Unlocking the secrets to protein–protein interface drug targets using structural mass spectrometry techniques

Protein–protein interactions (PPIs) drive all biologic systems at the subcellular and extracellular level. Changes in the specificity and affinity of these interactions can lead to cellular malfunctions and disease. Consequently, the binding interfaces between interacting protein partners are important drug targets for the next generation of therapies that block such interactions. Unfortunately, protein–protein contact points have proven to be very difficult pharmacological targets because they are hidden within complex 3D interfaces. For the vast majority of characterized binary PPIs, the specific amino acid sequence of their close contact regions remains unknown. There has been an important need for an experimental technology that can rapidly reveal the functionally important contact points of native protein complexes in solution. In this review, experimental techniques employing mass spectrometry to explore protein interaction binding sites are discussed. Hydrogen–deuterium exchange, hydroxyl radical footprinting, crosslinking and the newest technology protein painting are compared and contrasted.     

Fcγ1 fragment of IgG1 as a powerful affinity tag in recombinant Fc-fusion proteins: immunological,biochemical and therapeutic properties

Affinity tags are vital tools for the production of high-throughput recombinant proteins. Several affinity tags, such as the hexahistidine tag, maltose-binding protein, streptavidin-binding peptide tag, calmodulin-binding peptide, c-Myc tag, glutathione S-transferase and FLAG tag, have been introduced for recombinant protein production. The fragment crystallizable (Fc) domain of the IgG1 antibody is one of the useful affinity tags that can facilitate detection, purification and localization of proteins and can improve the immunogenicity, modulatory effects, physicochemical and pharmaceutical properties of proteins. Fcγ recombinant forms a group of recombinant proteins called Fc-fusion proteins (FFPs). FFPs are widely used in drug discovery, drug delivery, vaccine design and experimental research on receptor–ligand interactions. These fusion proteins have become successful alternatives to monoclonal antibodies for drug developments. In this review, the physicochemical, biochemical, immunological, pharmaceutical and therapeutic properties of recombinant FFPs were discussed as a new generation of bioengineering strategies.     

Foreword: The structural biology of membrane proteins

Membrane protein-protein interactions are important for regulation, targeting, and activity of proteins in membranes but are difficult to detect and analyse. This review covers current approaches to studying membrane protein interactions. In addition to standard biochemical and genetic techniques, the classic yeast nuclear two-hybrid system has been highly successful in identification and characterization of soluble protein-protein interactions. However, classic yeast two-hybrid assays do not work for membrane proteins because such yeast-based interactions must occur in the nucleus. Here, we highlight recent advances in yeast systems for the detection and characterization of eukaryote membrane protein-protein interactions. We discuss these implications for drug screening and discovery.     

Interactome Mapping: Using Protein Microarray Technology to Reconstruct Diverse Protein Networks

A major focus of systems biology is to characterize interactions between cellular components, in order to develop an accurate picture of the intricate networks within biological systems. Over the past decade, protein microarrays have greatly contributed to advances in proteomics and are becoming an important platform for systems biology. Protein microarrays are highly flexible, ranging from large-scale proteome microarrays to smaller customizable microarrays, making the technology amenable for detection of a broad spectrum of biochemical properties of proteins. In this article, we will focus on the numerous studies that have utilized protein microarrays to reconstruct biological networks including protein-DNA interactions, posttranslational protein modifications (PTMs), lectin-glycan recognition, pathogen-host interactions and hierarchical signaling cascades. The diversity in applications allows for integration of interaction data from numerous molecular classes and cellular states, providing insight into the structure of complex biological systems. We will also discuss emerging applications and future directions of protein microarray technology in the global frontier.     

Drug–drug plasma protein binding interactions of ivacaftor

Ivacaftor is a novel cystic fibrosis (CF) transmembrane conductance regulator (CFTR) potentiator that improves the pulmonary function for patients with CF bearing a G551D CFTR‐protein mutation. Because ivacaftor is highly bound (>97%) to plasma proteins, there is the strong possibility that co‐administered CF drugs may compete for the same plasma protein binding sites and impact the free drug concentration. This, in turn, could lead to drastic changes in the in vivo efficacy of ivacaftor and therapeutic outcomes. This biochemical study compares the binding affinity of ivacaftor and co‐administered CF drugs for human serum albumin (HSA) and α₁‐acid glycoprotein (AGP) using surface plasmon resonance and fluorimetric binding assays that measure the displacement of site‐selective probes. Because of their ability to strongly compete for the ivacaftor binding sites on HSA and AGP, drug–drug interactions between ivacaftor are to be expected with ducosate, montelukast, ibuprofen, dicloxacillin, omeprazole, and loratadine. The significance of these plasma protein drug–drug interactions is also interpreted in terms of molecular docking simulations. This in vitro study provides valuable insights into the plasma protein drug–drug interactions of ivacaftor with co‐administered CF drugs. The data may prove useful in future clinical trials for a staggered treatment that aims to maximize the effective free drug concentration and clinical efficacy of ivacaftor. Copyright © 2015 John Wiley & Sons, Ltd.     

An insight into major signaling pathways and protein–protein interaction networks involved in the pathogenesis of gestational diabetes mellitus

Gestational diabetes mellitus (GDM) is associated with the increase of glucose in the blood rather than being absorbed by the cells. A better understanding of the signaling pathways is necessary to understand the pathophysiology of GDM. This study provides details about a series of signaling pathways and protein–protein interactions involved in the pathogenesis of GDM and their evaluations in GDM development. Protein–protein interactions were found between proteins of several signaling pathways that suggest interlink between these signaling pathways. Protein–protein interactions were generated with high confidence interaction scores based on textmining, cooccurrence, coexpression, neighborhood, gene fusion, experiments, and databases. The dysregulation of signaling pathways may also contribute to the increased risk of complications associated with GDM in the mother and child. Further, studies on signaling pathways involved in the pathogenesis of GDM would help in the development of an effective intervention to prevent GDM along with the identification of key targets for effective therapies in the future.     

Photoaffinity labeling combined with mass spectrometric approaches as a tool for structural proteomics

Protein chemistry, such as crosslinking and photoaffinity labeling, in combination with modern mass spectrometric techniques, can provide information regarding protein–protein interactions beyond that normally obtained from protein identification and characterization studies. While protein crosslinking can make tertiary and quaternary protein structure information available, photoaffinity labeling can be used to obtain structural data about ligand–protein interaction sites, such as oligonucleotide–protein, drug–protein and protein–protein interaction. In this article, we describe mass spectrometry-based photoaffinity labeling methodologies currently used and discuss their current limitations. We also discuss their potential as a common approach to structural proteomics for providing 3D information regarding the binding region, which ultimately will be used for molecular modeling and structure-based drug design.     

Structural analysis of protein–protein interactions in type I polyketide synthases

Abstract

Polyketide synthases (PKSs) are responsible for synthesizing a myriad of natural products with agricultural, medicinal relevance. The PKSs consist of multiple functional domains of which each can catalyze a specified chemical reaction leading to the synthesis of polyketides. Biochemical studies showed that protein–substrate and protein–protein interactions play crucial roles in these complex regio-/stereo-selective biochemical processes. Recent developments on X-ray crystallography and protein NMR techniques have allowed us to understand the biosynthetic mechanism of these enzymes from their structures. These structural studies have facilitated the elucidation of the sequence–function relationship of PKSs and will ultimately contribute to the prediction of product structure. This review will focus on the current knowledge of type I PKS structures and the protein–protein interactions in this system.     

Tetra-substituted imidazoles as a new class of inhibitors of the p53–MDM2 interaction

Capitalizing on crystal structure information obtained from a previous effort in the search for non peptide inhibitors of the p53–MDM2 interaction, we have discovered another new class of compounds able to disrupt this protein–protein interaction, an important target in oncology drug research. The new inhibitors, based on a tetra-substituted imidazole scaffold, have been optimized to low nanomolar potency in a biochemical assay following a structure-guided approach. An appropriate strategy has allowed us to translate the high biochemical potency in significant anti-proliferative activity on a p53-dependent MDM2 amplified cell line.     

A reliability measure of protein–protein interactions and a reliability measure-based search engine

Many methods developed for estimating the reliability of protein–protein interactions are based on the topology of protein–protein interaction networks. This paper describes a new reliability measure for protein–protein interactions, which does not rely on the topology of protein interaction networks, but expresses biological information on functional roles, sub-cellular localisations and protein classes as a scoring schema. The new measure is useful for filtering many spurious interactions, as well as for estimating the reliability of protein interaction data. In particular, the reliability measure can be used to search protein–protein interactions with the desired reliability in databases. The reliability-based search engine is available at http://yeast.hpid.org. We believe this is the first search engine for interacting proteins, which is made available to public. The search engine and the reliability measure of protein interactions should provide useful information for determining proteins to focus on.     

Protein complementation assays: Approaches for the in vivo analysis of protein interactions

The in vivo identification and characterization of protein-protein interactions (PPIs) are essential to understand cellular events in living organisms. In this review, we focus on protein complementation assays (PCAs) that have been developed to detect in vivo protein interactions as well as their modulation or spatial and temporal changes. The uses of PCAs are increasing, spanning different areas such as the study of biochemical networks, screening for protein inhibitors and determination of drug effects. Emphasis is given to approaches that rely on signals of spectroscopic nature (i.e. fluorescence or luminescence), the ones that are more directly related to bioimaging.     

How do oncoprotein mutations rewire protein–protein interaction networks?

The acquisition of mutations that activate oncogenes or inactivate tumor suppressors is a primary feature of most cancers. Mutations that directly alter protein sequence and structure drive the development of tumors through aberrant expression and modification of proteins, in many cases directly impacting components of signal transduction pathways and cellular architecture. Cancer-associated mutations may have direct or indirect effects on proteins and their interactions and while the effects of mutations on signaling pathways have been widely studied, how mutations alter underlying protein–protein interaction networks is much less well understood. Systematic mapping of oncoprotein protein interactions using proteomics techniques as well as computational network analyses is revealing how oncoprotein mutations perturb protein–protein interaction networks and drive the cancer phenotype.     

Traceless and Site-specific Attachment of Proteins onto Solid Supports

Many experimental approaches in biology and biophysics, as well as applications in diagnosis and drug discovery, require proteins to be immobilized on solid supports. Protein microarrays, for example, provide a high-throughput format to study biomolecular interactions. The technique employed for protein immobilization is a key to the success of these applications. Recent biochemical developments are allowing, for the first time, the selective and traceless immobilization of proteins generated by cell-free systems without the need for purification and/or reconcentration prior to the immobilization step.     

Improved understanding of pathogenesis from protein interactions in Mycobacterium tuberculosis

Comprehensive mapping and analysis of protein–protein interactions provide not only systematic approaches for dissecting the infection and survival mechanisms of pathogens but also clues for discovering new antibacterial drug targets. Protein interaction data on Mycobacterium tuberculosis have rapidly accumulated over the past several years. This review summarizes the current progress of protein interaction studies on M. tuberculosis, the causative agent of tuberculosis. These efforts improve our knowledge on the stress response, signaling regulation, protein secretion and drug resistance of the bacteria. M. tuberculosis–host protein interaction studies, although still limited, have recently opened a new door for investigating the pathogenesis of the bacteria. Finally, this review discusses the importance of protein interaction data on identifying and screening new anti-tuberculosis targets and drugs, respectively.     

Computational and experimental investigation of DNA repair protein photolyase interactions with low molecular weight drugs

This paper reports the previously unknown interactions between eight low molecular weight commercially available drugs (130–800 Da) and DNA repair protein photolyase using computational docking simulations and surface plasmon resonance (SPR) experiments. Theoretical dissociation constants, K_d, obtained from molecular docking simulations were compared with the values found from SPR experiments. Among the eight drugs analyzed, computational and experimental values showed similar binding affinities between selected drug and protein pairs. We found no significant differences in binding interactions between pure and commercial forms of the drug lornoxicam and DNA photolyase. Among the eight drugs studied, prednisone, desloratadine, and azelastine exhibited the highest binding affinity (K_d = 1.65, 2.05, and 8.47 μM, respectively) toward DNA photolyase. Results obtained in this study are promising for use in the prediction of unknown interactions of common drugs with specific proteins such as human clock protein cryptochrome. Copyright © 2013 John Wiley & Sons, Ltd.     

Isolation of a peptide containing d-amino acid residues that inhibits the α-helix-mediated p53–MDM2 interaction from a one-bead one-compound library

α-Helix-mediated protein–protein interactions (PPIs) are important targets in biological research and drug development. Peptides containing d-amino acid residues are attractive molecules for inhibiting α-helix-mediated PPIs because of their wide surface area and high protease resistance. In this study, a peptide library was constructed using a one-bead one-compound format designed to isolate left-handed α-helical peptides, which are promising molecules as inhibitors of α-helix-mediated PPIs. Screening of the library against an α-helix-mediated PPI between MDM2 and p53 yielded an inhibitor of the PPI. Design and screening of the library, and biochemical and spectroscopic studies of the discovered peptide are presented.     

ChikvInt: a Chikungunya virus–host protein–protein interaction database

Chikungunya is a fast-mutating virus causing Chikungunya virus disease (ChikvD) with a significant load of disability-adjusted life years (DALY) around the world. The outbreak of this virus is significantly higher in the tropical countries. Several experiments have identified crucial viral–host protein–protein interactions (PPIs) between Chikungunya Virus (Chikv) and the human host. However, no standard database that catalogs this PPI information exists. Here we develop a Chikv-Human PPI database, ChikvInt, to facilitate understanding ChikvD disease pathogenesis and the progress of vaccine studies. ChikvInt consists of 109 interactions and is available at www.chikvint.com .