2025
Integrating epidemiology and genomics data to estimate the prevalence of acquired cysteine drug targets in the U.S. cancer patient population
Arun A, Liarakos D, Mendiratta G, Kim J, Goshua G, Olson P, Stites E. Integrating epidemiology and genomics data to estimate the prevalence of acquired cysteine drug targets in the U.S. cancer patient population. The Pharmacogenomics Journal 2025, 25: 5. PMID: 40044654, DOI: 10.1038/s41397-025-00364-3.Peer-Reviewed Original ResearchConceptsGenomic dataEstimates of mutation ratesSomatic missense mutationsGenomic informationPopulation-level estimatesCancer patient populationMissense mutationsNon-epidemiologicallyCancer patientsMutation ratePathogenic mutationsCysteine residuesCancer epidemiologyMutation-specificMutation abundanceDrug targetsMutationsIntegrates epidemiologyAbundancePatient populationEpidemiologyGenomePopulationTargeted therapyResiduesVoltage-gated sodium channels in excitable cells as drug targets
Alsaloum M, Dib-Hajj S, Page D, Ruben P, Krainer A, Waxman S. Voltage-gated sodium channels in excitable cells as drug targets. Nature Reviews Drug Discovery 2025, 1-21. PMID: 39901031, DOI: 10.1038/s41573-024-01108-x.Peer-Reviewed Original ResearchSodium channelsChannel subtypesControl action potential firingDevelopment of drugsDensity of voltage-gated sodiumExcitable cellsAction potential firingSubtype-specific drugsSodium channel subtypesVoltage-gated sodium channelsExpressing high densitiesVoltage-gated sodiumCardiac myocytesNav1.1-Nav1.9Potential firingCardiac disordersAction potentialsMuscle cellsMolecular targetsDrugSubtypesDrug developmentCellsDrug targetsMyocytes
2024
π-HuB: the proteomic navigator of the human body
He F, Aebersold R, Baker M, Bian X, Bo X, Chan D, Chang C, Chen L, Chen X, Chen Y, Cheng H, Collins B, Corrales F, Cox J, E W, Van Eyk J, Fan J, Faridi P, Figeys D, Gao G, Gao W, Gao Z, Goda K, Goh W, Gu D, Guo C, Guo T, He Y, Heck A, Hermjakob H, Hunter T, Iyer N, Jiang Y, Jimenez C, Joshi L, Kelleher N, Li M, Li Y, Lin Q, Liu C, Liu F, Liu G, Liu Y, Liu Z, Low T, Lu B, Mann M, Meng A, Moritz R, Nice E, Ning G, Omenn G, Overall C, Palmisano G, Peng Y, Pineau C, Poon T, Purcell A, Qiao J, Reddel R, Robinson P, Roncada P, Sander C, Sha J, Song E, Srivastava S, Sun A, Sze S, Tang C, Tang L, Tian R, Vizcaíno J, Wang C, Wang C, Wang X, Wang X, Wang Y, Weiss T, Wilhelm M, Winkler R, Wollscheid B, Wong L, Xie L, Xie W, Xu T, Xu T, Yan L, Yang J, Yang X, Yates J, Yun T, Zhai Q, Zhang B, Zhang H, Zhang L, Zhang L, Zhang P, Zhang Y, Zheng Y, Zhong Q, Zhu Y. π-HuB: the proteomic navigator of the human body. Nature 2024, 636: 322-331. PMID: 39663494, DOI: 10.1038/s41586-024-08280-5.Peer-Reviewed Original ResearchDeletion of miR‐33, a regulator of the ABCA1–APOE pathway, ameliorates neuropathological phenotypes in APP/PS1 mice
Tate M, Wijeratne H, Kim B, Philtjens S, You Y, Lee D, Gutierrez D, Sharify D, Wells M, Perez‐Cardelo M, Doud E, Fernandez‐Hernando C, Lasagna‐Reeves C, Mosley A, Kim J. Deletion of miR‐33, a regulator of the ABCA1–APOE pathway, ameliorates neuropathological phenotypes in APP/PS1 mice. Alzheimer's & Dementia 2024, 20: 7805-7818. PMID: 39345217, PMCID: PMC11567857, DOI: 10.1002/alz.14243.Peer-Reviewed Original ResearchAmyloid-betaAlzheimer's diseaseMicroglial migrationAmyloid mouse modelMiR-33Multi-omics studiesABCA1 levelsPotential drug targetsIncreased ABCA1 protein levelsMicroRNA-33ApoE lipidationProteomic changesRNA sequencingMulti-omicsNeuropathological phenotypeAmyloid pathologyInhibition of miR-33APP/PS1 micePhagocytosis in vitroRare variantsApolipoprotein EDrug targetsABCA1 protein levelsAmyloidPlaque depositionMitochondrial ATP synthase as a novel therapeutic drug target in neurodegenerative and ischemic heart diseases
Kumar A, da Fonseca Rezende e Mello J, Wu Y, Mezghani I, Smith E, Mnatsakanyan N. Mitochondrial ATP synthase as a novel therapeutic drug target in neurodegenerative and ischemic heart diseases. Biochimica Et Biophysica Acta (BBA) - Bioenergetics 2024, 1865: 149307. DOI: 10.1016/j.bbabio.2024.149307.Peer-Reviewed Original ResearchEvolutionary druggability for low-dimensional fitness landscapes toward new metrics for antimicrobial applications
Guerrero R, Dorji T, Harris R, Shoulders M, Ogbunugafor C. Evolutionary druggability for low-dimensional fitness landscapes toward new metrics for antimicrobial applications. ELife 2024, 12: rp88480. PMID: 38833384, PMCID: PMC11149929, DOI: 10.7554/elife.88480.Peer-Reviewed Original ResearchConceptsDrug targetsAllelic variantsStanding genetic variationEmpirical fitness landscapesFitness landscapeGenetic variationB-lactamasePathogenic variantsTarget proteinsVariant sensitivityB-lactamAllelesDrug-target interactionsPathogensMutationsVariantsDrug environmentMechanistic insightDrug developmentMolecular properties of drugsAntimicrobial applicationsApplication metricsLociVariant variablesPharmacological interventionsEvolutionary druggability for low-dimensional fitness landscapes toward new metrics for antimicrobial applications
Guerrero R, Dorji T, Harris R, Shoulders M, Ogbunugafor C. Evolutionary druggability for low-dimensional fitness landscapes toward new metrics for antimicrobial applications. ELife 2024, 12 DOI: 10.7554/elife.88480.3.Peer-Reviewed Original ResearchDrug targetsAllelic variantsStanding genetic variationEmpirical fitness landscapesFitness landscapeGenetic variationB-lactamasePathogenic variantsTarget proteinsVariant sensitivityB-lactamAllelesDrug-target interactionsPathogensMutationsVariantsDrug environmentMechanistic insightDruggabilityDrug developmentMolecular properties of drugsAntimicrobial applicationsApplication metricsLociVariant variablesSingle-cell genomics and regulatory networks for 388 human brains
Emani P, Liu J, Clarke D, Jensen M, Warrell J, Gupta C, Meng R, Lee C, Xu S, Dursun C, Lou S, Chen Y, Chu Z, Galeev T, Hwang A, Li Y, Ni P, Zhou X, Bakken T, Bendl J, Bicks L, Chatterjee T, Cheng L, Cheng Y, Dai Y, Duan Z, Flaherty M, Fullard J, Gancz M, Garrido-Martín D, Gaynor-Gillett S, Grundman J, Hawken N, Henry E, Hoffman G, Huang A, Jiang Y, Jin T, Jorstad N, Kawaguchi R, Khullar S, Liu J, Liu J, Liu S, Ma S, Margolis M, Mazariegos S, Moore J, Moran J, Nguyen E, Phalke N, Pjanic M, Pratt H, Quintero D, Rajagopalan A, Riesenmy T, Shedd N, Shi M, Spector M, Terwilliger R, Travaglini K, Wamsley B, Wang G, Xia Y, Xiao S, Yang A, Zheng S, Gandal M, Lee D, Lein E, Roussos P, Sestan N, Weng Z, White K, Won H, Girgenti M, Zhang J, Wang D, Geschwind D, Gerstein M, Akbarian S, Abyzov A, Ahituv N, Arasappan D, Almagro Armenteros J, Beliveau B, Berretta S, Bharadwaj R, Bhattacharya A, Brennand K, Capauto D, Champagne F, Chatzinakos C, Chen H, Cheng L, Chess A, Chien J, Clement A, Collado-Torres L, Cooper G, Crawford G, Dai R, Daskalakis N, Davila-Velderrain J, Deep-Soboslay A, Deng C, DiPietro C, Dracheva S, Drusinsky S, Duong D, Eagles N, Edelstein J, Galani K, Girdhar K, Goes F, Greenleaf W, Guo H, Guo Q, Hadas Y, Hallmayer J, Han X, Haroutunian V, He C, Hicks S, Ho M, Ho L, Huang Y, Huuki-Myers L, Hyde T, Iatrou A, Inoue F, Jajoo A, Jiang L, Jin P, Jops C, Jourdon A, Kellis M, Kleinman J, Kleopoulos S, Kozlenkov A, Kriegstein A, Kundaje A, Kundu S, Li J, Li M, Lin X, Liu S, Liu C, Loupe J, Lu D, Ma L, Mariani J, Martinowich K, Maynard K, Myers R, Micallef C, Mikhailova T, Ming G, Mohammadi S, Monte E, Montgomery K, Mukamel E, Nairn A, Nemeroff C, Norton S, Nowakowski T, Omberg L, Page S, Park S, Patowary A, Pattni R, Pertea G, Peters M, Pinto D, Pochareddy S, Pollard K, Pollen A, Przytycki P, Purmann C, Qin Z, Qu P, Raj T, Reach S, Reimonn T, Ressler K, Ross D, Rozowsky J, Ruth M, Ruzicka W, Sanders S, Schneider J, Scuderi S, Sebra R, Seyfried N, Shao Z, Shieh A, Shin J, Skarica M, Snijders C, Song H, State M, Stein J, Steyert M, Subburaju S, Sudhof T, Snyder M, Tao R, Therrien K, Tsai L, Urban A, Vaccarino F, van Bakel H, Vo D, Voloudakis G, Wang T, Wang S, Wang Y, Wei Y, Weimer A, Weinberger D, Wen C, Whalen S, Willsey A, Wong W, Wu H, Wu F, Wuchty S, Wylie D, Yap C, Zeng B, Zhang P, Zhang C, Zhang B, Zhang Y, Ziffra R, Zeier Z, Zintel T. Single-cell genomics and regulatory networks for 388 human brains. Science 2024, 384: eadi5199. PMID: 38781369, PMCID: PMC11365579, DOI: 10.1126/science.adi5199.Peer-Reviewed Original ResearchConceptsSingle-cell genomicsSingle-cell expression quantitative trait locusExpression quantitative trait lociDrug targetsQuantitative trait lociPopulation-level variationSingle-cell expressionCell typesDisease-risk genesTrait lociGene familyRegulatory networksGene expressionCell-typeMultiomics datasetsSingle-nucleiGenomeGenesCellular changesHeterogeneous tissuesExpressionCellsChromatinLociMultiomicsCirculating Proteins and IgA Nephropathy
Tang C, Chen P, Xu L, Lv J, Shi S, Zhou X, Liu L, Zhang H. Circulating Proteins and IgA Nephropathy. Journal Of The American Society Of Nephrology 2024, 35: 1045-1057. PMID: 38687828, PMCID: PMC11377805, DOI: 10.1681/asn.0000000000000379.Peer-Reviewed Original ResearchProtein-protein interaction networkProtein-disease pairsColocalization analysisInteraction networkEast Asian ancestryMendelian randomizationPotential drug targetsDrug repurposing opportunitiesVariant annotationAncestry populationsIdentified proteinsNetwork Mendelian randomizationMendelian randomization studiesAsian ancestryDrug targetsProteinAncestryEast AsiansTherapeutic targetColocalizationCirculating proteinsCausal effectsMedicationTargetAnnotationDurlobactam, a Diazabicyclooctane β‑Lactamase Inhibitor, Inhibits BlaC and Peptidoglycan Transpeptidases of Mycobacterium tuberculosis
Nantongo M, Nguyen D, Bethel C, Taracila M, Li Q, Dousa K, Shin E, Kurz S, Nguyen L, Kreiswirth B, Boom W, Plummer M, Bonomo R. Durlobactam, a Diazabicyclooctane β‑Lactamase Inhibitor, Inhibits BlaC and Peptidoglycan Transpeptidases of Mycobacterium tuberculosis. ACS Infectious Diseases 2024, 10: 1767-1779. PMID: 38619138, DOI: 10.1021/acsinfecdis.4c00119.Peer-Reviewed Original ResearchConceptsESI-MSElectrospray ionization mass spectrometryIonization mass spectrometryB-lactamase inhibitorsAcyl-enzyme complexMycobacterial cell wall synthesisMolecular dockingMass spectrometryActive siteInhibit BlaCPeptidoglycan transpeptidaseDiazabicyclooctaneSynthesisAntibiotic susceptibility testingCell wall synthesisInhibition kineticsDrug targetsB-lactamaseDurlobactamSusceptibility testingComplexDockingSpectrometryWall synthesisPeptidoglycan synthesisHighly Reactive Group I Introns Ubiquitous in Pathogenic Fungi
Liu T, Pyle A. Highly Reactive Group I Introns Ubiquitous in Pathogenic Fungi. Journal Of Molecular Biology 2024, 436: 168513. PMID: 38447889, DOI: 10.1016/j.jmb.2024.168513.Peer-Reviewed Original ResearchGroup I intronsAntifungal drug targetsRNA metabolismPathogenic fungiPhylogeny of fungiSelf-splicing intronsDrug targetsSystemic fungal infectionsGenetic hotspotsRiboregulatory elementsMitochondrial intronsMitochondrial genesBioinformatics pipelineC. aurisCandida aurisRelevant fungiRNA elementsAspergillus fumigatusC. albicansHousekeeping genesCandida albicansNoncoding transcriptomeCryptococcus neoformansFungal infectionsFungi
2023
Whole-genome sequencing uncovers two loci for coronary artery calcification and identifies ARSE as a regulator of vascular calcification
de Vries P, Conomos M, Singh K, Nicholson C, Jain D, Hasbani N, Jiang W, Lee S, Lino Cardenas C, Lutz S, Wong D, Guo X, Yao J, Young E, Tcheandjieu C, Hilliard A, Bis J, Bielak L, Brown M, Musharoff S, Clarke S, Terry J, Palmer N, Yanek L, Xu H, Heard-Costa N, Wessel J, Selvaraj M, Li R, Sun X, Turner A, Stilp A, Khan A, Newman A, Rasheed A, Freedman B, Kral B, McHugh C, Hodonsky C, Saleheen D, Herrington D, Jacobs D, Nickerson D, Boerwinkle E, Wang F, Heiss G, Jun G, Kinney G, Sigurslid H, Doddapaneni H, Hall I, Bensenor I, Broome J, Crapo J, Wilson J, Smith J, Blangero J, Vargas J, Mosquera J, Smith J, Viaud-Martinez K, Ryan K, Young K, Taylor K, Lange L, Emery L, Bittencourt M, Budoff M, Montasser M, Yu M, Mahaney M, Mahamdeh M, Fornage M, Franceschini N, Lotufo P, Natarajan P, Wong Q, Mathias R, Gibbs R, Do R, Mehran R, Tracy R, Kim R, Nelson S, Damrauer S, Kardia S, Rich S, Fuster V, Napolioni V, Zhao W, Tian W, Yin X, Min Y, Manning A, Peloso G, Kelly T, O’Donnell C, Morrison A, Curran J, Zapol W, Bowden D, Becker L, Correa A, Mitchell B, Psaty B, Carr J, Pereira A, Assimes T, Stitziel N, Hokanson J, Laurie C, Rotter J, Vasan R, Post W, Peyser P, Miller C, Malhotra R. Whole-genome sequencing uncovers two loci for coronary artery calcification and identifies ARSE as a regulator of vascular calcification. Nature Cardiovascular Research 2023, 2: 1159-1172. PMID: 38817323, PMCID: PMC11138106, DOI: 10.1038/s44161-023-00375-y.Peer-Reviewed Original ResearchGenome-wide association studiesMultiple ancestral groupsWhole-genome sequencingPotential drug targetsNovel lociAncestral groupsLociCoronary artery calcificationVascular smooth muscle cellsDrug targetsFunctional assaysPhenotypic switchingCoronary artery diseaseVascular smooth muscle cell phenotypic switchingHuman vascular smooth muscle cellsARSEG alleleArtery calcificationVascular calcificationPredictor of coronary artery diseaseReplicate analysesRegulation of vascular calcificationSmooth muscle cellsCalcifiersSequenceBabesia BdFE1 esterase is required for the anti-parasitic activity of the ACE inhibitor fosinopril
Vydyam P, Choi J, Gihaz S, Chand M, Gewirtz M, Thekkiniath J, Lonardi S, Gennaro J, Mamoun C. Babesia BdFE1 esterase is required for the anti-parasitic activity of the ACE inhibitor fosinopril. Journal Of Biological Chemistry 2023, 299: 105313. PMID: 37797695, PMCID: PMC10663679, DOI: 10.1016/j.jbc.2023.105313.Peer-Reviewed Original ResearchConceptsAngiotensin converting enzyme (ACE) inhibitorsACE inhibitor fosinoprilTick-borne illnessConverting Enzyme InhibitorsVector-borne parasitic diseaseClass of drugsNovel drug targetsApicomplexan parasitesMass spectrometry analysisAnti-parasitic activityHeart failureSafe therapyParasite developmentDrug targetsEnzyme inhibitorsParasitic diseasesDrug resistanceTreatment of diseasesHuman babesiosisBabesia parasitesIntraerythrocytic parasitesSuch diseasesDiseaseSpectrometry analysisParasites9. THE GENETIC ARCHITECTURE OF PAIN INTENSITY IN THE MILLION VETERAN PROGRAM
Toikumo S, Vickers-Smith R, Jinwala Z, Xu H, Saini D, Hartwell E, Pavicic M, Sullivan K, Jacobson D, Cheatle M, Zhou H, Waxman S, Justice A, Kember R, Kranzler H. 9. THE GENETIC ARCHITECTURE OF PAIN INTENSITY IN THE MILLION VETERAN PROGRAM. European Neuropsychopharmacology 2023, 75: s60-s61. DOI: 10.1016/j.euroneuro.2023.08.120.Peer-Reviewed Original ResearchIndependent lociGenetic architectureMillion Veteran ProgramGenome-wide association testingIndependent genetic lociLinkage disequilibrium score regressionDrug-gene interaction databaseDisequilibrium score regressionNovel genetic variantsPotential drug targetsComplex traitsGWAS resultsCausal genesDruggable genomeDrug repurposing analysisGenetic lociDruggable genesInteraction databasesDrug targetsGenetic correlationsMolecular contributorsAssociation testingLociPsychiatric traitsScore regressionThe Concise Guide to PHARMACOLOGY 2023/24: Ion channels
Alexander S, Mathie A, Peters J, Veale E, Striessnig J, Kelly E, Armstrong J, Faccenda E, Harding S, Davies J, Aldrich R, Attali B, Baggetta A, Becirovic E, Biel M, Bill R, Caceres A, Catterall W, Conner A, Davies P, De Clerq K, Delling M, Di Virgilio F, Falzoni S, Fenske S, Fortuny-Gomez A, Fountain S, George C, Goldstein S, Grimm C, Grissmer S, Ha K, Hammelmann V, Hanukoglu I, Hu M, Ijzerman A, Jabba S, Jarvis M, Jensen A, Jordt S, Kaczmarek L, Kellenberger S, Kennedy C, King B, Kitchen P, Liu Q, Lynch J, Meades J, Mehlfeld V, Nicke A, Offermanns S, Perez-Reyes E, Plant L, Rash L, Ren D, Salman M, Sieghart W, Sivilotti L, Smart T, Snutch T, Tian J, Trimmer J, Van den Eynde C, Vriens J, Wei A, Winn B, Wulff H, Xu H, Yang F, Fang W, Yue L, Zhang X, Zhu M. The Concise Guide to PHARMACOLOGY 2023/24: Ion channels. British Journal Of Pharmacology 2023, 180: s145-s222. PMID: 38123150, PMCID: PMC11339754, DOI: 10.1111/bph.16178.Peer-Reviewed Original ResearchConceptsBest available pharmacological toolsOpen access knowledgebase sourceOfficial IUPHAR classificationAvailable pharmacological toolsDrug targetsG protein-coupled receptorsIon channelsProtein-coupled receptorsNomenclature guidanceClinical pharmacologyMajor pharmacological targetCatalytic receptorsSelective pharmacologyNuclear hormone receptorsPharmacological targetsPharmacological toolsHormone receptorsPrevious GuidesReceptorsLandscape formatHuman drug targetsPharmacologyConcise guideBiennial publicationRelated targetsKDM5 Lysine Demethylases in Pathogenesis, from Basic Science Discovery to the Clinic
Zhang S, Cao J, Yan Q. KDM5 Lysine Demethylases in Pathogenesis, from Basic Science Discovery to the Clinic. Advances In Experimental Medicine And Biology 2023, 1433: 113-137. PMID: 37751138, DOI: 10.1007/978-3-031-38176-8_6.ChaptersConceptsPlant homeodomainFamily proteinsKey epigenetic markCell fate determinationHistone methylation marksCancer type-dependent mannerKetoglutarate-dependent dioxygenasesSelective KDM5 inhibitorsTumor suppressive functionType-dependent mannerEpigenetic marksTumor suppressive roleFate determinationJumonji CLysine 4Active chromatinMethylation marksHistone H3Lysine demethylasesCatalytic coreKDM5 inhibitorsDrug targetsKDM5Cancer metastasisSuppressive roleTTD: Therapeutic Target Database describing target druggability information
Zhou Y, Zhang Y, Zhao D, Yu X, Shen X, Zhou Y, Wang S, Qiu Y, Chen Y, Zhu F. TTD: Therapeutic Target Database describing target druggability information. Nucleic Acids Research 2023, 52: d1465-d1477. PMID: 37713619, PMCID: PMC10767903, DOI: 10.1093/nar/gkad751.Peer-Reviewed Original ResearchGenetically Regulated Gene Expression in the Brain Associated With Chronic Pain: Relationships With Clinical Traits and Potential for Drug Repurposing
Johnston K, Cote A, Hicks E, Johnson J, Huckins L. Genetically Regulated Gene Expression in the Brain Associated With Chronic Pain: Relationships With Clinical Traits and Potential for Drug Repurposing. Biological Psychiatry 2023, 95: 745-761. PMID: 37678542, PMCID: PMC10924073, DOI: 10.1016/j.biopsych.2023.08.023.Peer-Reviewed Original ResearchConceptsGenetically regulated gene expressionMultisite chronic painGene-tissue associationsMean pain scoreUnique genesChronic painAssociation studiesS-PrediXcanGene expressionPain scoresTranscriptome-wide association studyPhenome-wide association studyCardiac dysrhythmiasMetabolic syndromeGenome-wide association studiesAssociated with cardiac dysrhythmiasDrug targetsGenotype-phenotype gapChronic pain developmentAssociation study resultsGene expression changesJoint/ligament sprainsDirection of effectTranscriptome imputationPain traitsDYRK1A promotes viral entry of highly pathogenic human coronaviruses in a kinase-independent manner
Strine M, Cai W, Wei J, Alfajaro M, Filler R, Biering S, Sarnik S, Chow R, Patil A, Cervantes K, Collings C, DeWeirdt P, Hanna R, Schofield K, Hulme C, Konermann S, Doench J, Hsu P, Kadoch C, Yan Q, Wilen C. DYRK1A promotes viral entry of highly pathogenic human coronaviruses in a kinase-independent manner. PLOS Biology 2023, 21: e3002097. PMID: 37310920, PMCID: PMC10263356, DOI: 10.1371/journal.pbio.3002097.Peer-Reviewed Original ResearchConceptsGenome-wide CRISPR/Cas9 screenCRISPR/Cas9 screenPathogenic human coronavirusesKinase-independent mannerRegulated kinase 1AProviral host factorNovel drug targetsMultiple cell typesDNA accessibilityHost factorsKinase functionHuman coronavirusesHost genesDistal enhancerNovel regulatorCas9 screenKinase 1AGene expressionNeuronal developmentDYRK1ADrug targetsDiverse coronavirusesProviral activityCell typesSevere acute respiratory syndrome coronavirus 2Babesia duncani multi-omics identifies virulence factors and drug targets
Singh P, Lonardi S, Liang Q, Vydyam P, Khabirova E, Fang T, Gihaz S, Thekkiniath J, Munshi M, Abel S, Ciampossin L, Batugedara G, Gupta M, Lu X, Lenz T, Chakravarty S, Cornillot E, Hu Y, Ma W, Gonzalez L, Sánchez S, Estrada K, Sánchez-Flores A, Montero E, Harb O, Le Roch K, Mamoun C. Babesia duncani multi-omics identifies virulence factors and drug targets. Nature Microbiology 2023, 8: 845-859. PMID: 37055610, PMCID: PMC10159843, DOI: 10.1038/s41564-023-01360-8.Peer-Reviewed Original ResearchConceptsDrug targetsVirulence factorsCandidate virulence factorsRNA-seq dataIntraerythrocytic life cycleAttractive drug targetB. duncaniNuclear genomeGenome annotationApicomplexan parasitesApicomplexan pathogensEpigenetic profilesEpigenetic analysisParasite metabolismMalaria-like diseaseHuman erythrocytesLife cycle stagesBabesia speciesGenomeMetabolic requirementsCycle stagesLife cycleBiologySmall moleculesPotent inhibitor
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