Challenges and opportunities with drug repurposing: finding strategies to find alternative uses of therapeutics

New drug discovery and Hedonic Q: A new interpretation

Valuing intangible assets is crucial for both shareholders and stakeholders. This study revisits the Hedonic Q approach in the context of new drug discovery, employing a heterogeneous, time-varying difference-in-differences methodology to examine its effect on Hedonic Q. The findings suggest that new drug discovery has a positive and competitive impact on Hedonic Q, albeit with a lagged effect. Products in the early phases of drug discovery, including Phases I, II, and III, do not yield a positive impact on valuation in the short term. This study introduces an innovative framework to analyze the effect of new drug discovery on firm valuation in the pharmaceutical sector.

Overcoming antibiotic resistance: the potential and pitfalls of drug repurposing

Since its emergence shortly after the discovery of penicillin, antibiotic resistance has escalated dramatically, posing a significant health threat and economic burden. Drug repositioning, or drug repurposing, involves identifying new therapeutic applications for existing drugs, utilising their established safety profiles and pharmacological data to swiftly provide effective treatments against resistant pathogens. Several drugs, including otilonium bromide, penfluridol, eltrombopag, ibuprofen, and ceritinib, have demonstrated potent antibacterial activity against multidrug-resistant (MDR) bacteria. These drugs can disrupt biofilms, damage bacterial membranes, and inhibit bacterial growth. The combination of repurposed drugs with conventional antibiotics can reduce the required dosage of individual drugs, mitigate side effects, and delay the development of resistance, making it a promising strategy against MDR bacteria such as Staphylococcus aureus, Klebsiella pneumoniae, Pseudomonas aeruginosa, and Escherichia coli. Despite its promise, drug repurposing faces challenges such as potential off-target effects, toxicity, and regulatory and intellectual property issues, necessitating rigorous evaluations and strategic solutions. This article aims to explore the potential of drug repurposing as a strategy to combat antibiotic resistance, examining its benefits, challenges, and future prospects. We address the legal, economic, and practical challenges associated with repurposing existing drugs, highlight successful examples, and propose solutions to enhance the efficacy and viability of this approach in combating MDR bacterial infections.

The global prevalence of antibiotic self-medication among the adult population: systematic review and meta-analysis

BACKGROUND

Antibiotic self-medication (ASM) is when a person takes antibiotics without a prescription or consulting a healthcare professional. These practices contribute to the misuse of medicines and antibiotic resistance which is a growing global health threat that can lead to longer hospital stays, higher healthcare costs, and increased mortality rates. Though various studies have been conducted on ASM in different countries, there has not yet been a systematic review that comprehensively assesses the problem in the entire globe. Hence, this systematic review and meta-analysis aimed to evaluate the global pooled prevalence of antibiotic self-medication and the reasons for its practice.

METHOD

A systematic search of electronic registers and databases was conducted on PubMed, Medline, Embase, Scopus, Web of Science, Google Scholar, and gray literature including institutional repositories, and national health databases. It used carefully selected keywords and indexing terms in the past ten years. The Joanna Briggs Institute's critical checklist extracted relevant data after appraisal. Narrative analysis was used for descriptive data while Comprehensive Meta-Analysis (CMA) Software was used to analyze quantitative data. Statistics were used to look for heterogeneity, publication bias, and correlations. Sensitivity tests and sub-group analysis were employed to compare outcomes. A p-value < 0.05 was considered significant in all cases.

RESULTS

Seventy-one studies were included in this systematic review and meta-analysis. The total number of participants was 63,251 with sample sizes ranging from 110 to 15,526. In primary outcomes, ASM ranged from 0.65 to 92.2%. The pooled prevalence of ASM globally was 43.0% (95% CI: 38.0, 48.1%). A high degree of heterogeneity across studies was shown with I2 = 99.2%, p < 0.001 assuming a random effect model. In subgroup analysis, the highest ASM pooled prevalence was 55.2% (95% CI: 47.2, 63.2) in sub-Saharan Africa followed by the Middle East, North Africa, and Greater Arabia at 48.3% (95% CI: 38.3, 58.4), Europe at 34.7% (95% CI:18.0, 56.4), and Asia at 25.8% (95% CI: 18.6, 34.6). Students have been identified as the major users of ASM at 62.1% (95% CI: 53.7, 69.7). The meta-regression showed a coefficient of 0.0365, -0.0117, and -0.0001 for a year of publication, recall time, and total sample size, respectively. Publication bias was demonstrated from the asymmetrical distribution of the funnel plot, and the Eggers regression p-value was greater than 0.05 (0.264). Moreover, knowledge of antibiotics (46.19% (95% CI: 27.99, 65.46)), previous successful experiences (39.13% (95% CI: 30.13, 48.93)), and perceiving illness as minor (38.10% (95% CI: 27.19, 50.37)) were the top three reasons pooled proportion for practicing ASM.

CONCLUSION

ASM practice was higher among African and student users. The previous successful experience was the most frequent reason reported. Educational level, gender, and age were often mentioned as predictor factors. Hence, designing interventional approaches that consider the different burdens among the target population and tackle the reasons for the practices might benefit averting antimicrobial resistance.

A new era of psoriasis treatment: Drug repurposing through the lens of nanotechnology and machine learning

Psoriasis is a persistent inflammatory skin disorder characterized by hyper-proliferation and abnormal epidermal differentiation. Conventional treatments such as; topical therapies, phototherapy, systemic immune modulators, and biologics aim to relieve symptoms and improve patient quality of life. However, challenges like adverse effects, high costs, and individual response variability persist. Thus, the need for novel anti-psoriatic drugs has led to the exploration of drug repurposing, an approach that identifies new applications for existing drugs. This method is in its early stages but has gained popularity across both public and private sectors. Furthermore, artificial intelligence (AI) integration is revolutionizing the healthcare industry by enhancing efficiency, delivery, and personalization. Machine learning and deep learning algorithms have significantly impacted drug discovery, repurposing, and designing new molecules or drug delivery carriers. Nanotechnology, in addition to AI, plays a pivotal role in targeting repurposed drugs via the topical route with suitable nanocarriers. This method overcomes challenges associated with oral delivery, such as systemic toxicities, slow onset of action, first-pass effect, and poor bioavailability. This review addresses the practice of repurposing existing drugs for managing psoriasis, discussing the challenges of conventional therapy and how the incorporation of nanotechnology and AI can overcome these hurdles, facilitating the discovery of anti-psoriatic drugs and presenting promising strategies for novel therapeutics. Additionally, it discusses the general benefits of drug repurposing compared to de novo drug development and the potential drawbacks of drug repurposing.

Repurposing Drugs: A Promising Therapeutic Approach against Alzheimer's Disease

Alzheimer's disease (AD) is an insidious, irreversible, complex neurodegenerative disorder characterized by progressive cognitive decline and memory loss; affecting millions worldwide. Despite decades of research, no effective disease-modifying treatment exists. However, drug repurposing is a progressive step in identifying new therapeutic uses of existing drugs. It has emerged as a promising strategy in the quest to combat AD. Various classes of repurposed drugs, such as antidiabetic, antihypertensive, antimicrobial, and anti-inflammatory, have shown potential neuroprotective effects in preclinical and clinical studies. These drugs act by combating free radicals generation, neuroinflammation, amyloid-beta aggregation, and tau hyper-phosphorylation. Furthermore, repurposing offers several advantages, including reduced time and cost compared to de novo drug development. It holds immense promise as a complementary approach to traditional drug discovery. Future research efforts should focus on elucidating the underlying mechanisms of repurposed drugs in AD, optimizing drug combinations, and conducting large-scale clinical trials to validate their efficacy and safety profiles. This review overviews recent advancements and findings in preclinical and clinical fields of different repurposed drugs for AD treatment.

Efavirenz Repurposing Challenges: A Novel Nanomicelle-Based Antiviral Therapy Against Mosquito-Borne Flaviviruses

Background/Objective: World Health Organization latest statistics state that 17% of infectious diseases are transmitted by vectors, causing more than 700,000 deaths each year. Particularly, dengue (DENV), Zika (ZIKV) and yellow fever (YFV) viral infections have generated international awareness due to their epidemic proportion and risks of international spread. In this framework, the repositioning strategy of Efavirenz (EFV) represents a key clinical feature to improve different antiviral therapies. Therefore, the development of Soluplus®-based nanomicelles (NMs) loaded with EFV (10 mg/mL) for optimized oral pharmacotherapy against ZIKV, DENV and YFV infections was investigated. Methods: EFV-NMs were obtained by an acetone diffusion technique. Micellar size and in vitro micellar interaction with mucin were assessed by dynamic light scattering. In vitro cytocompatibility was investigated in A549 and Vero cells and micellar in vitro antiviral activity against ZIKV, DENV and YFV was evaluated. In vivo oral bioavailability and histological studies were assessed in Wistar rats. Results: EFV encapsulation within Soluplus® NMs increased the drug's apparent aqueous solubility up to 4803-fold with a unimodal micellar size distribution and a micellar size of ~90 nm at 25 and 37 °C. Micellar in vitro interaction with mucin was also assessed in a pH range of 1.2-7.5 and its storage micellar physicochemical stability at 4 °C was confirmed over 2 years. In vitro cytocompatibility assays in A549 and Vero cells confirmed that EFV micellar dispersions resulted in safe nanoformulations. Interestingly, EFV-loaded NMs exhibited significantly higher in vitro antiviral activity compared with EFV solution for all the tested flaviviruses. In addition, the selectivity index (SI) values reveal that EFV-loaded NMs exhibited considerably more biological efficacy compared to EFV solution in A549 and Vero cell lines and for each viral infection (SI > 10). Further, the drug pharmacokinetics parameters were enhanced after the oral administration of EFV-loaded NMs, being biocompatible by not causing damage in the gastrointestinal segments. Conclusions: Overall, our EFV nanoformulation highlighted its potential as a novel drug delivery platform for optimized ZIKV, DENV and YFV antiviral therapy.

Improvement of Mutant Galactose-1-Phosphate Uridylyltransferase (GALT) Activity by FDA-Approved Pharmacochaperones: A Preliminary Study

Classic galactosemia is a rare disease with long-term consequences that seriously affect the quality of life of patients. To date, various therapeutic approaches are being developed, but treatments that target the molecular defects in the mutant galactose-1-phosphate uridylyltransferase (GALT) gene are lacking. We conducted a computational search for putative pharmacochaperones by applying a drug repurposing strategy, and we found that one compound, already active as a pharmacochaperone in another pathology, doubled the enzymatic activity of the purified mutant enzyme in an in vitro test. Furthermore, an extensive computational search in a database of known active molecules found another compound able in its turn to improve in vitro enzymatic activity. Both compounds are predicted to interact with a cavity at the enzyme interface previously supposed to be an allosteric site for the GALT enzyme. In vitro tests confirmed also the reduced accumulation of galactose-1-phosphate (G1P) in fibroblasts of patients. Although these results must be considered preliminary, our findings pave the way for future research lines focused on the search for promising pharmacochaperones that can directly rescue the activity of the enzyme.

Drug Repurposing: Insights into Current Advances and Future Applications

Drug development is a complex and expensive process that involves extensive research and testing before a new drug can be approved for use. This has led to a limited availability of potential therapeutics for many diseases. Despite significant advances in biomedical science, the process of drug development remains a bottleneck, as all hypotheses must be tested through experiments and observations, which can be timeconsuming and costly. To address this challenge, drug repurposing has emerged as an innovative strategy for finding new uses for existing medications that go beyond their original intended use. This approach has the potential to speed up the drug development process and reduce costs, making it an attractive option for pharmaceutical companies and researchers alike. It involves the identification of existing drugs or compounds that have the potential to be used for the treatment of a different disease or condition. This can be done through a variety of approaches, including screening existing drugs against new disease targets, investigating the biological mechanisms of existing drugs, and analyzing data from clinical trials and electronic health records. Additionally, repurposing drugs can lead to the identification of new therapeutic targets and mechanisms of action, which can enhance our understanding of disease biology and lead to the development of more effective treatments. Overall, drug repurposing is an exciting and promising area of research that has the potential to revolutionize the drug development process and improve the lives of millions of people around the world. The present review provides insights on types of interaction, approaches, availability of databases, applications and limitations of drug repurposing.

Drug Repositioning for Scorpion Envenomation Treatment Through Dual Inhibition of Chlorotoxin and Leiurotoxin

Scorpion envenomation, a grave public health concern, is primarily driven by the potent neurotoxins chlorotoxin and leiurotoxin present in Leiurus species venom. Developing effective treatments is crucial to mitigate its impact. Utilizing a drug-repositioning bioinformatics-based approach, potential inhibitors of these neurotoxins were identified from Food and Drug Administration (FDA)-approved drugs. Through virtual screening and subsequent molecular dynamics simulations, their ability to stabilize the peptides over time was evaluated. Among the compounds scrutinized, bolazine emerged as a promising candidate, demonstrating significant affinity for both neurotoxins, indicating potential dual inhibitory activity. Molecular dynamics simulations further corroborated the enhanced stability of bolazine complexes compared to neurotoxins alone. These findings suggest the feasibility of repurposing existing drugs to develop new therapeutic strategies to treat scorpion envenomation. Such interventions hold promise in alleviating the severe health repercussions of scorpion stings and meeting the urgent demand for effective remedies in affected communities.

Advancing Efficacy Prediction for EHR-based Emulated Trials in Repurposing Heart Failure Therapies

Introduction

The High mortality rates associated with heart failure (HF) have propelled the strategy of drug repurposing, which seeks new therapeutic uses for existing, approved drugs to enhance the management of HF symptoms effectively. An emerging trend focuses on utilizing real-world data, like EHR, to mimic randomized controlled trials (RCTs) for evaluating treatment outcomes through what are known as emulated trials (ET). Nonetheless, the intricacies inherent in EHR data-comprising detailed patient histories in databases, the omission of certain biomarkers or specific diagnostic tests, and partial records of symptoms-introduce notable discrepancies between EHR data and the stringent standards of RCTs. This gap poses a substantial challenge in conducting an ET to accurately predict treatment efficacy.

Objective

The objective of this research is to predict the efficacy of drugs repurposed for HF in randomized trials by leveraging EHR in ET.

Methods

We proposed an ET framework to predict drug efficacy, integrating target prediction based on biomedical databases with statistical analysis using EHR data. Specifically, we developed a novel target prediction model that learns low-dimensional representations of drug molecules, protein sequences, and diverse biomedical associations from a knowledge graph. Additionally, we crafted strategies to improve the prediction by considering the interactions between HF drugs and biological factors in the context of HF prognostic markers.

Results

Our validation of the drug-target prediction model against the BETA benchmark demonstrated superior performance, with an average AUCROC of 97.7%, PRAUC of 97.4%, F1 score of 93.1%, and a General Score of 96.1%, surpassing existing baseline algorithms. Further analysis of our ET framework on identifying 17 repurposed drugs-derived from 266 phase 3 HF RCTs-using data from 59,000 patients at the Mayo Clinic highlighted the framework's remarkable predictive accuracy. This analysis took into account various factors such as biological variables (e.g., gender, age, ethnicity), HF medications (e.g., ACE inhibitors, Beta-blockers, ARBs, Loop Diuretics), types of HF (HFpEF and HFrEF), confounders, and prognostic markers (e.g., NT-proBNP, bUn, creatinine, and hemoglobin). The ET framework significantly improved the accuracy compared to the baseline efficacy analysis that utilized EHR data. Notably, the best results were improved in AUC-ROC from 75.71% to 93.57% and in PRAUC from 78.66% to 90.34%, compared to the baseline models.

Conclusion

Our study presents an ET framework that significantly enhances drug efficacy emulation by integrating EHR-based analysis with target prediction. We demonstrated substantial success in predicting the efficacy of 17 HF drugs repurposed for phase 3 RCTs, showcasing the framework's potential in advancing HF treatment strategies.

Investigational new drugs for the treatment of leishmaniasis

INTRODUCTION

Over the past 20 years, significant progress has been made in anti-leishmanial therapy. Three new drugs/formulations are available for the treatment of various forms of leishmaniasis, namely oral miltefosine, paromomycin and liposomal amphotericin B. However, these advances in drug development have added considerable complexity for clinicians including toxicity, emergence of resistance and decreased sensitivity of available drugs. The development of newer drugs with less toxicity and more efficacy is urgently needed.

AREAS COVERED

This review comprehensively examines the latest developments and current status of antileishmanial drugs for the treatment of leishmaniasis across the world. Several new investigational drugs that showed anti-leishmanial activity under in vitro or in vivo conditions and either underwent the phase-I/II clinical trials or are on the verge of entering the trials were reviewed. We also delve into the challenges of drug resistance and discuss the emergence of new and effective antileishmanial compounds.

EXPERT OPINION

The available treatments for leishmaniasis are limited in number, toxic, expensive, and demand extensive healthcare resources. Every available antileishmanial drug is associated with several disadvantages, such as drug resistance and toxicity or high cost. Miltefosine is potentially teratogenic. New antileishmanial drugs/treatment modalities are sorely needed for expanding future treatment options.

Repurposing metabolic regulators: antidiabetic drugs as anticancer agents

Drug repurposing in cancer taps into the capabilities of existing drugs, initially designed for other ailments, as potential cancer treatments. It offers several advantages over traditional drug discovery, including reduced costs, reduced development timelines, and a lower risk of adverse effects. However, not all drug classes align seamlessly with a patient's condition or long-term usage. Hence, repurposing of chronically used drugs presents a more attractive option. On the other hand, metabolic reprogramming being an important hallmark of cancer paves the metabolic regulators as possible cancer therapeutics. This review emphasizes the importance and offers current insights into the repurposing of antidiabetic drugs, including metformin, sulfonylureas, sodium-glucose cotransporter 2 (SGLT2) inhibitors, dipeptidyl peptidase 4 (DPP-4) inhibitors, glucagon-like peptide-1 receptor agonists (GLP-1RAs), thiazolidinediones (TZD), and α-glucosidase inhibitors, against various types of cancers. Antidiabetic drugs, regulating metabolic pathways have gained considerable attention in cancer research. The literature reveals a complex relationship between antidiabetic drugs and cancer risk. Among the antidiabetic drugs, metformin may possess anti-cancer properties, potentially reducing cancer cell proliferation, inducing apoptosis, and enhancing cancer cell sensitivity to chemotherapy. However, other antidiabetic drugs have revealed heterogeneous responses. Sulfonylureas and TZDs have not demonstrated consistent anti-cancer activity, while SGLT2 inhibitors and DPP-4 inhibitors have shown some potential benefits. GLP-1RAs have raised concerns due to possible associations with an increased risk of certain cancers. This review highlights that further research is warranted to elucidate the mechanisms underlying the potential anti-cancer effects of these drugs and to establish their efficacy and safety in clinical settings.

Network Pharmacology Reveals Key Targets and Pathways of Madhuca longifolia for Potential Alzheimer's Disease Treatment

Madhuca longifolia, commonly known as the mahua tree, has been traditionally used in medicine due to its anti-inflammatory, anti-diabetic, and antimicrobial properties. Its active compounds help in managing diabetes, alleviating cognitive impairment associated with Alzheimer's disease. Nonetheless, the exact neuroprotective mechanism of Madhuca longifolia against Alzheimer's disease remains unclear. This study looked into possible methods by which Madhuca longifolia protects against Alzheimer's disease using network pharmacology, molecular docking and molecular dynamic simulations studies. By applying pre-screening of active constituents, target prediction, Gene Ontology (GO) and Kyoto Encyclopaedia of Genes and Genomes (KEGG) pathway enrichment analysis, our study found that Madhuca longifolia is related to eight active ingredients (Ascorbic acid, Riboflavin, Pantothenic acid, (4 R)-2beta,3beta,23-trihydroxy-oleana-5,12-dien-28-oic acid, Quercetin, Nicotinic acid, Bassiaic acid Thiamine) and 272 common gene targets, with significant involvement in pathways such as PI3K-Akt signaling and neuroactive ligand-receptor interaction. Network analysis demonstrated how Madhuca longifolia can prevent AD by modifying important signalling networks, which may be one of the molecular mechanisms driving the plant's effectiveness against the disease. Molecular docking studies revealed that there were robust binding abilities of Quercetin, Riboflavin and Pantothenic acid to key target proteins AKT1, JUN, and STAT3. Later, molecular dynamic simulations was done to examine the successful activity of the active compounds against potential targets, and it was found that AKT1 and AKT1-Quercetin complex became stable at 260 ps. It may be seen through the study that quercetin may act as a good inhibitor for treatment. This thorough investigation provides a strong basis for future research and development efforts by advancing our understanding of Madhuca longifolia medicinal potential in Alzheimer's disease.

Exploring the therapeutic potential of SGLT2 inhibitors in cancer treatment: integrating in silico and in vitro investigations

The present study aimed to investigate the anti-cancer mechanism of canagliflozin (CANA) and dapagliflozin (DAPA), sodium-glucose co-transporter-2 (SGLT2) inhibitors, using in silico and in vitro approaches. Network pharmacology was employed to predict the targets of the inhibitors and GO gene enrichment analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway annotation conducted to explore the interacting pathways. Molecular docking and molecular dynamic (MD) simulation studies were performed to confirm the important targets and assess conformational stability. In vitro cytotoxicity assays, MIA-PaCa-2 and DU-145 cell lines CANA and DAPA was performed. Protein-protein interaction (PPI) network analysis indicated that CANA and DAPA exert anticancer effects through MAPK, mTOR, EGFR-KRAS-BRAF, FGFR, and PI3KA pathways. KEGG analysis revealed that these inhibitors could be used in the treatment of various cancers, including breast, prostate, pancreatic, chronic myeloid leukemia, thyroid, small cell lung, gastric, and bladder cancer. Docking results showed highest affinity for MAPK1 for CANA (- 9.60 kcal/mol) and DAPA (- 9.58 kcal/mol). MD simulation results showed that RMSD values for the MAPK1-compound exhibit remarkable stability over a timeframe of 100 ns. In cytotoxicity assays using MIA-PaCa-2 and DU-145 cell lines, CANA demonstrated a potential antiproliferative effect on the pancreatic cell line MIA-PaCa-2 after 48 h of treatment at a concentration of 100 µg/ml. Furthermore, CANA arrested the cell cycle in the sub-G1 phase and induced late apoptosis and necrosis in MIA-PaCa-2 cell line. Based on these findings, CANA shows promise as a potential novel treatment strategy for pancreatic cancer.

Repurposing lipid-lowering drugs on asthma and lung function: evidence from a genetic association analysis

OBJECTIVE

To explore the correlation between asthma risk and genetic variants affecting the expression or function of lipid-lowering drug targets.

METHODS

We conducted Mendelian randomization (MR) analyses using variants in several genes associated with lipid-lowering medication targets: HMGCR (statin target), PCSK9 (alirocumab target), NPC1L1 (ezetimibe target), APOB (mipomersen target), ANGPTL3 (evinacumab target), PPARA (fenofibrate target), and APOC3 (volanesorsen target), as well as LDLR and LPL. Our objective was to investigate the relationship between lipid-lowering drugs and asthma through MR. Finally, we assessed the efficacy and stability of the MR analysis using the MR Egger and inverse variance weighted (IVW) methods.

RESULTS

The elevated triglyceride (TG) levels associated with the APOC3, and LPL targets were found to increase asthma risk. Conversely, higher LDL-C levels driven by LDLR were found to decrease asthma risk. Additionally, LDL-C levels (driven by APOB, NPC1L1 and HMGCR targets) and TG levels (driven by the LPL target) were associated with improved lung function (FEV1/FVC). LDL-C levels driven by PCSK9 were associated with decreased lung function (FEV1/FVC).

CONCLUSION

In conclusion, our findings suggest a likely causal relationship between asthma and lipid-lowering drugs. Moreover, there is compelling evidence indicating that lipid-lowering therapies could play a crucial role in the future management of asthma.

From Drug Discovery to Drug Approval: A Comprehensive Review of the Pharmacogenomics Status Quo with a Special Focus on Egypt

Pharmacogenomics (PGx) is the hope for the full optimization of drug therapy while minimizing the accompanying adverse drug events that cost billions of dollars annually. Since years before the century, it has been known that inter-individual variations contribute to differences in specific drug responses. It is the bridge to what is well-known today as "personalized medicine". Addressing the drug's pharmacokinetics and pharmacodynamics is one of the features of this science, owing to patient characteristics that vary on so many occasions. Mainly in the liver parenchymal cells, intricate interactions between the drug molecules and enzymes family of so-called "Cytochrome P450" occur which hugely affects how the body will react to the drug in terms of metabolism, efficacy, and safety. Single nucleotide polymorphisms, once validated for a transparent and credible clinical utility, can be used to guide and ensure the succession of the pharmacotherapy plan. Novel tools of pharmacoeconomics science are utilized extensively to assess cost-effective pharmacogenes preceding the translation to the bedside. Drug development and discovery incorporate a drug-gene perspective and save more resources. Regulations and laws shaping the clinical PGx practice can be misconceived; however, these pre-/post approval processes ensure the product's safety and efficacy. National and international regulatory agencies seek guidance on maintaining conduct in PGx practice. In this patient-centric era, social and legal considerations manifest in a way that makes them unavoidable, involving patients and other stakeholders in a deliberate journey toward utmost patient well-being. In this comprehensive review, we contemporarily addressed the scientific leaps in PGx, along with various challenges that face the proper implementation of personalized medicine in Egypt. These informative insights were drawn to serve what the Egyptian population, in particular, would benefit from in terms of knowledge and know-how while maintaining the latest global trends. Moreover, this review is the first to discuss various modalities and challenges faced in Egypt regarding PGx, which we believe could be used as a pilot piece of literature for future studies locally, regionally, and internationally.

HGTDR: Advancing drug repurposing with heterogeneous graph transformers

MOTIVATION

Drug repurposing is a viable solution for reducing the time and cost associated with drug development. However, thus far, the proposed drug repurposing approaches still need to meet expectations. Therefore, it is crucial to offer a systematic approach for drug repurposing to achieve cost savings and enhance human lives. In recent years, using biological network-based methods for drug repurposing has generated promising results. Nevertheless, these methods have limitations. Primarily, the scope of these methods is generally limited concerning the size and variety of data they can effectively handle. Another issue arises from the treatment of heterogeneous data, which needs to be addressed or converted into homogeneous data, leading to a loss of information. A significant drawback is that most of these approaches lack end-to-end functionality, necessitating manual implementation and expert knowledge in certain stages.

RESULTS

We propose a new solution, Heterogeneous Graph Transformer for Drug Repurposing (HGTDR), to address the challenges associated with drug repurposing. HGTDR is a three-step approach for knowledge graph-based drug repurposing: (1) constructing a heterogeneous knowledge graph, (2) utilizing a heterogeneous graph transformer network, and (3) computing relationship scores using a fully connected network. By leveraging HGTDR, users gain the ability to manipulate input graphs, extract information from diverse entities, and obtain their desired output. In the evaluation step, we demonstrate that HGTDR performs comparably to previous methods. Furthermore, we review medical studies to validate our method's top 10 drug repurposing suggestions, which have exhibited promising results. We also demonstrated HGTDR's capability to predict other types of relations through numerical and experimental validation, such as drug-protein and disease-protein inter-relations.

AVAILABILITY AND IMPLEMENTATION

The source code and data are available at https://github.com/bcb-sut/HGTDR and http://git.dml.ir/BCB/HGTDR.

MEK inhibitors: a promising targeted therapy for cardiovascular disease

Cardiovascular disease (CVD) represents the leading cause of mortality and disability all over the world. Identifying new targeted therapeutic approaches has become a priority of biomedical research to improve patient outcomes and quality of life. The RAS-RAF-MEK (mitogen-activated protein kinase kinase)-ERK (extracellular signal-regulated kinase) pathway is gaining growing interest as a potential signaling cascade implicated in the pathogenesis of CVD. This pathway is pivotal in regulating cellular processes like proliferation, growth, migration, differentiation, and survival, which are vital in maintaining cardiovascular homeostasis. In addition, ERK signaling is involved in controlling angiogenesis, vascular tone, myocardial contractility, and oxidative stress. Dysregulation of this signaling cascade has been linked to cell dysfunction and vascular and cardiac pathological remodeling, which contribute to the onset and progression of CVD. Recent and ongoing research has provided insights into potential therapeutic interventions targeting the RAS-RAF-MEK-ERK pathway to improve cardiovascular pathologies. Preclinical studies have demonstrated the efficacy of targeted therapy with MEK inhibitors (MEKI) in attenuating ERK activation and mitigating CVD progression in animal models. In this article, we first describe how ERK signaling contributes to preserving cardiovascular health. We then summarize current knowledge of the roles played by ERK in the development and progression of cardiac and vascular disorders, including atherosclerosis, myocardial infarction, cardiac hypertrophy, heart failure, and aortic aneurysm. We finally report novel therapeutic strategies for these CVDs encompassing MEKI and discuss advantages, challenges, and future developments for MEKI therapeutics.

Strategies of Pharmacological Repositioning for the Treatment of Medically Relevant Mycoses

Fungal infections represent a worldwide concern for public health, due to their prevalence and significant increase in cases each year. Among the most frequent mycoses are those caused by members of the genera Candida, Cryptococcus, Aspergillus, Histoplasma, Pneumocystis, Mucor, and Sporothrix, which have been treated for years with conventional antifungal drugs, such as flucytosine, azoles, polyenes, and echinocandins. However, these microorganisms have acquired the ability to evade the mechanisms of action of these drugs, thus hindering their treatment. Among the most common evasion mechanisms are alterations in sterol biosynthesis, modifications of drug transport through the cell wall and membrane, alterations of drug targets, phenotypic plasticity, horizontal gene transfer, and chromosomal aneuploidies. Taking into account these problems, some research groups have sought new therapeutic alternatives based on drug repositioning. Through repositioning, it is possible to use existing pharmacological compounds for which their mechanism of action is already established for other diseases, and thus exploit their potential antifungal activity. The advantage offered by these drugs is that they may be less prone to resistance. In this article, a comprehensive review was carried out to highlight the most relevant repositioning drugs to treat fungal infections. These include antibiotics, antivirals, anthelmintics, statins, and anti-inflammatory drugs.

Current Perspectives of Antifungal Therapy: A Special Focus on Candida auris

Candida auris is an emerging Candida sp. that has rapidly spread all over the world. The evidence regarding its origin and emerging resistance is still unclear. The severe infection caused by this species results in significant mortality and morbidity among the elderly and immunocompromised individuals. The development of drug resistance is the major factor associated with the therapeutic failure of existing antifungal agents. Previous studies have addressed the antifungal resistance profile and drug discovery for C. auris. However, complete coverage of this information in a single investigation is not yet available. In this review, we have mainly focused on recent developments in therapeutic strategies against C. auris. Based on the available information, several different approaches were discussed, including existing antifungal drugs, chemical compounds, essential oils, natural products, antifungal peptides, immunotherapy, antimicrobial photodynamic therapy, drug repurposing, and drug delivery systems. Among them, synthetic chemicals, natural products, and antifungal peptides are the prime contributors. However, a limited number of resources are available to prove the efficiency of these potential therapies in clinical usage. Therefore, we anticipate that the findings gathered in this review will encourage further in vivo studies and clinical trials.

How health technology assessment can help to address challenges in drug repurposing: a conceptual framework

Drug repurposing faces various challenges that can impede its success. We developed a framework outlining key challenges in drug repurposing to explore when and how health technology assessment (HTA) methods can address them. We identified 20 drug-repurposing challenges across the categories of data access, research and development, collaboration, business case, regulatory and legal challenges. Early incorporation of HTA methods, including literature review, empirical research, stakeholder consultation, health economic evaluation and uncertainty assessment, can help to address these challenges. HTA methods canassess the value proposition of repurposed drugs, inform further research and ultimately help to bring cost-effective repurposed drugs to patients.

The fungicidal effectiveness of 2-Chloro-3-hydrazinylquinoxaline, a newly developed quinoxaline derivative, against Candida species

BACKGROUND

Candida represents a prevalent fungal infection, notable for its substantial implications on morbidity and mortality rates. In the landscape of prospective treatments, quinoxaline derivatives emerge as a category of compact compounds exhibiting notable potential in addressing infections. These derivatives showcase promising antimicrobial efficacy coupled with favorable pharmacokinetic and safety characteristics.

AIMS

The central aim of this investigation was to examine the antifungal characteristics of 2-Chloro-3-hydrazinylquinoxaline against diverse strains of Candida and Aspergillus in vitro. Additionally, we endeavored to assess the in vivo efficacy of 2-Chloro-3-hydrazinylquinoxaline using a murine model for oral candidiasis induced by C. albicans cells ATCC 10231.

RESULTS

2-Chloro-3-hydrazinylquinoxaline demonstrated noteworthy effectiveness when tested against various reference strains of Candida species. It exhibited heightened efficacy, particularly against Candida krusei isolates. However, its performance against Candida albicans, Candida tropicalis, Candida glabrata, Candida parapsilosis, and Candida auris isolates exhibited variability. Notably, 2-Chloro-3-hydrazinylquinoxaline manifests variable efficacy against Aspergillus fumigatus, Aspergillus niger, Aspergillus terreus and Aspergillus flavus and no effect against Aspergillus brasiliensis. In a murine model, 2-Chloro-3-hydrazinylquinoxaline exhibited significant efficacy in combating the C. albicans cells ATCC 10231 strain, underscoring its potential as a viable treatment option.

CONCLUSION

2-Chloro-3-hydrazinylquinoxaline has demonstrated substantial potential in effectively addressing various Candida and Aspergillus species, showcasing dual attributes of antifungal and anti-inflammatory properties. However, to attain a more comprehensive understanding of its therapeutic capabilities, further investigations, incorporating additional tests and experiments, are imperative.

G-K BertDTA: A graph representation learning and semantic embedding-based framework for drug-target affinity prediction

Developing new drugs is costly, time-consuming, and risky. Drug-target affinity (DTA), indicating the binding capability between drugs and target proteins, is a crucial indicator for drug development. Accurately predicting interaction strength between new drug-target pairs by analyzing previous experiments aids in screening potential drug molecules, repurposing them, and developing safe and effective medicines. Existing computational models for DTA prediction rely on strings or single-graph neural networks, lacking consideration of protein structure and molecular semantic information, leading to limited accuracy. Our experiments demonstrate that string-based methods may overlook protein conformations, causing a high root mean square error (RMSE) of 3.584 in affinity due to a lack of spatial context. Single graph networks also underperform on topology features, with a 6% lower confidence interval (CI) for activity classification. Absent semantic information also limits generalization across diverse compounds, resulting in 18% increment in RMSE and 5% in misclassifications within quantifications study, restricting potential drug discovery. To address these limitations, we propose G-K BertDTA, a novel framework for accurate DTA prediction incorporating protein features, molecular semantic features, and molecular structural information. In this proposed model, we represent drugs as graphs, with a GIN employed to learn the molecular topological information. For the extraction of protein structural features, we utilize a DenseNet architecture. A knowledge-based BERT semantic model is incorporated to obtain rich pre-trained semantic embeddings, thereby enhancing the feature information. We extensively evaluated our proposed approach on the publicly available benchmark datasets (i.e., KIBA and Davis), and experimental results demonstrate the promising performance of our method, which consistently outperforms previous state-of-the-art approaches. Code is available at https://github.com/AmbitYuki/G-K-BertDTA.

Regulatory considerations and intellectual property rights of repurposed drugs

Drug repurposing has emerged as a promising approach in the drug discovery and development process as it offers safe and effective therapeutic options in a time effective manner. Though the issues related to pre-clinical and clinical aspects of drug development process are greatly addressed during drug repurposing yet regulatory perspectives gain even more However, like traditional drug development the repurposed drugs face multiple challenges. Such challenges range from the patenting rights, novelty of repurposing, data and market exclusivity to affordability and equitable access to the patient population. In order to optimize the market access of repurposed drugs, regulatory organizations throughout the world have developed accelerated approval procedures. The regulatory bodies have recognized the importance of repurposing approaches and repurposed drugs. Regulatory bodies can encourage the development of repurposed drugs by providing incentives to pharmaceutical companies and more accessible and affordable repurposed agents for the general population. This chapter summarizes the regulatory and ethical considerations pertaining to the repurposed drugs and highlights a few cases of intellectual property rights for repurposed drugs that have helped improve patient's access to safe, efficacious and cost-effective therapeutic options.

Reimagining old drugs with new tricks: Mechanisms, strategies and notable success stories in drug repurposing for neurological diseases

Recent evolution in drug repurposing has brought new anticipation, especially in the conflict against neurodegenerative diseases (NDDs). The traditional approach to developing novel drugs for these complex disorders is laborious, time-consuming, and often abortive. However, drug reprofiling which is the implementation of illuminating novel therapeutic applications of existing approved drugs, has shown potential as a promising strategy to accelerate the hunt for therapeutics. The advancement of computational approaches and artificial intelligence has expedited drug repurposing. These progressive technologies have enabled scientists to analyse extensive datasets and predict potential drug-disease interactions. By prospecting into the existing pharmacological knowledge, scientists can recognise potential therapeutic candidates for reprofiling, saving precious time and resources. Preclinical models have also played a pivotal role in this field, confirming the effectiveness and mechanisms of action of repurposed drugs. Several studies have occurred in recent years, including the discovery of available drugs that demonstrate significant protective effects in NDDs, relieve debilitating symptoms, or slow down the progression of the disease. These findings highlight the potential of repurposed drugs to change the landscape of NDD treatment. Here, we present an overview of recent developments and major advances in drug repurposing intending to provide an in-depth analysis of traditional drug discovery and the strategies, approaches and technologies that have contributed to drug repositioning. In addition, this chapter attempts to highlight successful case studies of drug repositioning in various therapeutic areas related to NDDs and explore the clinical trials, challenges and limitations faced by researchers in the field. Finally, the importance of drug repositioning in drug discovery and development and its potential to address discontented medical needs is also highlighted.

Unlocking hidden potential: advancements, approaches, and obstacles in repurposing drugs for cancer therapy

High rates of failure, exorbitant costs, and the sluggish pace of new drug discovery and development have led to a growing interest in repurposing "old" drugs to treat both common and rare diseases, particularly cancer. Cancer, a complex and heterogeneous disease, often necessitates a combination of different treatment modalities to achieve optimal outcomes. The intrinsic polygenicity of cancer, intricate biological signalling networks, and feedback loops make the inhibition of a single target frequently insufficient for achieving the desired therapeutic impact. As a result, addressing these complex or "smart" malignancies demands equally sophisticated treatment strategies. Combinatory treatments that target the multifaceted oncogenic signalling network hold immense promise. Repurposed drugs offer a potential solution to this challenge, harnessing known compounds for new indications. By avoiding the prohibitive costs and long development timelines associated with novel cancer drugs, this approach holds the potential to usher in more effective, efficient, and cost-effective cancer treatments. The pursuit of combinatory therapies through drug repurposing may hold the key to achieving superior outcomes for cancer patients. However, drug repurposing faces significant commercial, technological and regulatory challenges that need to be addressed. This review explores the diverse approaches employed in drug repurposing, delves into the challenges faced by the drug repurposing community, and presents innovative solutions to overcome these obstacles. By emphasising the significance of combinatory treatments within the context of drug repurposing, we aim to unlock the full potential of this approach for enhancing cancer therapy. The positive aspects of drug repurposing in oncology are underscored here; encompassing personalized treatment, accelerated development, market opportunities for shelved drugs, cancer prevention, expanded patient reach, improved patient access, multi-partner collaborations, increased likelihood of approval, reduced costs, and enhanced combination therapy.

A transcriptomics-based drug repositioning approach to identify drugs with similar activities for the treatment of muscle pathologies in spinal muscular atrophy (SMA) models

Spinal muscular atrophy (SMA) is a genetic neuromuscular disorder caused by the reduction of survival of motor neuron (SMN) protein levels. Although three SMN-augmentation therapies are clinically approved that significantly slow down disease progression, they are unfortunately not cures. Thus, complementary SMN-independent therapies that can target key SMA pathologies and that can support the clinically approved SMN-dependent drugs are the forefront of therapeutic development. We have previously demonstrated that prednisolone, a synthetic glucocorticoid (GC) improved muscle health and survival in severe Smn-/-;SMN2 and intermediate Smn2B/- SMA mice. However, long-term administration of prednisolone can promote myopathy. We thus wanted to identify genes and pathways targeted by prednisolone in skeletal muscle to discover clinically approved drugs that are predicted to emulate prednisolone's activities. Using an RNA-sequencing, bioinformatics, and drug repositioning pipeline on skeletal muscle from symptomatic prednisolone-treated and untreated Smn-/-; SMN2 SMA and Smn+/-; SMN2 healthy mice, we identified molecular targets linked to prednisolone's ameliorative effects and a list of 580 drug candidates with similar predicted activities. Two of these candidates, metformin and oxandrolone, were further investigated in SMA cellular and animal models, which highlighted that these compounds do not have the same ameliorative effects on SMA phenotypes as prednisolone; however, a number of other important drug targets remain. Overall, our work further supports the usefulness of prednisolone's potential as a second-generation therapy for SMA, identifies a list of potential SMA drug treatments and highlights improvements for future transcriptomic-based drug repositioning studies in SMA.

Identification of Potentially Repurposable Drugs for Lewy Body Dementia Using a Network-Based Approach

The conventional method of one drug being used for one target has not yielded therapeutic solutions for Lewy body dementia (LBD), which is a leading progressive neurological disorder characterized by significant loss of neurons. The age-related disease is marked by memory loss, hallucinations, sleep disorder, mental health deterioration, palsy, and cognitive impairment, all of which have no known effective cure. The present study deploys a network medicine pipeline to repurpose drugs having considerable effect on the genes and proteins related to the diseases of interest. We utilized the novel SAveRUNNER algorithm to quantify the proximity of all drugs obtained from DrugBank with the disease associated gene dataset obtained from Phenopedia and targets in the human interactome. We found that most of the 154 FDA-approved drugs predicted by SAveRUNNER were used to treat nervous system disorders, but some off-label drugs like quinapril and selegiline were interestingly used to treat hypertension and Parkinson's disease (PD), respectively. Additionally, we performed gene set enrichment analysis using Connectivity Map (CMap) and pathway enrichment analysis using EnrichR to validate the efficacy of the drug candidates obtained from the pipeline approach. The investigation enabled us to identify the significant role of the synaptic vesicle pathway in our disease and accordingly finalize 8 suitable antidepressant drugs from the 154 drugs initially predicted by SAveRUNNER. These potential anti-LBD drugs are either selective or non-selective inhibitors of serotonin, dopamine, and norepinephrine transporters. The validated selective serotonin and norepinephrine inhibitors like milnacipran, protriptyline, and venlafaxine are predicted to manage LBD along with the affecting symptomatic issues.

A Surprising Repurposing of Central Nervous System Drugs against Squamous Cell Carcinoma of the Bladder, UM-UC-5

The potential benefits of drug repurposing have gained attention as an alternative to developing de novo drugs. The potential of using central nervous system (CNS) drugs as anticancer drugs has been explored in several types of human cancers, such as breast and colon cancer, among others. Here, we examine the effect of the CNS drugs sertraline, paroxetine, and chlorpromazine on human squamous carcinoma cells of the bladder (UM-UC-5). After exposing UM-UC-5 cells to increased concentrations of each drug for 48 h, we assessed their metabolic activity using an MTT assay. Based on those results, we calculated cell viability and the half-maximal inhibitory concentration (IC50) values. The results suggest that the CNS drugs were effective against UM-UC-5 in the order of potency of sertraline > chlorpromazine > paroxetine. Interestingly, sertraline was more potent than 5-fluorouracil (5-FU), a widely used anticancer drug. This study demonstrated, for the first time, the promising anticancer activity of CNS drugs on human bladder cancer cells in vitro and supports the repurposing of CNS drugs to improve cancer treatment. Nevertheless, further studies are necessary to understand their mechanism of action and in vivo activity.

Drug Repurposing in the Chemotherapy of Infectious Diseases

Repurposing is a universal mechanism for innovation, from the evolution of feathers to the invention of Velcro tape. Repurposing is particularly attractive for drug development, given that it costs more than a billion dollars and takes longer than ten years to make a new drug from scratch. The COVID-19 pandemic has triggered a large number of drug repurposing activities. At the same time, it has highlighted potential pitfalls, in particular when concessions are made to the target product profile. Here, we discuss the pros and cons of drug repurposing for infectious diseases and analyze different ways of repurposing. We distinguish between opportunistic and rational approaches, i.e., just saving time and money by screening compounds that are already approved versus repurposing based on a particular target that is common to different pathogens. The latter can be further distinguished into divergent and convergent: points of attack that are divergent share common ancestry (e.g., prokaryotic targets in the apicoplast of malaria parasites), whereas those that are convergent arise from a shared lifestyle (e.g., the susceptibility of bacteria, parasites, and tumor cells to antifolates due to their high rate of DNA synthesis). We illustrate how such different scenarios can be capitalized on by using examples of drugs that have been repurposed to, from, or within the field of anti-infective chemotherapy.

Towards halal pharmaceutical: Exploring alternatives to animal-based ingredients

Halal is a crucial concept for Muslim consumers regarding consumed products, including pharmaceutical ingredients, which are essential in modern medicine. To address the issue of using porcine-sourced ingredients in pharmaceuticals, it is essential to search for halal alternatives derived from poultry, animal by-products from meat processing, marine sources, and plants. However, the complexity of this problem is further compounded by the rapid advances in innovation and technology, which can lead to adulteration of ingredients derived from pigs. Other challenges include the sustainability of alternative materials, management of waste or by-products practice, halal awareness, certification, government policies, religious adherence of consumers, food suppliers, marketers, and purchasing of products. The importance of halal and non-halal problems, specifically in the context of pharmaceutical materials, is still rarely discussed, including alternatives derived from poultry, animal by-products, marine sources, and plants. Due to the increasing global population, there is a growing need to increase awareness and concern among Muslim consumers for halal products, including pharmaceuticals. Therefore, this research aimed to investigate the importance of halal and non-halal issues in pharmaceutical ingredients, the potential impact on the Muslim community, as well as opportunities and challenges in the search for alternative ingredients.

Drug Repositioning: A Monetary Stratagem to Discover a New Application of Drugs

Drug repurposing, also referred to as drug repositioning or drug reprofiling, is a scientific approach to the detection of any new application for an already approved or investigational drug. It is a useful policy for the invention and development of new pharmacological or therapeutic applications of different drugs. The strategy has been known to offer numerous advantages over developing a completely novel drug for certain problems. Drug repurposing has numerous methodologies that can be categorized as target-oriented, drug-oriented, and problem-oriented. The choice of the methodology of drug repurposing relies on the accessible information about the drug molecule and like pharmacokinetic, pharmacological, physicochemical, and toxicological profile of the drug. In addition, molecular docking studies and other computer-aided methods have been known to show application in drug repurposing. The variation in dosage for original target diseases and novel diseases presents a challenge for researchers of drug repurposing in present times. The present review critically discusses the drugs repurposed for cancer, covid-19, Alzheimer's, and other diseases, strategies, and challenges of drug repurposing. Moreover, regulatory perspectives related to different countries like the United States (US), Europe, and India have been delineated in the present review.

Anticancer Drug Discovery By Structure-Based Repositioning Approach

Despite the tremendous progress that has occurred in recent years in cell biology and oncology, in chemical, physical and computer sciences, the disease cancer has continued as the major cause of death globally. Research organizations, academic institutions and pharmaceutical companies invest huge amounts of money in the discovery and development of new anticancer drugs. Though much effort is continuing and whatever available approaches are being attempted, the success of bringing one effective drug into the market has been uncertain. To overcome problems associated with drug discovery, several approaches are being attempted. One such approach has been the use of known, approved and marketed drugs to screen these for new indications, which have gained considerable interest. This approach is known in different terms as "drug repositioning or drug repurposing." Drug repositioning refers to the structure modification of the active molecule by synthesis, in vitro/ in vivo screening and in silico computational applications where macromolecular structure-based drug design (SBDD) is employed. In this perspective, we aimed to focus on the application of repositioning or repurposing of essential drug moieties present in drugs that are already used for the treatment of some diseases such as diabetes, human immunodeficiency virus (HIV) infection and inflammation as anticancer agents. This review thus covers the available literature where molecular modeling of drugs/enzyme inhibitors through SBDD is reported for antidiabetics, anti-HIV and inflammatory diseases, which are structurally modified and screened for anticancer activity using respective cell lines.

Drug Repurposing against Novel Therapeutic Targets in Plasmodium falciparum for Malaria: The Computational Perspective

Malaria remains one of the most challenging tropical diseases. Since malaria cases are reportedly alarming in terms of infections and mortality, urgent attention is needed for addressing the issues of drug resistance in falciparum malaria. High throughput screening methods have paved way for rapid identification of anti-malarial. Furthermore, drug repurposing helps in shortening the time required for drug safety approvals. Hence, discovery of new antimalarials by drug repurposing is a promising approach for combating the disease. This article summarizes the recent computational approaches used for identifying novel antimalarials by using drug target interaction tools followed by pharmacokinetic studies.

Computer-Aided Drug Discovery and Design: Recent Advances and Future Prospects

Computer-aided drug discovery and design involve the use of information technologies to identify and develop, on a rational ground, chemical compounds that align a set of desired physicochemical and biological properties. In its most common form, it involves the identification and/or modification of an active scaffold (or the combination of known active scaffolds), although de novo drug design from scratch is also possible. Traditionally, the drug discovery and design processes have focused on the molecular determinants of the interactions between drug candidates and their known or intended pharmacological target(s). Nevertheless, in modern times, drug discovery and design are conceived as a particularly complex multiparameter optimization task, due to the complicated, often conflicting, property requirements.This chapter provides an updated overview of in silico approaches for identifying active scaffolds and guiding the subsequent optimization process. Recent groundbreaking advances in the field have also analyzed the integration of state-of-the-art machine learning approaches in every step of the drug discovery process (from prediction of target structure to customized molecular docking scoring functions), integration of multilevel omics data, and the use of a diversity of computational approaches to assist target validation and assess plausible binding pockets.

Targeting notch signaling pathway in breast cancer stem cells through drug repurposing approach

Breast cancer is recognized globally as one of the leading causes of malignant morbidity. It is a heterogeneous disease that accounts for 30 percent of all women diagnosed with cancer. To bring an anti-cancer drug from the bench to the bedside is an expensive and time-consuming process. The drug repurposing approach targets new enemies (new diseases) with old weapons (known drugs). The present study identified an FDA-approved drug targeting the γ-secretase complex involved in the Notch signaling pathway in breast cancer stem cells (BCSCs). A literature survey and in-silico study identified Venetoclax as a γ-secretase inhibitor (GSI) from 1615 FDA-approved drug compounds. In-silico docking potential of Venetoclax was better than the standard γ-secretase inhibitor RO4929097. Also, the molecular dynamics simulations of 200 ns confirmed the stability of the Venetoclax-γ-secretase complex. These findings suggest that the use of Venetoclax represents a potential γ-secretase inhibitor in breast cancer stem cells. Eventually, the in vitro and clinical evaluation will be needed to confirm the potential chemopreventive and treatment effects of Venetoclax against breast cancer and breast cancer stem cells. Venetoclax appeared as the most promising drug of the 1615 FDA-approved drugs. Our in-silico findings suggest that Venetoclax may act as a γ-secretase inhibitor against the Notch signaling pathway in breast cancer stem cells.

Repurposing Drugs: An Empowering Approach to Drug Discovery and Development

Drug discovery and development is a time-consuming and costly procedure that necessitates a substantial effort. Drug repurposing has been suggested as a method for developing medicines that takes less time than developing brand new medications and will be less expensive. Also known as drug repositioning or re-profiling, this strategy has been in use from the time of serendipitous drug discoveries to the modern computer aided drug designing and use of computational chemistry. In the light of the COVID-19 pandemic too, drug repurposing emerged as a ray of hope in the dearth of available medicines. Data availability by electronic recording, libraries, and improvements in computational techniques offer a vital substrate for systemic evaluation of repurposing candidates. In the not-too-distant future, it could be possible to create a global research archive for us to access, thus accelerating the process of drug development and repurposing. This review aims to present the evolution, benefits and drawbacks including current approaches, key players and the legal and regulatory hurdles in the field of drug repurposing. The vast quantities of available data secured in multiple drug databases, assisting in drug repurposing is also discussed.

Benzimidazoles Containing Piperazine Skeleton at C-2 Position as Promising Tubulin Modulators with Anthelmintic and Antineoplastic Activity

Benzimidazole anthelmintic drugs hold promise for repurposing as cancer treatments due to their interference with tubulin polymerization and depolymerization, manifesting anticancer properties. We explored the potential of benzimidazole compounds with a piperazine fragment at C-2 as tubulin-targeting agents. In particular, we assessed their anthelmintic activity against isolated Trichinella spiralis muscle larvae and their effects on glioblastoma (U-87 MG) and breast cancer (MDA-MB-231) cell lines. Compound 7c demonstrated exceptional anthelmintic efficacy, achieving a 92.7% reduction in parasite activity at 100 μg/mL after 48 hours. In vitro cytotoxicity analysis of MDA-MB 231 and U87 MG cell lines showed that derivatives 7b, 7d, and 7c displayed lower IC50 values compared to albendazole (ABZ), the control. These piperazine benzimidazoles effectively reduced cell migration in both cell lines, with compound 7c exhibiting the most significant reduction, making it a promising candidate for further study. The binding mode of the most promising compound 7c, was determined using the induced fit docking-molecular dynamics (IFD-MD) approach. Regular docking and IFD were also employed for comparison. The IFD-MD analysis revealed that 7c binds to tubulin in a unique binding cavity near that of ABZ, but the benzimidazole ring was fitted much deeper into the binding pocket. Finally, the absolute free energy of perturbation technique was applied to evaluate the 7c binding affinity, further confirming the observed binding mode.

Translating GWAS Findings to Inform Drug Repositioning Strategies for COVID-19 Treatment

We developed a computational framework that integrates Genome-Wide Association Studies (GWAS) and post-GWAS analyses, designed to facilitate drug repurposing for COVID-19 treatment. The comprehensive approach combines transcriptomic-wide associations, polygenic priority scoring, 3D genomics, viral-host protein-protein interactions, and small-molecule docking. Through GWAS, we identified nine druggable host genes associated with COVID-19 severity and SARS-CoV-2 infection, all of which show differential expression in COVID-19 patients. These genes include IFNAR1, IFNAR2, TYK2, IL10RB, CXCR6, CCR9, and OAS1. We performed an extensive molecular docking analysis of these targets using 553 small molecules derived from five therapeutically enriched categories, namely antibacterials, antivirals, antineoplastics, immunosuppressants, and anti-inflammatories. This analysis, which comprised over 20,000 individual docking analyses, enabled the identification of several promising drug candidates. All results are available via the DockCoV2 database (https://dockcov2.org/drugs/). The computational framework ultimately identified nine potential drug candidates: Peginterferon alfa-2b, Interferon alfa-2b, Interferon beta-1b, Ruxolitinib, Dactinomycin, Rolitetracycline, Irinotecan, Vinblastine, and Oritavancin. While its current focus is on COVID-19, our proposed computational framework can be applied more broadly to assist in drug repurposing efforts for a variety of diseases. Overall, this study underscores the potential of human genetic studies and the utility of a computational framework for drug repurposing in the context of COVID-19 treatment, providing a valuable resource for researchers in this field.

Exploiting the molecular subtypes and genetic landscape in pancreatic cancer: the quest to find effective drugs

Pancreatic Ductal Adenocarcinoma (PDAC) is a very lethal disease that typically presents at an advanced stage and is non-compliant with most treatments. Recent technologies have helped delineate associated molecular subtypes and genetic variations yielding important insights into the pathophysiology of this disease and having implications for the identification of new therapeutic targets. Drug repurposing has been evaluated as a new paradigm in oncology to accelerate the application of approved or failed target-specific molecules for the treatment of cancer patients. This review focuses on the impact of molecular subtypes on key genomic alterations in PDAC, and the progress made thus far. Importantly, these alterations are discussed in light of the potential role of drug repurposing in PDAC.

RDKG-115: Assisting drug repurposing and discovery for rare diseases by trimodal knowledge graph embedding

Rare diseases (RDs) may affect individuals in small numbers, but they have a significant impact on a global scale. Accurate diagnosis of RDs is challenging, and there is a severe lack of drugs available for treatment. Pharmaceutical companies have shown a preference for drug repurposing from existing drugs developed for other diseases due to the high investment, high risk, and long cycle involved in RD drug development. Compared to traditional approaches, knowledge graph embedding (KGE) based methods are more efficient and convenient, as they treat drug repurposing as a link prediction task. KGE models allow for the enrichment of existing knowledge by incorporating multimodal information from various sources. In this study, we constructed RDKG-115, a rare disease knowledge graph involving 115 RDs, composed of 35,643 entities, 25 relations, and 5,539,839 refined triplets, based on 372,384 high-quality literature and 4 biomedical datasets: DRKG, Pathway Commons, PharmKG, and PMapp. Subsequently, we developed a trimodal KGE model containing structure, category, and description embeddings using reverse-hyperplane projection. We utilized this model to infer 4199 reliable new inferred triplets from RDKG-115. Finally, we calculated potential drugs and small molecules for each of the 115 RDs, taking multiple sclerosis as a case study. This study provides a paradigm for large-scale screening of drug repurposing and discovery for RDs, which will speed up the drug development process and ultimately benefit patients with RDs. The source code and data are available at https://github.com/ZhuChaoY/RDKG-115.

Understanding the Clinical Use of Levosimendan and Perspectives on its Future in Oncology

Drug repurposing, also known as repositioning or reprofiling, has emerged as a promising strategy to accelerate drug discovery and development. This approach involves identifying new medical indications for existing approved drugs, harnessing the extensive knowledge of their bioavailability, pharmacokinetics, safety and efficacy. Levosimendan, a calcium sensitizer initially approved for heart failure, has been repurposed for oncology due to its multifaceted pharmacodynamics, including phosphodiesterase 3 inhibition, nitric oxide production and reduction of reactive oxygen species. Studies have demonstrated that levosimendan inhibits cancer cell migration and sensitizes hypoxic cells to radiation. Moreover, it exerts organ-protective effects by activating mitochondrial potassium channels. Combining levosimendan with traditional anticancer agents such as 5-fluorouracil (5-FU) has shown a synergistic effect in bladder cancer cells, highlighting its potential as a novel therapeutic approach. This drug repurposing strategy offers a cost-effective and time-efficient solution for developing new treatments, ultimately contributing to the advancement of cancer therapeutics and improved outcomes for patients. Further investigations and clinical trials are warranted to validate the effectiveness of levosimendan in oncology and explore its potential benefits in a clinical setting.

Drug Drop Test: How to Quickly Identify Potential Therapeutic Compounds for Mitochondrial Diseases Using Yeast Saccharomyces cerevisiae

Mitochondrial diseases (MDs) refer to a group of clinically and genetically heterogeneous pathologies characterized by defective mitochondrial function and energy production. Unfortunately, there is no effective treatment for most MDs, and current therapeutic management is limited to relieving symptoms. The yeast Saccharomyces cerevisiae has been efficiently used as a model organism to study mitochondria-related disorders thanks to its easy manipulation and well-known mitochondrial biogenesis and metabolism. It has been successfully exploited both to validate alleged pathogenic variants identified in patients and to discover potential beneficial molecules for their treatment. The so-called "drug drop test", a phenotype-based high-throughput screening, especially if coupled with a drug repurposing approach, allows the identification of molecules with high translational potential in a cost-effective and time-saving manner. In addition to drug identification, S. cerevisiae can be used to point out the drug's target or pathway. To date, drug drop tests have been successfully carried out for a variety of disease models, leading to very promising results. The most relevant aspect is that studies on more complex model organisms confirmed the effectiveness of the drugs, strengthening the results obtained in yeast and demonstrating the usefulness of this screening as a novel approach to revealing new therapeutic molecules for MDs.

Multi-spectroscopic and molecular simulation methods of analysis to explore the mode of binding of Mebendazole drug with calf-thymus DNA

UV-vis, fluorescence, circular dichroism (CD) and ¹H NMR spectroscopic techniques have been employed to explore the mode of binding of Mebendazole (MBZ) drug with calf thymus DNA (CT-DNA). UV-vis and fluorescence spectral studies suggested a complex formation between the drug and nucleic acid. The fluorescence of MBZ was found to enhance upon binding with CT-DNA through a ground state complex formation with K_b in the order of 10⁴ M^-1. The thermodynamic aspects indicated that the complex formation is a spontaneous process and an entropy-driven one. ΔH⁰ > 0 and ΔS⁰ > 0 revealed that hydrophobic interaction plays a dominant role in the stabilization of the complex. Competitive dye displacement assays with ethidium bromide (EB) and Hoechst 33258 dyes and viscosity measurements pointed out that MBZ binds with CT-DNA via intercalation mode, which is confirmed by CD and ¹H NMR spectral studies as well as denaturation studies. Molecular docking analysis could not match well with the experimental results. However, molecular simulation studies and the resultant free energy surface (FES) analysis clearly showed that the benzimidazole ring of MBZ intercalated between the base pairs of the nucleic acid, which is in excellent agreement with the results of the various biophysical experiments.

Potential Repurposed Drug Candidates for Tuberculosis Treatment: Progress and Update of Drugs Identified in Over a Decade

The devastating impact of Tuberculosis (TB) has been a menace to mankind for decades. The World Health Organization (WHO) End TB Strategy aims to reduce TB mortality up to 95% and 90% of overall TB cases worldwide, by 2035. This incessant urge will be achieved with a breakthrough in either a new TB vaccine or novel drugs with higher efficacy. However, the development of novel drugs is a laborious process involving a timeline of almost 20-30 years with huge expenditure; on the other hand, repurposing previously approved drugs is a viable technique for overcoming current bottlenecks in the identification of new anti-TB agents. The present comprehensive review discusses the progress of almost all the repurposed drugs that have been identified to the present day (∼100) and are in the development or clinical testing phase against TB. We have also emphasized the efficacy of repurposed drugs in combination with already available frontline anti-TB medications along with the scope of future investigations. This study would provide the researchers a detailed overview of nearly all identified anti-TB repurposed drugs and may assist them in selecting the lead compounds for further in vivo/clinical research.

Pharmacological updates of nifuroxazide: Promising preclinical effects and the underlying molecular mechanisms

Nifuroxazide (NFX) is a safe nitrofuran antibacterial drug used clinically to treat acute diarrhea and infectious traveler diarrhea or colitis. Recent studies revealed that NFX displays multiple pharmacological effects, including anticancer, antioxidant, and anti-inflammatory effects. NFX has potential roles in inhibiting thyroid, breast, lung, bladder, liver, and colon cancers and osteosarcoma, melanoma, and others mediated by suppressing STAT3 as well as ALDH1, MMP2, MMP9, Bcl2 and upregulating Bax. Moreover, it has promising effects against sepsis-induced organ injury, hepatic disorders, diabetic nephropathy, ulcerative colitis, and immune disorders. These promising effects appear to be mediated by suppressing STAT3 as well as NF-κB, TLR4, and β-catenin expressions and effectively decreasing downstream cytokines TNF-α, IL-1β, and IL-6. Our review summarizes the available studies on the molecular biological mechanisms of NFX in cancer and other diseases and it is recommended to translate the studies in experimental animals and cultured cells and repurpose NFX in various diseases for scientific evidence based on human studies.

Repurposing medications for treatment of age-related macular degeneration: Insights from novel approaches to data mining

The economic and visual burdens associated with age-related macular degeneration (AMD) are expected to significantly increase in the coming years. As of now, interventions to delay or prevent AMD are limited. Hence, there is an urgent and unmet need to expand our therapeutic tools for AMD in a manner, that is, both efficient and cost-effective. In this review, we consider the idea of drug repurposing, in which existing medications with other indications can be re-imagined for treating AMD. We detail the results of several population-level studies that have shown associations between several candidates and decreased risk of AMD development or progression. Such candidates include the more extensively studied metformin and statins, in addition to recently identified candidates fluoxetine and l-DOPA (levodopa) that show promise. We then briefly explore results from an advanced bioinformatics study, which provides further evidence that existing medications are associated with AMD risk genes. Many of these candidates warrant further study in prospective, clinical trials, where their potential causal relationships with AMD can be thoroughly assessed.

A novel machine learning-based screening identifies statins as inhibitors of the calcium pump SERCA

We report a novel small-molecule screening approach that combines data augmentation and machine learning to identify Food and Drug Administration (FDA)-approved drugs interacting with the calcium pump (Sarcoplasmic reticulum Ca2+-ATPase, SERCA) from skeletal (SERCA1a) and cardiac (SERCA2a) muscle. This approach uses information about small-molecule effectors to map and probe the chemical space of pharmacological targets, thus allowing to screen with high precision large databases of small molecules, including approved and investigational drugs. We chose SERCA because it plays a major role in the excitation-contraction-relaxation cycle in muscle and it represents a major target in both skeletal and cardiac muscle. The machine learning model predicted that SERCA1a and SERCA2a are pharmacological targets for seven statins, a group of FDA-approved 3-hydroxy-3-methylglutaryl coenzyme A reductase inhibitors used in the clinic as lipid-lowering medications. We validated the machine learning predictions by using in vitro ATPase assays to show that several FDA-approved statins are partial inhibitors of SERCA1a and SERCA2a. Complementary atomistic simulations predict that these drugs bind to two different allosteric sites of the pump. Our findings suggest that SERCA-mediated Ca2+ transport may be targeted by some statins (e.g., atorvastatin), thus providing a molecular pathway to explain statin-associated toxicity reported in the literature. These studies show the applicability of data augmentation and machine learning-based screening as a general platform for the identification of off-target interactions and the applicability of this approach extends to drug discovery.

Disruption of Irisin Dimerization by FDA-Approved Drugs: A Computational Repurposing Approach for the Potential Treatment of Lipodystrophy Syndromes

In this paper, we present the development of a computer-based repurposing approach to identify FDA-approved drugs that are potentially able to interfere with irisin dimerization. It has been established that altered levels of irisin dimers are a pure hallmark of lipodystrophy (LD) syndromes. Accordingly, the identification of compounds capable of slowing down or precluding the irisin dimers' formation could represent a valuable therapeutic strategy in LD. Combining several computational techniques, we identified five FDA-approved drugs with satisfactory computational scores (iohexol, XP score = -7.70 kcal/mol, SP score = -5.5 kcal/mol, ΔG_bind = -61.47 kcal/mol, ΔG_bind (average) = -60.71 kcal/mol; paromomycin, XP score = -7.23 kcal/mol, SP score = -6.18 kcal/mol, ΔG_bind = -50.14 kcal/mol, ΔG_bind (average) = -49.13 kcal/mol; zoledronate, XP score = -6.33 kcal/mol, SP score = -5.53 kcal/mol, ΔG_bind = -32.38 kcal/mol, ΔG_bind (average) = -29.42 kcal/mol; setmelanotide, XP score = -6.10 kcal/mol, SP score = -7.24 kcal/mol, ΔG_bind = -56.87 kcal/mol, ΔG_bind (average) = -62.41 kcal/mol; and theophylline, XP score = -5.17 kcal/mol, SP score = -5.55 kcal/mol, ΔG_bind = -33.25 kcal/mol, ΔG_bind (average) = -35.29 kcal/mol) that are potentially able to disrupt the dimerization of irisin. For this reason, they deserve further investigation to characterize them as irisin disruptors. Remarkably, the identification of drugs targeting this process can offer novel therapeutic opportunities for the treatment of LD. Furthermore, the identified drugs could provide a starting point for a repositioning approach, synthesizing novel analogs with improved efficacy and selectivity against the irisin dimerization process.

The endocannabinoid system, a new gatekeeper in the pharmacology of human hepatocellular carcinoma

Despite numerous prevention methodologies and treatment options, hepatocellular carcinoma (HCC) still remains as the third leading life-threatening cancer. It is thus pertinent to develop new treatment modality to fight this devastating carcinoma. Ample recent studies have shown the anti-inflammatory and antitumor roles of the endocannabinoid system in various forms of cancers. Preclinical studies have also confirmed that cannabinoid therapy can be an optimal regimen for cancer treatments. The endocannabinoid system is involved in many cancer-related processes, including induction of endoplasmic reticulum (ER) stress-dependent apoptosis, autophagy, PITRK and ERK signaling pathways, cell invasion, epithelial-mesenchymal transition (EMT), and cancer stem cell (CSC) phenotypes. Moreover, changes in signaling transduction of the endocannabinoid system can be a potential diagnostic and prognostic biomarker for HCC. Due to its pivotal role in lipid metabolism, the endocannabinoid system affects metabolic reprogramming as well as lipid content of exosomes. In addition, due to the importance of non-coding RNAs (ncRNAs), several studies have examined the relationship between microRNAs and the endocannabinoid system in HCC. However, HCC is a pathological condition with high heterogeneity, and therefore using the endocannabinoid system for treatment has faced many controversies. While some studies favored a role of the endocannabinoid system in carcinogenesis and tumor induction, others exhibited the anticancer potential of endocannabinoids in HCC. In this review, specific studies delineating the relationship between endocannabinoids and HCC are examined. Based on collected findings, detailed studies of the molecular mechanism of endocannabinoids as well as preclinical studies for investigating therapeutic or carcinogenic impacts in HCC cancer are strongly suggested.