Dataset Information

Screening bicyclic peptide libraries for protein-protein interaction inhibitors: discovery of a tumor necrosis factor-? antagonist.

ABSTRACT: Protein-protein interactions represent a new class of exciting but challenging drug targets, because their large, flat binding sites lack well-defined pockets for small molecules to bind. We report here a methodology for chemical synthesis and screening of large combinatorial libraries of bicyclic peptides displayed on rigid small-molecule scaffolds. With planar trimesic acid as the scaffold, the resulting bicyclic peptides are effective for binding to protein surfaces such as the interfaces of protein-protein interactions. Screening of a bicyclic peptide library against tumor necrosis factor-? (TNF?) identified a potent antagonist that inhibits the TNF?-TNF? receptor interaction and protects cells from TNF?-induced cell death. Bicyclic peptides of this type may provide a general solution for inhibition of protein-protein interactions.

SUBMITTER: Lian W

PROVIDER: S-EPMC3856571 | biostudies-literature | 2013 Aug

REPOSITORIES: biostudies-literature

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Publications

Screening bicyclic peptide libraries for protein-protein interaction inhibitors: discovery of a tumor necrosis factor-α antagonist.

Lian Wenlong W Upadhyaya Punit P Rhodes Curran A CA Liu Yusen Y Pei Dehua D

Journal of the American Chemical Society 20130801 32

Protein-protein interactions represent a new class of exciting but challenging drug targets, because their large, flat binding sites lack well-defined pockets for small molecules to bind. We report here a methodology for chemical synthesis and screening of large combinatorial libraries of bicyclic peptides displayed on rigid small-molecule scaffolds. With planar trimesic acid as the scaffold, the resulting bicyclic peptides are effective for binding to protein surfaces such as the interfaces of ...[more]

PMID: 23865589

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Project description:Protein-protein interactions (PPIs) may represent one of the next major classes of therapeutic targets. So far, only a minute fraction of the estimated 650,000 PPIs that comprise the human interactome are known with a tiny number of complexes being drugged. Such intricate biological systems cannot be cost-efficiently tackled using conventional high-throughput screening methods. Rather, time has come for designing new strategies that will maximize the chance for hit identification through a rationalization of the PPI inhibitor chemical space and the design of PPI-focused compound libraries (global or target-specific). Here, we train machine-learning-based models, mainly decision trees, using a dataset of known PPI inhibitors and of regular drugs in order to determine a global physico-chemical profile for putative PPI inhibitors. This statistical analysis unravels two important molecular descriptors for PPI inhibitors characterizing specific molecular shapes and the presence of a privileged number of aromatic bonds. The best model has been transposed into a computer program, PPI-HitProfiler, that can output from any drug-like compound collection a focused chemical library enriched in putative PPI inhibitors. Our PPI inhibitor profiler is challenged on the experimental screening results of 11 different PPIs among which the p53/MDM2 interaction screened within our own CDithem platform, that in addition to the validation of our concept led to the identification of 4 novel p53/MDM2 inhibitors. Collectively, our tool shows a robust behavior on the 11 experimental datasets by correctly profiling 70% of the experimentally identified hits while removing 52% of the inactive compounds from the initial compound collections. We strongly believe that this new tool can be used as a global PPI inhibitor profiler prior to screening assays to reduce the size of the compound collections to be experimentally screened while keeping most of the true PPI inhibitors. PPI-HitProfiler is freely available on request from our CDithem platform website, www.CDithem.com.

Dataset Information

Screening bicyclic peptide libraries for protein-protein interaction inhibitors: discovery of a tumor necrosis factor-? antagonist.

Publications

Screening bicyclic peptide libraries for protein-protein interaction inhibitors: discovery of a tumor necrosis factor-α antagonist.

Similar Datasets

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