scholarly journals A review of COVID-19 biomarkers and drug targets: resources and tools

2020 ◽  
Author(s):  
Francesca P Caruso ◽  
Giovanni Scala ◽  
Luigi Cerulo ◽  
Michele Ceccarelli
Keyword(s):  
Artificial Intelligence ◽  
Drug Targets ◽  
Vaccine Development ◽  
Target Identification ◽  
Drug Repurposing ◽  
Biomarker Identification ◽  
Risk Of Progression ◽  
Patients At Risk ◽  
Amount Of Knowledge ◽  
Bioinformatics Community

Abstract The stratification of patients at risk of progression of COVID-19 and their molecular characterization is of extreme importance to optimize treatment and to identify therapeutic options. The bioinformatics community has responded to the outbreak emergency with a set of tools and resource to identify biomarkers and drug targets that we review here. Starting from a consolidated corpus of 27 570 papers, we adopt latent Dirichlet analysis to extract relevant topics and select those associated with computational methods for biomarker identification and drug repurposing. The selected topics span from machine learning and artificial intelligence for disease characterization to vaccine development and to therapeutic target identification. Although the way to go for the ultimate defeat of the pandemic is still long, the amount of knowledge, data and tools generated so far constitutes an unprecedented example of global cooperation to this threat.

Coronavirus Disease 2019: Virology and Drug Targets

2020 ◽  
Vol 20 ◽  
Author(s):  
Praveen Thaggikuppe Krishnamurthy
Keyword(s):  
High Throughput Screening ◽  
Drug Targets ◽  
Vaccine Development ◽  
Antiviral Drug ◽  
Drug Repurposing ◽  
Structural Proteins ◽  
Current Status ◽  
Approved Drugs ◽  
Viral Target ◽  
Fda Approved Drugs

: The Coronavirus Disease 2019, a pandemic caused by novel Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2), is seriously affecting global health and the economy. As the vaccine development takes time, the current research is focused on repurposing FDA approved drugs against the viral target proteins. This review discusses the current understanding of SARS-CoV-2 virology, its target structural proteins (S- glycoprotein), non-structural proteins (3- chymotrypsin-like protease, papain-like protease, RNA-dependent RNA polymerase, and helicase) and accessory proteins, drug discovery strategies (drug repurposing, artificial intelligence, and high-throughput screening), and the current status of antiviral drug development.

Application of Artificial Intelligence in Drug Repurposing: A mini-review

2021 ◽  
Vol 01 ◽  
Author(s):  
Gurudeeban Selvaraj ◽  
Satyavani Kaliamurthi ◽  
Gilles H. Peslherbe ◽  
Dong-Qing Wei
Keyword(s):  
Artificial Intelligence ◽  
Drug Repositioning ◽  
Target Identification ◽  
Drug Repurposing ◽  
Search Term ◽  
Biomedical Data ◽  
Drug Candidates ◽  
Drug Target Identification ◽  
Speed Up ◽  
Tools And Techniques

Background and aim: Advancement of extra-ordinary biomedical data (genomics, proteomics, metabolomics, drug libraries, and patient care data), evolution of super-computers, and continuous development of new algorithms that lead to a generous revolution in artificial intelligence (AI). Currently, many biotech and pharmaceutical companies made reasonable investments in and have co-operation with AI companies and increasing the chance of better healthcare tools development, includes biomarker and drug target identification, designing a new class of drugs and drug repurposing. Thus, the study is intended to project the pros and cons of AI in the application of drug repositioning. Methods: Using the search term “AI” and “drug repurposing” the relevant literatures retrieved and reviewed from different sources includes PubMed, Google Scholar, and Scopus. Results: Drug discovery is a lengthy process, however, leveraging the AI approaches in drug repurposing via quick virtual screening may enhance and speed-up the identification of potential drug candidates against communicable and non-communicable diseases. Therefore, in this mini-review, we have discussed different algorithms, tools and techniques, advantages, limitations on predicting the target in repurposing a drug. Conclusions: AI technology in drug repurposing with the association of pharmacology can efficiently identify drug candidates against pandemic diseases.

scholarly journals Finding genetically-supported drug targets for Parkinson’s disease using Mendelian randomization of the druggable genome

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Catherine S. Storm ◽  
Demis A. Kia ◽  
Mona M. Almramhi ◽  
Sara Bandres-Ciga ◽  
Chris Finan ◽  
...  
Keyword(s):  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Drug Targets ◽  
Molecular Mechanisms ◽  
Mendelian Randomization ◽  
Disease Risk ◽  
Target Identification ◽  
Causal Effect ◽  
Age At Onset ◽  
Drug Repurposing

AbstractParkinson’s disease is a neurodegenerative movement disorder that currently has no disease-modifying treatment, partly owing to inefficiencies in drug target identification and validation. We use Mendelian randomization to investigate over 3,000 genes that encode druggable proteins and predict their efficacy as drug targets for Parkinson’s disease. We use expression and protein quantitative trait loci to mimic exposure to medications, and we examine the causal effect on Parkinson’s disease risk (in two large cohorts), age at onset and progression. We propose 23 drug-targeting mechanisms for Parkinson’s disease, including four possible drug repurposing opportunities and two drugs which may increase Parkinson’s disease risk. Of these, we put forward six drug targets with the strongest Mendelian randomization evidence. There is remarkably little overlap between our drug targets to reduce Parkinson’s disease risk versus progression, suggesting different molecular mechanisms. Drugs with genetic support are considerably more likely to succeed in clinical trials, and we provide compelling genetic evidence and an analysis pipeline to prioritise Parkinson’s disease drug development.

Systematic Design and Evaluation of Drug Repurposing-Oriented Alzheimer’s Disease Ontology (Preprint)

2020 ◽  
Author(s):  
Fang Li ◽  
Muhammad "Tuan" Amith ◽  
Grace Xiong ◽  
Jingcheng Du ◽  
Yang Xiang ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Drug Targets ◽  
Drug Repurposing ◽  
Essential Elements ◽  
Genomic Research ◽  
Core Knowledge ◽  
Disease Ontology ◽  
Hybrid Strategy ◽  
Complementary Strategy

BACKGROUND Alzheimer’s Disease (AD) is a devastating neurodegenerative disease, of which the pathophysiology is insufficiently understood, and the curative drugs are long-awaited to be developed. Computational drug repurposing introduces a promising complementary strategy of drug discovery, which benefits from an accelerated development process and decreased failure rate. However, generating new hypotheses in AD drug repurposing requires multi-dimensional and multi-disciplinary data integration and connection, posing a great challenge in the era of big data. By integrating data with computable semantics, ontologies could infer unknown relationships through automated reasoning and fulfill an essential role in supporting computational drug repurposing. OBJECTIVE The study aimed to systematically design a robust Drug Repurposing-Oriented Alzheimer’s Disease Ontology (DROADO), which could model fundamental elements and their relationships involved in AD drug repurposing and integrate their up-to-date research advance comprehensively. METHODS We devised a core knowledge model of computational AD drug repurposing, based on both pre-genomic and post-genomic research paradigms. The model centered on the possible AD pathophysiology and abstracted the essential elements and their relationships. We adopted a hybrid strategy to populate the ontology (classes and properties), including importing from well-curated databases, extracting from high-quality papers and reusing the existing ontologies. We also leveraged n-ary relations and nanopublication graphs to enrich the object relations, making the knowledge stored in the ontology more powerful in supporting computational processing. The initially built ontology was evaluated by a semiotic-driven and web-based tool Ontokeeper. RESULTS The current version of DROADO was composed of 1,021 classes, 23 object properties and 3,207 axioms, depicting a fundamental network related to computational neuroscience concepts and relationships. Assessment using semiotic evaluation metrics by OntoKeeper indicated sufficient preliminary quality (semantics, usefulness and community-consensus) of the ontology. CONCLUSIONS As an in-depth knowledge base, DROADO would be promising in enabling computational algorithms to realize supervised mining from multi-source data, and ultimately, facilitating the discovery of novel AD drug targets and the realization of AD drug repurposing.

scholarly journals Genomics-driven drug discovery based on disease-susceptibility genes

2021 ◽  
Vol 41 (1) ◽  
Author(s):  
Kyuto Sonehara ◽  
Yukinori Okada
Keyword(s):  
Drug Discovery ◽  
Drug Targets ◽  
Disease Susceptibility ◽  
Mendelian Randomization ◽  
Association Studies ◽  
Drug Repurposing ◽  
Susceptibility Genes ◽  
Genome Wide Association Studies ◽  
Genome Wide ◽  
Disease Associations

AbstractGenome-wide association studies have identified numerous disease-susceptibility genes. As knowledge of gene–disease associations accumulates, it is becoming increasingly important to translate this knowledge into clinical practice. This challenge involves finding effective drug targets and estimating their potential side effects, which often results in failure of promising clinical trials. Here, we review recent advances and future perspectives in genetics-led drug discovery, with a focus on drug repurposing, Mendelian randomization, and the use of multifaceted omics data.

Coronaviruses: A Scientist’s Race Against Time

2020 ◽  
Author(s):  
Saloni Chaurasia ◽  
Keyword(s):  
Healthcare Workers ◽  
Vaccine Development ◽  
Drug Repurposing ◽  
Alveolar Epithelial Cells ◽  
Contact Tracing ◽  
Medical Innovation ◽  
Alveolar Epithelial ◽  
Treatment And Prevention ◽  
Scientific World ◽  
Respiratory Droplets

As the clock ticks, more and more people are falling victim to COVID-19, and scientists are racing against time to find treatment and prevention strategies. But what’s stopping them? The answer comes from two primary problems. Firstly, coronaviruses (CoVs) are transmitted from person-to-person via respiratory droplets from an infected person’s coughs or sneezes, which makes them highly contagious (CDC, How COVID-19 Spreads, 2020). This can happen in minutes, and up to 25% of patients remain asymptomatic (Du, et al., 2020). This makes it difficult for healthcare workers and researchers to contain patients and establish contact tracing to isolate the infected population. Secondly, it is hard to target CoVs without damaging our cells. CoVs infect via spike protein, which binds to the ACE2 receptor located on the lung alveolar epithelial cells (Hoffmann, et al., 2020). Once they invade the cell, CoVs hijack the host cell’s mechanisms to replicate. Thus, it is hard to combat the virus without damaging the host cell. On the other hand, recent understanding of CoVs structure and mechanism of action enables the scientific world to create a cure or vaccine. The bad news is that these efforts will likely face the perennial hurdles of medical innovation and discovery, long timelines of clinical trials for drug repurposing, and vaccine development, sometimes fickle funding, and changing governmental priorities.

scholarly journals Mammalian deubiquitinating enzyme inhibitors display in vitro and in vivo activity against malaria parasites and potentiate artemisinin action

2020 ◽  
Author(s):  
Nelson V. Simwela ◽  
Katie R. Hughes ◽  
Michael T. Rennie ◽  
Michael P. Barrett ◽  
Andrew P. Waters
Keyword(s):  
Anticancer Agents ◽  
Drug Targets ◽  
Reverse Genetics ◽  
Enzyme Inhibitors ◽  
Artemisinin Resistance ◽  
Drug Repurposing ◽  
Antimalarial Drugs ◽  
Malaria Parasites

AbstractCurrent malaria control efforts rely significantly on artemisinin combinational therapies which have played massive roles in alleviating the global burden of the disease. Emergence of resistance to artemisinins is therefore, not just alarming but requires immediate intervention points such as development of new antimalarial drugs or improvement of the current drugs through adjuvant or combination therapies. Artemisinin resistance is primarily conferred by Kelch13 propeller mutations which are phenotypically characterised by generalised growth quiescence, altered haemoglobin trafficking and downstream enhanced activity of the parasite stress pathways through the ubiquitin proteasome system (UPS). Previous work on artemisinin resistance selection in a rodent model of malaria, which we and others have recently validated using reverse genetics, has also shown that mutations in deubiquitinating enzymes, DUBs (upstream UPS component) modulates susceptibility of malaria parasites to both artemisinin and chloroquine. The UPS or upstream protein trafficking pathways have, therefore, been proposed to be not just potential drug targets, but also possible intervention points to overcome artemisinin resistance. Here we report the activity of small molecule inhibitors targeting mammalian DUBs in malaria parasites. We show that generic DUB inhibitors can block intraerythrocytic development of malaria parasites in vitro and possess antiparasitic activity in vivo and can be used in combination with additive effect. We also show that inhibition of these upstream components of the UPS can potentiate the activity of artemisinin in vitro as well as in vivo to the extent that ART resistance can be overcome. Combinations of DUB inhibitors anticipated to target different DUB activities and downstream 20s proteasome inhibitors are even more effective at improving the potency of artemisinins than either inhibitors alone providing proof that targeting multiple UPS activities simultaneously could be an attractive approach to overcoming artemisinin resistance. These data further validate the parasite UPS as a target to both enhance artemisinin action and potentially overcome resistance. Lastly, we confirm that DUB inhibitors can be developed into in vivo antimalarial drugs with promise for activity against all of human malaria and could thus further exploit their current pursuit as anticancer agents in rapid drug repurposing programs.Graphical abstract

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