Dataset Information

Rational optimization of conformational effects induced by hydrocarbon staples in peptides and their binding interfaces.

ABSTRACT: eIF4E is frequently over-expressed in different cancers and causes increased translation of oncogenic proteins via deregulated cap-dependent translation. Inhibitors of the eIF4E:eIF4G interactions represent an approach that would normalize cap-dependent translation. Stapled peptides represent an emerging class of therapeutics that can target protein: protein interactions. We present here molecular dynamics simulations for a set of rationally designed stapled peptides in solution and in complex with eIF4E, supported with biophysical and crystallographic data. Clustering of the simulated structures revealed the favoured conformational states of the stapled peptides in their bound or free forms in solution. Identifying these populations has allowed us to design peptides with improved affinities by introducing mutations into the peptide sequence to alter their conformational distributions. These studies emphasise the effects that engineered mutations have on the conformations of free and bound peptides, and illustrate that both states must be considered in efforts to attain high affinity binding.

SUBMITTER: Lama D

PROVIDER: S-EPMC6506440 | biostudies-literature | 2013 Dec

REPOSITORIES: biostudies-literature

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Rational optimization of conformational effects induced by hydrocarbon staples in peptides and their binding interfaces.

Lama Dilraj D Quah Soo T ST Verma Chandra S CS Lakshminarayanan Rajamani R Beuerman Roger W RW Lane David P DP Brown Christopher J CJ

Scientific reports 20131213

eIF4E is frequently over-expressed in different cancers and causes increased translation of oncogenic proteins via deregulated cap-dependent translation. Inhibitors of the eIF4E:eIF4G interactions represent an approach that would normalize cap-dependent translation. Stapled peptides represent an emerging class of therapeutics that can target protein: protein interactions. We present here molecular dynamics simulations for a set of rationally designed stapled peptides in solution and in complex w ...[more]

PMID: 24336354

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Project description:Many protein-protein interactions (PPIs) are compelling targets for drug discovery, and in a number of cases can be disrupted by small molecules. The main goal of this study is to examine the mechanism of binding site formation in the interface region of proteins that are PPI targets by comparing ligand-free and ligand-bound structures. To avoid any potential bias, we focus on ensembles of ligand-free protein conformations obtained by nuclear magnetic resonance (NMR) techniques and deposited in the Protein Data Bank, rather than on ensembles specifically generated for this study. The measures used for structure comparison are based on detecting binding hot spots, i.e., protein regions that are major contributors to the binding free energy. The main tool of the analysis is computational solvent mapping, which explores the surface of proteins by docking a large number of small "probe" molecules. Although we consider conformational ensembles obtained by NMR techniques, the analysis is independent of the method used for generating the structures. Finding the energetically most important regions, mapping can identify binding site residues using ligand-free models based on NMR data. In addition, the method selects conformations that are similar to some peptide-bound or ligand-bound structure in terms of the properties of the binding site. This agrees with the conformational selection model of molecular recognition, which assumes such pre-existing conformations. The analysis also shows the maximum level of similarity between unbound and bound states that is achieved without any influence from a ligand. Further shift toward the bound structure assumes protein-peptide or protein-ligand interactions, either selecting higher energy conformations that are not part of the NMR ensemble, or leading to induced fit. Thus, forming the sites in protein-protein interfaces that bind peptides and can be targeted by small ligands always includes conformational selection, although other recognition mechanisms may also be involved.

Dataset Information

Rational optimization of conformational effects induced by hydrocarbon staples in peptides and their binding interfaces.

Publications

Rational optimization of conformational effects induced by hydrocarbon staples in peptides and their binding interfaces.

Similar Datasets

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