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Paudel KR, Singh M, De Rubis G, Kumbhar P, Mehndiratta S, Kokkinis S, El-Sherkawi T, Gupta G, Singh SK, Malik MZ, Mohammed Y, Oliver BG, Disouza J, Patravale V, Hansbro PM, Dua K. Computational and biological approaches in repurposing ribavirin for lung cancer treatment: Unveiling antitumorigenic strategies. Life Sci 2024; 352:122859. [PMID: 38925223 DOI: 10.1016/j.lfs.2024.122859] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/07/2024] [Revised: 03/11/2024] [Accepted: 06/18/2024] [Indexed: 06/28/2024]
Abstract
Lung cancer is among leading causes of death worldwide. The five-year survival rate of this disease is extremely low (17.8 %), mainly due to difficult early diagnosis and to the limited efficacy of currently available chemotherapeutics. This underlines the necessity to develop innovative therapies for lung cancer. In this context, drug repurposing represents a viable approach, as it reduces the turnaround time of drug development removing costs associated to safety testing of new molecular entities. Ribavirin, an antiviral molecule used to treat hepatitis C virus infections, is particularly promising as repurposed drug for cancer treatment, having shown therapeutic activity against glioblastoma, acute myeloid leukemia, and nasopharyngeal carcinoma. In the present study, we thoroughly investigated the in vitro anticancer activity of ribavirin against A549 human lung adenocarcinoma cells. From a functional standpoint, ribavirin significantly inhibits cancer hallmarks such as cell proliferation, migration, and colony formation. Mechanistically, ribavirin downregulates the expression of numerous proteins and genes regulating cell migration, proliferation, apoptosis, and cancer angiogenesis. The anticancer potential of ribavirin was further investigated in silico through gene ontology pathway enrichment and protein-protein interaction networks, identifying five putative molecular interactors of ribavirin (Erb-B2 Receptor Tyrosine Kinase 4 (Erb-B4); KRAS; Intercellular Adhesion Molecule 1 (ICAM-1); amphiregulin (AREG); and neuregulin-1 (NRG1)). These interactions were characterized via molecular docking and molecular dynamic simulations. The results of this study highlight the potential of ribavirin as a repurposed chemotherapy against lung cancer, warranting further studies to ascertain the in vivo anticancer activity of this molecule.
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Affiliation(s)
- Keshav Raj Paudel
- Centre of Inflammation, Centenary Institute and University of Technology Sydney, Faculty of Science, School of Life Sciences, Sydney, NSW 2007, Australia
| | - Manisha Singh
- Department of Biotechnology, Jaypee Institute of Information Technology (JIIT), Noida, Uttar Pradesh, India; Discipline of Pharmacy, Graduate School of Health, University of Technology Sydney, Sydney, NSW 2007, Australia; Faculty of Health, Australian Research Centre in Complementary and Integrative Medicine, University of Technology Sydney, Ultimo, NSW 2007, Australia
| | - Gabriele De Rubis
- Discipline of Pharmacy, Graduate School of Health, University of Technology Sydney, Sydney, NSW 2007, Australia; Faculty of Health, Australian Research Centre in Complementary and Integrative Medicine, University of Technology Sydney, Ultimo, NSW 2007, Australia
| | - Popat Kumbhar
- Department of Pharmaceutics, Tatyasaheb Kore College of Pharmacy, Warananagar, Tal: Panhala, Dist: Kolhapur, Maharashtra 416113, India
| | - Samir Mehndiratta
- Discipline of Pharmacy, Graduate School of Health, University of Technology Sydney, Sydney, NSW 2007, Australia; Faculty of Health, Australian Research Centre in Complementary and Integrative Medicine, University of Technology Sydney, Ultimo, NSW 2007, Australia
| | - Sofia Kokkinis
- Discipline of Pharmacy, Graduate School of Health, University of Technology Sydney, Sydney, NSW 2007, Australia; Faculty of Health, Australian Research Centre in Complementary and Integrative Medicine, University of Technology Sydney, Ultimo, NSW 2007, Australia
| | - Tammam El-Sherkawi
- Discipline of Pharmacy, Graduate School of Health, University of Technology Sydney, Sydney, NSW 2007, Australia; Faculty of Health, Australian Research Centre in Complementary and Integrative Medicine, University of Technology Sydney, Ultimo, NSW 2007, Australia
| | - Gaurav Gupta
- Centre for Research Impact & Outcome, Chitkara College of Pharmacy, Chitkara University, Rajpura, 140401, Punjab, India; Centre of Medical and Bio-allied Health Sciences Research, Ajman University, Ajman, United Arab Emirates
| | - Sachin Kumar Singh
- Faculty of Health, Australian Research Centre in Complementary and Integrative Medicine, University of Technology Sydney, Ultimo, NSW 2007, Australia; School of Pharmaceutical Sciences, Lovely Professional University, Jalandhar-Delhi GT Road, Phagwara 144411, Punjab, India
| | - Md Zubbair Malik
- Department of Genetics and Bioinformatics, Dasman Diabetes Institute, Dasman, Kuwait city 15462, Kuwait
| | - Yousuf Mohammed
- Frazer Institute, Faculty of Medicine, The University of Queensland, Brisbane, QLD 4102, Australia
| | - Brian G Oliver
- Woolcock Institute of Medical Research, University of Sydney, Sydney, New South Wales, Australia; School of Life Sciences, University of Technology Sydney, Ultimo, NSW 2007, Australia
| | - John Disouza
- Department of Pharmaceutics, Tatyasaheb Kore College of Pharmacy, Warananagar, Tal: Panhala, Dist: Kolhapur, Maharashtra 416113, India
| | - Vandana Patravale
- Department of Pharmaceutical Sciences and Technology, Institute of Chemical Technology, Nathalal Parekh Marg, Matunga, Mumbai 400019, Maharashtra, India
| | - Philip Michael Hansbro
- Centre of Inflammation, Centenary Institute and University of Technology Sydney, Faculty of Science, School of Life Sciences, Sydney, NSW 2007, Australia.
| | - Kamal Dua
- Discipline of Pharmacy, Graduate School of Health, University of Technology Sydney, Sydney, NSW 2007, Australia; Faculty of Health, Australian Research Centre in Complementary and Integrative Medicine, University of Technology Sydney, Ultimo, NSW 2007, Australia.
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Cavalcante BRR, Freitas RD, Siquara da Rocha LO, Santos RSB, Souza BSDF, Ramos PIP, Rocha GV, Gurgel Rocha CA. In silico approaches for drug repurposing in oncology: a scoping review. Front Pharmacol 2024; 15:1400029. [PMID: 38919258 PMCID: PMC11196849 DOI: 10.3389/fphar.2024.1400029] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/12/2024] [Accepted: 05/14/2024] [Indexed: 06/27/2024] Open
Abstract
Introduction: Cancer refers to a group of diseases characterized by the uncontrolled growth and spread of abnormal cells in the body. Due to its complexity, it has been hard to find an ideal medicine to treat all cancer types, although there is an urgent need for it. However, the cost of developing a new drug is high and time-consuming. In this sense, drug repurposing (DR) can hasten drug discovery by giving existing drugs new disease indications. Many computational methods have been applied to achieve DR, but just a few have succeeded. Therefore, this review aims to show in silico DR approaches and the gap between these strategies and their ultimate application in oncology. Methods: The scoping review was conducted according to the Arksey and O'Malley framework and the Joanna Briggs Institute recommendations. Relevant studies were identified through electronic searching of PubMed/MEDLINE, Embase, Scopus, and Web of Science databases, as well as the grey literature. We included peer-reviewed research articles involving in silico strategies applied to drug repurposing in oncology, published between 1 January 2003, and 31 December 2021. Results: We identified 238 studies for inclusion in the review. Most studies revealed that the United States, India, China, South Korea, and Italy are top publishers. Regarding cancer types, breast cancer, lymphomas and leukemias, lung, colorectal, and prostate cancer are the top investigated. Additionally, most studies solely used computational methods, and just a few assessed more complex scientific models. Lastly, molecular modeling, which includes molecular docking and molecular dynamics simulations, was the most frequently used method, followed by signature-, Machine Learning-, and network-based strategies. Discussion: DR is a trending opportunity but still demands extensive testing to ensure its safety and efficacy for the new indications. Finally, implementing DR can be challenging due to various factors, including lack of quality data, patient populations, cost, intellectual property issues, market considerations, and regulatory requirements. Despite all the hurdles, DR remains an exciting strategy for identifying new treatments for numerous diseases, including cancer types, and giving patients faster access to new medications.
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Affiliation(s)
- Bruno Raphael Ribeiro Cavalcante
- Gonçalo Moniz Institute, Oswaldo Cruz Foundation (IGM-FIOCRUZ/BA), Salvador, Brazil
- Department of Pathology and Forensic Medicine of the School of Medicine, Federal University of Bahia, Salvador, Brazil
| | - Raíza Dias Freitas
- Gonçalo Moniz Institute, Oswaldo Cruz Foundation (IGM-FIOCRUZ/BA), Salvador, Brazil
- Department of Social and Pediatric Dentistry of the School of Dentistry, Federal University of Bahia, Salvador, Brazil
| | - Leonardo de Oliveira Siquara da Rocha
- Gonçalo Moniz Institute, Oswaldo Cruz Foundation (IGM-FIOCRUZ/BA), Salvador, Brazil
- Department of Pathology and Forensic Medicine of the School of Medicine, Federal University of Bahia, Salvador, Brazil
| | | | - Bruno Solano de Freitas Souza
- Gonçalo Moniz Institute, Oswaldo Cruz Foundation (IGM-FIOCRUZ/BA), Salvador, Brazil
- D’Or Institute for Research and Education (IDOR), Salvador, Brazil
| | - Pablo Ivan Pereira Ramos
- Gonçalo Moniz Institute, Oswaldo Cruz Foundation (IGM-FIOCRUZ/BA), Salvador, Brazil
- Center of Data and Knowledge Integration for Health (CIDACS), Salvador, Brazil
| | - Gisele Vieira Rocha
- Gonçalo Moniz Institute, Oswaldo Cruz Foundation (IGM-FIOCRUZ/BA), Salvador, Brazil
- D’Or Institute for Research and Education (IDOR), Salvador, Brazil
| | - Clarissa Araújo Gurgel Rocha
- Gonçalo Moniz Institute, Oswaldo Cruz Foundation (IGM-FIOCRUZ/BA), Salvador, Brazil
- Department of Pathology and Forensic Medicine of the School of Medicine, Federal University of Bahia, Salvador, Brazil
- D’Or Institute for Research and Education (IDOR), Salvador, Brazil
- Department of Propaedeutics, School of Dentistry of the Federal University of Bahia, Salvador, Brazil
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Waseem T, Rajput TA, Mushtaq MS, Babar MM, Rajadas J. Computational biology approaches for drug repurposing. PROGRESS IN MOLECULAR BIOLOGY AND TRANSLATIONAL SCIENCE 2024; 205:91-109. [PMID: 38789189 DOI: 10.1016/bs.pmbts.2024.03.018] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/26/2024]
Abstract
The drug discovery and development (DDD) process greatly relies on the data available in various forms to generate hypotheses for novel drug design. The complex and heterogeneous nature of biological data makes it difficult to utilize or gather meaningful information as such. Computational biology techniques have provided us with opportunities to better understand biological systems through refining and organizing large amounts of data into actionable and systematic purviews. The drug repurposing approach has been utilized to overcome the expansive time periods and costs associated with traditional drug development. It deals with discovering new uses of already approved drugs that have an established safety and efficacy profile, thereby, requiring them to go through fewer development phases. Thus, drug repurposing through computational biology provides a systematic approach to drug development and overcomes the constraints of traditional processes. The current chapter covers the basics, approaches and tools of computational biology that can be employed to effectively develop repurposing profile of already approved drug molecules.
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Affiliation(s)
- Tanya Waseem
- Shifa College of Pharmaceutical Sciences, Shifa Tameer-e-Millat University, Islamabad, Pakistan
| | - Tausif Ahmed Rajput
- Shifa College of Pharmaceutical Sciences, Shifa Tameer-e-Millat University, Islamabad, Pakistan
| | | | - Mustafeez Mujtaba Babar
- Shifa College of Pharmaceutical Sciences, Shifa Tameer-e-Millat University, Islamabad, Pakistan; Advanced Drug Delivery and Regenerative Biomaterials Laboratory, Cardiovascular Institute and Pulmonary and Critical Care Medicine, Stanford University School of Medicine, Stanford University, Palo Alto, CA, United States.
| | - Jayakumar Rajadas
- Advanced Drug Delivery and Regenerative Biomaterials Laboratory, Cardiovascular Institute and Pulmonary and Critical Care Medicine, Stanford University School of Medicine, Stanford University, Palo Alto, CA, United States
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Saha S, Chatterjee P, Nasipuri M, Basu S, Chakraborti T. Computational drug repurposing for viral infectious diseases: a case study on monkeypox. Brief Funct Genomics 2024:elad058. [PMID: 38183212 DOI: 10.1093/bfgp/elad058] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/29/2023] [Revised: 12/04/2023] [Accepted: 12/12/2023] [Indexed: 01/07/2024] Open
Abstract
The traditional method of drug reuse or repurposing has significantly contributed to the identification of new antiviral compounds and therapeutic targets, enabling rapid response to developing infectious illnesses. This article presents an overview of how modern computational methods are used in drug repurposing for the treatment of viral infectious diseases. These methods utilize data sets that include reviewed information on the host's response to pathogens and drugs, as well as various connections such as gene expression patterns and protein-protein interaction networks. We assess the potential benefits and limitations of these methods by examining monkeypox as a specific example, but the knowledge acquired can be applied to other comparable disease scenarios.
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Affiliation(s)
- Sovan Saha
- Department of Computer Science and Engineering (Artificial Intelligence and Machine Learning), Techno Main Salt Lake, EM-4/1, Sector V, Bidhannagar, Kolkata, West Bengal 700091, India
| | - Piyali Chatterjee
- Department of Computer Science and Engineering, Netaji Subhash Engineering College, Garia, Kolkata-700152, India
| | - Mita Nasipuri
- Department of Computer Science and Engineering, Jadavpur University, Kolkata - 700032, India
| | - Subhadip Basu
- Department of Computer Science and Engineering, Jadavpur University, Kolkata - 700032, India
| | - Tapabrata Chakraborti
- Department of Medical Physics and Biomedical Engineering, University College London, UK
- Health Science Programme, The Alan Turing Institute, London, UK
- Linacre College, University of Oxford, UK
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Pinzi L, Rastelli G. Trends and Applications in Computationally Driven Drug Repurposing. Int J Mol Sci 2023; 24:16511. [PMID: 38003701 PMCID: PMC10671888 DOI: 10.3390/ijms242216511] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/30/2023] [Accepted: 11/06/2023] [Indexed: 11/26/2023] Open
Abstract
Drug repurposing is a widely used approach originally developed to aid in the identification of new uses of already existing drugs outside the scope of the original medical indication [...].
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Affiliation(s)
| | - Giulio Rastelli
- Department of Life Sciences, University of Modena and Reggio Emilia, Via Giuseppe Campi 103, 41125 Modena, Italy;
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Mohi-Ud-Din R, Chawla A, Sharma P, Mir PA, Potoo FH, Reiner Ž, Reiner I, Ateşşahin DA, Sharifi-Rad J, Mir RH, Calina D. Repurposing approved non-oncology drugs for cancer therapy: a comprehensive review of mechanisms, efficacy, and clinical prospects. Eur J Med Res 2023; 28:345. [PMID: 37710280 PMCID: PMC10500791 DOI: 10.1186/s40001-023-01275-4] [Citation(s) in RCA: 8] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/14/2023] [Accepted: 08/08/2023] [Indexed: 09/16/2023] Open
Abstract
Cancer poses a significant global health challenge, with predictions of increasing prevalence in the coming years due to limited prevention, late diagnosis, and inadequate success with current therapies. In addition, the high cost of new anti-cancer drugs creates barriers in meeting the medical needs of cancer patients, especially in developing countries. The lengthy and costly process of developing novel drugs further hinders drug discovery and clinical implementation. Therefore, there has been a growing interest in repurposing approved drugs for other diseases to address the urgent need for effective cancer treatments. The aim of this comprehensive review is to provide an overview of the potential of approved non-oncology drugs as therapeutic options for cancer treatment. These drugs come from various chemotherapeutic classes, including antimalarials, antibiotics, antivirals, anti-inflammatory drugs, and antifungals, and have demonstrated significant antiproliferative, pro-apoptotic, immunomodulatory, and antimetastatic properties. A systematic review of the literature was conducted to identify relevant studies on the repurposing of approved non-oncology drugs for cancer therapy. Various electronic databases, such as PubMed, Scopus, and Google Scholar, were searched using appropriate keywords. Studies focusing on the therapeutic potential, mechanisms of action, efficacy, and clinical prospects of repurposed drugs in cancer treatment were included in the analysis. The review highlights the promising outcomes of repurposing approved non-oncology drugs for cancer therapy. Drugs belonging to different therapeutic classes have demonstrated notable antitumor effects, including inhibiting cell proliferation, promoting apoptosis, modulating the immune response, and suppressing metastasis. These findings suggest the potential of these repurposed drugs as effective therapeutic approaches in cancer treatment. Repurposing approved non-oncology drugs provides a promising strategy for addressing the urgent need for effective and accessible cancer treatments. The diverse classes of repurposed drugs, with their demonstrated antiproliferative, pro-apoptotic, immunomodulatory, and antimetastatic properties, offer new avenues for cancer therapy. Further research and clinical trials are warranted to explore the full potential of these repurposed drugs and optimize their use in treating various cancer types. Repurposing approved drugs can significantly expedite the process of identifying effective treatments and improve patient outcomes in a cost-effective manner.
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Affiliation(s)
- Roohi Mohi-Ud-Din
- Department of General Medicine, Sher-I-Kashmir Institute of Medical Sciences (SKIMS), Srinagar, Jammu and Kashmir, 190001, India
| | - Apporva Chawla
- Khalsa College of Pharmacy, G.T. Road, Amritsar, Punjab, 143001, India
| | - Pooja Sharma
- Khalsa College of Pharmacy, G.T. Road, Amritsar, Punjab, 143001, India
| | - Prince Ahad Mir
- Khalsa College of Pharmacy, G.T. Road, Amritsar, Punjab, 143001, India
| | - Faheem Hyder Potoo
- Department of Pharmacology, College of Clinical Pharmacy, Imam Abdulrahman Bin Faisal University, 1982, 31441, Dammam, Saudi Arabia
| | - Željko Reiner
- Department of Internal Medicine, School of Medicine, University Hospital Center Zagreb, Zagreb, Croatia
| | - Ivan Reiner
- Department of Nursing Sciences, Catholic University of Croatia, Ilica 242, 10000, Zagreb, Croatia
| | - Dilek Arslan Ateşşahin
- Baskil Vocational School, Department of Plant and Animal Production, Fırat University, 23100, Elazıg, Turkey
| | | | - Reyaz Hassan Mir
- Pharmaceutical Chemistry Division, Department of Pharmaceutical Sciences, University of Kashmir, Hazratbal, Srinagar, Kashmir, 190006, India.
| | - Daniela Calina
- Department of Clinical Pharmacy, University of Medicine and Pharmacy of Craiova, 200349, Craiova, Romania.
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Ram S, More-Adate P, Tagalpallewar AA, Pawar AT, Nagar S, Baheti AM. An in-silico investigation and network pharmacology based approach to explore the anti-breast-cancer potential of Tecteria coadunata (Wall.) C. Chr. J Biomol Struct Dyn 2023:1-12. [PMID: 37655689 DOI: 10.1080/07391102.2023.2252091] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/03/2022] [Accepted: 08/21/2023] [Indexed: 09/02/2023]
Abstract
Uncontrolled cell proliferation is a common definition of cancer. After lung carcinoma, breast neoplasm is the second-most prevalent kind of cancer. The majority of breast cancer cells and healthy breast cells both have receptors for circulating oestrogen and progesterone. In order to promote the development and division of cancer cells, oestrogen and progesterone bind to the receptors and may collaborate with growth factors (such as oncogenes and mutant tumour suppressor genes). As per the literature, Tecteria coadunata (Wall.) C. Chr. has anticancer, antioxidant and anti-inflammatory potential. After the hydroalcoholic extraction of this rhizome, total of 200 phytochemicals were retrieved from HR-LCMS analysis. In this current study, Network pharmacology was carried out to explore the rationale of Tecteria coadunata (Wall.) C. Chr. by using different database using Cytoscape software. The network depicted the interaction of Bioactives with their targets and their association with several disease, especially breast cancer. Tecteria coadunata (Wall.) C. Chr. has offered new relationship with variety of genes and its applications in different types of breast cancers. Further Gene Ontology was carried out and it showed key targets were TP53, BRCA2, PGR and CHEK 2. Further Signalling pathways were also enriched. Flex-X software was used for molecular docking studies, and it verified that Dopaxanthin, Dantrolene and Orotidin shows the highest binding affinities with key targets. Additionally, Pharmacokinetic analysis revealed that all top three lead compounds which follows the Lipinski Rule (Rule of three) without interrupting the conditions of bioavailability with minimal toxicity.Communicated by Ramaswamy H. Sarma.
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Affiliation(s)
- Shraddha Ram
- School of Health Sciences and Technology, Dr. Vishwanath Karad MIT-World Peace University, Pune, Maharashtra, India
| | - Pallavi More-Adate
- School of Health Sciences and Technology, Dr. Vishwanath Karad MIT-World Peace University, Pune, Maharashtra, India
| | - Amol A Tagalpallewar
- School of Health Sciences and Technology, Dr. Vishwanath Karad MIT-World Peace University, Pune, Maharashtra, India
| | - Anil T Pawar
- School of Health Sciences and Technology, Dr. Vishwanath Karad MIT-World Peace University, Pune, Maharashtra, India
| | - Shuchi Nagar
- Bioinformatics Research Centre, Dr. D.Y. Patil. Biotechnology & Bioinformatics Institute, Dr. D.Y. Patil Vidyapeeth, Pune, Maharashtra, India
| | - Akshay M Baheti
- School of Health Sciences and Technology, Dr. Vishwanath Karad MIT-World Peace University, Pune, Maharashtra, India
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Elkashlan M, Ahmad RM, Hajar M, Al Jasmi F, Corchado JM, Nasarudin NA, Mohamad MS. A review of SARS-CoV-2 drug repurposing: databases and machine learning models. Front Pharmacol 2023; 14:1182465. [PMID: 37601065 PMCID: PMC10436567 DOI: 10.3389/fphar.2023.1182465] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/21/2023] [Accepted: 07/06/2023] [Indexed: 08/22/2023] Open
Abstract
The emergence of Severe Acute Respiratory Syndrome Corona Virus 2 (SARS-CoV-2) posed a serious worldwide threat and emphasized the urgency to find efficient solutions to combat the spread of the virus. Drug repurposing has attracted more attention than traditional approaches due to its potential for a time- and cost-effective discovery of new applications for the existing FDA-approved drugs. Given the reported success of machine learning (ML) in virtual drug screening, it is warranted as a promising approach to identify potential SARS-CoV-2 inhibitors. The implementation of ML in drug repurposing requires the presence of reliable digital databases for the extraction of the data of interest. Numerous databases archive research data from studies so that it can be used for different purposes. This article reviews two aspects: the frequently used databases in ML-based drug repurposing studies for SARS-CoV-2, and the recent ML models that have been developed for the prospective prediction of potential inhibitors against the new virus. Both types of ML models, Deep Learning models and conventional ML models, are reviewed in terms of introduction, methodology, and its recent applications in the prospective predictions of SARS-CoV-2 inhibitors. Furthermore, the features and limitations of the databases are provided to guide researchers in choosing suitable databases according to their research interests.
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Affiliation(s)
- Marim Elkashlan
- Health Data Science Lab, Department of Genetics and Genomics, College of Medical and Health Sciences, United Arab Emirates University, Al Ain, United Arab Emirates
| | - Rahaf M Ahmad
- Health Data Science Lab, Department of Genetics and Genomics, College of Medical and Health Sciences, United Arab Emirates University, Al Ain, United Arab Emirates
| | - Malak Hajar
- Health Data Science Lab, Department of Genetics and Genomics, College of Medical and Health Sciences, United Arab Emirates University, Al Ain, United Arab Emirates
| | - Fatma Al Jasmi
- Health Data Science Lab, Department of Genetics and Genomics, College of Medical and Health Sciences, United Arab Emirates University, Al Ain, United Arab Emirates
- Division of Metabolic Genetics, Department of Pediatrics, Tawam Hospital, Al Ain, United Arab Emirates
| | - Juan Manuel Corchado
- Departamento de Informática y Automática, Facultad de Ciencias, Grupo de Investigación BISITE, Instituto de Investigación Biomédica de Salamanca, University of Salamanca, Salamanca, Spain
| | - Nurul Athirah Nasarudin
- Health Data Science Lab, Department of Genetics and Genomics, College of Medical and Health Sciences, United Arab Emirates University, Al Ain, United Arab Emirates
| | - Mohd Saberi Mohamad
- Health Data Science Lab, Department of Genetics and Genomics, College of Medical and Health Sciences, United Arab Emirates University, Al Ain, United Arab Emirates
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Bayraktar A, Li X, Kim W, Zhang C, Turkez H, Shoaie S, Mardinoglu A. Drug repositioning targeting glutaminase reveals drug candidates for the treatment of Alzheimer's disease patients. J Transl Med 2023; 21:332. [PMID: 37210557 DOI: 10.1186/s12967-023-04192-6] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/26/2023] [Accepted: 05/11/2023] [Indexed: 05/22/2023] Open
Abstract
BACKGROUND Despite numerous clinical trials and decades of endeavour, there is still no effective cure for Alzheimer's disease. Computational drug repositioning approaches may be employed for the development of new treatment strategies for Alzheimer's patients since an extensive amount of omics data has been generated during pre-clinical and clinical studies. However, targeting the most critical pathophysiological mechanisms and determining drugs with proper pharmacodynamics and good efficacy are equally crucial in drug repurposing and often imbalanced in Alzheimer's studies. METHODS Here, we investigated central co-expressed genes upregulated in Alzheimer's disease to determine a proper therapeutic target. We backed our reasoning by checking the target gene's estimated non-essentiality for survival in multiple human tissues. We screened transcriptome profiles of various human cell lines perturbed by drug induction (for 6798 compounds) and gene knockout using data available in the Connectivity Map database. Then, we applied a profile-based drug repositioning approach to discover drugs targeting the target gene based on the correlations between these transcriptome profiles. We evaluated the bioavailability, functional enrichment profiles and drug-protein interactions of these repurposed agents and evidenced their cellular viability and efficacy in glial cell culture by experimental assays and Western blotting. Finally, we evaluated their pharmacokinetics to anticipate to which degree their efficacy can be improved. RESULTS We identified glutaminase as a promising drug target. Glutaminase overexpression may fuel the glutamate excitotoxicity in neurons, leading to mitochondrial dysfunction and other neurodegeneration hallmark processes. The computational drug repurposing revealed eight drugs: mitoxantrone, bortezomib, parbendazole, crizotinib, withaferin-a, SA-25547 and two unstudied compounds. We demonstrated that the proposed drugs could effectively suppress glutaminase and reduce glutamate production in the diseased brain through multiple neurodegeneration-associated mechanisms, including cytoskeleton and proteostasis. We also estimated the human blood-brain barrier permeability of parbendazole and SA-25547 using the SwissADME tool. CONCLUSIONS This study method effectively identified an Alzheimer's disease marker and compounds targeting the marker and interconnected biological processes by use of multiple computational approaches. Our results highlight the importance of synaptic glutamate signalling in Alzheimer's disease progression. We suggest repurposable drugs (like parbendazole) with well-evidenced activities that we linked to glutamate synthesis hereby and novel molecules (SA-25547) with estimated mechanisms for the treatment of Alzheimer's patients.
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Affiliation(s)
- Abdulahad Bayraktar
- Centre for Host-Microbiome Interactions, Faculty of Dentistry, Oral & Craniofacial Sciences, King's College London, London, SE1 9RT, UK
| | - Xiangyu Li
- Bash Biotech Inc, 600 West Broadway, Suite 700, San Diego, CA, 92101, USA
- Science for Life Laboratory, KTH-Royal Institute of Technology, SE-17121, Stockholm, Sweden
| | - Woonghee Kim
- Science for Life Laboratory, KTH-Royal Institute of Technology, SE-17121, Stockholm, Sweden
| | - Cheng Zhang
- Science for Life Laboratory, KTH-Royal Institute of Technology, SE-17121, Stockholm, Sweden
| | - Hasan Turkez
- Department of Medical Biology, Faculty of Medicine, Atatürk University, Erzurum, Turkey
| | - Saeed Shoaie
- Centre for Host-Microbiome Interactions, Faculty of Dentistry, Oral & Craniofacial Sciences, King's College London, London, SE1 9RT, UK
| | - Adil Mardinoglu
- Centre for Host-Microbiome Interactions, Faculty of Dentistry, Oral & Craniofacial Sciences, King's College London, London, SE1 9RT, UK.
- Science for Life Laboratory, KTH-Royal Institute of Technology, SE-17121, Stockholm, Sweden.
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Alam MS, Sultana A, Sun H, Wu J, Guo F, Li Q, Ren H, Hao Z, Zhang Y, Wang G. Bioinformatics and network-based screening and discovery of potential molecular targets and small molecular drugs for breast cancer. Front Pharmacol 2022; 13:942126. [PMID: 36204232 PMCID: PMC9531711 DOI: 10.3389/fphar.2022.942126] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/12/2022] [Accepted: 08/29/2022] [Indexed: 11/19/2022] Open
Abstract
Accurate identification of molecular targets of disease plays an important role in diagnosis, prognosis, and therapies. Breast cancer (BC) is one of the most common malignant cancers in women worldwide. Thus, the objective of this study was to accurately identify a set of molecular targets and small molecular drugs that might be effective for BC diagnosis, prognosis, and therapies, by using existing bioinformatics and network-based approaches. Nine gene expression profiles (GSE54002, GSE29431, GSE124646, GSE42568, GSE45827, GSE10810, GSE65216, GSE36295, and GSE109169) collected from the Gene Expression Omnibus (GEO) database were used for bioinformatics analysis in this study. Two packages, LIMMA and clusterProfiler, in R were used to identify overlapping differential expressed genes (oDEGs) and significant GO and KEGG enrichment terms. We constructed a PPI (protein–protein interaction) network through the STRING database and identified eight key genes (KGs) EGFR, FN1, EZH2, MET, CDK1, AURKA, TOP2A, and BIRC5 by using six topological measures, betweenness, closeness, eccentricity, degree, MCC, and MNC, in the Analyze Network tool in Cytoscape. Three online databases GSCALite, Network Analyst, and GEPIA were used to analyze drug enrichment, regulatory interaction networks, and gene expression levels of KGs. We checked the prognostic power of KGs through the prediction model using the popular machine learning algorithm support vector machine (SVM). We suggested four TFs (TP63, MYC, SOX2, and KDM5B) and four miRNAs (hsa-mir-16-5p, hsa-mir-34a-5p, hsa-mir-1-3p, and hsa-mir-23b-3p) as key transcriptional and posttranscriptional regulators of KGs. Finally, we proposed 16 candidate repurposing drugs YM201636, masitinib, SB590885, GSK1070916, GSK2126458, ZSTK474, dasatinib, fedratinib, dabrafenib, methotrexate, trametinib, tubastatin A, BIX02189, CP466722, afatinib, and belinostat for BC through molecular docking analysis. Using BC cell lines, we validated that masitinib inhibits the mTOR signaling pathway and induces apoptotic cell death. Therefore, the proposed results might play an effective role in the treatment of BC patients.
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Affiliation(s)
- Md Shahin Alam
- Laboratory of Molecular Neuropathology, Department of Pharmacology, Jiangsu Key Laboratory of Neuropsychiatric Diseases and College of Pharmaceutical Sciences, Soochow University, Suzhou, Jiangsu, China
| | - Adiba Sultana
- Laboratory of Molecular Neuropathology, Department of Pharmacology, Jiangsu Key Laboratory of Neuropsychiatric Diseases and College of Pharmaceutical Sciences, Soochow University, Suzhou, Jiangsu, China
| | - Hongyang Sun
- Laboratory of Molecular Neuropathology, Department of Pharmacology, Jiangsu Key Laboratory of Neuropsychiatric Diseases and College of Pharmaceutical Sciences, Soochow University, Suzhou, Jiangsu, China
| | - Jin Wu
- Laboratory of Molecular Neuropathology, Department of Pharmacology, Jiangsu Key Laboratory of Neuropsychiatric Diseases and College of Pharmaceutical Sciences, Soochow University, Suzhou, Jiangsu, China
| | - Fanfan Guo
- Department of Pharmacology, College of Pharmaceutical Science, Soochow University, Suzhou, Jiangsu, China
| | - Qing Li
- Department of Gastroenterology, the First People’s Hospital of Taicang, Taicang Affiliated Hospital of Soochow University, Suzhou, Jiangsu, China
| | - Haigang Ren
- Laboratory of Molecular Neuropathology, Department of Pharmacology, Jiangsu Key Laboratory of Neuropsychiatric Diseases and College of Pharmaceutical Sciences, Soochow University, Suzhou, Jiangsu, China
| | - Zongbing Hao
- Laboratory of Molecular Neuropathology, Department of Pharmacology, Jiangsu Key Laboratory of Neuropsychiatric Diseases and College of Pharmaceutical Sciences, Soochow University, Suzhou, Jiangsu, China
- *Correspondence: Zongbing Hao, ; Yi Zhang, ; Guanghui Wang,
| | - Yi Zhang
- Department of Pharmacology, College of Pharmaceutical Science, Soochow University, Suzhou, Jiangsu, China
- *Correspondence: Zongbing Hao, ; Yi Zhang, ; Guanghui Wang,
| | - Guanghui Wang
- Laboratory of Molecular Neuropathology, Department of Pharmacology, Jiangsu Key Laboratory of Neuropsychiatric Diseases and College of Pharmaceutical Sciences, Soochow University, Suzhou, Jiangsu, China
- *Correspondence: Zongbing Hao, ; Yi Zhang, ; Guanghui Wang,
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Repositioning Drugs for Rare Diseases Based on Biological Features and Computational Approaches. Healthcare (Basel) 2022; 10:healthcare10091784. [PMID: 36141396 PMCID: PMC9498751 DOI: 10.3390/healthcare10091784] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/02/2022] [Revised: 09/12/2022] [Accepted: 09/14/2022] [Indexed: 11/16/2022] Open
Abstract
Rare diseases are a group of uncommon diseases in the world population. To date, about 7000 rare diseases have been documented. However, most of them do not have a known treatment. As a result of the relatively low demand for their treatments caused by their scarce prevalence, the pharmaceutical industry has not sufficiently encouraged the research to develop drugs to treat them. This work aims to analyse potential drug-repositioning strategies for this kind of disease. Drug repositioning seeks to find new uses for existing drugs. In this context, it seeks to discover if rare diseases could be treated with medicines previously indicated to heal other diseases. Our approaches tackle the problem by employing computational methods that calculate similarities between rare and non-rare diseases, considering biological features such as genes, proteins, and symptoms. Drug candidates for repositioning will be checked against clinical trials found in the scientific literature. In this study, 13 different rare diseases have been selected for which potential drugs could be repositioned. By verifying these drugs in the scientific literature, successful cases were found for 75% of the rare diseases studied. The genetic associations and phenotypical features of the rare diseases were examined. In addition, the verified drugs were classified according to the anatomical therapeutic chemical (ATC) code to highlight the types with a higher predisposition to be repositioned. These promising results open the door for further research in this field of study.
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Siddiqui S, Deshmukh AJ, Mudaliar P, Nalawade AJ, Iyer D, Aich J. Drug repurposing: re-inventing therapies for cancer without re-entering the development pipeline—a review. J Egypt Natl Canc Inst 2022; 34:33. [PMID: 35934727 PMCID: PMC9358112 DOI: 10.1186/s43046-022-00137-0] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/07/2022] [Accepted: 07/10/2022] [Indexed: 11/25/2022] Open
Abstract
While majority of the current treatment approaches for cancer remain expensive and are associated with several side effects, development of new treatment modalities takes a significant period of research, time, and expenditure. An alternative novel approach is drug repurposing that focuses on finding new applications for the previously clinically approved drugs. The process of drug repurposing has also been facilitated by current advances in the field of proteomics, genomics, and information computational biology. This approach not only provides cheaper, effective, and potentially safer drugs with less side effects but also increases the processing pace of drug development. In this review, we wish to highlight some recent developments in the area of drug repurposing in cancer with a specific focus on the repurposing potential of anti-psychotic, anti-inflammatory and anti-viral drugs, anti-diabetic, antibacterial, and anti-fungal drugs.
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Repurposing Drugs via Network Analysis: Opportunities for Psychiatric Disorders. Pharmaceutics 2022; 14:pharmaceutics14071464. [PMID: 35890359 PMCID: PMC9319329 DOI: 10.3390/pharmaceutics14071464] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/01/2022] [Revised: 06/30/2022] [Accepted: 07/12/2022] [Indexed: 02/04/2023] Open
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 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.
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Combination Therapy of Ledipasvir and Itraconazole in the Treatment of COVID-19 Patients Coinfected with Black Fungus: An In Silico Statement. BIOMED RESEARCH INTERNATIONAL 2022; 2022:5904261. [PMID: 35463967 PMCID: PMC9020143 DOI: 10.1155/2022/5904261] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 12/26/2021] [Revised: 03/29/2022] [Accepted: 04/01/2022] [Indexed: 11/19/2022]
Abstract
The manuscript mainly aimed at providing clues on improving the innate immunity of coronavirus patients and safeguarding them from both new mutant strains and black fungus infections. Coronavirus is readily mutating from one variant to another. Among the several variants, we selected SARS-CoV-2 B.1.1.7 in this study. Upon infection of any virus, ideally, the phagocytic cells of the host engulf and destroy the virus by a mechanism called phagocytosis. However, compromised immunity impairs phagocytosis, and thus, restoring the immune system is crucial for a speedy recovery of infected patients. The autophagy and activation of Toll-like receptor-4 are the only ways to restore innate immunity. Recently, immunocompromised COVID-19 patients have been suffering from the coinfection of black fungus. Rhizomucor, a black fungus species, causes more than 75% of cases of mucormycosis. Here, we present the results of molecular docking studies of sixty approved antiviral drugs targeting receptors associated with the SARS-CoV-2 B 1.1.7 variant (PDB id: 7NEH), activating the innate immune system (PDB id: 5YEC and 5IJC). We also studied the twenty approved antifungal drugs with Rhizomucor miehei lipase propeptide (PDB id: 6QPR) to identify the possible combination therapy for patients coinfected with coronavirus and black fungus. The ledipasvir showed excellent docking interactions with the 7NEH, 5YEC, and 5IJC, indicating that it is a perfect candidate for the treatment of COVID-19 patients. Itraconazole showed significant interaction with 6QPR of Rhizomucor miehei, suggesting that itraconazole can treat black fungus infections. In conclusion, the combination therapy of ledipasvir and itraconazole can be a better alternative for treating COVID-19 patients coinfected with black fungus.
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Medhasi S, Chindamporn A, Worasilchai N. A Review: Antimicrobial Therapy for Human Pythiosis. Antibiotics (Basel) 2022; 11:antibiotics11040450. [PMID: 35453202 PMCID: PMC9029071 DOI: 10.3390/antibiotics11040450] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/14/2022] [Revised: 03/16/2022] [Accepted: 03/22/2022] [Indexed: 01/14/2023] Open
Abstract
Human pythiosis is associated with poor prognosis with significant mortality caused by Pythium insidiosum. Antimicrobials’ in vitro and in vivo results against P. insidiosum are inconsistent. Although antimicrobials are clinically useful, they are not likely to achieve therapeutic success alone without surgery and immunotherapy. New therapeutic options are therefore needed. This non-exhaustive review discusses the rationale antimicrobial therapy, minimum inhibitory concentrations, and efficacy of antibacterial and antifungal agents against P. insidiosum. This review further provides insight into the immunomodulating effects of antimicrobials that can enhance the immune response to infections. Current data support using antimicrobial combination therapy for the pharmacotherapeutic management of human pythiosis. Also, the success or failure of antimicrobial treatment in human pythiosis might depend on the immunomodulatory effects of drugs. The repurposing of existing drugs is a safe strategy for anti-P. insidiosum drug discovery. To improve patient outcomes in pythiosis, we suggest further research and a deeper understanding of P. insidiosum virulence factors, host immune response, and host immune system modification by antimicrobials.
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Affiliation(s)
- Sadeep Medhasi
- Department of Transfusion Medicine and Clinical Microbiology, Faculty of Allied Health Sciences, Chulalongkorn University, Bangkok 10330, Thailand;
| | - Ariya Chindamporn
- Department of Microbiology, Faculty of Medicine, Chulalongkorn University, Bangkok 10330, Thailand;
| | - Navaporn Worasilchai
- Department of Transfusion Medicine and Clinical Microbiology, Faculty of Allied Health Sciences, Immunomodulation of Natural Products Research Group, Chulalongkorn University, Bangkok 10330, Thailand
- Correspondence: ; Tel.: +66-2218-1065
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Recent Advances in Influenza, HIV and SARS-CoV-2 Infection Prevention and Drug Treatment—The Need for Precision Medicine. CHEMISTRY 2022. [DOI: 10.3390/chemistry4020019] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022] Open
Abstract
Viruses, and in particular, RNA viruses, dominate the WHO’s current list of ten global health threats. Of these, we review the widespread and most common HIV, influenza virus, and SARS-CoV-2 infections, as well as their possible prevention by vaccination and treatments by pharmacotherapeutic approaches. Beyond the vaccination, we discuss the virus-targeting and host-targeting drugs approved in the last five years, in the case of SARS-CoV-2 in the last one year, as well as new drug candidates and lead molecules that have been published in the same periods. We share our views on vaccination and pharmacotherapy, their mutually reinforcing strategic significance in combating pandemics, and the pros and cons of host and virus-targeted drug therapy. The COVID-19 pandemic has provided evidence of our limited armamentarium to fight emerging viral diseases. Novel broad-spectrum vaccines as well as drugs that could even be applied as prophylactic treatments or in early phases of the viremia, possibly through oral administration, are needed in all three areas. To meet these needs, the use of multi-data-based precision medicine in the practice and innovation of vaccination and drug therapy is inevitable.
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Drug Repurposing for the Management of Depression: Where Do We Stand Currently? Life (Basel) 2021; 11:life11080774. [PMID: 34440518 PMCID: PMC8398872 DOI: 10.3390/life11080774] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/29/2021] [Revised: 07/20/2021] [Accepted: 07/26/2021] [Indexed: 12/22/2022] Open
Abstract
A slow rate of new drug discovery and higher costs of new drug development attracted the attention of scientists and physicians for the repurposing and repositioning of old medications. Experimental studies and off-label use of drugs have helped drive data for further studies of approving these medications. A deeper understanding of the pathogenesis of depression encourages novel discoveries through drug repurposing and drug repositioning to treat depression. In addition to reducing neurotransmitters like epinephrine and serotonin, other mechanisms such as inflammation, insufficient blood supply, and neurotoxicants are now considered as the possible involved mechanisms. Considering the mentioned mechanisms has resulted in repurposed medications to treat treatment-resistant depression (TRD) as alternative approaches. This review aims to discuss the available treatments and their progress way during repositioning. Neurotransmitters’ antagonists, atypical antipsychotics, and CNS stimulants have been studied for the repurposing aims. However, they need proper studies in terms of formulation, matching with regulatory standards, and efficacy.
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Mohanty S, Rashid MHA, Mohanty C, Swayamsiddha S. Modern computational intelligence based drug repurposing for diabetes epidemic. Diabetes Metab Syndr 2021; 15:102180. [PMID: 34186343 DOI: 10.1016/j.dsx.2021.06.017] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/30/2020] [Revised: 06/12/2021] [Accepted: 06/14/2021] [Indexed: 12/18/2022]
Abstract
BACKGROUND AND AIM Objectives are to explore recent advances in discovery of new antidiabetic agents using repurposing strategies and to discuss modern technologies used for drug repurposing highlighting diabetic specific web portal. METHODS Recent literature were studied and analyzed from various sources such as Scopus, PubMed, and IEEE Xplore databases. RESULTS Drugs like Niclosamideethanolamine, Methazolamide, Diacerein, Berberine, Clobetasol, etc. with possibility of repurposing to curb diabetes can be potential late-stage clinical candidates, providing access to information on pharmacology, formulation, and probable toxicity if any. CONCLUSIONS With collaboration of artificial intelligence (AI) with pharmacology, the efficiency of drug repurposing can improve significantly.
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Affiliation(s)
- Sweta Mohanty
- School of Applied Science, KIIT University, Bhubaneswar, Odisha, India
| | | | - Chandana Mohanty
- School of Applied Science, KIIT University, Bhubaneswar, Odisha, India.
| | - Swati Swayamsiddha
- School of Electronics Engineering, KIIT University, Bhubaneswar, Odisha, India.
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