In silico generation of peptides by replica exchange monte carlo: Docking-based optimization of maltose-binding-protein ligands
Genre
Journal ArticleDate
2015-08-07Author
Russo, AScognamiglio, PL
Enriquez, RPH
Santambrogio, C
Grandori, R
Marasco, D
Giordano, A
Scoles, G
Fortuna, S
Subject
AlgorithmsAmino Acid Sequence
Fluorescence
Immobilized Proteins
Kinetics
Ligands
Maltose-Binding Proteins
Molecular Docking Simulation
Molecular Sequence Data
Monte Carlo Method
Peptides
Protein Binding
Spectrometry, Mass, Electrospray Ionization
Surface Plasmon Resonance
Thermodynamics
Tryptophan
Permanent link to this record
http://hdl.handle.net/20.500.12613/5211
Metadata
Show full item recordDOI
10.1371/journal.pone.0133571Abstract
© 2015 Russo et al. 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 exnovo optimization of peptide based binders. Copyright:Citation to related work
Public Library of Science (PLoS)Has part
PLoS ONEADA compliance
For Americans with Disabilities Act (ADA) accommodation, including help with reading this content, please contact scholarshare@temple.eduae974a485f413a2113503eed53cd6c53
http://dx.doi.org/10.34944/dspace/5193