Role of Ess1 in Growth, Morphogenetic Switching, and RNA Polymerase II Transcription in Candida Albicans.
Role of Ess1 in Growth, Morphogenetic Switching, and RNA Polymerase II Transcription in Candida albicans.
PLoS One. 2013; 8(3): e59094
Samaranayake D, Atencio D, Morse R, Wade JT, Chaturvedi V, Hanes SD
Candida albicans is a fungal pathogen that causes potentially fatal infections among immune-compromised individuals. The emergence of drug resistant C. albicans strains makes it important to identify new antifungal drug targets. Among potential targets are enzymes known as peptidyl-prolyl cis/trans isomerases (PPIases) that catalyze isomerization of peptide bonds preceding proline. We are investigating a PPIase called Ess1, which is conserved in all major human pathogenic fungi. Previously, we reported that C. albicans Ess1 is essential for growth and morphogenetic switching. In the present study, we re-evaluated these findings using more rigorous genetic analyses, including the use of additional CaESS1 mutant alleles, distinct marker genes, and the engineering of suitably-matched isogenic control strains. The results confirm that CaEss1 is essential for growth in C. albicans, but show that reduction of CaESS1 gene dosage by half (?/+) does not interfere with morphogenetic switching. However, further reduction of CaEss1 levels using a conditional allele does reduce morphogenetic switching. We also examine the role of the linker ?-helix that distinguishes C. albicans Ess1 from the human Pin1 enzyme, and present results of a genome-wide transcriptome analysis. The latter analysis indicates that CaEss1 has a conserved role in regulation of RNA polymerase II function, and is required for efficient termination of small nucleolar RNAs and repression of cryptic transcription in C. albicans. HubMed – drug
Detection of Rapalog-Mediated Therapeutic Response in Renal Cancer Xenografts Using (64)Cu-bevacizumab ImmunoPET.
PLoS One. 2013; 8(3): e58949
Chang AJ, Sohn R, Lu ZH, Arbeit JM, Lapi SE
The importance of neovascularization for primary and metastatic tumor growth fostered numerous clinical trials of angiogenesis inhibitors either alone or in combination with conventional antineoplastic therapies. One challenge with the use of molecularly targeted agents has been the disconnection between size reduction and tumor biologic behavior, either when the drug is efficacious or when tumor resistance emerges. Here, we report the synthesis and characterization of (64)Cu-NOTA-bevacizumab as a PET imaging agent for imaging intratumoral VEGF content in vivo. (64)Cu-NOTA-bevacizumab avidly accumulated in 786-O renal carcinoma xenografts with lower levels in host organs. RAD001 (everolimus) markedly attenuated (64)Cu-NOTA-bevacizumab accumulation within 786-O renal carcinoma xenografts. Tumor tissue and cellular molecular analysis validated PET imaging, demonstrating decreases in total and secreted VEGF content and VEGFR2 activation. Notably, (64)Cu-NOTA-bevacizumab PET imaging was concordant with the growth arrest of RAD001 tumors. These data suggest that immunoPET targeting of angiogenic factors such as VEGF could be a new class of surrogate markers complementing the RECIST criteria in patients receiving molecularly targeted therapies. HubMed – drug
A unified conformational selection and induced fit approach to protein-Peptide docking.
PLoS One. 2013; 8(3): e58769
Trellet M, Melquiond AS, Bonvin AM
Protein-peptide interactions are vital for the cell. They mediate, inhibit or serve as structural components in nearly 40% of all macromolecular interactions, and are often associated with diseases, making them interesting leads for protein drug design. In recent years, large-scale technologies have enabled exhaustive studies on the peptide recognition preferences for a number of peptide-binding domain families. Yet, the paucity of data regarding their molecular binding mechanisms together with their inherent flexibility makes the structural prediction of protein-peptide interactions very challenging. This leaves flexible docking as one of the few amenable computational techniques to model these complexes. We present here an ensemble, flexible protein-peptide docking protocol that combines conformational selection and induced fit mechanisms. Starting from an ensemble of three peptide conformations (extended, a-helix, polyproline-II), flexible docking with HADDOCK generates 79.4% of high quality models for bound/unbound and 69.4% for unbound/unbound docking when tested against the largest protein-peptide complexes benchmark dataset available to date. Conformational selection at the rigid-body docking stage successfully recovers the most relevant conformation for a given protein-peptide complex and the subsequent flexible refinement further improves the interface by up to 4.5 Å interface RMSD. Cluster-based scoring of the models results in a selection of near-native solutions in the top three for ?75% of the successfully predicted cases. This unified conformational selection and induced fit approach to protein-peptide docking should open the route to the modeling of challenging systems such as disorder-order transitions taking place upon binding, significantly expanding the applicability limit of biomolecular interaction modeling by docking. HubMed – drug