. Existing computational methods only focus on single information, such as drug and virus similarity or drug-virus network feature, which is not sufficient to predict potential drugs. In this paper, a sequence combined attentive network embedding model SANE is proposed for identifying drugs based on sequence features and network features. On the one hand, drug SMILES and virus sequence features are extracted by encoder-decoder in SANE as node initial embedding in drug-virus network. On the other hand, SANE obtains fields for each node by attention-based Depth-First-Search (DFS) to reduce noises and improve efficiency in representation learning and adopts a bottom-up aggregation strategy to learn node network representation from selected fields. Finally, a forward neural network is used for classifying. Experiment results show that SANE has achieved the performance with 81.98% accuracy and 0.8961 AUC value and outperformed state-of-the-art baselines. Further case study on COVID-19 indicates that SANE has a strong predictive ability since 25 of the top 40 (62.5%) drugs are verified by valuable dataset and literatures. Therefore, SANE is powerful to reposition drugs for COVID-19 and provides a new perspective for drug repositioning.

Development of a core evaluation framework of value-added medicines: report 1 on methodology and findings

Background

Medicines that are based on known molecules and are further developed to address healthcare needs and deliver relevant improvement for patients, healthcare professionals and/or payers are called value-added medicines (VAMs). The evaluation process of VAMs is heterogeneous across countries, and it has been primarily designed for originator pharmaceuticals with confirmatory evidence collected alongside pivotal clinical trials. There is a mismatch between evidence requirements by public decision-makers and evidence generated by manufacturers of VAMs. Our objective was to develop a core evaluation framework for VAMs.

Methods

Potential benefits offered by VAMs were collected through a systematic literature review and allocated to separate domains in an iterative process. The draft list of domains and their applicability were validated during two consecutive virtual workshops by health policy experts representing countries with different economic statuses, geographical and decision-making contexts.

Results

Based on 158 extracted studies, the final consensus on the evaluation framework resulted in 11 value domains in 5 main clusters, including unmet medical needs, health gain (measured by health care professionals), patient-reported outcomes, burden on households, and burden on the health care system.

Conclusions

The proposed framework could reduce the heterogeneity in value assessment processes across countries and create incentives for manufacturers to invest in incremental innovation. However, some domains may not be equally relevant or accepted in all countries, therefore the core framework needs thorough adaptation in specific jurisdictions.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12962-021-00311-6.

Dexamethasone Sensitizes Cancer Stem Cells to Gemcitabine and 5-Fluorouracil by Increasing Reactive Oxygen Species Production through NRF2 Reduction

Cancer stem cells (CSCs) have high tumor-initiating capacity and are resistant to chemotherapeutic reagents; thus eliminating CSCs is essential to improving the prognosis. Recently, we reported that dexamethasone increases the effects of gemcitabine on pancreatic CSCs; however, the mechanism involved remains to be fully elucidated. In this study, we explored the role of reactive oxygen species (ROS) in the dexamethasone-induced chemosensitization of CSCs. Dexamethasone increased the growth-inhibitory effects of gemcitabine and 5-fluorouracil, whereas N-acetyl-cysteine, a ROS scavenger, abolished this effect. Although dexamethasone alone did not increase ROS levels, dexamethasone promoted the increase in ROS levels induced by gemcitabine and 5-fluorouracil. Dexamethasone treatment reduced the expression of NRF2, a key regulator of antioxidant responses, which was attenuated by siRNA-mediated knockdown of the glucocorticoid receptor. Furthermore, brusatol, a suppressor of NRF2, sensitized pancreatic CSCs to gemcitabine and 5-fluorouracil. Of note, essentially, the same mechanism was functional in ovarian and colon CSCs treated by the combination of dexamethasone and chemotherapeutic agents. Our study suggests that dexamethasone can sensitize CSCs to chemotherapeutic agents by promoting chemotherapy-induced ROS production through suppressing NRF2 expression.

Deep fusion learning facilitates anatomical therapeutic chemical recognition in drug repurposing and discovery

The advent of large-scale biomedical data and computational algorithms provides new opportunities for drug repurposing and discovery. It is of great interest to find an appropriate data representation and modeling method to facilitate these studies. The anatomical therapeutic chemical (ATC) classification system, proposed by the World Health Organization (WHO), is an essential source of information for drug repurposing and discovery. Besides, computational methods are applied to predict drug ATC classification. We conducted a systematic review of ATC computational prediction studies and revealed the differences in data sets, data representation, algorithm approaches, and evaluation metrics. We then proposed a deep fusion learning (DFL) framework to optimize the ATC prediction model, namely DeepATC. The methods based on graph convolutional network, inferring biological network and multimodel attentive fusion network were applied in DeepATC to extract the molecular topological information and low-dimensional representation from the molecular graph and heterogeneous biological networks. The results indicated that DeepATC achieved superior model performance with area under the curve (AUC) value at 0.968. Furthermore, the DFL framework was performed for the transcriptome data-based ATC prediction, as well as another independent task that is significantly relevant to drug discovery, namely drug-target interaction. The DFL-based model achieved excellent performance in the above-extended validation task, suggesting that the idea of aggregating the heterogeneous biological network and node's (molecule or protein) self-topological features will bring inspiration for broader drug repurposing and discovery research.

Drug Repurposing to Identify a Synergistic High-Order Drug Combination to Treat Sunitinib-Resistant Renal Cell Carcinoma

Simple Summary

In this study, drug combination screening was used to design a multidrug combination consisting of repurposed drugs to treat sunitinib-resistant clear cell renal cell carcinoma. In the frame of this project, the multidrug combination has been optimized and validated and an insight into the mechanism of action is given. The multidrug combinations significantly altered the transcription of genes related to apoptosis and metabolic pathways. Further analysis of the metabolism revealed strong upregulation of the presence of sphingolipids after multidrug combination treatment. Final evaluation for translation of the multidrug combination in ex vivo organoid-like cultures demonstrated significant anti-cancer efficacy.

Abstract

Repurposed drugs have been evaluated for the management of clear cell renal cell carcinoma (ccRCC), but only a few have influenced the overall survival of patients with advanced disease. To combine repurposed non-oncology with oncological drugs, we applied our validated phenotypic method, which consisted of a reduced experimental part and data modeling. A synergistic optimized multidrug combination (ODC) was identified to significantly reduce the energy levels in cancer remaining inactive in non-cancerous cells. The ODC consisted of Rapta-C, erlotinib, metformin and parthenolide and low doses. Molecular and functional analysis of ODC revealed a loss of adhesiveness and induction of apoptosis. Gene-expression network analysis displayed significant alterations in the cellular metabolism, confirmed by LC-MS based metabolomic analysis, highlighting significant changes in the lipid classes. We used heterotypic in vitro 3D co-cultures and ex vivo organoids to validate the activity of the ODC, maintaining an efficacy of over 70%. Our results show that repurposed drugs can be combined to target cancer cells selectively with prominent activity. The strong impact on cell adherence and metabolism indicates a favorable mechanism of action of the ODC to treat ccRCC.

Drug Repurposing of Pantoprazole and Vitamin C Targeting Tumor Microenvironment Conditions Improves Anticancer Effect in Metastatic Castration-Resistant Prostate Cancer

The effective and economical therapeutic strategy for metastatic castration-resistant prostate cancer (mCRPC) is still requested from patients, who are not available for Lu-177 or Ra-223 treatment. Drug repurposing as a cost-effective and time-saving alternative to traditional drug development has been increasingly discussed. Proton pump inhibitors (PPIs) such as pantroprazole, which are commonly used as antacids, have also been shown to be effective in cancer chemoprevention via induction of apoptosis in multiple cancer cell lines. Vitamin C is an essential micronutrient for human body, has been proposed as a potential anti-cancer agent. In this context, have we investigated the combination of vitamin C and pantoprazole for the management of metastatic castration-resistant prostate cancer (mCRPC). Six chosen human adenocarcinoma cell lines were used to investigate the influence of pantoprazole on the microenvironment of cancer cells (extracellular pH and production of exosomes). Tumor growth and tumor 18F-FDG uptake in PC3 xenografts were analyzed following varied treatment. Our in vitro Results have suggested that pantoprazole enhanced the cytotoxic activity of vitamin C by regulating pH values and production of exosomes in cancer cells. Moreover, the synergistic effect of pantoprazole and vitamin C was pH-dependent since pantoprazole was more effective at a slightly acidic pH. In vivo, the combined treatment using pantoprazole and vitamin C produced better therapeutic outcomes than treatment with vitamin C or pantoprazole alone, as demonstrated via tumor growth and uptake of 18F-FDG. Therefore, we suggest that pantoprazole combined with vitamin C could be as a possible strategy to manage mCRPC.

Spectrum of deep learning algorithms in drug discovery

Deep learning (DL) algorithms are a subset of machine learning algorithms with the aim of modeling complex mapping between a set of elements and their classes. In parallel to the advance in revealing the molecular bases of diseases, a notable innovation has been undertaken to apply DL in data/libraries management, reaction optimizations, differentiating uncertainties, molecule constructions, creating metrics from qualitative results, and prediction of structures or interactions. From source identification to lead discovery and medicinal chemistry of the drug candidate, drug delivery, and modification, the challenges can be subjected to artificial intelligence algorithms to aid in the generation and interpretation of data. Discovery and design approach, both demand automation, large data management and data fusion by the advance in high-throughput mode. The application of DL can accelerate the exploration of drug mechanisms, finding novel indications for existing drugs (drug repositioning), drug development, and preclinical and clinical studies. The impact of DL in the workflow of drug discovery, design, and their complementary tools are highlighted in this review. Additionally, the type of DL algorithms used for this purpose, and their pros and cons along with the dominant directions of future research are presented.

Proteomics and Drug Repurposing in CLL towards Precision Medicine

Simple Summary

Despite continued efforts, the current status of knowledge in CLL molecular pathobiology, diagnosis, prognosis and treatment remains elusive and imprecise. Proteomics approaches combined with advanced bioinformatics and drug repurposing promise to shed light on the complex proteome heterogeneity of CLL patients and mitigate, improve, or even eliminate the knowledge stagnation. In relation to this concept, this review presents a brief overview of all the available proteomics and drug repurposing studies in CLL and suggests the way such studies can be exploited to find effective therapeutic options combined with drug repurposing strategies to adopt and accost a more “precision medicine” spectrum.

Abstract

CLL is a hematological malignancy considered as the most frequent lymphoproliferative disease in the western world. It is characterized by high molecular heterogeneity and despite the available therapeutic options, there are many patient subgroups showing the insufficient effectiveness of disease treatment. The challenge is to investigate the individual molecular characteristics and heterogeneity of these patients. Proteomics analysis is a powerful approach that monitors the constant state of flux operators of genetic information and can unravel the proteome heterogeneity and rewiring into protein pathways in CLL patients. This review essences all the available proteomics studies in CLL and suggests the way these studies can be exploited to find effective therapeutic options combined with drug repurposing approaches. Drug repurposing utilizes all the existing knowledge of the safety and efficacy of FDA-approved or investigational drugs and anticipates drug alignment to crucial CLL therapeutic targets, leading to a better disease outcome. The drug repurposing studies in CLL are also discussed in this review. The next goal involves the integration of proteomics-based drug repurposing in precision medicine, as well as the application of this procedure into clinical practice to predict the most appropriate drugs combination that could ensure therapy and the long-term survival of each CLL patient.

Current status and future prospects of drug-target interaction prediction

Drug-target interaction prediction is important for drug development and drug repurposing. Many computational methods have been proposed for drug-target interaction prediction due to their potential to the time and cost reduction. In this review, we introduce the molecular docking and machine learning-based methods, which have been widely applied to drug-target interaction prediction. Particularly, machine learning-based methods are divided into different types according to the data processing form and task type. For each type of method, we provide a specific description and propose some solutions to improve its capability. The knowledge of heterogeneous network and learning to rank are also summarized in this review. As far as we know, this is the first comprehensive review that summarizes the knowledge of heterogeneous network and learning to rank in the drug-target interaction prediction. Moreover, we propose three aspects that can be explored in depth for future research.

Inhibition of the Human Hsc70 System by Small Ligands as a Potential Anticancer Approach

Simple Summary

High levels of Heat shock proteins (Hsps) in specific cancers are usually linked to a poor prognosis, tumor progression, invasiveness, and resistance to treatment. Chaperone inhibition could therefore be toxic for cancer cells due to their high dependence on chaperone activity to survive. This study shows the potential to repurpose the small chemical compound pinaverium bromide, currently used to treat functional gastrointestinal disorders, as a possible antitumor drug since it displays a marked toxicity against two melanoma cell lines without affecting the viability of fibroblast and primary melanocytes. This compound interacts with structural regions shared by representatives of the Hsp70 and Hsp110 families, inhibiting the substrate remodeling ability of the Hsp70 system in vitro and in a cellular context.

Abstract

Heat shock protein (Hsp) synthesis is upregulated in a wide range of cancers to provide the appropriate environment for tumor progression. The Hsp110 and Hsp70 families have been associated to cancer cell survival and resistance to chemotherapy. In this study, we explore the strategy of drug repurposing to find new Hsp70 and Hsp110 inhibitors that display toxicity against melanoma cancer cells. We found that the hits discovered using Apg2, a human representative of the Hsp110 family, as the initial target bind also to structural regions present in members of the Hsp70 family, and therefore inhibit the remodeling activity of the Hsp70 system. One of these compounds, the spasmolytic agent pinaverium bromide used for functional gastrointestinal disorders, inhibits the intracellular chaperone activity of the Hsp70 system and elicits its cytotoxic activity specifically in two melanoma cell lines by activating apoptosis. Docking and molecular dynamics simulations indicate that this compound interacts with regions located in the nucleotide-binding domain and the linker of the chaperones, modulating their ATPase activity. Thus, repurposing of pinaverium bromide for cancer treatment appears as a promising novel therapeutic approach.

Multiple-Molecule Drug Design Based on Systems Biology Approaches and Deep Neural Network to Mitigate Human Skin Aging

Human skin aging is affected by various biological signaling pathways, microenvironment factors and epigenetic regulations. With the increasing demand for cosmetics and pharmaceuticals to prevent or reverse skin aging year by year, designing multiple-molecule drugs for mitigating skin aging is indispensable. In this study, we developed strategies for systems medicine design based on systems biology methods and deep neural networks. We constructed the candidate genomewide genetic and epigenetic network (GWGEN) via big database mining. After doing systems modeling and applying system identification, system order detection and principle network projection methods with real time-profile microarray data, we could obtain core signaling pathways and identify essential biomarkers based on the skin aging molecular progression mechanisms. Afterwards, we trained a deep neural network of drug–target interaction in advance and applied it to predict the potential candidate drugs based on our identified biomarkers. To narrow down the candidate drugs, we designed two filters considering drug regulation ability and drug sensitivity. With the proposed systems medicine design procedure, we not only shed the light on the skin aging molecular progression mechanisms but also suggested two multiple-molecule drugs for mitigating human skin aging from young adulthood to middle age and middle age to old age, respectively.

Sildenafil in Combination Therapy against Cancer: A Literature Review

The concepts of drug repurposing and Sildenafil or blue pill are tightly linked over the years. Indeed, in addition to its initial clinical application as an anti-hypertensive drug in the pulmonary system, Sildenafil is also known for its beneficial effects in erectile dysfunction. Moreover, evidence has been accumulated to support its value in anti-cancer therapy, either alone or in combination with other clinically efficient chemotherapy drugs. In this review, we focused on the old and recent in vitro and in vivo studies demonstrating the cellular and molecular rationale for the application of Sildenafil in combination therapy in various types of cancer. We emphasized on the different molecular targets as well as the different signaling pathways involved in cancer cells. The pro-apoptotic effect of Sildenafil through nitric oxide (NO)/ phosphodiesterase type 5 (PDE5)-dependent manner seems to be one of the most common mechanisms. However, the activation of autophagy, as well as the modulation of the anti-tumor immunity, constitutes the other pathways triggered by Sildenafil. Overall, the studies converged to reveal the complexity of the anti-cancer potential of Sildenafil. Thus, through our review, we aimed to present an updated and simplified picture of such repurposing of Sildenafil in the field of oncology.

Antidepressants and Antipsychotic Agents as Repurposable Oncological Drug Candidates

Drug repurposing, also known as drug repositioning/reprofiling, is a relatively new strategy for the identification of alternative uses of well-known therapeutics that are outside the scope of their original medical indications. Such an approach might entail a number of advantages compared to standard de novo drug development, including less time needed to introduce the drug to the market, and lower costs. The group of compounds that could be considered as promising candidates for repurposing in oncology include the central nervous system drugs, especially selected antidepressant and antipsychotic agents. In this article, we provide an overview of some antidepressants (citalopram, fluoxetine, paroxetine, sertraline) and antipsychotics (chlorpromazine, pimozide, thioridazine, trifluoperazine) that have the potential to be repurposed as novel chemotherapeutics in cancer treatment, as they have been found to exhibit preventive and/or therapeutic action in cancer patients. Nevertheless, although drug repurposing seems to be an attractive strategy to search for oncological drugs, we would like to clearly indicate that it should not replace the search for new lead structures, but only complement de novo drug development.

Brief Overview of Approaches and Challenges in New Antibiotic Development: A Focus On Drug Repurposing

Drug repurposing, or identifying new uses for existing drugs, has emerged as an alternative to traditional drug discovery processes involving de novo synthesis. Drugs that are currently approved or under development for non-antibiotic indications may possess antibiotic properties, and therefore may have repurposing potential, either alone or in combination with an antibiotic. They might also serve as "antibiotic adjuvants" to enhance the activity of certain antibiotics.

Statin as a Potential Chemotherapeutic Agent: Current Updates as a Monotherapy, Combination Therapy, and Treatment for Anti-Cancer Drug Resistance

Cancer is incurable because progressive phenotypic and genotypic changes in cancer cells lead to resistance and recurrence. This indicates the need for the development of new drugs or alternative therapeutic strategies. The impediments associated with new drug discovery have necessitated drug repurposing (i.e., the use of old drugs for new therapeutic indications), which is an economical, safe, and efficacious approach as it is emerged from clinical drug development or may even be marketed with a well-established safety profile and optimal dosing. Statins are inhibitors of HMG-CoA reductase in cholesterol biosynthesis and are used in the treatment of hypercholesterolemia, atherosclerosis, and obesity. As cholesterol is linked to the initiation and progression of cancer, statins have been extensively used in cancer therapy with a concept of drug repurposing. Many studies including in vitro and in vivo have shown that statin has been used as monotherapy to inhibit cancer cell proliferation and induce apoptosis. Moreover, it has been used as a combination therapy to mediate synergistic action to overcome anti-cancer drug resistance as well. In this review, the recent explorations are done in vitro, in vivo, and clinical trials to address the action of statin either single or in combination with anti-cancer drugs to improve the chemotherapy of the cancers were discussed. Here, we discussed the emergence of statin as a lipid-lowering drug; its use to inhibit cancer cell proliferation and induction of apoptosis as a monotherapy; and its use in combination with anti-cancer drugs for its synergistic action to overcome anti-cancer drug resistance. Furthermore, we discuss the clinical trials of statins and the current possibilities and limitations of preclinical and clinical investigations.

Exploring new uses for existing drugs: innovative mechanisms to fund independent clinical research

BACKGROUND

Finding new therapeutic uses for existing medicines could lead to safe, affordable and timely new treatment options for patients with high medical needs. However, due to a lack of economic incentives, pharmaceutical developers are rarely interested to invest in research with approved medicines, especially when they are out of basic patent or regulatory protection. Consequently, potential new uses for these medicines are mainly studied in independent clinical trials initiated and led by researchers from academia, research institutes, or collaborative groups. Yet, additional financial support is needed to conduct expensive phase III clinical trials to confirm the results from exploratory research.

METHODS

In this study, scientific and grey literature was searched to identify and evaluate new mechanisms for funding clinical trials with repurposed medicines. Semi-structured interviews were conducted with 16 European stakeholders with expertise in clinical research, funding mechanisms and/or drug repurposing between November 2018 and February 2019 to consider the future perspectives of applying new funding mechanisms.

RESULTS

Traditional grant funding awarded by government and philanthropic organisations or companies is well known and widely implemented in all research fields. In contrast, only little research has focused on the application potential of newer mechanisms to fund independent clinical research, such as social impact bonds, crowdfunding or public-private partnerships. Interviewees stated that there is a substantial need for additional financial support in health research, especially in areas where there is limited commercial interest. However, the implementation of new funding mechanisms is facing several practical and financial challenges, such as a lack of expertise and guidelines, high transaction costs and difficulties to measure health outcomes. Furthermore, interviewees highlighted the need for increased collaboration and centralisation at a European and international level to make clinical research more efficient and reduce the need for additional funding.

CONCLUSIONS

New funding mechanisms to support clinical research may become more important in the future but the unresolved issues identified in the current study warrant further exploration.

Repositioning of Antiparasitic Drugs for Tumor Treatment

Drug repositioning is a strategy for identifying new antitumor drugs; this strategy allows existing and approved clinical drugs to be innovatively repurposed to treat tumors. Based on the similarities between parasitic diseases and cancer, recent studies aimed to investigate the efficacy of existing antiparasitic drugs in cancer. In this review, we selected two antihelminthic drugs (macrolides and benzimidazoles) and two antiprotozoal drugs (artemisinin and its derivatives, and quinolines) and summarized the research progresses made to date on the role of these drugs in cancer. Overall, these drugs regulate tumor growth via multiple targets, pathways, and modes of action. These antiparasitic drugs are good candidates for comprehensive, in-depth analyses of tumor occurrence and development. In-depth studies may improve the current tumor diagnoses and treatment regimens. However, for clinical application, current investigations are still insufficient, warranting more comprehensive analyses.

Multiscale Virtual Screening Optimization for Shotgun Drug Repurposing Using the CANDO Platform

Drug repurposing, the practice of utilizing existing drugs for novel clinical indications, has tremendous potential for improving human health outcomes and increasing therapeutic development efficiency. The goal of multi-disease multitarget drug repurposing, also known as shotgun drug repurposing, is to develop platforms that assess the therapeutic potential of each existing drug for every clinical indication. Our Computational Analysis of Novel Drug Opportunities (CANDO) platform for shotgun multitarget repurposing implements several pipelines for the large-scale modeling and simulation of interactions between comprehensive libraries of drugs/compounds and protein structures. In these pipelines, each drug is described by an interaction signature that is compared to all other signatures that are subsequently sorted and ranked based on similarity. Pipelines within the platform are benchmarked based on their ability to recover known drugs for all indications in our library, and predictions are generated based on the hypothesis that (novel) drugs with similar signatures may be repurposed for the same indication(s). The drug-protein interactions used to create the drug-proteome signatures may be determined by any screening or docking method, but the primary approach used thus far has been BANDOCK, our in-house bioanalytical or similarity docking protocol. In this study, we calculated drug-proteome interaction signatures using the publicly available molecular docking method Autodock Vina and created hybrid decision tree pipelines that combined our original bio- and chem-informatic approach with the goal of assessing and benchmarking their drug repurposing capabilities and performance. The hybrid decision tree pipeline outperformed the two docking-based pipelines from which it was synthesized, yielding an average indication accuracy of 13.3% at the top10 cutoff (the most stringent), relative to 10.9% and 7.1% for its constituent pipelines, and a random control accuracy of 2.2%. We demonstrate that docking-based virtual screening pipelines have unique performance characteristics and that the CANDO shotgun repurposing paradigm is not dependent on a specific docking method. Our results also provide further evidence that multiple CANDO pipelines can be synthesized to enhance drug repurposing predictive capability relative to their constituent pipelines. Overall, this study indicates that pipelines consisting of varied docking-based signature generation methods can capture unique and useful signals for accurate comparison of drug-proteome interaction signatures, leading to improvements in the benchmarking and predictive performance of the CANDO shotgun drug repurposing platform.

Lithium and Atypical Antipsychotics: The Possible WNT/β Pathway Target in Glaucoma

Glaucoma is a progressive neurodegenerative disease that represents the major cause of irreversible blindness. Recent findings have shown which oxidative stress, inflammation, and glutamatergic pathway have main roles in the causes of glaucoma. Lithium is the major commonly used drug for the therapy of chronic mental illness. Lithium therapeutic mechanisms remain complex, including several pathways and gene expression, such as neurotransmitter and receptors, circadian modulation, ion transport, and signal transduction processes. Recent studies have shown that the benefits of lithium extend beyond just the therapy of mood. Neuroprotection against excitotoxicity or brain damages are other actions of lithium. Moreover, recent findings have investigated the role of lithium in glaucoma. The combination of lithium and atypical antipsychotics (AAPs) has been the main common choice for the treatment of bipolar disorder. Due to the possible side effects gradually introduced in therapy. Currently, no studies have focused on the possible actions of AAPs in glaucoma. Recent studies have shown a down regulation of the WNT/β-catenin pathway in glaucoma, associated with the overactivation of the GSK-3β signaling. The WNT/β-catenin pathway is mainly associated with oxidative stress, inflammation and glutamatergic pathway. Lithium is correlated with upregulation the WNT/β-catenin pathway and downregulation of the GSK-3β activity. Thus, this review focuses on the possible actions of lithium and AAPs, as possible therapeutic strategies, on glaucoma and some of the presumed mechanisms by which these drugs provide their possible benefit properties through the WNT/β-catenin pathway.

Examination of the antiepileptic effects of valacyclovir using kindling mice- search for novel antiepileptic agents by drug repositioning using a large medical information database

Despite the availability of more than 20 clinical antiepileptic drugs, approximately 30% of patients with epilepsy do not respond to antiepileptic drug treatment. Therefore, it is important to develop antiepileptic products that function via novel mechanisms. In the present study, we evaluated data from one of the largest global databases to identify drugs with antiepileptic effects, and subsequently attempted to understand the effect of the combination of antiepileptic drugs and valacyclovir in epileptic seizures using a kindling model. To induce kindling in mice, pentylenetetrazol at a dose of 40 mg/kg was administered once every 48 h. Valacyclovir was orally administered 30 min before antiepileptic drug injection in kindled mice, and behavioral seizures were monitored for 20 min following pentylenetetrazol administration. Additionally, c-Fos expression in the hippocampal dentate gyrus was measured in kindled mice. Valacyclovir showed inhibitory effects on pentylenetetrazol-induced kindled seizures. In addition, simultaneous use of levetiracetam and valacyclovir caused more potent inhibition of seizure activity, and neither valproic acid nor diazepam augmented the anti-seizure effect in kindled mice. Furthermore, kindled mice showed increased c-Fos levels in the dentate gyrus. The increase in c-Fos expression was significantly inhibited by the simultaneous use of levetiracetam and valacyclovir. The findings of the present study indicate that a combination of levetiracetam and valacyclovir had possible anticonvulsive effects on pentylenetetrazol-induced kindled epileptic seizures. These results suggest that valacyclovir may have an antiseizure effect in patients with epilepsy.

Parkinson's Disease Drug Development Since 1999: A Story of Repurposing and Relative Success

Background:

A global overview of drug development programs in Parkinson’s disease over the last few decades is lacking, while such programs are challenging given the multifaceted and heterogeneous nature of the disease.

Objective:

To indirectly assess drug development programs in Parkinson’s disease, exploring some factors associated with compound attrition at different trial phases.

Methods:

We assessed all Parkinson’s disease trials in the WHO trials portal, from inception (1999) to September 2019. Independent authors selected trials and extracted data. The success rate was the number of compounds that progressed to the next drug development phase divided by the number of compounds in that phase.

Results:

Overall, 357 trials (studying 152 compounds) fulfilled our inclusion criteria, with 62 (17.3%) phase 1 trials, 135 (37.8%) phase 2 trials, 85 (23.8%) phase 3 trials, and 53 (14.8%) phase 4 trials. The success rate was 42.4% from phase 2 to 3. Original compounds received regulatory approval by the FDA in 21.4% of cases, compared with 6.7% of repurposed compounds, representing an overall success rate of 14.9%. We found 172 trials (48.2%) conducted for repurposing previously licensed compounds. These figures were approximately the same regarding approval by the EMA. Most compounds were approved to treat parkinsonism and motor fluctuations.

Conclusion:

We found a moderate-to-high success rate in all phases of drug development. This was largely based on the success of original compounds, despite almost half of the identified trials attempting compound repurposing.

Exploration of databases and methods supporting drug repurposing: a comprehensive survey

Drug development involves a deep understanding of the mechanisms of action and possible side effects of each drug, and sometimes results in the identification of new and unexpected uses for drugs, termed as drug repurposing. Both in case of serendipitous observations and systematic mechanistic explorations, confirmation of new indications for a drug requires hypothesis building around relevant drug-related data, such as molecular targets involved, and patient and cellular responses. These datasets are available in public repositories, but apart from sifting through the sheer amount of data imposing computational bottleneck, a major challenge is the difficulty in selecting which databases to use from an increasingly large number of available databases. The database selection is made harder by the lack of an overview of the types of data offered in each database. In order to alleviate these problems and to guide the end user through the drug repurposing efforts, we provide here a survey of 102 of the most promising and drug-relevant databases reported to date. We summarize the target coverage and types of data available in each database and provide several examples of how multi-database exploration can facilitate drug repurposing.

An Analytical Review of Computational Drug Repurposing

Drug repurposing is a vital function in pharmaceutical fields and has gained popularity in recent years in both the pharmaceutical industry and research community. It refers to the process of discovering new uses and indications for existing or failed drugs. It is cost-effective and reliable in contrast to experimental drug discovery, which is a costly, time-consuming, and risky process and limited to a relatively small number of targets. Accordingly, a plethora of computational methodologies have been propounded to repurpose drugs on a large scale by utilizing available high throughput data. The available literature, however, lacks a contemporary and comprehensive analysis of the current computational drug repurposing methodologies. In this paper, we presented a systematic analysis of computational drug repurposing which consists of three main sections: Initially, we categorize the computational drug repurposing methods based on their technical approach and artificial intelligence perspective and discuss the strengths and weaknesses of various methods. Secondly, some general criteria are recommended to analyze our proposed categorization. In the third and final section, a qualitative comparison is made between each approach which is a guide to understanding their preference to one another. Further, this systematic analysis can help in the efficient selection and improvement of drug repurposing techniques based on the nature of computational methods implemented on biological resources.

Screening novel drug candidates for Alzheimer's disease by an integrated network and transcriptome analysis

MOTIVATION

Alzheimer's disease (AD) is a serious degenerative brain disease and the most common cause of dementia. The current available drugs for AD provide symptomatic benefit, but there is no effective drug to cure the disease. The emergence of large-scale genomic, pharmacological data provides new opportunities for drug discovery and drug repositioning as a promising strategy in searching novel drug for AD.

RESULTS

In this study, we took advantage of our increasing understanding based on systems biology approaches on the pathway and network levels and perturbation datasets from the Library of Integrated Network-Based Cellular Signatures to introduce a systematic computational process to discover new drugs implicated in AD. First, we collected 561 genes that have reported to be risk genes of AD, and applied functional enrichment analysis on these genes. Then, by quantifying proximity between 5595 molecule drugs and AD based on human interactome, we filtered out 1092 drugs that were proximal to the disease. We further performed an Inverted Gene Set Enrichment analysis on these drug candidates, which allowed us to estimate effect of perturbations on gene expression and identify 24 potential drug candidates for AD treatment. Results from this study also provided insights for understanding the molecular mechanisms underlying AD. As a useful systematic method, our approach can also be used to identify efficacious therapies for other complex diseases.

AVAILABILITY AND IMPLEMENTATION

The source code is available at https://github.com/zer0o0/drug-repo.git.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Into the Fray! A Beginner's Guide to Medicinal Chemistry

Modern medicinal chemistry is a complex, multidimensional discipline that operates at the interface of the chemical and biological sciences. The medicinal chemistry contribution to drug discovery is typically described in the context of the well-recited linear progression of the drug discovery pipeline. However, compound optimization is idiosyncratic to each project, and clear definitions of hit and lead molecules and the subsequent progress along the pipeline becomes easily blurred. In addition, this description lacks insight into the entangled relationship between chemical and pharmacological properties, and thus provides limited guidance on how innovative medicinal chemistry strategies can be applied to solve optimization problems, regardless of the stage in the pipeline. Through discussion and illustrative examples, this article seeks to provide insights into the finesse of medicinal chemistry and the subtlety of balancing chemical properties pharmacology. In so doing, it aims to serve as an accessible and simple-to-digest guide for anyone who wishes to learn about the underlying principles of medicinal chemistry, in a context that has been decoupled from the pipeline description.

Artificial intelligence, machine learning, and drug repurposing in cancer

Introduction: Drug repurposing provides a cost-effective strategy to re-use approved drugs for new medical indications. Several machine learning (ML) and artificial intelligence (AI) approaches have been developed for systematic identification of drug repurposing leads based on big data resources, hence further accelerating and de-risking the drug development process by computational means.Areas covered: The authors focus on supervised ML and AI methods that make use of publicly available databases and information resources. While most of the example applications are in the field of anticancer drug therapies, the methods and resources reviewed are widely applicable also to other indications including COVID-19 treatment. A particular emphasis is placed on the use of comprehensive target activity profiles that enable a systematic repurposing process by extending the target profile of drugs to include potent off-targets with therapeutic potential for a new indication.Expert opinion: The scarcity of clinical patient data and the current focus on genetic aberrations as primary drug targets may limit the performance of anticancer drug repurposing approaches that rely solely on genomics-based information. Functional testing of cancer patient cells exposed to a large number of targeted therapies and their combinations provides an additional source of repurposing information for tissue-aware AI approaches.

Current and promising pharmacotherapeutic options for candidiasis

Introduction: Candida spp. are commensal yeasts capable of causing infections such as superficial, oral, vaginal, or systemic infections. Despite medical advances, the antifungal pharmacopeia remains limited and the development of alternative strategies is needed.Areas covered: We discuss available treatments for Candida spp. infections, highlighting advantages and limitations related to pharmacokinetics, cytotoxicity, and antimicrobial resistance. Moreover, we present new perspectives to improve the activity of the available antifungals, discussing their immunomodulatory potential and advances on drug delivery carriers. New therapeutic approaches are presented including recent synthesized antifungal compounds (Enchochleated-Amphotericin B, tetrazoles, rezafungin, enfumafungin, manogepix and arylamidine); drug repurposing using a diversity of antibacterial, antiviral and non-antimicrobial drugs; combination therapies with different compounds or photodynamic therapy; and innovations based on nano-particulate delivery systems.Expert opinion: With the lack of novel drugs, the available assets must be leveraged to their best advantage through modifications that enhance delivery, efficacy, and solubility. However, these efforts are met with continuous challenges presented by microbes in their infinite plight to resist and survive therapeutic drugs. The pharmacotherapeutic options in development need to focus on new antimicrobial targets. The success of each antimicrobial agent brings strategic insights to the next phased approach in treatingCandida spp. infections.

An Early Stage Researcher's Primer on Systems Medicine Terminology

Background: Systems Medicine is a novel approach to medicine, that is, an interdisciplinary field that considers the human body as a system, composed of multiple parts and of complex relationships at multiple levels, and further integrated into an environment. Exploring Systems Medicine implies understanding and combining concepts coming from diametral different fields, including medicine, biology, statistics, modeling and simulation, and data science. Such heterogeneity leads to semantic issues, which may slow down implementation and fruitful interaction between these highly diverse fields. Methods: In this review, we collect and explain more than100 terms related to Systems Medicine. These include both modeling and data science terms and basic systems medicine terms, along with some synthetic definitions, examples of applications, and lists of relevant references. Results: This glossary aims at being a first aid kit for the Systems Medicine researcher facing an unfamiliar term, where he/she can get a first understanding of them, and, more importantly, examples and references for digging into the topic.

Chloroquine and hydroxychloroquine for COVID-19: Perspectives on their failure in repurposing

WHAT IS KNOWN AND OBJECTIVE

Non-clinical studies suggest that chloroquine (CQ) and hydroxychloroquine (HCQ) have antiviral activities. Early clinical reports of successful HCQ-associated reduction in viral load from small studies in COVID-19 patients spurred a large number of national and international clinical trials to test their therapeutic potential. The objective of this review is to summarize the current evidence on the safety and efficacy of these two agents and to provide a perspective on why their repurposing has hitherto failed.

METHODS

Published studies and rapidly emerging data were reviewed to gather evidence on safety and efficacy of CQ and HCQ in patients with COVID-19 infection or as prophylaxis. The focus is on clinically relevant efficacy endpoints and their adverse effects on QT interval.

RESULTS AND DISCUSSION

At the doses used, the two agents, given alone or with azithromycin (AZM), are not effective in COVID-19 infection. The choice of (typically subtherapeutic) dosing regimens, influenced partly by "QT-phobia," varied widely and seems anecdotal without any pharmacologically reliable supporting clinical evidence. A substantial proportion of patients receiving CQ/HCQ/AZM regimen developed QTc interval prolongation, many with absolute QTc interval exceeding the potential proarrhythmic threshold, but very few developed proarrhythmia.

WHAT IS NEW AND CONCLUSION

The strategy to repurpose CQ/HCQ to combat COVID-19 infection is overshadowed by concerns about their QT liability, resulting in choice of potentially subtherapeutic doses. Although the risk of QT-related proarrhythmia is real, it is low and manageable by careful monitoring. Recent discontinuation of HCQ from at least four large studies effectively marks the end of efforts at repurposing of CQ or HCQ for COVID-19 infection. This episode leaves behind important questions on dose selection and risk/benefit balance in repurposing drugs generally.

Repurposing of Drug Candidates for Treatment of Skin Cancer

Skin cancers are highly prevalent malignancies that affect millions of people worldwide. These include melanomas and nonmelanoma skin cancers. Melanomas are among the most dangerous cancers, while nonmelanoma skin cancers generally exhibit a more benign clinical pattern; however, they may sometimes be aggressive and metastatic. Melanomas typically appear in body regions exposed to the sun, although they may also appear in areas that do not usually get sun exposure. Thus, their development is multifactorial, comprising endogenous and exogenous risk factors. The management of skin cancer depends on the type; it is usually based on surgery, chemotherapy, immunotherapy, and targeted therapy. In this respect, oncological treatments have demonstrated some progress in the last years; however, current therapies still present various disadvantages such as little cell specificity, recurrent relapses, high toxicity, and increased costs. Furthermore, the pursuit of novel medications is expensive, and the authorization for their clinical utilization may take 10–15 years. Thus, repositioning of drugs previously approved and utilized for other diseases has emerged as an excellent alternative. In this mini-review, we aimed to provide an updated overview of drugs’ repurposing to treat skin cancer and discuss future perspectives.

Drug repositioning and repurposing for Alzheimer disease

Drug repositioning and repurposing can enhance traditional drug development efforts and could accelerate the identification of new treatments for individuals with Alzheimer disease (AD) dementia and mild cognitive impairment. Transcriptional profiling offers a new and highly efficient approach to the identification of novel candidates for repositioning and repurposing. In the future, novel AD transcriptional signatures from cells isolated at early stages of disease, or from human neurons or microglia that carry mutations that increase the risk of AD, might be used as probes to identify additional candidate drugs. Phase II trials assessing repurposed agents must consider the best target population for a specific candidate therapy as well as the mechanism of action of the treatment. In this Review, we highlight promising compounds to prioritize for clinical trials in individuals with AD, and discuss the value of Delphi consensus methodology and evidence-based reviews to inform this prioritization process. We also describe emerging work, focusing on the potential value of transcript signatures as a cost-effective approach to the identification of novel candidates for repositioning.