Drug repositioning: current approaches and their implications in the precision medicine era

Revolutionising Neurological Therapeutics: Investigating Drug Repurposing Strategies

Repurposing drugs (DR) has become a viable approach to hasten the search for cures for neurodegenerative diseases (NDs). This review examines different off-target and on-target drug discovery techniques and how they might be used to find possible treatments for non-diagnostic depressions. Off-target strategies look at the known or unknown side effects of currently approved drugs for repositioning, whereas on-target strategies connect disease pathways to targets that can be treated with drugs. The review highlights the potential of experimental and computational methodologies, such as machine learning, proteomic techniques, network and genomics-based approaches, and in silico screening, in uncovering new drug-disease correlations. It also looks at difficulties and failed attempts at drug repurposing for NDs, highlighting the necessity of exact and standardised procedures to increase success rates. This review's objectives are to address the purpose of drug repurposing in human disorders, particularly neurological diseases, and to provide an overview of repurposing candidates that are presently undergoing clinical trials for neurological conditions, along with any possible causes and early findings. We then include a list of drug repurposing strategies, restrictions, and difficulties for upcoming research.

Levofloxacin reposition-based design: synthesis, biological evaluation of new levofloxacin derivatives targeting topoisomerase II beta polymerase as promising anticancer agents, molecular docking, and physicochemical characterization

Repositioning of already approved medications through repurposing or re-profiling for new medical uses after certain structural modifications is a novel approach in drug discovery. Fluoroquinolone antibiotics are one of the cardinal agents investigated for potential anticancer activities. In this work, levofloxacin was repositioned for anticancer activities. A series of levofloxacin-based compounds were designed and synthesized through the derivatization of levofloxacin's carboxylic acid functionality. The newly synthesized compounds were screened for cytotoxic activities against breast, liver, and leukemia cancer cell lines. Their effect on normal cells was also investigated. The target compounds were evaluated for their proliferative inhibitory activity toward topoisomerase II beta polymerization. Compound 5 showed higher inhibitory activity against a breast cancer cell line (MCF-7) with IC50 = 1.4 μM and lesser side effects on a normal breast cell line (MCF-10a) with IC50 = 30.40 μM than reference drugs. The best activity against a liver cancer cell line (Hep3B) was exhibited by compounds 3c, 4b, 5, 7, 8, 13a and 13c with IC50 values ranging from 0.43 to 8.79 μM. Regarding the effect of compounds 5 and 13a on a leukemia cancer cell line (L-SR), their IC50 values were 0.96 and 3.12 μM, respectively. Compounds 3c and 5 showed Topo2β inhibitory effects on Hep3B cells (81.33% and 83.73%, respectively), which was better than levofloxacin and etoposide as reference drugs. Cytometry cell cycle analysis revealed that compounds 3c and 5 arrested the cell cycle at the S phase (37.56% and 39.09%, respectively). Compounds 3c and 5 exhibited an elevation in active caspase-3 levels by 4.9 and 4.5 folds, respectively. Molecular modeling simulation of compounds 3c and 5 demonstrated energy scores (-29.77 and -20.46 kcal mol-1, respectively) more than those of the reference drugs as they interact with the most essential amino acids required for good affinity towards human topoisomerase II beta enzyme (PDB ID: 3QX3). Physicochemical characteristics of the most promising cytotoxic compounds 3c and 5 were investigated and compared to etoposide and levofloxacin as reference drugs. However, they showed high gastrointestinal absorption and could not penetrate the blood-brain barrier.

Synergizing drug repurposing and target identification for neurodegenerative diseases

Despite dedicated research efforts, the absence of disease-curing remedies for neurodegenerative diseases (NDDs) continues to jeopardize human society and stands as a challenge. Drug repurposing is an attempt to find new functionality of existing drugs and take it as an opportunity to discourse the clinically unmet need to treat neurodegeneration. However, despite applying this approach to rediscover a drug, it can also be used to identify the target on which a drug could work. The primary objective of target identification is to unravel all the possibilities of detecting a new drug or repurposing an existing drug. Lately, scientists and researchers have been focusing on specific genes, a particular site in DNA, a protein, or a molecule that might be involved in the pathogenesis of the disease. However, the new era discusses directing the signaling mechanism involved in the disease progression, where receptors, ion channels, enzymes, and other carrier molecules play a huge role. This review aims to highlight how target identification can expedite the whole process of drug repurposing. Here, we first spot various target-identification methods and drug-repositioning studies, including drug-target and structure-based identification studies. Moreover, we emphasize various drug repurposing approaches in NDDs, namely, experimental-based, mechanism-based, and in silico approaches. Later, we draw attention to validation techniques and stress on drugs that are currently undergoing clinical trials in NDDs. Lastly, we underscore the future perspective of synergizing drug repurposing and target identification in NDDs and present an unresolved question to address the issue.

A gene regulatory network approach harmonizes genetic and epigenetic signals and reveals repurposable drug candidates for multiple sclerosis

Multiple sclerosis (MS) is a complex dysimmune disorder of the central nervous system. Genome-wide association studies (GWAS) have identified 233 genetic variations associated with MS at the genome-wide significant level. Epigenetic studies have pinpointed differentially methylated CpG sites in MS patients. However, the interplay between genetic risk factors and epigenetic regulation remains elusive. Here, we employed a network model to integrate GWAS summary statistics of 14 802 MS cases and 26 703 controls with DNA methylation profiles from 140 MS cases and 139 controls and the human interactome. We identified differentially methylated genes by aggregating additive effects of differentially methylated CpG sites within promoter regions. We reconstructed a gene regulatory network (GRN) using literature-curated transcription factor knowledge. Colocalization of the MS GWAS and methylation quantitative trait loci (mQTL) was performed to assess the GRN. The resultant MS-associated GRN highlighted several single nucleotide polymorphisms with GWAS-mQTL colocalization: rs6032663, rs6065926 and rs2024568 of CD40 locus, rs9913597 of STAT3 locus, and rs887864 and rs741175 of CIITA locus. Moreover, synergistic mQTL and expression QTL signals were identified in CD40, suggesting gene expression alteration was likely induced by epigenetic changes. Web-based Cell-type Specific Enrichment Analysis of Genes (WebCSEA) indicated that the GRN was enriched in T follicular helper cells (P-value = 0.0016). Drug target enrichment analysis of annotations from the Therapeutic Target Database revealed the GRN was also enriched with drug target genes (P-value = 3.89 × 10-4), revealing repurposable candidates for MS treatment. These candidates included vorinostat (HDAC1 inhibitor) and sivelestat (ELANE inhibitor), which warrant further investigation.

Combating Lassa Fever in West African Sub-Region: Progress, Challenges, and Future Perspectives

Lassa fever (LF) is a rodent-borne disease that threatens human health in the sub-region of West Africa where the zoonotic host of Lassa virus (LASV) is predominant. Currently, treatment options for LF are limited and since no preventive vaccine is approved for its infectivity, there is a high mortality rate in endemic areas. This narrative review explores the transmission, pathogenicity of LASV, advances, and challenges of different treatment options. Our findings indicate that genetic diversity among the different strains of LASV and their ability to circumvent the immune system poses a critical challenge to the development of LASV vaccines/therapeutics. Thus, understanding the biochemistry, physiology and genetic polymorphism of LASV, mechanism of evading host immunity are essential for development of effective LASV vaccines/therapeutics to combat this lethal viral disease. The LASV nucleoprotein (NP) is a novel target for therapeutics as it functions significantly in several aspects of the viral life cycle. Consequently, LASV NP inhibitors could be employed as effective therapeutics as they will potentially inhibit LASV replication. Effective preventive control measures, vaccine development, target validation, and repurposing of existing drugs, such as ribavirin, using activity or in silico-based and computational bioinformatics, would aid in the development of novel drugs for LF management.

Drug Repurposing at the Interface of Melanoma Immunotherapy and Autoimmune Disease

Cancer cells have a remarkable ability to evade recognition and destruction by the immune system. At the same time, cancer has been associated with chronic inflammation, while certain autoimmune diseases predispose to the development of neoplasia. Although cancer immunotherapy has revolutionized antitumor treatment, immune-related toxicities and adverse events detract from the clinical utility of even the most advanced drugs, especially in patients with both, metastatic cancer and pre-existing autoimmune diseases. Here, the combination of multi-omics, data-driven computational approaches with the application of network concepts enables in-depth analyses of the dynamic links between cancer, autoimmune diseases, and drugs. In this review, we focus on molecular and epigenetic metastasis-related processes within cancer cells and the immune microenvironment. With melanoma as a model, we uncover vulnerabilities for drug development to control cancer progression and immune responses. Thereby, drug repurposing allows taking advantage of existing safety profiles and established pharmacokinetic properties of approved agents. These procedures promise faster access and optimal management for cancer treatment. Together, these approaches provide new disease-based and data-driven opportunities for the prediction and application of targeted and clinically used drugs at the interface of immune-mediated diseases and cancer towards next-generation immunotherapies.

Therapeutic drug repositioning with special emphasis on neurodegenerative diseases: Threats and issues

Drug repositioning or repurposing is the process of discovering leading-edge indications for authorized or declined/abandoned molecules for use in different diseases. This approach revitalizes the traditional drug discovery method by revealing new therapeutic applications for existing drugs. There are numerous studies available that highlight the triumph of several drugs as repurposed therapeutics. For example, sildenafil to aspirin, thalidomide to adalimumab, and so on. Millions of people worldwide are affected by neurodegenerative diseases. According to a 2021 report, the Alzheimer's disease Association estimates that 6.2 million Americans are detected with Alzheimer's disease. By 2030, approximately 1.2 million people in the United States possibly acquire Parkinson's disease. Drugs that act on a single molecular target benefit people suffering from neurodegenerative diseases. Current pharmacological approaches, on the other hand, are constrained in their capacity to unquestionably alter the course of the disease and provide patients with inadequate and momentary benefits. Drug repositioning-based approaches appear to be very pertinent, expense- and time-reducing strategies for the enhancement of medicinal opportunities for such diseases in the current era. Kinase inhibitors, for example, which were developed for various oncology indications, demonstrated significant neuroprotective effects in neurodegenerative diseases. This review expounds on the classical and recent examples of drug repositioning at various stages of drug development, with a special focus on neurodegenerative disorders and the aspects of threats and issues viz. the regulatory, scientific, and economic aspects.

Medicinal Chemistry of Inhibitors Targeting Resistant Bacteria

The discovery of antibiotics was a revolutionary feat that provided countless health benefits. The identification of penicillin by Alexander Fleming initiated the era of antibiotics, represented by constant discoveries that enabled effective treatments for the different classes of diseases caused by bacteria. However, the indiscriminate use of these drugs allowed the emergence of resistance mechanisms of these microorganisms against the available drugs. In addition, the constant discoveries in the 20th century generated a shortage of new molecules, worrying health agencies and professionals about the appearance of multidrug-resistant strains against available drugs. In this context, the advances of recent years in molecular biology and microbiology have allowed new perspectives in drug design and development, using the findings related to the mechanisms of bacterial resistance to generate new drugs that are not affected by such mechanisms and supply new molecules to be used to treat resistant bacterial infections. Besides, a promising strategy against bacterial resistance is the combination of drugs through adjuvants, providing new expectations in designing new antibiotics and new antimicrobial therapies. Thus, this manuscript will address the main mechanisms of bacterial resistance under the understanding of medicinal chemistry, showing the main active compounds against efflux mechanisms, and also the application of the use of drug delivery systems, and finally, the main potential natural products as adjuvants or with promising activity against resistant strains.

RP-HPLC Method Development, Validation, and Drug Repurposing of Sofosbuvir Pharmaceutical Dosage Form: A Multidimensional Study

A smooth, exceptionally sensitive, correct, and extra reproducible RP-HPLC technique was developed and demonstrated to estimate Sofosbuvir (SOF) in pharmaceutical dosage formulations. This process was carried out by Agilent High-Pressure Liquid Chromatograph 1260 with GI311C Quat. Pump, Phenomenex Luna C-18 (150 mm × 4.6 mm × 5 μm) (USA), and Photodiode Array Detector (PDA) G1315D. The cell section, including acetonitrile and methanol with 80:20 v/v and solution (B) 0.1% phosphoric acid (40:60), was used for the study. However, 10 μL of the sample was injected with a drift flow of 1 mL/min. The separation occurred at a column temperature of 30 °C, and the eluents used PDA set at 260 nm. The retention time of SOF was 5 min. The calibration curve was modified linearly within the range of 0.05-0.15 mg/mL with a correlation coefficient of 0.99 and genuine linear dating among top vicinity and consciousness in the calibration curve. The detection and quantification restrictions were 0.001 and 0.003 mg/mL, respectively. SOF recovery from pharmaceutical components ranged from 98% to 99%. The percentage assay of SOF was 99%. Analytical validation parameters, such as specificity, linearity, precision, accuracy, and selectivity, were studied, and the percentage relative standard deviation (%RSD) was less than 2%. All other key parameters were observed within the desired thresholds. Hence, the proposed RP-HPLC technique was proven effective for developing SOF in bulk and pharmaceutical pill dosage forms. SOF was found to interact with SARS-COV-2 nsp12, and molecular docking results revealed its high affinity and firm binding within the active site groove of nsp12. The key interacting residues include; LYS-72, GLN-75, MET-80 ALA-99, ASN-99, TRP-100, TYR-101 with ASN-99 and TRP-100 forming hydrogen bonds. Molecular Dynamics simulation of SOF and nsp12 complex elucidated that the system was stable throughout 20ns. Therefore, this drug repurposing strategy for SOF can be used for treating COVID-19 infections by performing animal experiments and accurate clinical trials in the future.

Dual Acting Immuno-Antibiotics: Computational Investigation on Antibacterial Efficacy of Immune Boosters Against Isoprenoid H Enzyme

Drug-resistant infections have become a serious threat to human health in the past two decades. Global Antimicrobial Surveillance (GLASS) in January 2018 reported widespread antibiotic resistance among 1.5 million people infected with bacteria across 22 countries. According to prominent economist Jim O'Neil, antimicrobial resistance is estimated to kill ∼10 million people affected by microorganisms each year by 2050. Even though multiple therapeutics are now available to treat the infections, more and more bacterial strains have acquired resistance to these treatments through various techniques. Moreover, the decrease in the pipeline of antibacterial medicines under clinical development has become a significant problem. In this scenario, the development of novel antibiotics that act on untapped pathways is necessary to combat the bacterial infections. Isoprenoid H (IspH) synthetase has become an attractive antibacterial target as there is no human homologue. IspH is an enzyme involved in methyl-d-erythritol phosphate (MEP) pathway of isoprenoid synthesis and is conserved in gram-negative bacteria, mycobacteria, and apicomplexans. Since, IspH is a novel therapeutic target, explorations are only just beginning, and despite the progress made in this area, no single IspH inhibitor is available in the market for therapeutic use. In this article, we have repurposed 35 immune boosters against IspH enzyme using methods such as extra-precision docking and Molecular Mechanics Generalized Born Surface Area (MMGBSA). Among them, 4'-fluorouridine was found to be active because of its glide score and significant binding affinity with IspH enzyme. Furthermore, this study requires more in vitro, in vivo, and molecular dynamics studies to support our findings.

Old drugs, new tricks: Emerging role of drug repurposing in the management of atopic dermatitis

Atopic dermatitis is a chronic recurring pruritic inflammatory skin disease manifested by increased pro-inflammatory mediators which lead to dry, thickened, cracked, scaly skin. The current treatment options for atopic dermatitis management comprise drawbacks and leave unmet effective clinical needs. So, the approach for repurposing existing drugs for atopic dermatitis management may potentially overcome these unmet needs. Diseases that share the common pathophysiological pathways with atopic dermatitis can serve as a foundation for the repurposing of drugs. Drugs used in the management of cancer, rheumatoid arthritis, and other immune-mediated diseases such as psoriasis are under investigation to know the potential in atopic dermatitis management by utilizing repurposing strategies for a novel therapeutic indication. This review mainly envisages the probable repurposing of drugs for the management of atopic dermatitis disease; the barriers and regulatory aspects involved in the repurposing of existing drugs.

Inhibition of PRMT5 by market drugs as a novel cancer therapeutic avenue

Market drugs, such as Food and Drug Administration (FDA) or European Medicines Agency (EMA)-approved drugs for specific indications provide opportunities for repurposing for newer therapeutics. This potentially saves resources invested in clinical trials that verify drug safety and tolerance in humans prior to alternative indication approval. Protein arginine methyltransferase 5 (PRMT5) overexpression has been linked to promoting the tumor phenotype in several cancers, including pancreatic ductal adenocarcinoma (PDAC), colorectal cancer (CRC), and breast cancer (BC), making PRMT5 an important target for cancer therapy. Previously, we showed that PRMT5-mediated methylation of the nuclear factor (NF)-κB, partially contributes to its constitutive activation observed in cancers. In this study, we utilized an AlphaLISA-based high-throughput screening method adapted in our lab, and identified one FDA-approved drug, Candesartan cilexetil (Can, used in hypertension treatment) and one EMA-approved drug, Cloperastine hydrochloride (Clo, used in cough treatment) that had significant PRMT5-inhibitory activity, and their anti-tumor properties were validated using cancer phenotypic assays in vitro. Furthermore, PRMT5 selective inhibition of methyltransferase activity was confirmed by reduction of both NF-κB methylation and its subsequent activation upon drug treatment. Using in silico prediction, we identified critical residues on PRMT5 targeted by these drugs that may interfere with its enzymatic activity. Finally, Clo and Can treatment have exhibited marked reduction in tumor growth in vivo. Overall, we provide basis for pursuing repurposing Clo and Can as anti-PRMT5 cancer therapies. Our study offers potential safe and fast repurposing of previously unknown PRMT5 inhibitors into clinical practice.

Evaluating the performance of drug-repurposing technologies

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

Repurposing Antihypertensive Drugs for the Management of Alzheimer's Disease

Alzheimer's disease (AD) is a neurodegenerative disorder that has affected millions of people worldwide. However, currently, there is no treatment to cure the disease. The AD drugs available in the market only manage the disease symptomatically and the effects are usually short-term. Thus, there is a need to look at alternatives AD therapies. This literature review aims to shed some light on the potential of repurposing antihypertensives to treat AD. Mid-life hypertension has not only been recognised as a risk factor for AD, but its relation with AD has also been well established. Hence, antihypertensives were postulated to be beneficial in managing AD. Four classes of antihypertensives, as well as their potential limitations and prospects in being utilised as AD therapeutics, were discussed in this review.

An Analytical Review of Computational Drug Repurposing

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

Signature-based approaches for informed drug repurposing: targeting CNS disorders

CNS disorders, and in particular psychiatric illnesses, lack definitive disease-altering therapeutics. The limited understanding of the mechanisms driving these illnesses with the slow pace and high cost of drug development exacerbates this issue. For these reasons, drug repurposing - both a less expensive and time-efficient practice compared to de novo drug development - has been a promising strategy to overcome the paucity of treatments available for these debilitating disorders. While empirical drug-repurposing has been a routine practice in clinical psychiatry, innovative, informed, and cost-effective repurposing efforts using big data ("omics") have been designed to characterize drugs by structural and transcriptomic signatures. These strategies, in conjunction with ontological integration, provide an important opportunity to address knowledge-based challenges associated with drug development for CNS disorders. In this review, we discuss various signature-based in silico approaches to drug repurposing, its integration with multiple omics platforms, and how this data can be used for clinically relevant, evidence-based drug repurposing. These tools provide an exciting translational avenue to merge omics-based drug discovery platforms with patient-specific disease signatures, ultimately facilitating the identification of new therapies for numerous psychiatric disorders.

Repurposing Drugs for COVID-19: Pharmacokinetics and Pharmacogenomics of Chloroquine and Hydroxychloroquine

Background

A new coronavirus SARS-CoV-2 has been identified as the etiological agent of the severe acute respiratory syndrome, COVID-19, the source and cause of the 2019–20 coronavirus pandemic. Hydroxychloroquine and chloroquine have gathered extraordinary attention as therapeutic candidates against SARS-CoV-2 infections. While there is growing scientific data on the therapeutic effect, there is also concern for toxicity of the medications. The therapy of COVID-19 by hydroxychloroquine and chloroquine is off-label. Studies to analyze the personalized effect and safety are lacking.

Methods

A review of the literature was performed using Medline/PubMed/Embase database. A variety of keywords were employed in keyword/title/abstract searches. The electronic search was followed by extensive hand searching using reference lists from the identified articles.

Results

A total of 126 results were obtained after screening all sources. Mechanisms underlying variability in drug concentrations and therapeutic response with chloroquine and hydroxychloroquine in mediating beneficial and adverse effects of chloroquine and hydroxychloroquine were reviewed and analyzed. Pharmacogenomic studies from various disease states were evaluated to elucidate the role of genetic variation in drug response and toxicity.

Conclusion

Knowledge of the pharmacokinetics and pharmacogenomics of chloroquine and hydroxychloroquine is necessary for effective and safe dosing and to avoid treatment failure and severe complications.

Utilizing drug repurposing against COVID-19 - Efficacy, limitations, and challenges

The recent outbreak of Coronavirus disease (COVID-19), first in Eastern Asia and then essentially across the world has been declared a pandemic by the WHO. COVID-19 is caused by a novel virus SARS-CoV2 (2019-nCoV), against which there is currently no vaccine available; and current antiviral therapies have failed, causing a very high mortality rate. Drug repurposing i.e. utilizing an approved drug for different indication, offers a time- and cost-efficient alternative for making new therapies available to patients. Although there are several reports presenting novel approaches to treat COVID-19, still an attentive review of previous scientific literature is essential to overcome their failure to exhibit efficacy. There is an urgent need to provide a comprehensive outlook toward utilizing drug repurposing as a tool for discovery of new therapies against COVID-19. In this article, we aim to provide a to-the-point review of current literature regarding efficacy of repurposed drugs against COVID-19 and other respiratory infections caused by coronaviruses. We have briefly discussed COVID-19 epidemiology, and then have discussed drug repurposing approaches and examples, specific to respiratory viruses. Limitations of utilization of repurposed drug molecules such as dosage regimen and associated challenges such as localized delivery in respiratory tract have also been discussed in detail.

Applications of Genome-Wide Screening and Systems Biology Approaches in Drug Repositioning

Modern drug discovery through de novo drug discovery entails high financial costs, low success rates, and lengthy trial periods. Drug repositioning presents a suitable approach for overcoming these issues by re-evaluating biological targets and modes of action of approved drugs. Coupling high-throughput technologies with genome-wide essentiality screens, network analysis, genome-scale metabolic modeling, and machine learning techniques enables the proposal of new drug-target signatures and uncovers unanticipated modes of action for available drugs. Here, we discuss the current issues associated with drug repositioning in light of curated high-throughput multi-omic databases, genome-wide screening technologies, and their application in systems biology/medicine approaches.

Identifying Drug Repurposing Opportunities in Oncology

The never-ending explosion in the cost of new oncology drugs is reducing in many countries the access to the most recent, effective anticancer therapies and represents a significant obstacle to the design and realization of combinatorial trials. Already approved, anticancer and nonanticancer drugs can be considered for in silico, preclinical, and clinical repurposing approaches and offer the significant advantages of a potentially cheaper, faster, and safer validation. This review discusses recent advances and challenges in the field.

Has Drug Repurposing Fulfilled its Promise in Acute Myeloid Leukaemia?

Drug repurposing is a method of drug discovery that consists of finding a new therapeutic context for an old drug. Compound identification arises from screening of large libraries of active compounds, through interrogating databases of cell line gene expression response upon treatment or by merging several types of information concerning disease-drug relationships. Although, there is a general consensus on the potential and advantages of this drug discovery modality, at the practical level to-date no non-anti-cancer repurposed compounds have been introduced into standard acute myeloid leukaemia (AML) management, albeit that preclinical validation yielded several candidates. The review presents the state-of-the-art drug repurposing approach in AML and poses the question of what has to be done in order to take a full advantage of it, both at the stage of screening design and later when progressing from the preclinical to the clinical phases of drug development. We argue that improvements are needed to model and read-out systems as well as to screening technologies, but also to more funding and trust in drug repurposing strategies.

Inkjet Bioprinting on Parchment Paper for Hit Identification from Small Molecule Libraries

In this study, an inkjet bioprinting-based high-throughput screening (HTS) system was designed and applied for the first time to a catecholpyrimidine-based small molecule library to find hit compounds that inhibit c-Jun NH₂-terminal kinase1 (JNK1). JNK1 kinase, inactivated MAPKAPK2, and specific fluorescent peptides along with bioink were printed on parchment paper under optimized printing conditions that did not allow rapid evaporation of printed media based on Triton-X and glycerol. Subsequently, different small compounds were printed and tested against JNK1 kinase to evaluate their degree of phosphorylation inhibition. After printing and incubation, fluorescence intensities from the phosphorylated/nonphosphorylated peptide were acquired for the % phosphorylation analysis. The IM₅₀ (inhibitory mole 50) value was determined as 1.55 × 10^-15 mol for the hit compound, 22. Thus, this work demonstrated that inkjet bioprinting-based HTS can potentially be adopted for the drug discovery process using small molecule libraries, and cost-effective HTS can be expected to be established based on its low nano- to picoliter printing volume.

The assessment of efficient representation of drug features using deep learning for drug repositioning

BACKGROUND

De novo drug discovery is a time-consuming and expensive process. Nowadays, drug repositioning is utilized as a common strategy to discover a new drug indication for existing drugs. This strategy is mostly used in cases with a limited number of candidate pairs of drugs and diseases. In other words, they are not scalable to a large number of drugs and diseases. Most of the in-silico methods mainly focus on linear approaches while non-linear models are still scarce for new indication predictions. Therefore, applying non-linear computational approaches can offer an opportunity to predict possible drug repositioning candidates.

RESULTS

In this study, we present a non-linear method for drug repositioning. We extract four drug features and two disease features to find the semantic relations between drugs and diseases. We utilize deep learning to extract an efficient representation for each feature. These representations reduce the dimension and heterogeneity of biological data. Then, we assess the performance of different combinations of drug features to introduce a pipeline for drug repositioning. In the available database, there are different numbers of known drug-disease associations corresponding to each combination of drug features. Our assessment shows that as the numbers of drug features increase, the numbers of available drugs decrease. Thus, the proposed method with large numbers of drug features is as accurate as small numbers.

CONCLUSION

Our pipeline predicts new indications for existing drugs systematically, in a more cost-effective way and shorter timeline. We assess the pipeline to discover the potential drug-disease associations based on cross-validation experiments and some clinical trial studies.

Computational Drug Repurposing Algorithm Targeting TRPA1 Calcium Channel as a Potential Therapeutic Solution for Multiple Sclerosis

Multiple sclerosis (MS) is a chronic autoimmune disease affecting the central nervous system (CNS) through neurodegeneration and demyelination, leading to physical/cognitive disability and neurological defects. A viable target for treating MS appears to be the Transient Receptor Potential Ankyrin 1 (TRPA1) calcium channel, whose inhibition has been shown to have beneficial effects on neuroglial cells and protect against demyelination. Using computational drug discovery and data mining methods, we performed an in silico screening study combining chemical graph mining, quantitative structure-activity relationship (QSAR) modeling, and molecular docking techniques in a global prediction model in order to identify repurposable drugs as potent TRPA1 antagonists that may serve as potential treatments for MS patients. After screening the DrugBank database with the combined generated algorithm, 903 repurposable structures were selected, with 97 displaying satisfactory inhibition probabilities and pharmacokinetics. Among the top 10 most probable inhibitors of TRPA1 with good blood brain barrier (BBB) permeability, desvenlafaxine, paliperidone, and febuxostat emerged as the most promising repurposable agents for treating MS. Molecular docking studies indicated that desvenlafaxine, paliperidone, and febuxostat are likely to induce allosteric TRPA1 channel inhibition. Future in vitro and in vivo studies are needed to confirm the biological activity of the selected hit molecules.

In silico Guided Drug Repurposing: Discovery of New Competitive and Non-competitive Inhibitors of Falcipain-2

Malaria is among the leading causes of death worldwide. The emergence of Plasmodium falciparum resistant strains with reduced sensitivity to the first line combination therapy and suboptimal responses to insecticides used for Anopheles vector management have led to renewed interest in novel therapeutic options. Here, we report the development and validation of an ensemble of ligand-based computational models capable of identifying falcipain-2 inhibitors, and their subsequent application in the virtual screening of DrugBank and Sweetlead libraries. Among four hits submitted to enzymatic assays, two (odanacatib, an abandoned investigational treatment for osteoporosis and bone metastasis, and the antibiotic methacycline) confirmed inhibitory effects on falcipain-2, with Ki of 98.2 nM and 84.4 μM. Interestingly, Methacycline proved to be a non-competitive inhibitor (α = 1.42) of falcipain-2. The effects of both hits on falcipain-2 hemoglobinase activity and on the development of P. falciparum were also studied.

Insights into Computational Drug Repurposing for Neurodegenerative Disease

Computational drug repurposing has the ability to remarkably reduce drug development time and cost in an era where these factors are prohibitively high. Several examples of successful repurposed drugs exist in fields such as oncology, diabetes, leprosy, inflammatory bowel disease, among others, however computational drug repurposing in neurodegenerative disease has presented several unique challenges stemming from the lack of validation methods and difficulty in studying heterogenous diseases of aging. Here, we examine existing approaches to computational drug repurposing, including molecular, clinical, and biophysical methods, and propose data sources and methods to advance computational drug repurposing in neurodegenerative disease using Alzheimer's disease as an example.

Using What We Already Have: Uncovering New Drug Repurposing Strategies in Existing Omics Data

The promise of drug repurposing is to accelerate the translation of knowledge to treatment of human disease, bypassing common challenges associated with drug development to be more time- and cost-efficient. Repurposing has an increased chance of success due to the previous validation of drug safety and allows for the incorporation of omics. Hypothesis-generating omics processes inform drug repurposing decision-making methods on drug efficacy and toxicity. This review summarizes drug repurposing strategies and methodologies in the context of the following omics fields: genomics, epigenomics, transcriptomics, proteomics, metabolomics, microbiomics, phenomics, pregomics, and personomics. While each omics field has specific strengths and limitations, incorporating omics into the drug repurposing landscape is integral to its success.

DrugR+: A comprehensive relational database for drug repurposing, combination therapy, and replacement therapy

Drug repurposing or repositioning, which introduces new applications of the existing drugs, is an emerging field in drug discovery scope. To enhance the success rate of the research and development (R&D) process in a cost- and time-effective manner, a number of pharmaceutical companies worldwide have made tremendous investments. Besides, many researchers have proposed various methods and databases for the repurposing of various drugs. However, there is not a proper and well-organized database available. To this end, for the first time, we developed a new database based on DrugBank and KEGG data, which is named "DrugR+". Our developed database provides some advantages relative to the DrugBank, and its interface supplies new capabilities for both single and synthetic repositioning of drugs. Moreover, it includes four new datasets which can be used for predicting drug-target interactions using supervised machine learning methods. As a case study, we introduced novel applications of some drugs and discussed the obtained results. A comparison of several machine learning methods on the generated datasets has also been reported in the Supplementary File. Having included several normalized tables, DrugR + has been organized to provide key information on data structures for the repurposing and combining applications of drugs. It provides the SQL query capability for professional users and an appropriate method with different options for unprofessional users. Additionally, DrugR + consists of repurposing service that accepts a drug and proposes a list of potential drugs for some usages. Taken all, DrugR+ is a free web-based database and accessible using (http://www.drugr.ir), which can be updated through a map-reduce parallel processing method to provide the most relevant information.

Review on chemogenomic approaches towards hepatitis C viral targets

Hepatitis C virus (HCV) is the most prevalent viral pathogen that infects more than 185 million people worldwide. HCV infection leads to chronic liver diseases such as liver cirrhosis and hepatocellular carcinoma. Direct-acting antivirals (DAAs) are the recent combination therapy for HCV infection with reduced side effects than prior therapies. Sustained virological response (SVR) acts as a gold standard marker to monitor the success of antiviral treatment. Older treatment therapies attain 50-55% of SVR compared with DAAs which attain around 90-95%. The current review emphasizes the recent chemogenomic updates that have been unfolded through structure-based drug design of HCV drug target proteins (NS3/4A, NS5A, and NS5B) and ligand-based drug design of DAAs in achieving a stable HCV viral treatment strategies.