Off-Target Effects of Psychoactive Drugs Revealed by Genome-Wide Assays in Yeast
Open accessAbstract
To better understand off-target effects of widely prescribed psychoactive drugs, we performed a comprehensive series of chemogenomic screens using the budding yeast Saccharomyces cerevisiae as a model system. Because the known human targets of these drugs do not exist in yeast, we could employ the yeast gene deletion collections and parallel fitness profiling to explore potential off-target effects in a genome-wide manner. Among 214 tested, documented psychoactive drugs, we identified 81 compounds that inhibited wild-type yeast growth and were thus selected for genome-wide fitness profiling. Many of these drugs had a propensity to affect multiple cellular functions. The sensitivity profiles of half of the analyzed drugs were enriched for core cellular processes such as secretion, protein folding, RNA processing, and chromatin structure. Interestingly, fluoxetine (Prozac) interfered with establishment of cell polarity, cyproheptadine (Periactin) targeted essential genes with chromatin-remodeling roles, while paroxetine (Paxil) interfered with essential RNA metabolism genes, suggesting potential secondary drug targets. We also found that the more recently developed atypical antipsychotic clozapine (Clozaril) had no fewer off-target effects in yeast than the typical antipsychotics haloperidol (Haldol) and pimozide (Orap). Our results suggest that model organism pharmacogenetic studies provide a rational foundation for understanding the off-target effects of clinically important psychoactive agents and suggest a rational means both for devising compound derivatives with fewer side effects and for tailoring drug treatment to individual patient genotypes.
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In S. cerevisiae, the most notable effect of fluoxetine was on establishment of polarity, that of paroxetine was RNA processing, and that of sertraline was vesicle-mediated transport.
“With the same approach, Ericson et al., showed that in S. cerevisiae, the most notable effect of fluoxetine was on the establishment of polarity, that of paroxetine was RNA processing, and that of sertraline was vesicle-mediated transport [107].”
From Antimicrobial Properties of Antidepressants and Antipsychotics—Possibilities and Implications (2021) · cites this paper as [107]
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A unique and universal molecular barcode array
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“This compound collection represented largely uncharacterized chemical space compared with previous large-scale chemogenomic studies (Ericson et al., 2008; Hillenmeyer et al., 2008; Lee et al., 2014) and was comprised of approximately 50% approved drugs or drug-like compounds, 40% synthetic products…”
Self-citationSystematic analysis of genome-wide fitness data in yeast reveals novel gene function and drug action
Hillenmeyer, M. E., Ericson, E., Davis, R. W., Nislow, C., Koller, D., & Giaever, G. (2010) · Genome Biology · doi:10.1186/gb-2010-11-3-r30 · Cited by 112 · see citing works
“Because their neurological targets do not exist in yeast, the sensitivity we observe is likely a result of these compounds affecting additional cellular targets in yeast [44]; these 'secondary' targets, if conserved, may correspond to additional targets of these compounds in human cells.”
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Antifungal Drug Discovery: The Process and Outcomes
Calderone, R., Sun, N., Gay‐Andrieu, F., Groutas, W. C., Weerawarna, P. M., Prasad, S., Alex, D., & Li, D. (2014) · Future Microbiology · doi:10.2217/fmb.14.32 · Cited by 98 · see citing works
Yeast chemical genomics and drug discovery: an update
Hoon, S. S., St.Onge, R. P., Giaever, G. N., & Nislow, C. (2008) · Trends in Pharmacological Sciences · doi:10.1016/j.tips.2008.07.006 · Cited by 96 · see citing works
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“cerevisiae indicated that many psychoactive molecules have antifungal activity (41).”
Backgrounddos Santos, S. C. (2012) · Frontiers in Genetics · doi:10.3389/fgene.2012.00063 · Cited by 79 · see citing works
“In an illustrative example, Ericson et al. (2008) identified 81 psychoactive drugs that affected yeast fitness at the level of evolutionarily conserved cellular processes such as secretion, protein folding, RNA processing, and chromatin structure.”
BackgroundCombining functional genomics and chemical biology to identify targets of bioactive compounds
Ho, C. H., Piotrowski, J., Dixon, S. J., Baryshnikova, A., Costanzo, M., & Boone, C. (2011) · Current Opinion in Chemical Biology · doi:10.1016/j.cbpa.2010.10.023 · Cited by 78 · see citing works
“Despite lacking orthologs to the human target genes, many essential yeast genes involved in the establishment of cell polarity were haploinsufficient to fluoxetine (Prozac) while decreased dosage of RNA metabolic genes conferred sensitivity to paroxetine (Paxil) [16].”
BackgroundInfluentialFunctional genomics to uncover drug mechanism of action
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“Paroxetine also has targets other than the serotonin transport channel; paroxetine was shown to interact with yeast proteins that metabolize RNA and with a P4-type ATPase, NEO-1, which confers neomycin resistance in yeast (Ericson et al., 2008).”
Antifungal Application of Nonantifungal Drugs
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Functional Toxicogenomics: Mechanism-Centered Toxicology
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“TAG3/4 214 psychoactive drugs Homozygous; heterozygous [49]”
High-content phenotypic and pathway profiling to advance drug discovery in diseases of unmet need
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CYSTM, a novel cysteine-rich transmembrane module with a role in stress tolerance across eukaryotes
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“Based on the pattern of conserved cysteines and data from different chemical genetics studies, we suggest that CYSTM proteins might have critical role in responding to deleterious compounds at the plasma membrane via chelation or redox-based mechanisms.”
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Self-citationThe Antidepressant Sertraline Targets Intracellular Vesiculogenic Membranes in Yeast
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Antimicrobial Properties of Antidepressants and Antipsychotics—Possibilities and Implications
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Compound Prioritization Methods Increase Rates of Chemical Probe Discovery in Model Organisms
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Functional Expression of Parasite Drug Targets and Their Human Orthologs in Yeast
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“). By performing genome-wide drug sensitivity screens (chemogenomic profiling)”
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“Often the gene networks that confer sensitivity or resistance to a given compound are conserved from yeast to mammalian cells (Ericson et al., 2008; Yu et al., 2008).”
BackgroundMethodInfluentialSelf-citationChemical genetics in drug discovery
Cacace, E., Kritikos, G., & Typas, A. (2017) · Current Opinion in Systems Biology · doi:10.1016/j.coisb.2017.05.020 · Cited by 40 · see citing works
Chemical-genomic profiling: Systematic analysis of the cellular targets of bioactive molecules
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Advances in fungal chemical genomics for the discovery of new antifungal agents
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Fangjiomics: In Search of Effective and Safe Combination Therapies
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“Applying the knowledge of omics to disease-related drug targets would be beneficial for developing a new generation of better drugs.(5) This might involve construction of complex networks that provide a new framework for understanding the molecular basis of physiological or pathophysiological states and the mechanisms…”
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“It targets and affects various cellular processes which include protein localization, establishment of cell polarity and cytoskeleton biogenesis and organization.(92) For Listeria monocytogenes, an intracellular Gram-positive bacterium, 20 one compounds targeting cell functions like calcium signaling, actin polymeriza…”
BackgroundGlobal analysis of the yeast knockout phenome
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Exploring Gene Function and Drug Action Using Chemogenomic Dosage Assays
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Dinér, P., Vilg, J. V., Kjellén, J., Migdal, I., Andersson, T., Gebbia, M., Giaever, G. N., Nislow, C., Hohmann, S., Wysocki, R., et al. (2011) · PLoS ONE · doi:10.1371/journal.pone.0020012 · Cited by 27 · see citing works
“Screens were performed essentially as described by Ericson et al,”
MethodSelf-citationThe Automated Cell: Compound and Environment Screening System (ACCESS) for Chemogenomic Screening
Proctor, M. J., Urbanus, M. L., Fung, E., Jaramillo, D. F., Davis, R. W., Nislow, C., & Giaever, G. N. (2011) · Methods in molecular biology · doi:10.1007/978-1-61779-173-4_15 · Cited by 26 · see citing works
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Sphingolipid signaling in yeast potential implications for understanding disease
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Genetic Basis of Haloperidol Resistance in Saccharomyces cerevisiae Is Complex and Dose Dependent
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“In Saccharomyces cerevisiae (which does not contain the pharmacologically relevant haloperidol targets), haloperidol exerts effects on vesicle transport and amino acid metabolism [17], demonstrating”
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Kleemann, R., Bureeva, S. V., Perlina, A., Kaput, J., Verschuren, L., Wielinga, P. Y., Hurt‐Camejo, E., Nikolsky, Y., van Ommen, B., & Kooistra, T. (2011) · BMC Systems Biology · doi:10.1186/1752-0509-5-125 · Cited by 16 · see citing works
“Background In addition to their established pharmacological activities, many preclinical and commercial drugs exert effects that are not predictable from their presumed mode of action and primary target [1-3].”
BackgroundContributions of Saccharomyces cerevisiae to Understanding Mammalian Gene Function and Therapy
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Barcode Sequencing for Understanding Drug–Gene Interactions
Smith, A. M., Durbic, T., Kittanakom, S., Giaever, G. N., & Nislow, C. (2012) · Methods in molecular biology · doi:10.1007/978-1-61779-965-5_4 · Cited by 16 · see citing works
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“For example, three large chemogenomic studies [32, 34, 36] have been performed; these are consolidated in the searchable data base NetwoRx [33], which includes 466 drugs and compounds.”
Mattiazzi, M., Petrovič, U., & Križaj, I. (2012) · Toxicon · doi:10.1016/j.toxicon.2012.03.014 · Cited by 18 · see citing works
“These genes can belong either to the target pathway or to a pathway that buffers the target pathway (Butcher and Schreiber, 2003; Parsons et al., 2004, 2006; Ericson et al., 2008; Hillenmeyer et al., 2008).”
BackgroundChemogenomic Approaches to Elucidation of Gene Function and Genetic Pathways
Pierce, S. E., Davis, R. W., Nislow, C., & Giaever, G. N. (2009) · Methods in molecular biology · doi:10.1007/978-1-59745-540-4_7 · Cited by 14 · see citing works
Self-citationPredicting therapeutic and side effects from drug binding affinities to human proteome structures
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NetwoRx: connecting drugs to networks and phenotypes in Saccharomyces cerevisiae
Fortney, K., Xie, W., Kotlyar, M., Griesman, J., Kotseruba, Y., & Jurišica, I. (2012) · Nucleic Acids Research · doi:10.1093/nar/gks1106 · Cited by 12 · see citing works
“tested 81 psychoactive drugs in yeast and identified secondary drug targets that help explain side effects in human patients (3), and Blackman et al.”
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“This methodology (chemical-genetic fitness profiling) has been successfully applied to identification of the cellular targets of known and prospective drugs and to study of their mechanisms of action and potential side effects (4, 6, 13, 18, 21, 35).”
MethodA High‐Throughput Screen for Chemical Inhibitors of Exocytic Transport in Yeast
Zhang, L., Nebane, N. M., Wennerberg, K., Li, Y., Neubauer, V., Hobrath, J. V., McKellip, S. N., Rasmussen, L. A., Shindo, N., Sosa, M. I., et al. (2010) · ChemBioChem · doi:10.1002/cbic.200900681 · Cited by 11 · see citing works
Comparative Interaction Networks: Bridging Genotype to Phenotype
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“Chemical-genetic studies provide insight into the function of the genes that are perturbed but can also be used to identify the mode-of-action of bioactive compounds, including medically relevant drugs [66, 67], antifungal [68], or antibiotic compounds [69].”
BackgroundOff-target effects of neuroleptics and antidepressants on Saccharomyces cerevisiae
Caldara, M., Graziano, S., Gullì, M., Cadonici, S., & Marmiroli, N. (2017) · Toxicological Sciences · doi:10.1093/toxsci/kfx007 · Cited by 8 · see citing works
“secondary effects in humans, whose mechanisms are poorly understood (Ericson et al., 2008).”
BackgroundInfluentialTamble, C. M., St.Onge, R. P., Giaever, G. N., Nislow, C., Williams, A. G., Stuart, J. M., & Lokey, R. S. (2011) · Molecular BioSystems · doi:10.1039/c0mb00298d · Cited by 7 · see citing works
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Miniature Short Hairpin RNA Screens to Characterize Antiproliferative Drugs
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“Despite a greater risk of false-positive results that could arise from using relatively high doses of drug, the study of nonantiproliferative compounds can also prove useful in understanding secondary activities (Ericson et al. 2008).”
BackgroundSelf-citationPharmacogenetics and adverse drug reactions
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Utilizing yeast chemogenomic profiles for the prediction of pharmacogenomic associations in humans
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“…for a set of different stresses and environmental conditions identified an extensive transcriptional network underlying cellular stress responses (Gasch et al., 2000), but also enables the discovery of direct as well as off-targets of bioactive compounds (Ericson et al., 2008; Parsons et al., 2006).”
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- Authors
- Ericson, E., Gebbia, M., Heisler, L. E., Wildenhain, J., Tyers, M., Giaever, G., & Nislow, C.
- Affiliations
- University of Toronto (CA)
- University of Edinburgh (GB)
- Mount Sinai Hospital (CA)
- Corresponding author
- Nislow, Corey
- ORCID
- Venue
- PLoS Genetics
- Publisher
- Public Library of Science (PLoS)
- Published
- 2008-08-08
- Volume
- 4
- Issue
- 8
- Pages
- e1000151
- ISSN
- 1553-7390 (ISSN-L)
- 1553-7404
- PMC
- PMC2483942
- OpenAlex
- W2168192378
- Cited by
- 89
- References
- 53
- Citations by year
- 2026: 1 · 2025: 1 · 2024: 1 · 2023: 2 · 2022: 2 · 2021: 7 · 2020: 1 · 2019: 2 · 2018: 1 · 2017: 3 · 2016: 3 · 2015: 4 · 2014: 2 · 2013: 7 · 2012: 12
- FWCI
- 5.48
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Locations
- PLoS Genetics (publishedVersion, cc-by)
- Europe PMC (PubMed Central) (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Figshare (submittedVersion, cc-by)
- Edinburgh Research Explorer (University of Edinburgh) (submittedVersion, other-oa)
- Funders
- Howard Hughes Medical Institute
- National Institutes of Health
- Canadian Institutes of Health Research (84305_1, 81340, (MO)P-81340, 84305)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Fungal and yeast genetics research
- Physical Sciences › Computer Science › Computational Theory and Mathematics › Computational Drug Discovery Methods
- Life Sciences › Pharmacology, Toxicology and Pharmaceutics › Pharmacology › Pharmacogenetics and Drug Metabolism
- Keywords
- off-target effects, psychoactive substances, Saccharomyces cerevisiae, drug sensitivity, fluoxetine, cyproheptadine, paroxetine, clozapine, haloperidol, pimozide, chromatin remodeling, RNA metabolism, cell polarity, pharmacogenetics, adverse drug reactions
- MeSH terms
- Drug Resistance, Drug Evaluation, Preclinical, Humans, Psychotropic Drugs, Saccharomyces cerevisiae, Protein Biosynthesis, Telomere, Genome, Fungal, Cell Polarity, Oligonucleotide Array Sequence Analysis, Gene Expression Profiling, Protein Transport, Saccharomyces cerevisiae Proteins, Lipid Metabolism
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