RESUMEN
Eukaryotic transcription activators stimulate the expression of specific sets of target genes through recruitment of co-activators such as the RNA polymerase II-interacting Mediator complex. Aberrant function of transcription activators has been implicated in several diseases. However, therapeutic targeting efforts have been hampered by a lack of detailed molecular knowledge of the mechanisms of gene activation by disease-associated transcription activators. We previously identified an activator-targeted three-helix bundle KIX domain in the human MED15 Mediator subunit that is structurally conserved in Gal11/Med15 Mediator subunits in fungi. The Gal11/Med15 KIX domain engages pleiotropic drug resistance transcription factor (Pdr1) orthologues, which are key regulators of the multidrug resistance pathway in Saccharomyces cerevisiae and in the clinically important human pathogen Candida glabrata. The prevalence of C. glabrata is rising, partly owing to its low intrinsic susceptibility to azoles, the most widely used antifungal agent. Drug-resistant clinical isolates of C. glabrata most commonly contain point mutations in Pdr1 that render it constitutively active, suggesting that this transcriptional activation pathway represents a linchpin in C. glabrata multidrug resistance. Here we perform sequential biochemical and in vivo high-throughput screens to identify small-molecule inhibitors of the interaction of the C. glabrata Pdr1 activation domain with the C. glabrata Gal11A KIX domain. The lead compound (iKIX1) inhibits Pdr1-dependent gene activation and re-sensitizes drug-resistant C. glabrata to azole antifungals in vitro and in animal models for disseminated and urinary tract C. glabrata infection. Determining the NMR structure of the C. glabrata Gal11A KIX domain provides a detailed understanding of the molecular mechanism of Pdr1 gene activation and multidrug resistance inhibition by iKIX1. We have demonstrated the feasibility of small-molecule targeting of a transcription factor-binding site in Mediator as a novel therapeutic strategy in fungal infectious disease.
Asunto(s)
Antifúngicos/farmacología , Candida glabrata/efectos de los fármacos , Candida glabrata/metabolismo , Farmacorresistencia Fúngica/efectos de los fármacos , Proteínas Fúngicas/metabolismo , Complejo Mediador/metabolismo , Transactivadores/metabolismo , Animales , Sitios de Unión/efectos de los fármacos , Candida glabrata/genética , Candidiasis/tratamiento farmacológico , Candidiasis/microbiología , Proteínas de Unión al ADN/genética , Proteínas de Unión al ADN/metabolismo , Farmacorresistencia Fúngica Múltiple/efectos de los fármacos , Fluconazol/farmacología , Regulación Fúngica de la Expresión Génica/efectos de los fármacos , Hidrazinas/farmacocinética , Hidrazinas/farmacología , Cetoconazol/farmacología , Complejo Mediador/química , Ratones , Modelos Moleculares , Resonancia Magnética Nuclear Biomolecular , Unión Proteica/efectos de los fármacos , Estructura Terciaria de Proteína , Proteínas de Saccharomyces cerevisiae/química , Proteínas de Saccharomyces cerevisiae/genética , Proteínas de Saccharomyces cerevisiae/metabolismo , Tiourea/análogos & derivados , Tiourea/farmacocinética , Tiourea/farmacología , Transactivadores/química , Factores de Transcripción/genética , Factores de Transcripción/metabolismo , Activación Transcripcional/efectos de los fármacos , Regulación hacia Arriba/efectos de los fármacosRESUMEN
We report here a novel method for predicting melting temperatures of DNA sequences based on a molecular-level hypothesis on the phenomena underlying the thermal denaturation of DNA. The model presented here attempts to quantify the energetic components stabilizing the structure of DNA such as base pairing, stacking, and ionic environment which are partially disrupted during the process of thermal denaturation. The model gives a Pearson product-moment correlation coefficient (r) of approximately 0.98 between experimental and predicted melting temperatures for over 300 sequences of varying lengths ranging from 15-mers to genomic level and at different salt concentrations. The approach is implemented as a web tool (www.scfbio-iitd.res.in/chemgenome/Tm_predictor.jsp) for the prediction of melting temperatures of DNA sequences.