A comprehensive SARS-CoV-2 genomic analysis identifies potential targets for drug repurposing

Background: The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) which is a novel human coronavirus strain (HCoV) initially reported in December 2019 in Wuhan City, China causing pneumonia-like symptoms and other respiratory tract illness. It’s higher transmission and infection rate has successfully enabled it to have a global spread over a matter of small time. With 6,529,240 cases and about 385,264 deaths, this pandemic has become a global concern with certain drugs and vaccines failing at later clinical trials. Materials and Methods: Phylogenetic Analysis, Haplotype Network, Analysis of conserved genes and population-level variants, Using conserved genes as targets for drug designing, Docking studies and Molecular Dynamics (MD) simulations to predict the stability of Drug-Ligand Complex. Results: We identified the most common haplotypes from the haplotype network and at least seven different clusters were found signifying seven different viral lineages across the globe. We studied the mutation frequency across the SARS-CoV-2 viral genome. The conserved genes and population level variants were analyzed and NSP10, Nucleoprotein, Plpro and 3CLpro which were conserved at the highest threshold were used as drug targets for molecular dynamics simulations. Darifenacin, Nebivolol, Bictegravir, Alvimopan and Irbesartan are among the potential drugs which are suggested for further pre-clinical and clinical trials. Significance: This particular study provides a comprehensive targeting of the conserved genes as a novel approach for drug targeting. The conserved gene approach could also be of a big use while designing vaccines and cure. Mutations in the viral genome make the designing of the drugs a challenging task which has a higher risk of failure at later clinical trials. This approach of targeting the stable genes for drug discovery would provide a better therapeutic approach and confidence in the successive clinical trials. We also identified the global level spread of SARS-CoV-2 and mutation frequencies across the viral genome. Our study gives insights of the origin and global spread of the SARS-CoV-2. The data provided in this study can further be used by other groups to understand and combat Covid 19.

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A Comprehensive SARS-CoV-2 Genomic Analysis Identifies Potential Targets for Drug Repurposing

10.26434/chemrxiv.12430919.v1 ◽

2020 ◽

Author(s):

Nithishwer Mouroug Anand ◽

Devang Haresh Liya ◽

Arpit Kumar Pradhan ◽

Nitish Tayal ◽

Abhinav Bansal ◽

...

Keyword(s):

Molecular Dynamics ◽

Clinical Trials ◽

Viral Genome ◽

Drug Targets ◽

Population Level ◽

Haplotype Network ◽

Small Time ◽

Ligand Complex ◽

Global Spread ◽

Conserved Genes

Background: The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) which is a novel human coronavirus strain (HCoV) initially reported in December 2019 in Wuhan City, China causing pneumonia-like symptoms and other respiratory tract illness. It’s higher transmission and infection rate has successfully enabled it to have a global spread over a matter of small time. With 6,529,240 cases and about 385,264 deaths, this pandemic has become a global concern with certain drugs and vaccines failing at later clinical trials. Materials and Methods: Phylogenetic Analysis, Haplotype Network, Analysis of conserved genes and population-level variants, Using conserved genes as targets for drug designing, Docking studies and Molecular Dynamics (MD) simulations to predict the stability of Drug-Ligand Complex. Results: We identified the most common haplotypes from the haplotype network and at least seven different clusters were found signifying seven different viral lineages across the globe. We studied the mutation frequency across the SARS-CoV-2 viral genome. The conserved genes and population level variants were analyzed and NSP10, Nucleoprotein, Plpro and 3CLpro which were conserved at the highest threshold were used as drug targets for molecular dynamics simulations. Darifenacin, Nebivolol, Bictegravir, Alvimopan and Irbesartan are among the potential drugs which are suggested for further pre-clinical and clinical trials. Significance: This particular study provides a comprehensive targeting of the conserved genes as a novel approach for drug targeting. The conserved gene approach could also be of a big use while designing vaccines and cure. Mutations in the viral genome make the designing of the drugs a challenging task which has a higher risk of failure at later clinical trials. This approach of targeting the stable genes for drug discovery would provide a better therapeutic approach and confidence in the successive clinical trials. We also identified the global level spread of SARS-CoV-2 and mutation frequencies across the viral genome. Our study gives insights of the origin and global spread of the SARS-CoV-2. The data provided in this study can further be used by other groups to understand and combat Covid 19.

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Drug Repurposing Approach, Potential Drugs, and Novel Drug Targets for COVID-19 Treatment

Journal of Environmental and Public Health ◽

10.1155/2021/6631721 ◽

2021 ◽

Vol 2021 ◽

pp. 1-11

Author(s):

Zemene Demelash Kifle ◽

Akeberegn Gorems Ayele ◽

Engidaw Fentahun Enyew

Keyword(s):

Drug Targets ◽

Protein Targeting ◽

Drug Repurposing ◽

Structural Protein ◽

Angiotensin Converting Enzyme 2 ◽

Dipeptidyl Peptidase 4 ◽

Novel Coronavirus ◽

Novel Drug ◽

Novel Drug Targets ◽

Viral Enzyme

Novel coronavirus first appeared in Wuhan, China, in December 2019, and it speedily expanded globally. Some medications which are used to treat other diseases seem to be effective in treating COVID-19 even without explicit support. The existing drugs that are summarized in this review primarily focused on therapeutic agents that possessed activity against other RNA viruses such as MERS-CoV and SARS-CoV. Drug repurposing or repositioning is a promising field in drug discovery that identifies new therapeutic opportunities for existing drugs such as corticosteroids, RNA-dependent RNA polymerase inhibitors, interferons, protease inhibitors, ivermectin, melatonin, teicoplanin, and some others. A search for new drug/drug targets is underway. Thus, blocking coronavirus structural protein, targeting viral enzyme, dipeptidyl peptidase 4, and membrane fusion blocker (angiotensin-converting enzyme 2 and CD147 inhibitor) are major sites based on molecular targets for the management of COVID-19 infection. The possible impact of biologics for the management of COVID19 is promising and includes a wide variety of options such as cytokines, nucleic acid-based therapies targeting virus gene expression, bioengineered and vectored antibodies, and various types of vaccines. This review demonstrates that the available data are not sufficient to suggest any treatment for the eradication of COVID-19 to be used at the clinical level. This article aims to review the roles of existing drugs and drug targets for COVID-19 treatment.

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

10.2196/preprints.17944 ◽

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.

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Family history assessment significantly enhances delivery of precision medicine in the genomics era

Genome Medicine ◽

10.1186/s13073-020-00819-1 ◽

2021 ◽

Vol 13 (1) ◽

Author(s):

Yasmin Bylstra ◽

Weng Khong Lim ◽

Sylvia Kam ◽

Koei Wan Tham ◽

R. Ryanne Wu ◽

...

Keyword(s):

Family History ◽

Cancer Risk ◽

Clinical Care ◽

Genomic Analysis ◽

Population Level ◽

Cancer Genes ◽

Family History Information ◽

Screening Programs ◽

Family History Assessment ◽

Risk Of Cancer

Abstract Background Family history has traditionally been an essential part of clinical care to assess health risks. However, declining sequencing costs have precipitated a shift towards genomics-first approaches in population screening programs rendering the value of family history unknown. We evaluated the utility of incorporating family history information for genomic sequencing selection. Methods To ascertain the relationship between family histories on such population-level initiatives, we analysed whole genome sequences of 1750 research participants with no known pre-existing conditions, of which half received comprehensive family history assessment of up to four generations, focusing on 95 cancer genes. Results Amongst the 1750 participants, 866 (49.5%) had high-quality standardised family history available. Within this group, 73 (8.4%) participants had an increased family history risk of cancer (increased FH risk cohort) and 1 in 7 participants (n = 10/73) carried a clinically actionable variant inferring a sixfold increase compared with 1 in 47 participants (n = 17/793) assessed at average family history cancer risk (average FH risk cohort) (p = 0.00001) and a sevenfold increase compared to 1 in 52 participants (n = 17/884) where family history was not available (FH not available cohort) (p = 0.00001). The enrichment was further pronounced (up to 18-fold) when assessing only the 25 cancer genes in the American College of Medical Genetics (ACMG) Secondary Findings (SF) genes. Furthermore, 63 (7.3%) participants had an increased family history cancer risk in the absence of an apparent clinically actionable variant. Conclusions These findings demonstrate that the collection and analysis of comprehensive family history and genomic data are complementary and in combination can prioritise individuals for genomic analysis. Thus, family history remains a critical component of health risk assessment, providing important actionable data when implementing genomics screening programs. Trial registration ClinicalTrials.gov NCT02791152. Retrospectively registered on May 31, 2016.

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Genomics-driven drug discovery based on disease-susceptibility genes

Inflammation and Regeneration ◽

10.1186/s41232-021-00158-7 ◽

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.

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

10.1101/2020.08.13.249425 ◽

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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Translational and Clinical Pharmacology Considerations in Drug Repurposing for X-linked Adrenoleukodystrophy-A Rare Peroxisomal Disorder

10.22541/au.162610374.45880274/v1 ◽

2021 ◽

Author(s):

Julianne Tieu ◽

Siddhee Sahasrabudhe ◽

Paul Orchard ◽

James Cloyd ◽

Reena Kartha

Keyword(s):

Drug Target ◽

Drug Targets ◽

Drug Repurposing ◽

Pharmacokinetics And Pharmacodynamics ◽

Drug Candidates ◽

Target Patient Population ◽

Site Of Action ◽

Repurposed Drugs ◽

Gait Disturbances ◽

Spastic Quadriparesis

X-linked adrenoleukodystrophy (X-ALD) is an inherited, neurodegenerative rare disease that can result in devastating symptoms of blindness, gait disturbances, and spastic quadriparesis due to progressive demyelination. Typically, the disease progresses rapidly, causing death within the first decade of life. With limited treatments available, efforts to determine an effective therapy that can alter disease progression or mitigate symptoms have been undertaken for many years, particularly through drug repurposing. Repurposing has generally been guided through clinical experience and small trials. At this time, none of the drug candidates have been approved for use, which may be due, in part, to the lack of pharmacokinetic/pharmacodynamic (PK/PD) information on the repurposed medications in the target patient population. Greater consideration for the disease pathophysiology, drug pharmacology, and potential drug-target interactions, specifically at the site of action, would improve drug repurposing and facilitate development. Although there is a good understanding of X-ALD pathophysiology, the absence of information on drug targets, pharmacokinetics, and pharmacodynamics hinders the repurposing of drugs for this condition. Incorporating advanced translational and clinical pharmacological approaches in preclinical studies and early stages clinical trials will improve the success of repurposed drugs for X-ALD as well as other rare diseases.

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Identifying Nootropic Drug Targets via Large-Scale Cognitive GWAS and Transcriptomics

10.1101/2020.02.06.934752 ◽

2020 ◽

Author(s):

Max Lam ◽

Chen Chia-Yen ◽

Xia Yan ◽

W. David Hill ◽

Joey W. Trampush ◽

...

Keyword(s):

Cognitive Ability ◽

Drug Targets ◽

Large Scale ◽

Drug Repurposing ◽

Gene Identification ◽

Summary Statistics ◽

General Cognitive Ability ◽

Nootropic Drug ◽

Genome Wide ◽

Meta Analyses

AbstractBackgroundCognitive traits demonstrate significant genetic correlations with many psychiatric disorders and other health-related traits. Many neuropsychiatric and neurodegenerative disorders are marked by cognitive deficits. Therefore, genome-wide association studies (GWAS) of general cognitive ability might suggest potential targets for nootropic drug repurposing. Our previous effort to identify “druggable genes” (i.e., GWAS-identified genes that produce proteins targeted by known small molecules) was modestly powered due to the small cognitive GWAS sample available at the time. Since then, two large cognitive GWAS meta-analyses have reported 148 and 205 genome-wide significant loci, respectively. Additionally, large-scale gene expression databases, derived from post-mortem human brain, have recently been made available for GWAS annotation. Here, we 1) reconcile results from these two cognitive GWAS meta-analyses to further enhance power for locus discovery; 2) employ several complementary transcriptomic methods to identify genes in these loci with variants that are credibly associated with cognition; and 3) further annotate the resulting genes to identify “druggable” targets.MethodsGWAS summary statistics were harmonized and jointly analysed using Multi-Trait Analysis of GWAS [MTAG], which is optimized for handling sample overlaps. Downstream gene identification was carried out using MAGMA, S-PrediXcan/S-TissueXcan Transcriptomic Wide Analysis, and eQTL mapping, as well as more recently developed methods that integrate GWAS and eQTL data via Summary-statistics Mendelian Randomization [SMR] and linkage methods [HEIDI], Available brain-specific eQTL databases included GTEXv7, BrainEAC, CommonMind, ROSMAP, and PsychENCODE. Intersecting credible genes were then annotated against multiple chemoinformatic databases [DGIdb, KI, and a published review on “druggability”].ResultsUsing our meta-analytic data set (N = 373,617) we identified 241 independent cognition-associated loci (29 novel), and 76 genes were identified by 2 or more methods of gene identification. 26 genes were associated with general cognitive ability via SMR, 16 genes via STissueXcan/S-PrediXcan, 47 genes via eQTL mapping, and 68 genes via MAGMA pathway analysis. The use of the HEIDI test permitted the exclusion of candidate genes that may have been artifactually associated to cognition due to linkage, rather than direct causal or indirect pleiotropic effects. Actin and chromatin binding gene sets were identified as novel pathways that could be targeted via drug repurposing. Leveraging on our various transcriptome and pathway analyses, as well as available chemoinformatic databases, we identified 16 putative genes that may suggest drug targets with nootropic properties.DiscussionResults converged on several categories of significant drug targets, including serotonergic and glutamatergic genes, voltage-gated ion channel genes, carbonic anhydrase genes, and phosphodiesterase genes. The current results represent the first efforts to apply a multi-method approach to integrate gene expression and SNP level data to identify credible actionable genes for general cognitive ability.

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Genetic association and causal inference converge on hyperglycaemia as a modifiable factor to improve lung function

eLife ◽

10.7554/elife.63115 ◽

2021 ◽

Vol 10 ◽

Author(s):

William R Reay ◽

Sahar I El Shair ◽

Michael P Geaghan ◽

Carlos Riveros ◽

Elizabeth G Holliday ◽

...

Keyword(s):

Lung Function ◽

Drug Targets ◽

Fasting Glucose ◽

Drug Repurposing ◽

Gene Interactions ◽

Improve Lung Function ◽

Polygenic Scores ◽

Modifiable Factor ◽

Respiratory Outcomes ◽

Novel Drug

Measures of lung function are heritable, and thus, we sought to utilise genetics to propose drug-repurposing candidates that could improve respiratory outcomes. Lung function measures were found to be genetically correlated with seven druggable biochemical traits, with further evidence of a causal relationship between increased fasting glucose and diminished lung function. Moreover, we developed polygenic scores for lung function specifically within pathways with known drug targets and investigated their relationship with pulmonary phenotypes and gene expression in independent cohorts to prioritise individuals who may benefit from particular drug-repurposing opportunities. A transcriptome-wide association study (TWAS) of lung function was then performed which identified several drug–gene interactions with predicted lung function increasing modes of action. Drugs that regulate blood glucose were uncovered through both polygenic scoring and TWAS methodologies. In summary, we provided genetic justification for a number of novel drug-repurposing opportunities that could improve lung function.

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