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Nelly Panté

University of British Columbia

ORCID: 0000-0002-0926-9378

Publishes on Nuclear Structure and Function, RNA Research and Splicing, Virus-based gene therapy research. 94 papers and 7.6k citations.

94Publications
7.6kTotal Citations

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Top publicationsby citations

Nuclear Pore Complex Is Able to Transport Macromolecules with Diameters of ∼39 nm
Nelly Panté, Michael Kann|Molecular Biology of the Cell|2002
Cited by 772Open Access

Bidirectional transport of macromolecules between the nucleus and the cytoplasm occurs through the nuclear pore complexes (NPCs) by a signal-mediated mechanism that is directed by targeting signals (NLSs) residing on the transported molecules or "cargoes." Nuclear transport starts after interaction of the targeting signal with soluble cellular receptors. After the formation of the cargo-receptor complex in the cytosol, this complex crosses the NPC. Herein, we use gold particles of various sizes coated with cargo-receptor complexes to determine precisely how large macromolecules crossing the NPC by the signal-mediated transport mechanism could be. We found that cargo-receptor-gold complexes with diameter close to 39 nm could be translocated by the NPC. This implies that macromolecules much larger than the assumed functional NPC diameter of 26 nm can be transported into the karyoplasm. The physiological relevance of this finding was supported by the observation that intact nucleocapsids of human hepatitis B virus with diameters of 32 and 36 nm are able to cross the nuclear pore without disassembly.

The C-terminal domain of TAP interacts with the nuclear pore complex and promotes export of specific CTE-bearing RNA substrates
Cited by 327Open Access

Messenger RNAs are exported from the nucleus as large ribonucleoprotein complexes (mRNPs). To date, proteins implicated in this process include TAP/Mex67p and RAE1/Gle2p and are distinct from the nuclear transport receptors of the beta-related, Ran-binding protein family. Mex67p is essential for mRNA export in yeast. Its vertebrate homolog TAP has been implicated in the export of cellular mRNAs and of simian type D viral RNAs bearing the constitutive transport element (CTE). Here we show that TAP is predominantly localized in the nucleoplasm and at both the nucleoplasmic and cytoplasmic faces of the nuclear pore complex (NPC). TAP interacts with multiple components of the NPC including the nucleoporins CAN, Nup98, Nup153, p62, and with three major NPC subcomplexes. The nucleoporin-binding domain of TAP comprises residues 508-619. In HeLa cells, this domain is necessary and sufficient to target GFP-TAP fusions to the nuclear rim. Moreover, the isolated domain strongly competes multiple export pathways in vivo, probably by blocking binding sites on the NPC that are shared with other transport receptors. Microinjection experiments implicate this domain in the export of specific CTE-containing RNAs. Finally, we show that TAP interacts with transportin and with two proteins implicated in the export of cellular mRNAs: RAE1/hGle2 and E1B-AP5. The interaction of TAP with nucleoporins, its direct binding to the CTE RNA, and its association with two mRNP binding proteins suggest that TAP is an RNA export mediator that may bridge the interaction between specific RNP export substrates and the NPC.

Identification of Novel Antibacterial Peptides by Chemoinformatics and Machine Learning
Christopher D. Fjell, Håvard Jenssen, Kai Hilpert et al.|Journal of Medicinal Chemistry|2009
Cited by 295

The rise of antibiotic resistant pathogens is one of the most pressing global health issues. Discovery of new classes of antibiotics has not kept pace; new agents often suffer from cross-resistance to existing agents of similar structure. Short, cationic peptides with antimicrobial activity are essential to the host defenses of many organisms and represent a promising new class of antimicrobials. This paper reports the successful in silico screening for potent antibiotic peptides using a combination of QSAR and machine learning techniques. On the basis of initial high-throughput measurements of activity of over 1400 random peptides, artificial neural network models were built using QSAR descriptors and subsequently used to screen an in silico library of approximately 100,000 peptides. In vitro validation of the modeling showed 94% accuracy in identifying highly active peptides. The best peptides identified through screening were found to have activities comparable or superior to those of four conventional antibiotics and superior to the peptide most advanced in clinical development against a broad array of multiresistant human pathogens.