Targets of drugs are generally and targets of drugs having side effects are specifically good spreaders of human interactome perturbations

Perez-Lopez, Aron R.; Szalay, Kristof Z.; Türei, Dénes; Módos, Dezső; Lenti, Katalin; Korcsmáros, Tamás; Csermely, Péter

doi:10.1038/srep10182

Cited by 23 publications

(18 citation statements)

References 59 publications

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“…In particular, the observed higher P indicates that these proteins play an important role in connecting different modules within the network, suggesting that they are pleiotropic and participate in diverse biological processes, which could explain why they are mediators of both, therapeutic and side effects of drugs. These results are in line with those of Perez-Lopez et al (2015) who showed that drug targets that mediate side effects are better spreaders of perturbations in a human global interactome, than targets of drugs having no reported side effects, and non-target proteins. Our results also support those of Kotlyar et al (2012) who showed that drug targets and drug-regulated genes have higher degree and betweenness, and lower clustering coefficients.…”

Section: Discussionsupporting

confidence: 91%

Network, Transcriptomic and Genomic Features Differentiate Genes Relevant for Drug Response

et al. 2018

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Understanding the mechanisms underlying drug therapeutic action and toxicity is crucial for the prevention and management of drug adverse reactions, and paves the way for a more efficient and rational drug design. The characterization of drug targets, drug metabolism proteins, and proteins associated to side effects according to their expression patterns, their tolerance to genomic variation and their role in cellular networks, is a necessary step in this direction. In this contribution, we hypothesize that different classes of proteins involved in the therapeutic effect of drugs and in their adverse effects have distinctive transcriptomics, genomics and network features. We explored the properties of these proteins within global and organ-specific interactomes, using multi-scale network features, evaluated their gene expression profiles in different organs and tissues, and assessed their tolerance to loss-of-function variants leveraging data from 60K subjects. We found that drug targets that mediate side effects are more central in cellular networks, more intolerant to loss-of-function variation, and show a wider breadth of tissue expression than targets not mediating side effects. In contrast, drug metabolizing enzymes and transporters are less central in the interactome, more tolerant to deleterious variants, and are more constrained in their tissue expression pattern. Our findings highlight distinctive features of proteins related to drug action, which could be applied to prioritize drugs with fewer probabilities of causing side effects.

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Section: Discussionsupporting

confidence: 91%

Network, Transcriptomic and Genomic Features Differentiate Genes Relevant for Drug Response

et al. 2018

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“…More recently, networks were used to predict disease mechanisms by modeling pathogen induced perturbations (Gulbahce et al , ), and effects of node or edge removal (Zhong et al , ; Sahni et al , ). Networks have also been effective for developing treatments: identifying drug targets (Yeh et al , ; Emig et al , ), understanding drug mechanism of action (Perez‐Lopez et al , ), predicting side effects (Huang et al , ), predicting drug–drug interactions (Huang et al , ), and characterizing drug‐regulated genes and toxicity (Kotlyar et al , ).…”

Section: Visualization Analysis and Biological Validation Of Ppi Datamentioning

confidence: 99%

Fundamentals of protein interaction network mapping

Snider

Kotlyar

Saraon

et al. 2015

Molecular Systems Biology

250

184

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Studying protein interaction networks of all proteins in an organism (“interactomes”) remains one of the major challenges in modern biomedicine. Such information is crucial to understanding cellular pathways and developing effective therapies for the treatment of human diseases. Over the past two decades, diverse biochemical, genetic, and cell biological methods have been developed to map interactomes. In this review, we highlight basic principles of interactome mapping. Specifically, we discuss the strengths and weaknesses of individual assays, how to select a method appropriate for the problem being studied, and provide general guidelines for carrying out the necessary follow‐up analyses. In addition, we discuss computational methods to predict, map, and visualize interactomes, and provide a summary of some of the most important interactome resources. We hope that this review serves as both a useful overview of the field and a guide to help more scientists actively employ these powerful approaches in their research.

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“…The ability to spread perturbations through the cell and cause phenotypic changes is a key property of drug targets, which is reflected by topological properties in protein-protein interaction (PPI) networks 34 . We explain the network topology properties in Supplementary Fig.…”

Section: Resultsmentioning

confidence: 99%

Tissue-specific genes as an underutilized resource in drug discovery

Ryaboshapkina

Hammar

2018

Preprint

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25Tissue-specific genes are believed to be good drug targets due to improved safety. 26 Here we show that this intuitive notion is not reflected in phase 1 and 2 clinical trials, 27 despite the historic success of tissue-specific targets and their 2.3-fold 28 overrepresentation among targets of marketed non-oncology drugs. We compare 29 properties of tissue-specific genes and drug targets. We show that tissue-specificity of 30 the target may also be related to efficacy of the drug. The relationship may be indirect 31 (enrichment in Mendelian disease genes) or direct (elevated ability to spread 32 perturbations in human protein-protein interactome for tissue-specifically produced 33 enzymes and secreted proteins). Reduced evolutionary conservation of tissue-specific 34 genes may represent a bottleneck for drug projects, prompting development of novel 35 models with smaller evolutionary gap to humans. We highlight numerous open 36 opportunities to use tissue-specific genes in drug research and hope that the current 37 study will facilitate discovery efforts. 38 39 40 41 42 43 44 45 46 47 48 65 (2018) 14 . Thus, systematic studies showing a significant overrepresentation of tissue-66 specific genes among drug targets and comprehensive resources have been available 67 since 2008. The average time from a lead compound to entering phase 1 clinical trial 68 is 31.2 months 15 . Let's assume that validation of the biological hypothesis and 69 identification of a lead compound take an equally long time. Then, ten years are 70 sufficient for the findings of basic research to find reflection in early phase clinical trials. 71 Now is good time to test if the industry took advantage of omics studies and pursued 72 tissue-specific targets or not. 73 4 In this study, we examine the prevalence of tissue-specific genes among targets of 74 marketed drugs and drugs in clinical trials. We also investigate properties of tissue-75 specific genes compared to drug targets. Why are these questions important to 76 address? If tissue-specific targets are not actively pursued in early clinical trials, such 77 study would raise awareness of open opportunities. Opportunities to discover new 78 targets are not exhausted. A recent study by Oprea et al. indicates that only 3% of 79 human proteins are targeted by marketed or clinical trial drugs ("Tclin") whereas 35% 80 have an unknown biological function and are not actively studied ("Tdark") 16 . Also, an 81 important parallel exists between tissue-specific genes and targets of marketed drugs. 82 As first demonstrated in 2004, tissue-specific genes are enriched in Mendelian 83 disorder genes 17 . The enrichment was confirmed by Yang et al. in 2016 9 . 53% targets 84 of marketed drugs are implicated in Mendelian disorders 18 . Drugs targeting genes with 85 a genetic link to human disease are less likely to fail in clinical trials due to lack of 86 efficacy 19 . Thus, there may be a relationship between tissue-specificity of the target 87 and efficacy of the drug. In fact, a recent study ...

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Targets of drugs are generally and targets of drugs having side effects are specifically good spreaders of human interactome perturbations

Cited by 23 publications

References 59 publications

Network, Transcriptomic and Genomic Features Differentiate Genes Relevant for Drug Response

Network, Transcriptomic and Genomic Features Differentiate Genes Relevant for Drug Response

Fundamentals of protein interaction network mapping

Tissue-specific genes as an underutilized resource in drug discovery

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