| Naslov: | In silico generation of peptides by replica exchange Monte Carlo: Docking-based optimization of maltose-binding-protein ligands |
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| Avtorji: | ID Russo, Anna (Avtor)
ID Scognamiglio, Pasqualina Liana (Avtor)
ID Hong Enriquez, Rolando Pablo (Avtor)
ID Santambrogio, Carlo (Avtor)
ID Grandori, Rita (Avtor)
ID Marasco, Daniela (Avtor)
ID Giordano, Antonio (Avtor)
ID Scoles, Giacinto (Avtor)
ID Fortuna, Sara (Avtor) |
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| Datoteke: |  11_Russo_MBP.pdf (4,27 MB)
MD5: 885643A85EBD46544C3538AAAB074FB6
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| Jezik: | Angleški jezik |
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| Vrsta gradiva: | Delo ni kategorizirano |
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| Tipologija: | 1.01 - Izvirni znanstveni članek |
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| Organizacija: | UNG - Univerza v Novi Gorici
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| Opis: | Short peptides can be designed in silico and synthesized through automated techniques, making them advantageous and versatile protein binders. A number of docking-based algorithms allow for a computational screening of peptides as binders. Here we developed ex-novo peptides targeting the maltose site of the Maltose Binding Protein, the prototypical system for the study of protein ligand recognition. We used a Monte Carlo based protocol, to computationally evolve a set of octapeptides starting from a polialanine sequence. We screened in silico the candidate peptides and characterized their binding abilities by surface plasmon resonance, fluorescence and electrospray ionization mass spectrometry assays. These experiments showed the designed binders to recognize their target with micromolar affinity. We finally discuss the obtained results in the light of further improvement in the ex-novo optimization of peptide based binders. |
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| Ključne besede: | peptides, docking, optimisation, computation, maltose binding protein, probe, ligand |
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| Leto izida: | 2015 |
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| Št. strani: | 16 |
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| Številčenje: | 10, 8 |
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| PID: | 20.500.12556/RUNG-2691  |
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| COBISS.SI-ID: | 4536059 |
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| DOI: | 10.1371/journal.pone.0133571 |
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| NUK URN: | URN:SI:UNG:REP:Z4VVUB3F |
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| Datum objave v RUNG: | 12.10.2016 |
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| Število ogledov: | 4816 |
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| Število prenosov: | 142 |
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| Metapodatki: |    |
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