The IUPHAR/BPS guide to PHARMACOLOGY in 2022: curating pharmacology for COVID-19, malaria and antibacterials

Harding, Simon D; Armstrong, Jane F.; Faccenda, Elena; Southan, Christopher; Alexander, Stephen P.H.; Davenport, Anthony P.; Pawson, Adam J.; Spedding, Michael; Davies, Jamie A.; Nc-Iuphar,

doi:10.1093/nar/gkab1010

Cited by 132 publications

(136 citation statements)

References 31 publications

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“…Drug–gene/protein interactions were collected from DrugBank [ 45 ], the Therapeutic Target Database [ 46 ], and the PharmGKB databases [ 47 ]. Only experimentally validated binding affinities (inhibition potency, dissociation constant, median effective concentration, and median inhibitory concentration ≤ 10 µM) from ChEMBL [ 48 ], BindingDB [ 49 ], and IUPHAR/BPS Guide to PHARMACOLOGY databases [ 50 , 51 ] were included. Proteins that cannot be mapped to a unique UniProt accession number were excluded.…”

Section: Methodsmentioning

confidence: 99%

DOTA: Deep Learning Optimal Transport Approach to Advance Drug Repositioning for Alzheimer’s Disease

Chyr¹,

Gong

Zhou³

2022

Biomolecules

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Alzheimer’s disease (AD) is the leading cause of age-related dementia, affecting over 5 million people in the United States and incurring a substantial global healthcare cost. Unfortunately, current treatments are only palliative and do not cure AD. There is an urgent need to develop novel anti-AD therapies; however, drug discovery is a time-consuming, expensive, and high-risk process. Drug repositioning, on the other hand, is an attractive approach to identify drugs for AD treatment. Thus, we developed a novel deep learning method called DOTA (Drug repositioning approach using Optimal Transport for Alzheimer’s disease) to repurpose effective FDA-approved drugs for AD. Specifically, DOTA consists of two major autoencoders: (1) a multi-modal autoencoder to integrate heterogeneous drug information and (2) a Wasserstein variational autoencoder to identify effective AD drugs. Using our approach, we predict that antipsychotic drugs with circadian effects, such as quetiapine, aripiprazole, risperidone, suvorexant, brexpiprazole, olanzapine, and trazadone, will have efficacious effects in AD patients. These drugs target important brain receptors involved in memory, learning, and cognition, including serotonin 5-HT2A, dopamine D2, and orexin receptors. In summary, DOTA repositions promising drugs that target important biological pathways and are predicted to improve patient cognition, circadian rhythms, and AD pathogenesis.

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Section: Methodsmentioning

confidence: 99%

DOTA: Deep Learning Optimal Transport Approach to Advance Drug Repositioning for Alzheimer’s Disease

Chyr¹,

Gong

Zhou³

2022

Biomolecules

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“…This year also sees Update papers from two major general resources in drug design. The IUPHAR/BPS guide to PHARMACOLOGY ( 97 ) reports on its efforts to curate information on drugs and drug targets for SARS-CoV-2, as well as updates to its sections on Malaria and antibacterials. The paper from the Therapeutic Target Database (TTD) ( 98 ) reports significant updates including many new kinds of data including information on weak or non-binders of targets, prodrug-drug pairs and AlphaFold models of drug targets for which experimental structures are not yet available.…”

Section: New and Updated Databasesmentioning

confidence: 99%

The 2022Nucleic Acids Researchdatabase issue and the online molecular biology database collection

Rigden

Fernández

2021

Nucleic Acids Research

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The 2022 Nucleic Acids Research Database Issue contains 185 papers, including 87 papers reporting on new databases and 85 updates from resources previously published in the Issue. Thirteen additional manuscripts provide updates on databases most recently published elsewhere. Seven new databases focus specifically on COVID-19 and SARS-CoV-2, including SCoV2-MD, the first of the Issue's Breakthrough Articles. Major nucleic acid databases reporting updates include MODOMICS, JASPAR and miRTarBase. The AlphaFold Protein Structure Database, described in the second Breakthrough Article, is the stand-out in the protein section, where the Human Proteoform Atlas and GproteinDb are other notable new arrivals. Updates from DisProt, FuzDB and ELM comprehensively cover disordered proteins. Under the metabolism and signalling section Reactome, ConsensusPathDB, HMDB and CAZy are major returning resources. In microbial and viral genomes taxonomy and systematics are well covered by LPSN, TYGS and GTDB. Genomics resources include Ensembl, Ensembl Genomes and UCSC Genome Browser. Major returning pharmacology resource names include the IUPHAR/BPS guide and the Therapeutic Target Database. New plant databases include PlantGSAD for gene lists and qPTMplants for post-translational modifications. The entire Database Issue is freely available online on the Nucleic Acids Research website (https://academic.oup.com/nar). Our latest update to the NAR online Molecular Biology Database Collection brings the total number of entries to 1645. Following last year's major cleanup, we have updated 317 entries, listing 89 new resources and trimming 80 discontinued URLs. The current release is available at http://www.oxfordjournals.org/nar/database/c/.

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“…Moreover, genes contributing the most to the first principal component are relevant to the cells’ functions, such as their secretory phenotype (e.g., Gcg, Gip, Pyy). After this correction, all sample groups were clustered using genes from three subsets of the transcriptomes: protein coding genes (n = 15779), genes coding for ligands and target proteins (using the IUPHAR/BPS Guide to PHARMACOLOGY, “an expert-curated resource of pharmacological targets and the substances that act on them” ( Harding et al, 2022 )) (n = 2,621) or genes coding for G-protein-coupled receptors (GPCRs) and ion channels (n = 584). In all three cases, the transcriptome of GLUTag cells was observed to be most similar to entero-endocrine cells (regardless of species/tissues) compared to samples containing non-EEC cells ( Figure 3A ), although the GLUTag cells seem to preferentially cluster with human ileal cells rather than the mouse duodenal cells when restricted to GPCRs and ion channel genes ( Figure 3A ; Supplementary Figure S4 ).…”

Section: Resultsmentioning

confidence: 99%

“…The results were then plotted as a heatmap using the default parameters (complete linkage hierarchical clustering using the Euclidean distances) of the pheatmap function of the R package ComplexHeatmap (v. 2.6.2) ( Gu et al, 2016 ). BioMart annotations and the IUPHAR/BPS Guide to PHARMACOLOGY complete “target and family” list (v. 2021.3) were used to restrict the analyses to specific gene types and families ( Harding et al, 2022 ). For within-dataset comparisons (gene expression plots), non-batch corrected transcript-per-million (TPM) values were used (corresponding to count-per-million (CPM) for the QuantSeq 3′ mRNA sequencing data).…”

Section: Methodsmentioning

confidence: 99%

NMDA Receptor Antagonists Increase the Release of GLP-1 From Gut Endocrine Cells

et al. 2022

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Type 2 diabetes mellitus (T2DM) remains one of the most pressing health issues facing modern society. Several antidiabetic drugs are currently in clinical use to treat hyperglycaemia, but there is a need for new treatments that effectively restore pancreatic islet function in patients. Recent studies reported that both murine and human pancreatic islets exhibit enhanced insulin release and β-cell viability in response to N-methyl-D-aspartate (NMDA) receptor antagonists. Furthermore, oral administration of dextromethorphan, an over-the-counter NMDA receptor antagonist, to diabetic patients in a small clinical trial showed improved glucose tolerance and increased insulin release. However, the effects of NMDA receptor antagonists on the secretion of the incretin hormone GLP-1 was not tested, and nothing is known regarding how NMDA receptor antagonists may alter the secretion of gut hormones. This study demonstrates for the first time that, similar to β-cells, the NMDA receptor antagonist MK-801 increases the release of GLP-1 from a murine L-cell enteroendocrine model cell line, GLUTag cells. Furthermore, we report the 3′ mRNA expression profiling of GLUTag cells, with a specific focus on glutamate-activated receptors. We conclude that if NMDA receptor antagonists are to be pursued as an alternative, orally administered treatment for T2DM, it is essential that the effects of these drugs on the release of gut hormones, and specifically the incretin hormones, are fully investigated.

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The IUPHAR/BPS guide to PHARMACOLOGY in 2022: curating pharmacology for COVID-19, malaria and antibacterials

Cited by 132 publications

References 31 publications

DOTA: Deep Learning Optimal Transport Approach to Advance Drug Repositioning for Alzheimer’s Disease

DOTA: Deep Learning Optimal Transport Approach to Advance Drug Repositioning for Alzheimer’s Disease

The 2022Nucleic Acids Researchdatabase issue and the online molecular biology database collection

NMDA Receptor Antagonists Increase the Release of GLP-1 From Gut Endocrine Cells

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