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

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.

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.

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.

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.

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.

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 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.

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.

Artificial Intelligence-based Efficacy Prediction of Phase 3 Clinical Trial for Repurposing Heart Failure Therapies

Introduction

Drug repurposing involves finding new therapeutic uses for already approved drugs, which can save costs as their pharmacokinetics and pharmacodynamics are already known. Predicting efficacy based on clinical endpoints is valuable for designing phase 3 trials and making Go/No-Go decisions, given the potential for confounding effects in phase 2.

Objectives

This study aims to predict the efficacy of the repurposed Heart Failure (HF) drugs for the Phase 3 Clinical Trial.

Methods

Our study presents a comprehensive framework for predicting drug efficacy in phase 3 trials, which combines drug-target prediction using biomedical knowledgebases with statistical analysis of real-world data. We developed a novel drug-target prediction model that uses low-dimensional representations of drug chemical structures and gene sequences, and biomedical knowledgebase. Furthermore, we conducted statistical analyses of electronic health records to assess the effectiveness of repurposed drugs in relation to clinical measurements (e.g., NT-proBNP).

Results

We identified 24 repurposed drugs (9 with a positive effect and 15 with a non-positive) for heart failure from 266 phase 3 clinical trials. We used 25 genes related to heart failure for drug-target prediction, as well as electronic health records (EHR) from the Mayo Clinic for screening, which contained over 58,000 heart failure patients treated with various drugs and categorized by heart failure subtypes. Our proposed drug-target predictive model performed exceptionally well in all seven tests in the BETA benchmark compared to the six cutting-edge baseline methods (i.e., best performed in 266 out of 404 tasks). For the overall prediction of the 24 drugs, our model achieved an AUCROC of 82.59% and PRAUC (average precision) of 73.39%.

Conclusion

The study demonstrated exceptional results in predicting the efficacy of repurposed drugs for phase 3 clinical trials, highlighting the potential of this method to facilitate computational drug repurposing.

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.

Thalassemia and Nanotheragnostics: Advanced Approaches for Diagnosis and Treatment

Thalassemia is a monogenic autosomal recessive disorder caused by mutations, which lead to abnormal or reduced production of hemoglobin. Ineffective erythropoiesis, hemolysis, hepcidin suppression, and iron overload are common manifestations that vary according to genotypes and dictate, which diagnosis and therapeutic modalities, including transfusion therapy, iron chelation therapy, HbF induction, gene therapy, and editing, are performed. These conventional therapeutic methods have proven to be effective, yet have several disadvantages, specifically iron toxicity, associated with them; therefore, there are demands for advanced therapeutic methods. Nanotechnology-based applications, such as the use of nanoparticles and nanomedicines for theragnostic purposes have emerged that are simple, convenient, and cost-effective methods. The therapeutic potential of various nanoparticles has been explored by developing artificial hemoglobin, nano-based iron chelating agents, and nanocarriers for globin gene editing by CRISPR/Cas9. Au, Ag, carbon, graphene, silicon, porous nanoparticles, dendrimers, hydrogels, quantum dots, etc., have been used in electrochemical biosensors development for diagnosis of thalassemia, quantification of hemoglobin in these patients, and analysis of conventional iron chelating agents. This review summarizes the potential of nanotechnology in the development of various theragnostic approaches to determine thalassemia-causing gene mutations using various nano-based biosensors along with the employment of efficacious nano-based therapeutic procedures, in contrast to conventional therapies.

Targeting Inflammation in Non-Small Cell Lung Cancer through Drug Repurposing

Lung cancer is the most common cause of cancer-related deaths. Lung cancers can be classified as small-cell (SCLC) or non-small cell (NSCLC). About 84% of all lung cancers are NSCLC and about 16% are SCLC. For the past few years, there have been a lot of new advances in the management of NSCLC in terms of screening, diagnosis and treatment. Unfortunately, most of the NSCLCs are resistant to current treatments and eventually progress to advanced stages. In this perspective, we discuss some of the drugs that can be repurposed to specifically target the inflammatory pathway of NSCLC utilizing its well-defined inflammatory tumor microenvironment. Continuous inflammatory conditions are responsible to induce DNA damage and enhance cell division rate in lung tissues. There are existing anti-inflammatory drugs which were found suitable for repurposing in non-small cell lung carcinoma (NSCLC) treatment and drug modification for delivery via inhalation. Repurposing anti-inflammatory drugs and their delivery through the airway is a promising strategy to treat NSCLC. In this review, suitable drug candidates that can be repurposed to treat inflammation-mediated NSCLC will be comprehensively discussed together with their administration via inhalation from physico-chemical and nanocarrier perspectives.

Enzymatic synthesis of amlodipine amides and evaluation of their anti-Trypanosoma cruzi activity

Advancing with our project about the development of new antiparasitic agents, we have enzymatically synthesized a series of amides derived from amlodipine, a calcium channel blocker used as an antihypertensive drug. Through lipase-catalyzed acylation with different carboxylic acids, nineteen amlodipine derivatives were obtained, eighteen of which were new compounds. To optimize the reaction conditions, the influence of several reaction parameters was analyzed, finding different requisites for aliphatic carboxylic acids and phenylacetic acids. All synthesized compounds were evaluated as antiproliferative agents against Trypanosoma cruzi, the etiological agent of American trypanosomiasis (Chagas' disease). Some of them showed significant activity against the amastigote form of T. cruzi, the clinically relevant form of the parasite. Among synthesized compounds, the derivatives of myristic and linolenic acids showed higher efficacy and lower cytotoxicity. These results added to the advantages shown by the enzymatic methodology, such as mild reaction conditions and low environmental impact, making this approach a valuable way to synthesize these amlodipine derivatives with an application as promising antiparasitic agents.

Are patents important indicators of innovation for Chagas disease treatment?

INTRODUCTION

Chagas disease is a neglected, endemic disease in 21 countries, spreading to non-endemic countries too. Like other neglected diseases affecting primarily low- and middle-income countries, low investment and the absence of new chemical entities from the industry occurred. Increased knowledge about the parasite, drug targets, and vector control has been observed, but this was not translated into new drugs. The partnerships of pharmaceutical companies with academies and consolidated networks to increment the new drugs and treatment research in Chagas disease are shown. The current review analyzes in detail the patents dealing with compounds candidates for new drugs and treatment. The patent search was performed using Orbit Intelligence® software in the 2001-2021 period.

AREAS COVERED

The author focused specifically on patents for the treatment, the new candidates disclosed in the patents, and the barriers to innovation.

EXPERT OPINION

Patents in Chagas disease have been increasing in the last years, although they do not bring new compounds to an effective treatment.

Significant perspectives on various viral infections targeted antiviral drugs and vaccines including COVID-19 pandemicity

A virus enters a living organism and recruits host metabolism to reproduce its own genome and proteins. The viral infections are intricate and cannot be completely removed through existing antiviral drugs. For example, the herpes, influenza, hepatitis and human immunodeficiency viruses are a few dreadful ones amongst them. Significant studies are needed to understand the viral entry and their growth in host cells to design effective antivirals. This review emphasizes the range of therapeutical antiviral drugs, inhibitors along with vaccines to fight against viral pathogens, especially for combating COVID-19. Moreover, we have provided the basic and in depth information about viral targets, drugs availability, their mechanisms of action, method of prevention of viral diseases and highlighted the significances of anticoagulants, convalescent plasma for COVID-19 treatment, scientific details of airborne transmission, characteristics of antiviral drug delivery using nanoparticles/carriers, nanoemulsions, nanogels, metal based nanoparticles, alike the future nanosystems through nanobubbles, nanofibers, nanodiamonds, nanotraps, nanorobots and eventually, the therapeutic applications of micro- and nanoparticulates, current status for clinical development against COVID-19 together with environmental implications of antivirals, gene therapy etc., which may be useful for repurposing and designing of novel antiviral drugs against various dreadful diseases, especially the SARS-CoV-2 and other associated variants.

Development of a ternary cyclodextrin–arginine–ciprofloxacin antimicrobial complex with enhanced stability

Designing useful functionalities in clinically validated, old antibiotics holds promise to provide the most economical solution for the global lack of effective antibiotics, as undoubtedly a serious health threat. Here we show that using the surface chemistry of the cyclodextrin (βCD) cycle and arginine (arg) as a linker, provides more stable ternary antibiotic complex (βCD-arg-cpx). In contrast to classical less stable inclusion complexes, which only modify antibiotic solubility, here-presented ternary complex is more stable and controls drug release. The components of the complex intensify interactions with bacterial membranes and increase the drug’s availability inside bacterial cells, thereby improving its antimicrobial efficacy and safety profile. Multifunctional antibiotics, formulated as drug delivery systems per se, that take the drug to the site of action, maximize its efficacy, and provide optical detectability are envisaged as the future in fighting against infections. Their role as a tool against multiresistant strains remains as interesting challenge open for further research.

The Allergic Rhinitis and Its Impact on Asthma (ARIA) Approach of Value-Added Medicines: As-Needed Treatment in Allergic Rhinitis

Drug repurposing is a major field of value-added medicine. It involves investigating and evaluating existing drugs for new therapeutic purposes that address unmet healthcare needs. Several unmet needs in allergic rhinitis could be improved by drug repurposing. This could be game-changing for disease management. Current medications for allergic rhinitis are centered on continuous long-term treatment, and medication registration is based on randomized controlled trials carried out for a minimum of 14 days with adherence of 70% or greater. A new way of treating allergic rhinitis is to propose as-needed treatment depending on symptoms, rather than classical continuous treatment. This rostrum will discuss existing clinical trials on as-needed treatment for allergic rhinitis and real-world data obtained by the mobile health app MASK-air, which focuses on digitally-enabled, patient-centered care pathways.

Utilizing clinical pharmacology in the drug repurposing arena: a look into COVID-19

INTRODUCTION

Drug repurposing represented an important contribution in the management of COVID-19, becoming the first line of defense to mitigate the effects of the new coronavirus. In a brief time, drug repurposing (DR) provided potentially effective and already available drugs for COVID-19, while specific therapies against SARS-CoV-2 and/or vaccines were developing. Identifying repurposed drugs requires a multidisciplinary approach, where clinical pharmacology represents the missing piece of the puzzle.

AREAS COVERED

Nowadays, clinical pharmacology is recognized as a discipline at the core of translational science, whose activities lead to the identification of the right drug for the right patient. In the context of the COVID-19 pandemic, its role in drug development and therapy choice has been decisive and itself repositioned. In this review, we tried to highlight the important role of clinical pharmacology in the identification and evaluation of possible repurposed drugs for COVID-19.

EXPERT OPINION

We believe that clinical pharmacology had an important role in identifying patient-oriented therapy during the COVID-19 pandemic. In this context, DR was just one of the challenges for clinical pharmacology, which proved that this discipline is ready to respond to future threats.

Drug repurposing-an emerging strategy in cancer therapeutics

Cancer is a complex disease affecting millions of people around the world. Despite advances in surgical and radiation therapy, chemotherapy continues to be an important therapeutic option for the treatment of cancer. The current treatment is expensive and has several side effects. Also, over time, cancer cells develop resistance to chemotherapy, due to which there is a demand for new drugs. Drug repurposing is a novel approach that focuses on finding new applications for the old clinically approved drugs. Current advances in the high-dimensional multiomics landscape, especially proteomics, genomics, and computational omics-data analysis, have facilitated drug repurposing. The drug repurposing approach provides cheaper, effective, and safe drugs with fewer side effects and fastens the process of drug development. The review further delineates each repurposed drug's original indication and mechanism of action in cancer. Along with this, the article also provides insight upon artificial intelligence and its application in drug repurposing. Clinical trials are vital for determining medication safety and effectiveness, and hence the clinical studies for each repurposed medicine in cancer, including their stages, status, and National Clinical Trial (NCT) identification, are reported in this review article. Various emerging evidences imply that repurposing drugs is critical for the faster and more affordable discovery of anti-cancerous drugs, and the advent of artificial intelligence-based computational tools can accelerate the translational cancer-targeting pipeline.