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Superchiral Plasmonic Phase Sensitivity for Fingerprinting of Protein Interface Structure.

ABSTRACT: The structure adopted by biomaterials, such as proteins, at interfaces is a crucial parameter in a range of important biological problems. It is a critical property in defining the functionality of cell/bacterial membranes and biofilms (i.e., in antibiotic-resistant infections) and the exploitation of immobilized enzymes in biocatalysis. The intrinsically small quantities of materials at interfaces precludes the application of conventional spectroscopic phenomena routinely used for (bio)structural analysis due to a lack of sensitivity. We show that the interaction of proteins with superchiral fields induces asymmetric changes in retardation phase effects of excited bright and dark modes of a chiral plasmonic nanostructure. Phase retardations are obtained by a simple procedure, which involves fitting the line shape of resonances in the reflectance spectra. These interference effects provide fingerprints that are an incisive probe of the structure of interfacial biomolecules. Using these fingerprints, layers composed of structurally related proteins with differing geometries can be discriminated. Thus, we demonstrate a powerful tool for the bioanalytical toolbox.

SUBMITTER: Tullius R

PROVIDER: S-EPMC6034627 | biostudies-literature | 2017 Dec

REPOSITORIES: biostudies-literature

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Superchiral Plasmonic Phase Sensitivity for Fingerprinting of Protein Interface Structure.

Tullius Ryan R Platt Geoffrey W GW Khosravi Khorashad Larousse L Gadegaard Nikolaj N Lapthorn Adrian J AJ Rotello Vincent M VM Cooke Graeme G Barron Laurence D LD Govorov Alexander O AO Karimullah Affar S AS Kadodwala Malcolm M

ACS nano 20171215 12

The structure adopted by biomaterials, such as proteins, at interfaces is a crucial parameter in a range of important biological problems. It is a critical property in defining the functionality of cell/bacterial membranes and biofilms (i.e., in antibiotic-resistant infections) and the exploitation of immobilized enzymes in biocatalysis. The intrinsically small quantities of materials at interfaces precludes the application of conventional spectroscopic phenomena routinely used for (bio)structur ...[more]

PMID: 29220155

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Project description:BackgroundIdentifying protein interfaces can inform how proteins interact with their binding partners, uncover the regulatory mechanisms that control biological functions and guide the development of novel therapeutic agents. A variety of computational approaches have been developed for predicting a protein's interfacial residues from its known sequence and structure. Methods using the known three-dimensional structures of proteins can be template-based or template-free. Template-based methods have limited success in predicting interfaces when homologues with known complex structures are not available to use as templates. The prediction performance of template-free methods that only rely only upon proteins' intrinsic properties is limited by the amount of biologically relevant features that can be included in an interface prediction model.ResultsWe describe the development of an integrated method for protein interface prediction (ISPIP) to explore the hypothesis that the efficacy of a computational prediction method of protein binding sites can be enhanced by using a combination of methods that rely on orthogonal structure-based properties of a query protein, combining and balancing both template-free and template-based features. ISPIP is a method that integrates these approaches through simple linear or logistic regression models and more complex decision tree models. On a diverse test set of 156 query proteins, ISPIP outperforms each of its individual classifiers in identifying protein binding interfaces.ConclusionsThe integrated method captures the best performance of individual classifiers and delivers an improved interface prediction. The method is robust and performs well even when one of the individual classifiers performs poorly on a particular query protein. This work demonstrates that integrating orthogonal methods that depend on different structural properties of proteins performs better at interface prediction than any individual classifier alone.

Project description:An active segment of the research community designing small molecules ("minimalist mimics" of peptide fragments) to interfere with protein-protein interactions have based their studies on an implicit hypothesis. Here we refer to this as the Secondary Structure Hypothesis, that might be defined as, "If a small molecule can orient amino acid side-chains in directions that resemble side-chains of the parent secondary structure at the interface, then that small molecule is a candidate to perturb the protein-protein interaction". Rigorous tests of this hypothesis require co-crystallization of minimalist mimics with protein receptors, and comparison of the bound conformations with the interface secondary structures they were designed to resemble. Unfortunately, to the best of our knowledge, there is no such analysis in the literature, and it is unlikely that enough examples will emerge in the near future to test the hypothesis. Research described here was designed to challenge this hypothesis from a different perspective. In a previous study, preferred conformations of a series of novel minimalist mimics were simulated then systematically overlaid on >240 000 crystallographically characterized protein-protein interfaces. Select data from that overlay procedure revealed chemotypes that overlay side chains on various PPI interfaces with a relatively high frequency of occurrence. The first aim of this work was to determine if good secondary structure mimics overlay frequently on PPI interfaces. The second aim of this work was to determine if overlays of preferred conformers at interface regions involve secondary structures. Thus situations where these conformations overlaid extremely well on PPI interfaces were analyzed to determine if secondary structures featured the PPI regions where these molecules overlaid in the previous study. Combining conclusions from these two studies enabled us to formulate a hypothesis that is complementary to the Secondary Structure Hypothesis, but, unlike this, is supported by abundant data. We call this the Interface Mimicry Hypothesis.

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Superchiral Plasmonic Phase Sensitivity for Fingerprinting of Protein Interface Structure.

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Superchiral Plasmonic Phase Sensitivity for Fingerprinting of Protein Interface Structure.

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