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General approach for characterizing in vitro selected peptides with protein binding affinity.

ABSTRACT: In vitro selection technologies are important tools for identifying high affinity peptides to proteins of broad medical and biological interest. However, the technological advances that have made it possible to generate long lists of candidate peptides have far outpaced our ability to characterize the binding properties of individual peptides. Here, we describe a low cost strategy to rapidly synthesize, purify, screen, and characterize peptides for high binding affinity. Peptides are assayed in a 96-well dot blot apparatus using membranes that enable partitioning of bound and unbound peptide-protein complexes. We have validated the binding affinity constants produced by this method using known peptide ligands and applied this process to discover five new peptides with nanomolar affinity to human ?-thrombin. Given the need for new analytical tools that can accelerate peptide discovery and characterization, we feel that this approach would be useful to a wide range of technologies that utilize high affinity peptides.

SUBMITTER: Larsen AC

PROVIDER: S-EPMC4215864 | biostudies-other | 2014 Aug

REPOSITORIES: biostudies-other

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General approach for characterizing in vitro selected peptides with protein binding affinity.

Larsen Andrew C AC Gillig Annabelle A Shah Pankti P Sau Sujay P SP Fenton Kathryn E KE Chaput John C JC

Analytical chemistry 20140714 15

In vitro selection technologies are important tools for identifying high affinity peptides to proteins of broad medical and biological interest. However, the technological advances that have made it possible to generate long lists of candidate peptides have far outpaced our ability to characterize the binding properties of individual peptides. Here, we describe a low cost strategy to rapidly synthesize, purify, screen, and characterize peptides for high binding affinity. Peptides are assayed in ...[more]

PMID: 24970615

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Project description:The protein targets for general anesthetics remain unclear. A tool to predict anesthetic binding for potential binding targets is needed. In this study, we explored whether a computational method, AutoDock, could serve as such a tool.High-resolution crystal data of water-soluble proteins (cytochrome C, apoferritin, and human serum albumin), and a membrane protein (a pentameric ligand-gated ion channel from Gloeobacter violaceus [GLIC]) were used. Isothermal titration calorimetry (ITC) experiments were performed to determine anesthetic affinity in solution conditions for apoferritin. Docking calculations were performed using DockingServer with the Lamarckian genetic algorithm and the Solis and Wets local search method (http://www.dockingserver.com/web). Twenty general anesthetics were docked into apoferritin. The predicted binding constants were compared with those obtained from ITC experiments for potential correlations. In the case of apoferritin, details of the binding site and their interactions were compared with recent cocrystallization data. Docking calculations for 6 general anesthetics currently used in clinical settings (isoflurane, sevoflurane, desflurane, halothane, propofol, and etomidate) with known 50% effective concentration (EC(50)) values were also performed in all tested proteins. The binding constants derived from docking experiments were compared with known EC(50) values and octanol/water partition coefficients for the 6 general anesthetics.All 20 general anesthetics docked unambiguously into the anesthetic binding site identified in the crystal structure of apoferritin. The binding constants for 20 anesthetics obtained from the docking calculations correlate significantly with those obtained from ITC experiments (P = 0.04). In the case of GLIC, the identified anesthetic binding sites in the crystal structure are among the docking predicted binding sites, but not the top ranked site. Docking calculations suggest a most probable binding site located in the extracellular domain of GLIC. The predicted affinities correlated significantly with the known EC(50) values for the 6 frequently used anesthetics in GLIC for the site identified in the experimental crystal data (P = 0.006). However, predicted affinities in apoferritin, human serum albumin, and cytochrome C did not correlate with these 6 anesthetics' known experimental EC(50) values. A weak correlation between the predicted affinities and the octanol/water partition coefficients was observed for the sites in GLIC.We demonstrated that anesthetic binding sites and relative affinities can be predicted using docking calculations in an automatic docking server (AutoDock) for both water-soluble and membrane proteins. Correlation of predicted affinity and EC(50) for 6 frequently used general anesthetics was only observed in GLIC, a member of a protein family relevant to anesthetic mechanism.

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General approach for characterizing in vitro selected peptides with protein binding affinity.

Publications

General approach for characterizing in vitro selected peptides with protein binding affinity.

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