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Sun G, Dong D, Dong Z, Zhang Q, Fang H, Wang C, Zhang S, Wu S, Dong Y, Wan Y. Drug repositioning: A bibliometric analysis. Front Pharmacol 2022; 13:974849. [PMID: 36225586 PMCID: PMC9549161 DOI: 10.3389/fphar.2022.974849] [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: 06/21/2022] [Accepted: 08/12/2022] [Indexed: 11/14/2022] Open
Abstract
Drug repurposing has become an effective approach to drug discovery, as it offers a new way to explore drugs. Based on the Science Citation Index Expanded (SCI-E) and Social Sciences Citation Index (SSCI) databases of the Web of Science core collection, this study presents a bibliometric analysis of drug repurposing publications from 2010 to 2020. Data were cleaned, mined, and visualized using Derwent Data Analyzer (DDA) software. An overview of the history and development trend of the number of publications, major journals, major countries, major institutions, author keywords, major contributors, and major research fields is provided. There were 2,978 publications included in the study. The findings show that the United States leads in this area of research, followed by China, the United Kingdom, and India. The Chinese Academy of Science published the most research studies, and NIH ranked first on the h-index. The Icahn School of Medicine at Mt Sinai leads in the average number of citations per study. Sci Rep, Drug Discov. Today, and Brief. Bioinform. are the three most productive journals evaluated from three separate perspectives, and pharmacology and pharmacy are unquestionably the most commonly used subject categories. Cheng, FX; Mucke, HAM; and Butte, AJ are the top 20 most prolific and influential authors. Keyword analysis shows that in recent years, most research has focused on drug discovery/drug development, COVID-19/SARS-CoV-2/coronavirus, molecular docking, virtual screening, cancer, and other research areas. The hotspots have changed in recent years, with COVID-19/SARS-CoV-2/coronavirus being the most popular topic for current drug repurposing research.
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Affiliation(s)
- Guojun Sun
- Institute of Pharmaceutical Preparations, Department of Pharmacy, Zhejiang University of Technology, Hangzhou, China
| | - Dashun Dong
- Institute of Pharmaceutical Preparations, Department of Pharmacy, Zhejiang University of Technology, Hangzhou, China
| | - Zuojun Dong
- Institute of Pharmaceutical Preparations, Department of Pharmacy, Zhejiang University of Technology, Hangzhou, China
| | - Qian Zhang
- Institute of Pharmaceutical Preparations, Department of Pharmacy, Zhejiang University of Technology, Hangzhou, China
| | - Hui Fang
- Institute of Information Resource, Zhejiang University of Technology, Hangzhou, China
| | - Chaojun Wang
- Hangzhou Aeronautical Sanatorium for Special Service of Chinese Air Force, Hangzhou, China
| | - Shaoya Zhang
- Institute of Pharmaceutical Preparations, Department of Pharmacy, Zhejiang University of Technology, Hangzhou, China
| | - Shuaijun Wu
- Institute of Pharmaceutical Preparations, Department of Pharmacy, Zhejiang University of Technology, Hangzhou, China
| | - Yichen Dong
- Faculty of Chinese Medicine, Macau University of Science and Technology, Macau, China
| | - Yuehua Wan
- Institute of Information Resource, Zhejiang University of Technology, Hangzhou, China
- *Correspondence: Yuehua Wan,
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2
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Recent advances in drug repurposing using machine learning. Curr Opin Chem Biol 2021; 65:74-84. [PMID: 34274565 DOI: 10.1016/j.cbpa.2021.06.001] [Citation(s) in RCA: 22] [Impact Index Per Article: 7.3] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/11/2021] [Revised: 05/28/2021] [Accepted: 06/01/2021] [Indexed: 12/11/2022]
Abstract
Drug repurposing aims to find new uses for already existing and approved drugs. We now provide a brief overview of recent developments in drug repurposing using machine learning alongside other computational approaches for comparison. We also highlight several applications for cancer using kinase inhibitors, Alzheimer's disease as well as COVID-19.
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Anderson E, Havener TM, Zorn KM, Foil DH, Lane TR, Capuzzi SJ, Morris D, Hickey AJ, Drewry DH, Ekins S. Synergistic drug combinations and machine learning for drug repurposing in chordoma. Sci Rep 2020; 10:12982. [PMID: 32737414 PMCID: PMC7395084 DOI: 10.1038/s41598-020-70026-w] [Citation(s) in RCA: 17] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/23/2020] [Accepted: 07/20/2020] [Indexed: 12/18/2022] Open
Abstract
Chordoma is a devastating rare cancer that affects one in a million people. With a mean-survival of just 6 years and no approved medicines, the primary treatments are surgery and radiation. In order to speed new medicines to chordoma patients, a drug repurposing strategy represents an attractive approach. Drugs that have already advanced through human clinical safety trials have the potential to be approved more quickly than de novo discovered medicines on new targets. We have taken two strategies to enable this: (1) generated and validated machine learning models of chordoma inhibition and screened compounds of interest in vitro. (2) Tested combinations of approved kinase inhibitors already being individually evaluated for chordoma. Several published studies of compounds screened against chordoma cell lines were used to generate Bayesian Machine learning models which were then used to score compounds selected from the NIH NCATS industry-provided assets. Out of these compounds, the mTOR inhibitor AZD2014, was the most potent against chordoma cell lines (IC50 0.35 µM U-CH1 and 0.61 µM U-CH2). Several studies have shown the importance of the mTOR signaling pathway in chordoma and suggest it as a promising avenue for targeted therapy. Additionally, two currently FDA approved drugs, afatinib and palbociclib (EGFR and CDK4/6 inhibitors, respectively) demonstrated synergy in vitro (CI50 = 0.43) while AZD2014 and afatanib also showed synergy (CI50 = 0.41) against a chordoma cell in vitro. These findings may be of interest clinically, and this in vitro- and in silico approach could also be applied to other rare cancers.
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Affiliation(s)
- Edward Anderson
- UNC Catalyst for Rare Diseases, Eshelman School of Pharmacy, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Tammy M Havener
- UNC Catalyst for Rare Diseases, Eshelman School of Pharmacy, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Kimberley M Zorn
- Collaborations Pharmaceuticals, Inc., 840 Main Campus Drive, Lab 3510, Raleigh, NC, USA
| | - Daniel H Foil
- Collaborations Pharmaceuticals, Inc., 840 Main Campus Drive, Lab 3510, Raleigh, NC, USA
| | - Thomas R Lane
- Collaborations Pharmaceuticals, Inc., 840 Main Campus Drive, Lab 3510, Raleigh, NC, USA
| | - Stephen J Capuzzi
- UNC Catalyst for Rare Diseases, Eshelman School of Pharmacy, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Dave Morris
- UNC Catalyst for Rare Diseases, Eshelman School of Pharmacy, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Anthony J Hickey
- UNC Catalyst for Rare Diseases, Eshelman School of Pharmacy, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
- RTI International, Research Triangle Park, NC, USA
| | - David H Drewry
- Structural Genomics Consortium, UNC Eshelman School of Pharmacy, University of North Carolina at Chapel Hill, Chapel Hill, NC, 27599, USA
| | - Sean Ekins
- UNC Catalyst for Rare Diseases, Eshelman School of Pharmacy, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.
- Collaborations Pharmaceuticals, Inc., 840 Main Campus Drive, Lab 3510, Raleigh, NC, USA.
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4
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Hei Y, Teng B, Zeng Z, Zhang S, Li Q, Pan J, Luo Z, Xiong C, Wei S. Multifunctional Immunoliposomes Combining Catalase and PD-L1 Antibodies Overcome Tumor Hypoxia and Enhance Immunotherapeutic Effects Against Melanoma. Int J Nanomedicine 2020; 15:1677-1691. [PMID: 32214807 PMCID: PMC7082626 DOI: 10.2147/ijn.s225807] [Citation(s) in RCA: 36] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/02/2019] [Accepted: 02/03/2020] [Indexed: 12/18/2022] Open
Abstract
Background Immune checkpoint blockades (ICBs) are a promising treatment for cancers such as melanoma by blocking important inhibitory pathways that enable tumor cells to evade immune attack. Programmed death ligand 1 monoclonal antibodies (aPDL1s) can be used as an ICB to significantly enhance the effectiveness of tumor immunotherapy by blocking the PD-1/PD-L1 inhibitory pathway. However, the effectiveness of aPDL1s may be limited by low selectivity in vivo and immunosuppressed tumor microenvironment including hypoxia. Purpose To overcome the limitations, we develop a multifunctional immunoliposome, called CAT@aPDL1-SSL, with catalase (CAT) encapsulated inside to overcome tumor hypoxia and aPDL1s modified on the surface to enhance immunotherapeutic effects against melanoma. Methods The multifunctional immunoliposomes (CAT@aPDL1-SSLs) are prepared using the film dispersion/post-insertion method. The efficacy of CAT@aPDL1-SSLs is verified by multiple experiments in vivo and in vitro. Results The results of this study suggest that the multifunctional immunoliposomes preserve and protect the enzyme activity of CAT and ameliorate tumor hypoxia. Moreover, the enhanced cellular uptake of CAT@aPDL1-SSLs in vitro and their in vivo biodistribution suggest that CAT@aPDL1-SSLs have great targeting ability,resulting in improved delivery and accumulation of immunoliposomes in tumor tissue.Finally, by activating and increasing the infiltration of CD8+ T cells at the tumor site, CAT@aPDL1-SSLs inhibit the growth of tumor and prolong survival time of mice,with low systemic toxicity. Conclusion In conclusion, the multifunctional immunoliposomes developed and proposed in this study are a promising candidate for melanoma immunotherapy, and could potentially be combined with other cancer therapies like radiotherapy and chemotherapy to produce positive outcomes.
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Affiliation(s)
- Yu Hei
- Department of Mechanics and Engineering Science, College of Engineering, Peking University, Beijing, People's Republic of China
| | - Binhong Teng
- Department of Oral and Maxillofacial Surgery, School and Hospital of Stomatology, Peking University, Beijing, People's Republic of China.,Laboratory of Biomaterials and Regenerative Medicine, Academy for Advanced Interdisciplinary Studies, Peking University, Beijing, People's Republic of China
| | - Ziqian Zeng
- Department of Oral and Maxillofacial Surgery, School and Hospital of Stomatology, Peking University, Beijing, People's Republic of China.,Laboratory of Biomaterials and Regenerative Medicine, Academy for Advanced Interdisciplinary Studies, Peking University, Beijing, People's Republic of China
| | - Siqi Zhang
- Laboratory of Biomaterials and Regenerative Medicine, Academy for Advanced Interdisciplinary Studies, Peking University, Beijing, People's Republic of China
| | - Qian Li
- Laboratory of Biomaterials and Regenerative Medicine, Academy for Advanced Interdisciplinary Studies, Peking University, Beijing, People's Republic of China
| | - Jijia Pan
- Laboratory of Biomaterials and Regenerative Medicine, Academy for Advanced Interdisciplinary Studies, Peking University, Beijing, People's Republic of China
| | - Zuyuan Luo
- Laboratory of Biomaterials and Regenerative Medicine, Academy for Advanced Interdisciplinary Studies, Peking University, Beijing, People's Republic of China
| | - Chunyang Xiong
- Department of Mechanics and Engineering Science, College of Engineering, Peking University, Beijing, People's Republic of China
| | - Shicheng Wei
- Department of Oral and Maxillofacial Surgery, School and Hospital of Stomatology, Peking University, Beijing, People's Republic of China.,Laboratory of Biomaterials and Regenerative Medicine, Academy for Advanced Interdisciplinary Studies, Peking University, Beijing, People's Republic of China
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Southan C, Sharman JL, Faccenda E, Pawson AJ, Harding SD, Davies JA. Challenges of Connecting Chemistry to Pharmacology: Perspectives from Curating the IUPHAR/BPS Guide to PHARMACOLOGY. ACS OMEGA 2018; 3:8408-8420. [PMID: 30087946 PMCID: PMC6070956 DOI: 10.1021/acsomega.8b00884] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 05/02/2018] [Accepted: 07/12/2018] [Indexed: 06/08/2023]
Abstract
Connecting chemistry to pharmacology has been an objective of Guide to PHARMACOLOGY (GtoPdb) and its precursor the International Union of Basic and Clinical Pharmacology Database (IUPHAR-DB) since 2003. This has been achieved by populating our database with expert-curated relationships between documents, assays, quantitative results, chemical structures, their locations within the documents, and the protein targets in the assays (D-A-R-C-P). A wide range of challenges associated with this are described in this perspective, using illustrative examples from GtoPdb entries. Our selection process begins with judgments of pharmacological relevance and scientific quality. Even though we have a stringent focus for our small-data extraction, we note that assessing the quality of papers has become more difficult over the last 15 years. We discuss ambiguity issues with the resolution of authors' descriptions of A-R-C-P entities to standardized identifiers. We also describe developments that have made this somewhat easier over the same period both in the publication ecosystem and recent enhancements of our internal processes. This perspective concludes with a look at challenges for the future, including the wider capture of mechanistic nuances and possible impacts of text mining on automated entity extraction.
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6
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Ashenden SK, Kogej T, Engkvist O, Bender A. Innovation in Small-Molecule-Druggable Chemical Space: Where are the Initial Modulators of New Targets Published? J Chem Inf Model 2017; 57:2741-2753. [PMID: 29068231 DOI: 10.1021/acs.jcim.7b00295] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Abstract
It is well-established that the number of publications of novel small molecule modulators, and their associated targets, has increased over the years. This work focuses on publishing trends over the years with a particular focus on the comparison between patents and scientific literature which is accessible via the ChEMBL and GOSTAR databases. More precisely, the patents and scientific literature associated with bioactive molecules and their target annotations have been compared to identify where novelty (in the meaning of the first modulator of a protein target) originated from. Comparing the published date of the first small molecule modulator published in literature and patents for a particular target (with either identical or different structure) shows that modulators are usually published in both scientific literature and in patents (45%), or in scientific literature alone (51%), but rarely in patents only. When looking at the time when first modulators are published in both sources, 65% of the time they are disseminated in literature first. Finally, when analyzing just the novel small molecule modulators, regardless of the protein targets they have been published with, those structures representing novel chemistry tend to be published in patents first 61% of the time.
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Affiliation(s)
- Stephanie K Ashenden
- Centre for Molecular Informatics, Department of Chemistry, University of Cambridge , Cambridge, CB2 1EW, United Kingdom
| | - Thierry Kogej
- Discovery Sciences, IMED Biotech Unit, AstraZeneca , Gothenburg 431 50 SE, Sweden
| | - Ola Engkvist
- Discovery Sciences, IMED Biotech Unit, AstraZeneca , Gothenburg 431 50 SE, Sweden
| | - Andreas Bender
- Centre for Molecular Informatics, Department of Chemistry, University of Cambridge , Cambridge, CB2 1EW, United Kingdom
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7
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Zhang R, Song X, Liang C, Yi X, Song G, Chao Y, Yang Y, Yang K, Feng L, Liu Z. Catalase-loaded cisplatin-prodrug-constructed liposomes to overcome tumor hypoxia for enhanced chemo-radiotherapy of cancer. Biomaterials 2017; 138:13-21. [PMID: 28550753 DOI: 10.1016/j.biomaterials.2017.05.025] [Citation(s) in RCA: 166] [Impact Index Per Article: 23.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/09/2017] [Revised: 05/08/2017] [Accepted: 05/17/2017] [Indexed: 12/15/2022]
Abstract
Aiming at improved therapeutic efficacies, the combination of chemotherapy and radiotherapy (chemo-radiotherapy) has been widely studied and applied in clinic. However, the hostile characteristics of tumor microenvironment such as hypoxia often limit the efficacies in both types of cancer therapies. Herein, catalase (CAT), an antioxidant enzyme, is encapsulated inside liposomes constituted by cisplatin (IV)-prodrug-conjugated phospholipid, forming CAT@Pt (IV)-liposome for enhanced chemo-radiotherapy of cancer. After being loaded inside liposomes, CAT within CAT@Pt (IV)-liposome shows retained and well-protected enzyme activity, and is able to trigger decomposition of H2O2 produced by tumor cells, so as to produce additional oxygen for hypoxia relief. As the result, treatment of CAT@Pt (IV)-liposome induces the highest level of DNA damage in cancer cells after X-ray radiation compared to the control groups. In vivo tumor treatment further demonstrates a remarkably improved therapeutic outcome in chemo-radiotherapy with such CAT@Pt (IV)-liposome nanoparticles. Hence, an exquisite type of liposome-based nanoparticles is developed in this work by integrating cisplatin-based chemotherapy and catalase-induced tumor hypoxia relief together for combined chemo-radiotherapy with great synergistic efficacy, promising for clinical translation in cancer treatment.
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Affiliation(s)
- Rui Zhang
- Institute of Functional Nano & Soft Materials (FUNSOM), Jiangsu Key Laboratory for Carbon-Based Functional Materials & Devices, Soochow University, Suzhou, 215123, China
| | - Xuejiao Song
- Institute of Functional Nano & Soft Materials (FUNSOM), Jiangsu Key Laboratory for Carbon-Based Functional Materials & Devices, Soochow University, Suzhou, 215123, China
| | - Chao Liang
- Institute of Functional Nano & Soft Materials (FUNSOM), Jiangsu Key Laboratory for Carbon-Based Functional Materials & Devices, Soochow University, Suzhou, 215123, China
| | - Xuan Yi
- School of Radiation Medicine and Protection & School for Radiological and Interdisciplinary Sciences (RAD-X), Medical College of Soochow University, Suzhou, Jiangsu, 215123, China
| | - Guosheng Song
- Institute of Functional Nano & Soft Materials (FUNSOM), Jiangsu Key Laboratory for Carbon-Based Functional Materials & Devices, Soochow University, Suzhou, 215123, China
| | - Yu Chao
- Institute of Functional Nano & Soft Materials (FUNSOM), Jiangsu Key Laboratory for Carbon-Based Functional Materials & Devices, Soochow University, Suzhou, 215123, China
| | - Yu Yang
- Institute of Functional Nano & Soft Materials (FUNSOM), Jiangsu Key Laboratory for Carbon-Based Functional Materials & Devices, Soochow University, Suzhou, 215123, China
| | - Kai Yang
- School of Radiation Medicine and Protection & School for Radiological and Interdisciplinary Sciences (RAD-X), Medical College of Soochow University, Suzhou, Jiangsu, 215123, China
| | - Liangzhu Feng
- Institute of Functional Nano & Soft Materials (FUNSOM), Jiangsu Key Laboratory for Carbon-Based Functional Materials & Devices, Soochow University, Suzhou, 215123, China.
| | - Zhuang Liu
- Institute of Functional Nano & Soft Materials (FUNSOM), Jiangsu Key Laboratory for Carbon-Based Functional Materials & Devices, Soochow University, Suzhou, 215123, China.
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8
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Barnes PJ, Bonini S, Seeger W, Belvisi MG, Ward B, Holmes A. Barriers to new drug development in respiratory disease. Eur Respir J 2016; 45:1197-207. [PMID: 25931481 DOI: 10.1183/09031936.00007915] [Citation(s) in RCA: 82] [Impact Index Per Article: 10.3] [Reference Citation Analysis] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/05/2023]
Affiliation(s)
- Peter J Barnes
- Airways Disease Section, National Heart and Lung Institute, Imperial College London, London, UK
| | - Sergio Bonini
- Second University of Naples, Caserta, Italy Institute of Translational Pharmacology-CNR, Rome, Italy European Medicines Agency, London, UK
| | - Werner Seeger
- University of Giessen and Marburg Lung Centre, Member of the German Centre for Lung Research (DZL), Giessen, Germany
| | - Maria G Belvisi
- Airways Disease Section, National Heart and Lung Institute, Imperial College London, London, UK
| | - Brian Ward
- European Affairs Dept, European Respiratory Society, Brussels, Belgium
| | - Anthony Holmes
- National Centre for the Replacement, Refinement and Reduction of Animals in Research (NC3Rs), London, UK
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9
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Frail DE, Brady M, Escott KJ, Holt A, Sanganee HJ, Pangalos MN, Watkins C, Wegner CD. Pioneering government-sponsored drug repositioning collaborations: progress and learning. Nat Rev Drug Discov 2015; 14:833-41. [DOI: 10.1038/nrd4707] [Citation(s) in RCA: 40] [Impact Index Per Article: 4.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/10/2023]
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10
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Ai N, Fan X, Ekins S. In silico methods for predicting drug-drug interactions with cytochrome P-450s, transporters and beyond. Adv Drug Deliv Rev 2015; 86:46-60. [PMID: 25796619 DOI: 10.1016/j.addr.2015.03.006] [Citation(s) in RCA: 24] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/19/2014] [Revised: 01/05/2015] [Accepted: 03/11/2015] [Indexed: 12/13/2022]
Abstract
Drug-drug interactions (DDIs) are associated with severe adverse effects that may lead to the patient requiring alternative therapeutics and could ultimately lead to drug withdrawal from the market if they are severe. To prevent the occurrence of DDI in the clinic, experimental systems to evaluate drug interaction have been integrated into the various stages of the drug discovery and development process. A large body of knowledge about DDI has also accumulated through these studies and pharmacovigillence systems. Much of this work to date has focused on the drug metabolizing enzymes such as cytochrome P-450s as well as drug transporters, ion channels and occasionally other proteins. This combined knowledge provides a foundation for a hypothesis-driven in silico approach, using either cheminformatics or physiologically based pharmacokinetics (PK) modeling methods to assess DDI potential. Here we review recent advances in these approaches with emphasis on hypothesis-driven mechanistic models for important protein targets involved in PK-based DDI. Recent efforts with other informatics approaches to detect DDI are highlighted. Besides DDI, we also briefly introduce drug interactions with other substances, such as Traditional Chinese Medicines to illustrate how in silico modeling can be useful in this domain. We also summarize valuable data sources and web-based tools that are available for DDI prediction. We finally explore the challenges we see faced by in silico approaches for predicting DDI and propose future directions to make these computational models more reliable, accurate, and publically accessible.
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Affiliation(s)
- Ni Ai
- Pharmaceutical Informatics Institute, College of Pharmaceutical Sciences, Zhejiang University, 866 Yuhangtang Road, Hangzhou, Zhejiang 310058, PR China
| | - Xiaohui Fan
- Pharmaceutical Informatics Institute, College of Pharmaceutical Sciences, Zhejiang University, 866 Yuhangtang Road, Hangzhou, Zhejiang 310058, PR China.
| | - Sean Ekins
- Collaborations in Chemistry, 5616 Hilltop Needmore Road, Fuquay-Varina, NC 27526, USA.
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11
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Langedijk J, Mantel-Teeuwisse AK, Slijkerman DS, Schutjens MHDB. Drug repositioning and repurposing: terminology and definitions in literature. Drug Discov Today 2015; 20:1027-34. [PMID: 25975957 DOI: 10.1016/j.drudis.2015.05.001] [Citation(s) in RCA: 177] [Impact Index Per Article: 19.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/08/2015] [Revised: 04/17/2015] [Accepted: 05/01/2015] [Indexed: 01/18/2023]
Abstract
Drug repositioning and similar terms have been a trending topic in literature and represent novel drug development strategies. We analysed in a quantitative and qualitative manner how these terms were used and defined in the literature. In total, 217 articles referred to 'drug repositioning', 'drug repurposing', 'drug reprofiling', 'drug redirecting' and/or 'drug rediscovery'. Only 67 included a definition ranging from brief and general to extensive and specific. No common definition was identified. Nevertheless, four common features were found: concept, action, use and product. The different wording used for these features often leads to essential differences in meaning between definitions. In case a clear definition is needed, for example from a legal or regulatory perspective, the features can provide further guidance.
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Affiliation(s)
- Joris Langedijk
- Department of Pharmacoepidemiology & Clinical Pharmacology, Utrecht Institute for Pharmaceutical Sciences (UIPS), Utrecht University, Utrecht, The Netherlands; Medicines Evaluation Board, Utrecht, The Netherlands
| | - Aukje K Mantel-Teeuwisse
- Department of Pharmacoepidemiology & Clinical Pharmacology, Utrecht Institute for Pharmaceutical Sciences (UIPS), Utrecht University, Utrecht, The Netherlands.
| | | | - Marie-Hélène D B Schutjens
- Department of Pharmacoepidemiology & Clinical Pharmacology, Utrecht Institute for Pharmaceutical Sciences (UIPS), Utrecht University, Utrecht, The Netherlands; Schutjens de Bruin, Tilburg, The Netherlands
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12
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Abstract
The current Ebola virus epidemic may provide some suggestions of how we can better prepare for the next pathogen outbreak. We propose several cost effective steps that could be taken that would impact the discovery and use of small molecule therapeutics including: 1. text mine the literature, 2. patent assignees and/or inventors should openly declare their relevant filings, 3. reagents and assays could be commoditized, 4. using manual curation to enhance database links, 5. engage database and curation teams, 6. consider open science approaches, 7. adapt the "box" model for shareable reference compounds, and 8. involve the physician's perspective.
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Affiliation(s)
- Sean Ekins
- Collaborations in Chemistry, 5616 Hilltop Needmore Road, Fuquay-Varina, NC, 27526, USA ; Collaborative Drug Discovery, 1633 Bayshore Highway, Suite 342, Burlingame, CA, 94010, USA
| | - Christopher Southan
- IUPHAR/BPS Guide to PHARMACOLOGY, Centre for Integrative Physiology, University of Edinburgh, Hugh Robson Building, Edinburgh, EH8 9XD, UK
| | - Megan Coffee
- Center for Infectious Diseases and Emergency Readiness, University of California at Berkeley, 1918 University Ave, Berkeley, CA, 94704, USA
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13
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Abstract
The current Ebola virus epidemic may provide some suggestions of how we can better prepare for the next pathogen outbreak. We propose several cost effective steps that could be taken that would impact the discovery and use of small molecule therapeutics including: 1. text mine the literature, 2. patent assignees and/or inventors should openly declare their relevant filings, 3. reagents and assays could be commoditized, 4. using manual curation to enhance database links, 5. engage database and curation teams, 6. consider open science approaches, 7. adapt the "box" model for shareable reference compounds, and 8. involve the physician's perspective.
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Affiliation(s)
- Sean Ekins
- Collaborations in Chemistry, 5616 Hilltop Needmore Road, Fuquay-Varina, NC, 27526, USA ; Collaborative Drug Discovery, 1633 Bayshore Highway, Suite 342, Burlingame, CA, 94010, USA
| | - Christopher Southan
- IUPHAR/BPS Guide to PHARMACOLOGY, Centre for Integrative Physiology, University of Edinburgh, Hugh Robson Building, Edinburgh, EH8 9XD, UK
| | - Megan Coffee
- Center for Infectious Diseases and Emergency Readiness, University of California at Berkeley, 1918 University Ave, Berkeley, CA, 94704, USA
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14
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Ekins S, Litterman NK, Arnold RJG, Burgess RW, Freundlich JS, Gray SJ, Higgins JJ, Langley B, Willis DE, Notterpek L, Pleasure D, Sereda MW, Moore A. A brief review of recent Charcot-Marie-Tooth research and priorities. F1000Res 2015; 4:53. [PMID: 25901280 PMCID: PMC4392824 DOI: 10.12688/f1000research.6160.1] [Citation(s) in RCA: 25] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 02/24/2015] [Indexed: 12/14/2022] Open
Abstract
This brief review of current research progress on Charcot-Marie-Tooth (CMT) disease is a summary of discussions initiated at the Hereditary Neuropathy Foundation (HNF) scientific advisory board meeting on November 7, 2014. It covers recent published and unpublished
in vitro and
in vivo research. We discuss recent promising preclinical work for CMT1A, the development of new biomarkers, the characterization of different animal models, and the analysis of the frequency of gene mutations in patients with CMT. We also describe how progress in related fields may benefit CMT therapeutic development, including the potential of gene therapy and stem cell research. We also discuss the potential to assess and improve the quality of life of CMT patients. This summary of CMT research identifies some of the gaps which may have an impact on upcoming clinical trials. We provide some priorities for CMT research and areas which HNF can support. The goal of this review is to inform the scientific community about ongoing research and to avoid unnecessary overlap, while also highlighting areas ripe for further investigation. The general collaborative approach we have taken may be useful for other rare neurological diseases.
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Affiliation(s)
- Sean Ekins
- Hereditary Neuropathy Foundation, New York, NY, 10016, USA ; Collaborations in Chemistry, Fuquay Varina, NC, 27526, USA ; Collaborative Drug Discovery, Burlingame, CA, 94010, USA
| | | | - Renée J G Arnold
- Arnold Consultancy & Technology LLC, New York, NY, 10023, USA ; Master of Public Health Program, Mount Sinai School of Medicine, New York, NY, 10029, USA ; Quorum Consulting, Inc, San Francisco, CA, 94104, USA
| | - Robert W Burgess
- The Jackson Laboratory in Bar Harbor, Bar Harbour, ME, 04609, USA
| | - Joel S Freundlich
- Department of Medicine, Center for Emerging and Reemerging Pathogens, Rutgers University - New Jersey Medical School, Newark, NJ, 07103, USA
| | - Steven J Gray
- Gene Therapy Center and Dept. of Ophthalmology, University of North Carolina at Chapel Hill, Chapel Hill, NC, 27599-7352, USA
| | | | - Brett Langley
- Burke-Cornell Medical Research Institute, White Plains, NY, 10605, USA ; Department of Neurology and Neuroscience, Weill Medical College of Cornell University, New York, NY, 10065, USA
| | - Dianna E Willis
- Burke-Cornell Medical Research Institute, White Plains, NY, 10605, USA
| | - Lucia Notterpek
- Department of Neuroscience, College of Medicine, McKnight Brain Institute, University of Florida, Gainesville, FL, 32611, USA
| | - David Pleasure
- Institute for Pediatric Regenerative Medicine, University of California Davis, School of Medicine, Sacramento, CA, 95817, USA ; Department of Neurology, University of California, Davis, School of Medicine, c/o Shriners Hospital, Sacramento, CA, 95817, USA
| | - Michael W Sereda
- Department of Neurogenetics, Max Planck Institute (MPI) of Experimental Medicine, Göttingen, 37075, Germany ; Department of Clinical Neurophysiology, University Medical Center (UMG), Göttingen, D-37075, Germany
| | - Allison Moore
- Hereditary Neuropathy Foundation, New York, NY, 10016, USA
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15
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Lipinski CA, Litterman NK, Southan C, Williams AJ, Clark AM, Ekins S. Parallel worlds of public and commercial bioactive chemistry data. J Med Chem 2014; 58:2068-76. [PMID: 25415348 PMCID: PMC4360371 DOI: 10.1021/jm5011308] [Citation(s) in RCA: 23] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/27/2022]
Abstract
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The
availability of structures and linked bioactivity data in databases
is powerfully enabling for drug discovery and chemical biology. However,
we now review some confounding issues with the divergent expansions
of public and commercial sources of chemical structures. These are
associated with not only expanding patent extraction but also increasingly
large vendor collections amassed via different selection criteria
between SciFinder from Chemical Abstracts Service (CAS) and major
public sources such as PubChem, ChemSpider, UniChem, and others. These
increasingly massive collections may include both real and virtual
compounds, as well as so-called prophetic compounds from patents.
We address a range of issues raised by the challenges faced resolving
the NIH probe compounds. In addition we highlight the confounding
of prior-art searching by virtual compounds that could impact the
composition of matter patentability of a new medicinal chemistry lead.
Finally, we propose some potential solutions.
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Affiliation(s)
- Christopher A Lipinski
- Christopher A. Lipinski, Ph.D., LLC , 10 Connshire Drive, Waterford, Connecticut 06385-4122, United States
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16
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Abstract
Rare disease research has reached a tipping point, with the confluence of scientific and technologic developments that if appropriately harnessed, could lead to key breakthroughs and treatments for this set of devastating disorders. Industry-wide trends have revealed that the traditional drug discovery research and development (R&D) model is no longer viable, and drug companies are evolving their approach. Rather than only pursue blockbuster therapeutics for heterogeneous, common diseases, drug companies have increasingly begun to shift their focus to rare diseases. In academia, advances in genetics analyses and disease mechanisms have allowed scientific understanding to mature, but the lack of funding and translational capability severely limits the rare disease research that leads to clinical trials. Simultaneously, there is a movement towards increased research collaboration, more data sharing, and heightened engagement and active involvement by patients, advocates, and foundations. The growth in networks and social networking tools presents an opportunity to help reach other patients but also find researchers and build collaborations. The growth of collaborative software that can enable researchers to share their data could also enable rare disease patients and foundations to manage their portfolio of funded projects for developing new therapeutics and suggest drug repurposing opportunities. Still there are many thousands of diseases without treatments and with only fragmented research efforts. We will describe some recent progress in several rare diseases used as examples and propose how collaborations could be facilitated. We propose that the development of a center of excellence that integrates and shares informatics resources for rare diseases sponsored by all of the stakeholders would help foster these initiatives.
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Affiliation(s)
| | - Michele Rhee
- National Brain Tumor Society, Newton, MA, 02458, USA
| | - David C Swinney
- Institute for Rare and Neglected Diseases Drug Discovery (iRND3), Mountain View, CA, 94043, USA
| | - Sean Ekins
- Collaborative Drug Discovery, Inc., Burlingame, CA, 94010, USA ; Collaborations in Chemistry, Fuquay Varina, NC, 27526, USA ; Phoenix Nest Inc., Brooklyn, NY, 11215, USA ; Hereditary Neuropathy Foundation, New York, NY, 10016, USA ; Hannah's Hope Fund, Rexford, NY, NY 12148, USA
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17
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Wynne GM, Russell AJ. Drug Discovery Approaches for Rare Neuromuscular Diseases. ORPHAN DRUGS AND RARE DISEASES 2014. [DOI: 10.1039/9781782624202-00257] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/29/2023]
Abstract
Rare neuromuscular diseases encompass many diverse and debilitating musculoskeletal disorders, ranging from ultra-orphan conditions that affect only a few families, to the so-called ‘common’ orphan diseases like Duchenne muscular dystrophy (DMD) and spinal muscular atrophy (SMA), which affect several thousand individuals worldwide. Increasingly, pharmaceutical and biotechnology companies, in an effort to improve productivity and rebuild dwindling pipelines, are shifting their business models away from the formerly popular ‘blockbuster’ strategy, with rare diseases being an area of increased focus in recent years. As a consequence of this paradigm shift, coupled with high-profile campaigns by not-for-profit organisations and patient advocacy groups, rare neuromuscular diseases are attracting considerable attention as new therapeutic areas for improved drug therapy. Much pioneering work has taken place to elucidate the underlying pathological mechanisms of many rare neuromuscular diseases. This, in conjunction with the availability of new screening technologies, has inspired the development of several truly innovative therapeutic strategies aimed at correcting the underlying pathology. A survey of medicinal chemistry approaches and the resulting clinical progress for new therapeutic agents targeting this devastating class of degenerative diseases is presented, using DMD and SMA as examples. Complementary strategies using small-molecule drugs and biological agents are included.
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Affiliation(s)
- Graham M. Wynne
- Chemistry Research Laboratory, University of Oxford 12 Mansfield Road Oxford OX1 3TA UK
| | - Angela J. Russell
- Chemistry Research Laboratory, University of Oxford 12 Mansfield Road Oxford OX1 3TA UK
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18
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Ekins S, Freundlich JS, Reynolds RC. Are bigger data sets better for machine learning? Fusing single-point and dual-event dose response data for Mycobacterium tuberculosis. J Chem Inf Model 2014; 54:2157-65. [PMID: 24968215 DOI: 10.1021/ci500264r] [Citation(s) in RCA: 30] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/07/2023]
Abstract
Tuberculosis is a major, neglected disease for which the quest to find new treatments continues. There is an abundance of data from large phenotypic screens in the public domain against Mycobacterium tuberculosis (Mtb). Since machine learning methods can learn from past data, we were interested in addressing whether more data builds better models. We now describe using Bayesian machine learning to assess whether we can improve our models by combining the large quantities of single-point data with the much smaller (higher quality) dual-event data sets, which use both dose-response data for both whole-cell antitubercular activity and Vero cell cytotoxicity. We have evaluated 12 models ranging from different single-point, dual-event dose-response, single-point and dual-event dose-response as well as combined data sets for three distinct data sets from the same laboratory. We used a fourth data set of active and inactive compounds from the same group as well as a smaller set of 177 active compounds from GlaxoSmithKline as test sets. Our data suggest combining single-point with dual-event dose-response data does not diminish the internal or external predictive ability of the models based on the receiver operator curve (ROC) for these models (internal ROC range 0.83-0.91, external ROC range 0.62-0.83) compared to the orders of magnitude smaller dual-event models (internal ROC range 0.6-0.83 and external ROC 0.54-0.83). In conclusion, models developed with 1200-5000 compounds appear to be as predictive as those generated with 25 000-350 000 molecules. Our results have implications for justifying further high-throughput screening versus focused testing based on model predictions.
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Affiliation(s)
- Sean Ekins
- Collaborations in Chemistry , 5616 Hilltop Needmore Road, Fuquay-Varina, North Carolina 27526, United States
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19
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Tracking 20 years of compound-to-target output from literature and patents. PLoS One 2013; 8:e77142. [PMID: 24204758 PMCID: PMC3812171 DOI: 10.1371/journal.pone.0077142] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/05/2013] [Accepted: 08/28/2013] [Indexed: 12/19/2022] Open
Abstract
The statistics of drug development output and declining yield of approved medicines has been the subject of many recent reviews. However, assessing research productivity that feeds development is more difficult. Here we utilise an extensive database of structure-activity relationships extracted from papers and patents. We have used this database to analyse published compounds cumulatively linked to nearly 4000 protein target identifiers from multiple species over the last 20 years. The compound output increases up to 2005 followed by a decline that parallels a fall in pharmaceutical patenting. Counts of protein targets have plateaued but not fallen. We extended these results by exploring compounds and targets for one large pharmaceutical company. In addition, we examined collective time course data for six individual protease targets, including average molecular weight of the compounds. We also tracked the PubMed profile of these targets to detect signals related to changes in compound output. Our results show that research compound output had decreased 35% by 2012. The major causative factor is likely to be a contraction in the global research base due to mergers and acquisitions across the pharmaceutical industry. However, this does not rule out an increasing stringency of compound quality filtration and/or patenting cost control. The number of proteins mapped to compounds on a yearly basis shows less decline, indicating the cumulative published target capacity of global research is being sustained in the region of 300 proteins for large companies. The tracking of six individual targets shows uniquely detailed patterns not discernible from cumulative snapshots. These are interpretable in terms of events related to validation and de-risking of targets that produce detectable follow-on surges in patenting. Further analysis of the type we present here can provide unique insights into the process of drug discovery based on the data it actually generates.
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20
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Southan C. InChI in the wild: an assessment of InChIKey searching in Google. J Cheminform 2013; 5:10. [PMID: 23399051 PMCID: PMC3598674 DOI: 10.1186/1758-2946-5-10] [Citation(s) in RCA: 31] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/29/2012] [Accepted: 02/08/2013] [Indexed: 11/22/2022] Open
Abstract
While chemical databases can be queried using the InChI string and InChIKey (IK) the latter was designed for open-web searching. It is becoming increasingly effective for this since more sources enhance crawling of their websites by the Googlebot and consequent IK indexing. Searchers who use Google as an adjunct to database access may be less familiar with the advantages of using the IK as explored in this review. As an example, the IK for atorvastatin retrieves ~200 low-redundancy links from a Google search in 0.3 of a second. These include most major databases and a very low false-positive rate. Results encompass less familiar but potentially useful sources and can be extended to isomer capture by using just the skeleton layer of the IK. Google Advanced Search can be used to filter large result sets. Image searching with the IK is also effective and complementary to open-web queries. Results can be particularly useful for less-common structures as exemplified by a major metabolite of atorvastatin giving only three hits. Testing also demonstrated document-to-document and document-to-database joins via structure matching. The necessary generation of an IK from chemical names can be accomplished using open tools and resources for patents, papers, abstracts or other text sources. Active global sharing of local IK-linked information can be accomplished via surfacing in open laboratory notebooks, blogs, Twitter, figshare and other routes. While information-rich chemistry (e.g. approved drugs) can exhibit swamping and redundancy effects, the much smaller IK result sets for link-poor structures become a transformative first-pass option. The IK indexing has therefore turned Google into a de-facto open global chemical information hub by merging links to most significant sources, including over 50 million PubChem and ChemSpider records. The simplicity, specificity and speed of matching make it a useful option for biologists or others less familiar with chemical searching. However, compared to rigorously maintained major databases, users need to be circumspect about the consistency of Google results and provenance of retrieved links. In addition, community engagement may be necessary to ameliorate possible future degradation of utility.
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