Computational Drug Repurposing for Neurodegenerative Diseases

Savva, Kyriaki; Zachariou, Margarita; Oulas, Anastasis; Minadakis, George; Sokratous, Kleitos; Dietis, Nikolas

doi:10.1016/b978-0-12-816125-8.00004-3

Cited by 10 publications

(7 citation statements)

References 142 publications

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“…In network models pairwise relations between various objects is exhibited. Schematically, in such networks, nodes are represented by entities (genes, proteins, complexes, metabolite, disease), while edges represent interactions or relationship between two nodes such the relationship between drugs and known gene targets and large number of diverse connections between two nodes can be displayed concurrently ( Savva et al, 2019 ). Despite of the potency of such approaches has been verified for considerable times with drug-target interaction prediction, these methods are afflicted by the deficiency of current knowledge on molecular interactome, leading to noisy results.…”

Section: Drug Repurposing Approachesmentioning

confidence: 99%

“…For the past few years, genome wide association studies (GWAS) has been another source of data which is being exploited for new information regarding the association of specific genomic variations known as single nucleotide polymorphisms (SNPs), with complex trait human diseases, such as AD, multiple sclerosis, etc. ( Savva et al, 2019 ). GWAS can distinguish thousands of SNPs synchronously and these data are used by researchers to detect genes that are linked with a specific disease trait and to analyse how these variations affect responses to drugs.…”

Section: Drug Repurposing Approachesmentioning

confidence: 99%

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

2022

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

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Section: Drug Repurposing Approachesmentioning

confidence: 99%

Section: Drug Repurposing Approachesmentioning

confidence: 99%

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

2022

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“…Computational drug repurposing methods include the following: Structure-based virtual screening (molecular docking), Ligand-based methods (Pharmacophore model, Quantitative structure–activity relationship, and Reverse docking methods), 159 Transcriptomic-based methods, 160 genome-wide association study (GWAS) methods, 161 Literature-based discovery methods, 162 and Network-based, Multisource data integration and Machine-Learning approaches. 163 …”

Section: Concepts From Systems Medicine Modeling and Data Sciencementioning

confidence: 99%

An Early Stage Researcher's Primer on Systems Medicine Terminology

Zanin

Aitya

Basílio

et al. 2021

Network and Systems Medicine

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Background: Systems Medicine is a novel approach to medicine, that is, an interdisciplinary field that considers the human body as a system, composed of multiple parts and of complex relationships at multiple levels, and further integrated into an environment. Exploring Systems Medicine implies understanding and combining concepts coming from diametral different fields, including medicine, biology, statistics, modeling and simulation, and data science. Such heterogeneity leads to semantic issues, which may slow down implementation and fruitful interaction between these highly diverse fields. Methods: In this review, we collect and explain more than100 terms related to Systems Medicine. These include both modeling and data science terms and basic systems medicine terms, along with some synthetic definitions, examples of applications, and lists of relevant references. Results: This glossary aims at being a first aid kit for the Systems Medicine researcher facing an unfamiliar term, where he/she can get a first understanding of them, and, more importantly, examples and references for digging into the topic.

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“…Most previous reviews of drug repurposing technologies have focused on methods development [3,[21][22][23][24][25][26][27][28][29][30][31][32][33][34][35], with only a few providing cursory analysis of evaluation of those methods [29,35,36]. Brown and Patel have previously reported a review of "validation" strategies for computational drug repurposing [37], broadly categorizing various evaluation metrics into "(1) validation with a single example or case study of a single disease area, (2) sensitivitybased validation only and (3) both sensitivity-and specificity-based validation" [37].…”

Section: Introductionmentioning

confidence: 99%

Evaluating Performance of Drug Repurposing Technologies

Schuler

Falls

Mangione

et al. 2020

Preprint

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

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Computational Drug Repurposing for Neurodegenerative Diseases

Cited by 10 publications

References 142 publications

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

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

An Early Stage Researcher's Primer on Systems Medicine Terminology

Evaluating Performance of Drug Repurposing Technologies

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