In Silico Strategies for Prospective Drug Repositionings

A special issue of Pharmaceutics (ISSN 1999-4923). This special issue belongs to the section "Pharmacokinetics and Pharmacodynamics".

Deadline for manuscript submissions: closed (20 May 2022) | Viewed by 49553

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Special Issue Editors


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Guest Editor
Department I—Drug Analysis, “Victor Babeş” University of Medicine and Pharmacy Timişoara, 300041 Timişoara, Romania
Interests: drug repositioning; network pharmacology; drug–drug interactions; drug–drug similarity networks; drug solubility; drug bioavailability; biopharmacy; drug–cyclodextrin inclusion complexes
Special Issues, Collections and Topics in MDPI journals

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Guest Editor
Faculty of Pharmacy, “Victor Babeș” University of Medicine and Pharmacy Timișoara, Romania; Institute of Chemistry Timișoara of the Romanian Academy
Interests: computational chemistry; quantum chemistry calculations; conformational analysis; molecular modeling; biological activity; QSAR; QSPR; molecular docking; drug repositioning

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Guest Editor
Ming Hsieh Department of Electrical Engineering, University of Southern California, Los Angeles, CA 90007, USA
Interests: drug–drug interaction networks; network science for drug repurposing; complex networks; artificial intelligence; data science
Special Issues, Collections and Topics in MDPI journals

E-Mail Website
Guest Editor
Department of Computer and Information Technology, Politehnica University of Timișoara, Timișoara, Romania
Interests: bioinformatics; complex network analysis; network science for drug repurposing; machine learning; big data exploration and visualization

Special Issue Information

Dear Colleagues,

The discovery of new drugs is one of the most exciting and challenging tasks of pharmaceutical research. Unfortunately, the conventional drug discovery procedure is chronophagous and seldom successful; furthermore, new drugs are needed to address the clinical challenges we face (e.g., new antibiotics, new anticancer drugs, new antivirals).

Within this framework, drug repositioning—finding new pharmacodynamic properties for already approved drugs—becomes a worthy drug discovery strategy.

Recent drug discovery techniques combine traditional tools with in silico strategies to identify previously unaccounted properties for drugs already in use. Indeed, big data exploration techniques capitalize on the ever-growing knowledge of drugs' structural and physicochemical properties, the drug–target and drug–drug interactions, the advances in human biochemistry, and the latest discoveries in molecular and cellular biology.

We are welcoming papers presenting innovative methods that connect traditional drug discovery techniques with computer-based tools to deliver robust drug repurposing hints. We do not necessarily require in vitro or in vivo validation of such hints; however, the authors need to perform cross-validation with existing knowledge (i.e., databases and literature) or other state-of-the-art drug repurposing pipelines.

Dr. Lucreția Udrescu
Prof. Dr. Ludovic Kurunczi
Prof. Dr. Paul Bogdan
Prof. Dr. Mihai Udrescu
Guest Editors

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Keywords

  • drug repositioning
  • systems pharmacology
  • drug–drug interactions
  • drug–drug similarity networks
  • complex network analysis

Published Papers (15 papers)

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Research

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15 pages, 1669 KiB  
Article
Drug-Disease Severity and Target-Disease Severity Interaction Networks in COVID-19 Patients
by Verena Schöning and Felix Hammann
Pharmaceutics 2022, 14(9), 1828; https://doi.org/10.3390/pharmaceutics14091828 - 30 Aug 2022
Viewed by 1651
Abstract
Drug interactions with other drugs are a well-known phenomenon. Similarly, however, pre-existing drug therapy can alter the course of diseases for which it has not been prescribed. We performed network analysis on drugs and their respective targets to investigate whether there are drugs [...] Read more.
Drug interactions with other drugs are a well-known phenomenon. Similarly, however, pre-existing drug therapy can alter the course of diseases for which it has not been prescribed. We performed network analysis on drugs and their respective targets to investigate whether there are drugs or targets with protective effects in COVID-19, making them candidates for repurposing. These networks of drug-disease interactions (DDSIs) and target-disease interactions (TDSIs) revealed a greater share of patients with diabetes and cardiac co-morbidities in the non-severe cohort treated with dipeptidyl peptidase-4 (DPP4) inhibitors. A possible protective effect of DPP4 inhibitors is also plausible on pathophysiological grounds, and our results support repositioning efforts of DPP4 inhibitors against SARS-CoV-2. At target level, we observed that the target location might have an influence on disease progression. This could potentially be attributed to disruption of functional membrane micro-domains (lipid rafts), which in turn could decrease viral entry and thus disease severity. Full article
(This article belongs to the Special Issue In Silico Strategies for Prospective Drug Repositionings)
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15 pages, 2273 KiB  
Article
Drug Repurposing Based on Protozoan Proteome: In Vitro Evaluation of In Silico Screened Compounds against Toxoplasma gondii
by Débora Chaves Cajazeiro, Paula Pereira Marques Toledo, Natália Ferreira de Sousa, Marcus Tullius Scotti and Juliana Quero Reimão
Pharmaceutics 2022, 14(8), 1634; https://doi.org/10.3390/pharmaceutics14081634 - 05 Aug 2022
Cited by 5 | Viewed by 1860
Abstract
Toxoplasma gondii is a protozoan that infects up to a third of the world’s population. This parasite can cause serious problems, especially if a woman is infected during pregnancy, when toxoplasmosis can cause miscarriage, or serious complications to the baby, or in an [...] Read more.
Toxoplasma gondii is a protozoan that infects up to a third of the world’s population. This parasite can cause serious problems, especially if a woman is infected during pregnancy, when toxoplasmosis can cause miscarriage, or serious complications to the baby, or in an immunocompromised person, when the infection can possibly affect the patient’s eyes or brain. To identify potential drug candidates that could counter toxoplasmosis, we selected 13 compounds which were pre-screened in silico based on the proteome of T. gondii to be evaluated in vitro against the parasite in a cell-based assay. Among the selected compounds, three demonstrated in vitro anti-T. gondii activity in the nanomolar range (almitrine, bortezomib, and fludarabine), and ten compounds demonstrated anti-T. gondii activity in the micromolar range (digitoxin, digoxin, doxorubicin, fusidic acid, levofloxacin, lomefloxacin, mycophenolic acid, ribavirin, trimethoprim, and valproic acid). Almitrine demonstrated a Selectivity Index (provided by the ratio between the Half Cytotoxic Concentration against human foreskin fibroblasts and the Half Effective Concentration against T. gondii tachyzoites) that was higher than 47, whilst being considered a lead compound against T. gondii. Almitrine showed interactions with the Na+/K+ ATPase transporter for Homo sapiens and Mus musculus, indicating a possible mechanism of action of this compound. Full article
(This article belongs to the Special Issue In Silico Strategies for Prospective Drug Repositionings)
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14 pages, 3634 KiB  
Article
Integration of In Silico Strategies for Drug Repositioning towards P38α Mitogen-Activated Protein Kinase (MAPK) at the Allosteric Site
by Utid Suriya, Panupong Mahalapbutr and Thanyada Rungrotmongkol
Pharmaceutics 2022, 14(7), 1461; https://doi.org/10.3390/pharmaceutics14071461 - 13 Jul 2022
Cited by 4 | Viewed by 2149
Abstract
P38α mitogen-activated protein kinase (p38α MAPK), one of the p38 MAPK isoforms participating in a signaling cascade, has been identified for its pivotal role in the regulation of physiological processes such as cell proliferation, differentiation, survival, and death. Herein, by shedding light on [...] Read more.
P38α mitogen-activated protein kinase (p38α MAPK), one of the p38 MAPK isoforms participating in a signaling cascade, has been identified for its pivotal role in the regulation of physiological processes such as cell proliferation, differentiation, survival, and death. Herein, by shedding light on docking- and 100-ns dynamic-based screening from 3210 FDA-approved drugs, we found that lomitapide (a lipid-lowering agent) and nilotinib (a Bcr-Abl fusion protein inhibitor) could alternatively inhibit phosphorylation of p38α MAPK at the allosteric site. All-atom molecular dynamics simulations and free energy calculations including end-point and QM-based ONIOM methods revealed that the binding affinity of the two screened drugs exhibited a comparable level as the known p38α MAPK inhibitor (BIRB796), suggesting the high potential of being a novel p38α MAPK inhibitor. In addition, noncovalent contacts and the number of hydrogen bonds were found to be corresponding with the great binding recognition. Key influential amino acids were mostly hydrophobic residues, while the two charged residues including E71 and D168 were considered crucial ones due to their ability to form very strong H-bonds with the focused drugs. Altogether, our contributions obtained here could be theoretical guidance for further conducting experimental-based preclinical studies necessary for developing therapeutic agents targeting p38α MAPK. Full article
(This article belongs to the Special Issue In Silico Strategies for Prospective Drug Repositionings)
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14 pages, 8146 KiB  
Article
A Single-Cell Network-Based Drug Repositioning Strategy for Post-COVID-19 Pulmonary Fibrosis
by Albert Li, Jhih-Yu Chen, Chia-Lang Hsu, Yen-Jen Oyang, Hsuan-Cheng Huang and Hsueh-Fen Juan
Pharmaceutics 2022, 14(5), 971; https://doi.org/10.3390/pharmaceutics14050971 - 30 Apr 2022
Cited by 2 | Viewed by 3398
Abstract
Post-COVID-19 pulmonary fibrosis (PCPF) is a long-term complication that appears in some COVID-19 survivors. However, there are currently limited options for treating PCPF patients. To address this problem, we investigated COVID-19 patients’ transcriptome at single-cell resolution and combined biological network analyses to repurpose [...] Read more.
Post-COVID-19 pulmonary fibrosis (PCPF) is a long-term complication that appears in some COVID-19 survivors. However, there are currently limited options for treating PCPF patients. To address this problem, we investigated COVID-19 patients’ transcriptome at single-cell resolution and combined biological network analyses to repurpose the drugs treating PCPF. We revealed a novel gene signature of PCPF. The signature is functionally associated with the viral infection and lung fibrosis. Further, the signature has good performance in diagnosing and assessing pulmonary fibrosis. Next, we applied a network-based drug repurposing method to explore novel treatments for PCPF. By quantifying the proximity between the drug targets and the signature in the interactome, we identified several potential candidates and provided a drug list ranked by their proximity. Taken together, we revealed a novel gene expression signature as a theragnostic biomarker for PCPF by integrating different computational approaches. Moreover, we showed that network-based proximity could be used as a framework to repurpose drugs for PCPF. Full article
(This article belongs to the Special Issue In Silico Strategies for Prospective Drug Repositionings)
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17 pages, 6707 KiB  
Article
In Silico Screening of Available Drugs Targeting Non-Small Cell Lung Cancer Targets: A Drug Repurposing Approach
by Muthu Kumar Thirunavukkarasu, Utid Suriya, Thanyada Rungrotmongkol and Ramanathan Karuppasamy
Pharmaceutics 2022, 14(1), 59; https://doi.org/10.3390/pharmaceutics14010059 - 28 Dec 2021
Cited by 12 | Viewed by 2823
Abstract
The RAS–RAF–MEK–ERK pathway plays a key role in malevolent cell progression in many tumors. The high structural complexity in the upstream kinases limits the treatment progress. Thus, MEK inhibition is a promising strategy since it is easy to inhibit and is a gatekeeper [...] Read more.
The RAS–RAF–MEK–ERK pathway plays a key role in malevolent cell progression in many tumors. The high structural complexity in the upstream kinases limits the treatment progress. Thus, MEK inhibition is a promising strategy since it is easy to inhibit and is a gatekeeper for the many malignant effects of its downstream effector. Even though MEK inhibitors are under investigation in many cancers, drug resistance continues to be the principal limiting factor to achieving cures in patients with cancer. Hence, we accomplished a high-throughput virtual screening to overcome this bottleneck by the discovery of dual-targeting therapy in cancer treatment. Here, a total of 11,808 DrugBank molecules were assessed through high-throughput virtual screening for their activity against MEK. Further, the Glide docking, MLSF and prime-MM/GBSA methods were implemented to extract the potential lead compounds from the database. Two compounds, DB012661 and DB07642, were outperformed in all the screening analyses. Further, the study results reveal that the lead compounds also have a significant binding capability with the co-target PIM1. Finally, the SIE-based free energy calculation reveals that the binding of compounds was majorly affected by the van der Waals interactions with MEK receptor. Overall, the in silico binding efficacy of these lead compounds against both MEK and PIM1 could be of significant therapeutic interest to overcome drug resistance in the near future. Full article
(This article belongs to the Special Issue In Silico Strategies for Prospective Drug Repositionings)
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27 pages, 41070 KiB  
Article
Drug Repurposing Using Modularity Clustering in Drug-Drug Similarity Networks Based on Drug–Gene Interactions
by Vlad Groza, Mihai Udrescu, Alexandru Bozdog and Lucreţia Udrescu
Pharmaceutics 2021, 13(12), 2117; https://doi.org/10.3390/pharmaceutics13122117 - 08 Dec 2021
Cited by 10 | Viewed by 3720
Abstract
Drug repurposing is a valuable alternative to traditional drug design based on the assumption that medicines have multiple functions. Computer-based techniques use ever-growing drug databases to uncover new drug repurposing hints, which require further validation with in vitro and in vivo experiments. Indeed, [...] Read more.
Drug repurposing is a valuable alternative to traditional drug design based on the assumption that medicines have multiple functions. Computer-based techniques use ever-growing drug databases to uncover new drug repurposing hints, which require further validation with in vitro and in vivo experiments. Indeed, such a scientific undertaking can be particularly effective in the case of rare diseases (resources for developing new drugs are scarce) and new diseases such as COVID-19 (designing new drugs require too much time). This paper introduces a new, completely automated computational drug repurposing pipeline based on drug–gene interaction data. We obtained drug–gene interaction data from an earlier version of DrugBank, built a drug–gene interaction network, and projected it as a drug–drug similarity network (DDSN). We then clustered DDSN by optimizing modularity resolution, used the ATC codes distribution within each cluster to identify potential drug repurposing candidates, and verified repurposing hints with the latest DrugBank ATC codes. Finally, using the best modularity resolution found with our method, we applied our pipeline to the latest DrugBank drug–gene interaction data to generate a comprehensive drug repurposing hint list. Full article
(This article belongs to the Special Issue In Silico Strategies for Prospective Drug Repositionings)
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13 pages, 1604 KiB  
Article
Combining Human Genetics of Multiple Sclerosis with Oxidative Stress Phenotype for Drug Repositioning
by Stefania Olla, Maristella Steri, Alessia Formato, Michael B. Whalen, Silvia Corbisiero and Cristina Agresti
Pharmaceutics 2021, 13(12), 2064; https://doi.org/10.3390/pharmaceutics13122064 - 02 Dec 2021
Cited by 3 | Viewed by 2288
Abstract
In multiple sclerosis (MS), oxidative stress (OS) is implicated in the neurodegenerative processes that occur from the beginning of the disease. Unchecked OS initiates a vicious circle caused by its crosstalk with inflammation, leading to demyelination, axonal damage and neuronal loss. The failure [...] Read more.
In multiple sclerosis (MS), oxidative stress (OS) is implicated in the neurodegenerative processes that occur from the beginning of the disease. Unchecked OS initiates a vicious circle caused by its crosstalk with inflammation, leading to demyelination, axonal damage and neuronal loss. The failure of MS antioxidant therapies relying on the use of endogenous and natural compounds drives the application of novel approaches to assess target relevance to the disease prior to preclinical testing of new drug candidates. To identify drugs that can act as regulators of intracellular oxidative homeostasis, we applied an in silico approach that links genome-wide MS associations and molecular quantitative trait loci (QTLs) to proteins of the OS pathway. We found 10 drugs with both central nervous system and oral bioavailability, targeting five out of the 21 top-scoring hits, including arginine methyltransferase (CARM1), which was first linked to MS. In particular, the direction of brain expression QTLs for CARM1 and protein kinase MAPK1 enabled us to select BIIB021 and PEITC drugs with the required target modulation. Our study highlights OS-related molecules regulated by functional MS variants that could be targeted by existing drugs as a supplement to the approved disease-modifying treatments. Full article
(This article belongs to the Special Issue In Silico Strategies for Prospective Drug Repositionings)
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18 pages, 2817 KiB  
Article
Discovery of a Potent Candidate for RET-Specific Non-Small-Cell Lung Cancer—A Combined In Silico and In Vitro Strategy
by Priyanka Ramesh, Woong-Hee Shin and Shanthi Veerappapillai
Pharmaceutics 2021, 13(11), 1775; https://doi.org/10.3390/pharmaceutics13111775 - 24 Oct 2021
Cited by 7 | Viewed by 2158
Abstract
Rearranged during transfection (RET) is a tyrosine kinase oncogenic receptor, activated in several cancers including non-small-cell lung cancer (NSCLC). Multiple kinase inhibitors vandetanib and cabozantinib are commonly used in the treatment of RET-positive NSCLC. However, specificity, toxicity, and reduced efficacy limit the usage [...] Read more.
Rearranged during transfection (RET) is a tyrosine kinase oncogenic receptor, activated in several cancers including non-small-cell lung cancer (NSCLC). Multiple kinase inhibitors vandetanib and cabozantinib are commonly used in the treatment of RET-positive NSCLC. However, specificity, toxicity, and reduced efficacy limit the usage of multiple kinase inhibitors in targeting RET protein. Thus, in the present investigation, we aimed to figure out novel and potent candidates for the inhibition of RET protein using combined in silico and in vitro strategies. In the present study, screening of 11,808 compounds from the DrugBank repository was accomplished by different hypotheses such as pharmacophore, e-pharmacophore, and receptor cavity-based models in the initial stage. The results from the different hypotheses were then integrated to eliminate the false positive prediction. The inhibitory activities of the screened compounds were tested by the glide docking algorithm. Moreover, RF score, Tanimoto coefficient, prime-MM/GBSA, and density functional theory calculations were utilized to re-score the binding free energy of the docked complexes with high precision. This procedure resulted in three lead molecules, namely DB07194, DB03496, and DB11982, against the RET protein. The screened lead molecules together with reference compounds were then subjected to a long molecular dynamics simulation with a 200 ns time duration to validate the inhibitory activity. Further analysis of compounds using MM-PBSA and mutation studies resulted in the identification of potent compound DB07194. In essence, a cell viability assay with RET-specific lung cancer cell line LC-2/ad was also carried out to confirm the in vitro biological activity of the resultant compound, DB07194. Indeed, the results from our study conclude that DB07194 can be effectively translated for this new therapeutic purpose, in contrast to the properties for which it was originally designed and synthesized. Full article
(This article belongs to the Special Issue In Silico Strategies for Prospective Drug Repositionings)
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26 pages, 723 KiB  
Article
Exploring Drugs and Vaccines Associated with Altered Risks and Severity of COVID-19: A UK Biobank Cohort Study of All ATC Level-4 Drug Categories Reveals Repositioning Opportunities
by Yong Xiang, Kenneth Chi-Yin Wong and Hon-Cheong So
Pharmaceutics 2021, 13(9), 1514; https://doi.org/10.3390/pharmaceutics13091514 - 18 Sep 2021
Cited by 10 | Viewed by 4136
Abstract
Effective therapies for COVID-19 are still lacking, and drug repositioning is a promising approach to address this problem. Here, we adopted a medical informatics approach to repositioning. We leveraged a large prospective cohort, the UK-Biobank (UKBB, N ~ 397,000), and studied associations of [...] Read more.
Effective therapies for COVID-19 are still lacking, and drug repositioning is a promising approach to address this problem. Here, we adopted a medical informatics approach to repositioning. We leveraged a large prospective cohort, the UK-Biobank (UKBB, N ~ 397,000), and studied associations of prior use of all level-4 ATC drug categories (N = 819, including vaccines) with COVID-19 diagnosis and severity. Effects of drugs on the risk of infection, disease severity, and mortality were investigated separately. Logistic regression was conducted, controlling for main confounders. We observed strong and highly consistent protective associations with statins. Many top-listed protective drugs were also cardiovascular medications, such as angiotensin-converting enzyme inhibitors (ACEI), angiotensin receptor blockers (ARB), calcium channel blocker (CCB), and beta-blockers. Some other drugs showing protective associations included biguanides (metformin), estrogens, thyroid hormones, proton pump inhibitors, and testosterone-5-alpha reductase inhibitors, among others. We also observed protective associations by influenza, pneumococcal, and several other vaccines. Subgroup and interaction analyses were also conducted, which revealed differences in protective effects in various subgroups. For example, protective effects of flu/pneumococcal vaccines were weaker in obese individuals, while protection by statins was stronger in cardiovascular patients. To conclude, our analysis revealed many drug repositioning candidates, for example several cardiovascular medications. Further studies are required for validation. Full article
(This article belongs to the Special Issue In Silico Strategies for Prospective Drug Repositionings)
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19 pages, 2927 KiB  
Article
3D-ALMOND-QSAR Models to Predict the Antidepressant Effect of Some Natural Compounds
by Speranta Avram, Miruna Silvia Stan, Ana Maria Udrea, Cătălin Buiu, Anca Andreea Boboc and Maria Mernea
Pharmaceutics 2021, 13(9), 1449; https://doi.org/10.3390/pharmaceutics13091449 - 10 Sep 2021
Cited by 9 | Viewed by 2591
Abstract
The current treatment of depression involves antidepressant synthetic drugs that have a variety of side effects. In searching for alternatives, natural compounds could represent a solution, as many studies reported that such compounds modulate the nervous system and exhibit antidepressant effects. We used [...] Read more.
The current treatment of depression involves antidepressant synthetic drugs that have a variety of side effects. In searching for alternatives, natural compounds could represent a solution, as many studies reported that such compounds modulate the nervous system and exhibit antidepressant effects. We used bioinformatics methods to predict the antidepressant effect of ten natural compounds with neuroleptic activity, reported in the literature. For all compounds we computed their drug-likeness, absorption, distribution, metabolism, excretion (ADME), and toxicity profiles. Their antidepressant and neuroleptic activities were predicted by 3D-ALMOND-QSAR models built by considering three important targets, namely serotonin transporter (SERT), 5-hydroxytryptamine receptor 1A (5-HT1A), and dopamine D2 receptor. For our QSAR models we have used the following molecular descriptors: hydrophobicity, electrostatic, and hydrogen bond donor/acceptor. Our results showed that all compounds present drug-likeness features as well as promising ADME features and no toxicity. Most compounds appear to modulate SERT, and fewer appear as ligands for 5-HT1A and D2 receptors. From our prediction, linalyl acetate appears as the only ligand for all three targets, neryl acetate appears as a ligand for SERT and D2 receptors, while 1,8-cineole appears as a ligand for 5-HT1A and D2 receptors. Full article
(This article belongs to the Special Issue In Silico Strategies for Prospective Drug Repositionings)
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13 pages, 1733 KiB  
Article
Combination Therapy with Fluoxetine and the Nucleoside Analog GS-441524 Exerts Synergistic Antiviral Effects against Different SARS-CoV-2 Variants In Vitro
by Linda Brunotte, Shuyu Zheng, Angeles Mecate-Zambrano, Jing Tang, Stephan Ludwig, Ursula Rescher and Sebastian Schloer
Pharmaceutics 2021, 13(9), 1400; https://doi.org/10.3390/pharmaceutics13091400 - 03 Sep 2021
Cited by 34 | Viewed by 3672
Abstract
The ongoing SARS-CoV-2 pandemic requires efficient and safe antiviral treatment strategies. Drug repurposing represents a fast and low-cost approach to the development of new medical treatment options. The direct antiviral agent remdesivir has been reported to exert antiviral activity against SARS-CoV-2. Whereas remdesivir [...] Read more.
The ongoing SARS-CoV-2 pandemic requires efficient and safe antiviral treatment strategies. Drug repurposing represents a fast and low-cost approach to the development of new medical treatment options. The direct antiviral agent remdesivir has been reported to exert antiviral activity against SARS-CoV-2. Whereas remdesivir only has a very short half-life time and a bioactivation, which relies on pro-drug activating enzymes, its plasma metabolite GS-441524 can be activated through various kinases including the adenosine kinase (ADK) that is moderately expressed in all tissues. The pharmacokinetics of GS-441524 argue for a suitable antiviral drug that can be given to patients with COVID-19. Here, we analyzed the antiviral property of a combined treatment with the remdesivir metabolite GS-441524 and the antidepressant fluoxetine in a polarized Calu-3 cell culture model against SARS-CoV-2. The combined treatment with GS-441524 and fluoxetine were well-tolerated and displayed synergistic antiviral effects against three circulating SARS-CoV-2 variants in vitro in the commonly used reference models for drug interaction. Thus, combinatory treatment with the virus-targeting GS-441524 and the host-directed drug fluoxetine might offer a suitable therapeutic treatment option for SARS-CoV-2 infections. Full article
(This article belongs to the Special Issue In Silico Strategies for Prospective Drug Repositionings)
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16 pages, 9816 KiB  
Article
Drug Repurposing for COVID-19 Treatment by Integrating Network Pharmacology and Transcriptomics
by Dan-Yang Liu, Jia-Chen Liu, Shuang Liang, Xiang-He Meng, Jonathan Greenbaum, Hong-Mei Xiao, Li-Jun Tan and Hong-Wen Deng
Pharmaceutics 2021, 13(4), 545; https://doi.org/10.3390/pharmaceutics13040545 - 14 Apr 2021
Cited by 16 | Viewed by 4982
Abstract
Since coronavirus disease 2019 (COVID-19) is a serious new worldwide public health crisis with significant morbidity and mortality, effective therapeutic treatments are urgently needed. Drug repurposing is an efficient and cost-effective strategy with minimum risk for identifying novel potential treatment options by repositioning [...] Read more.
Since coronavirus disease 2019 (COVID-19) is a serious new worldwide public health crisis with significant morbidity and mortality, effective therapeutic treatments are urgently needed. Drug repurposing is an efficient and cost-effective strategy with minimum risk for identifying novel potential treatment options by repositioning therapies that were previously approved for other clinical outcomes. Here, we used an integrated network-based pharmacologic and transcriptomic approach to screen drug candidates novel for COVID-19 treatment. Network-based proximity scores were calculated to identify the drug–disease pharmacological effect between drug–target relationship modules and COVID-19 related genes. Gene set enrichment analysis (GSEA) was then performed to determine whether drug candidates influence the expression of COVID-19 related genes and examine the sensitivity of the repurposing drug treatment to peripheral immune cell types. Moreover, we used the complementary exposure model to recommend potential synergistic drug combinations. We identified 18 individual drug candidates including nicardipine, orantinib, tipifarnib and promethazine which have not previously been proposed as possible treatments for COVID-19. Additionally, 30 synergistic drug pairs were ultimately recommended including fostamatinib plus tretinoin and orantinib plus valproic acid. Differential expression genes of most repurposing drugs were enriched significantly in B cells. The findings may potentially accelerate the discovery and establishment of an effective therapeutic treatment plan for COVID-19 patients. Full article
(This article belongs to the Special Issue In Silico Strategies for Prospective Drug Repositionings)
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18 pages, 1993 KiB  
Article
A COVID-19 Drug Repurposing Strategy through Quantitative Homological Similarities Using a Topological Data Analysis-Based Framework
by Raul Pérez-Moraga, Jaume Forés-Martos, Beatriz Suay-García, Jean-Louis Duval, Antonio Falcó and Joan Climent
Pharmaceutics 2021, 13(4), 488; https://doi.org/10.3390/pharmaceutics13040488 - 02 Apr 2021
Cited by 12 | Viewed by 3565
Abstract
Since its emergence in March 2020, the SARS-CoV-2 global pandemic has produced more than 116 million cases and 2.5 million deaths worldwide. Despite the enormous efforts carried out by the scientific community, no effective treatments have been developed to date. We applied a [...] Read more.
Since its emergence in March 2020, the SARS-CoV-2 global pandemic has produced more than 116 million cases and 2.5 million deaths worldwide. Despite the enormous efforts carried out by the scientific community, no effective treatments have been developed to date. We applied a novel computational pipeline aimed to accelerate the process of identifying drug repurposing candidates which allows us to compare three-dimensional protein structures. Its use in conjunction with two in silico validation strategies (molecular docking and transcriptomic analyses) allowed us to identify a set of potential drug repurposing candidates targeting three viral proteins (3CL viral protease, NSP15 endoribonuclease, and NSP12 RNA-dependent RNA polymerase), which included rutin, dexamethasone, and vemurafenib. This is the first time that a topological data analysis (TDA)-based strategy has been used to compare a massive number of protein structures with the final objective of performing drug repurposing to treat SARS-CoV-2 infection. Full article
(This article belongs to the Special Issue In Silico Strategies for Prospective Drug Repositionings)
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Review

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22 pages, 1951 KiB  
Review
Repurposing Drugs via Network Analysis: Opportunities for Psychiatric Disorders
by Trang T. T. Truong, Bruna Panizzutti, Jee Hyun Kim and Ken Walder
Pharmaceutics 2022, 14(7), 1464; https://doi.org/10.3390/pharmaceutics14071464 - 14 Jul 2022
Cited by 7 | Viewed by 3770
Abstract
Despite advances in pharmacology and neuroscience, the path to new medications for psychiatric disorders largely remains stagnated. Drug repurposing offers a more efficient pathway compared with de novo drug discovery with lower cost and less risk. Various computational approaches have been applied to [...] Read more.
Despite advances in pharmacology and neuroscience, the path to new medications for psychiatric disorders largely remains stagnated. Drug repurposing offers a more efficient pathway compared with de novo drug discovery with lower cost and less risk. Various computational approaches have been applied to mine the vast amount of biomedical data generated over recent decades. Among these methods, network-based drug repurposing stands out as a potent tool for the comprehension of multiple domains of knowledge considering the interactions or associations of various factors. Aligned well with the poly-pharmacology paradigm shift in drug discovery, network-based approaches offer great opportunities to discover repurposing candidates for complex psychiatric disorders. In this review, we present the potential of network-based drug repurposing in psychiatry focusing on the incentives for using network-centric repurposing, major network-based repurposing strategies and data resources, applications in psychiatry and challenges of network-based drug repurposing. This review aims to provide readers with an update on network-based drug repurposing in psychiatry. We expect the repurposing approach to become a pivotal tool in the coming years to battle debilitating psychiatric disorders. Full article
(This article belongs to the Special Issue In Silico Strategies for Prospective Drug Repositionings)
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22 pages, 3539 KiB  
Systematic Review
Hidradenitis Suppurativa and Comorbid Disorder Biomarkers, Druggable Genes, New Drugs and Drug Repurposing—A Molecular Meta-Analysis
by Viktor A. Zouboulis, Konstantin C. Zouboulis and Christos C. Zouboulis
Pharmaceutics 2022, 14(1), 44; https://doi.org/10.3390/pharmaceutics14010044 - 26 Dec 2021
Cited by 18 | Viewed by 4008
Abstract
Chronic inflammation and dysregulated epithelial differentiation, especially of hair follicle keratinocytes, have been suggested as the major pathogenetic pathways of hidradenitis suppurativa/acne inversa (HS). On the other hand, obesity and metabolic syndrome have additionally been considered as an important risk factor. With adalimumab, [...] Read more.
Chronic inflammation and dysregulated epithelial differentiation, especially of hair follicle keratinocytes, have been suggested as the major pathogenetic pathways of hidradenitis suppurativa/acne inversa (HS). On the other hand, obesity and metabolic syndrome have additionally been considered as an important risk factor. With adalimumab, a drug has already been approved and numerous other compounds are in advanced-stage clinical studies. A systematic review was conducted to detect and corroborate HS pathogenetic mechanisms at the molecular level and identify HS molecular markers. The obtained data were used to confirm studied and off-label administered drugs and to identify additional compounds for drug repurposing. A robust, strongly associated group of HS biomarkers was detected. The triad of HS pathogenesis, namely upregulated inflammation, altered epithelial differentiation and dysregulated metabolism/hormone signaling was confirmed, the molecular association of HS with certain comorbid disorders, such as inflammatory bowel disease, arthritis, type I diabetes mellitus and lipids/atherosclerosis/adipogenesis was verified and common biomarkers were identified. The molecular suitability of compounds in clinical studies was confirmed and 31 potential HS repurposing drugs, among them 10 drugs already launched for other disorders, were detected. This systematic review provides evidence for the importance of molecular studies to advance the knowledge regarding pathogenesis, future treatment and biomarker-supported clinical course follow-up in HS. Full article
(This article belongs to the Special Issue In Silico Strategies for Prospective Drug Repositionings)
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