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.     

Towards a mechanistic understanding of reciprocal drug–microbiome interactions

Broad‐spectrum antibiotics target multiple gram‐positive and gram‐negative bacteria, and can collaterally damage the gut microbiota. Yet, our knowledge of the extent of damage, the antibiotic activity spectra, and the resistance mechanisms of gut microbes is sparse. This limits our ability to mitigate microbiome‐facilitated spread of antibiotic resistance. In addition to antibiotics, non‐antibiotic drugs affect the human microbiome, as shown by metagenomics as well as in vitro studies. Microbiome–drug interactions are bidirectional, as microbes can also modulate drugs. Chemical modifications of antibiotics mostly function as antimicrobial resistance mechanisms, while metabolism of non‐antibiotics can also change the drugs’ pharmacodynamic, pharmacokinetic, and toxic properties. Recent studies have started to unravel the extensive capacity of gut microbes to metabolize drugs, the mechanisms, and the relevance of such events for drug treatment. These findings raise the question whether and to which degree these reciprocal drug–microbiome interactions will differ across individuals, and how to take them into account in drug discovery and precision medicine. This review describes recent developments in the field and discusses future study areas that will benefit from systems biology approaches to better understand the mechanistic role of the human gut microbiota in drug actions.     

A 96-well DNase I footprinting screen for drug–DNA interactions

The established protocol for DNase I footprinting has been modified to allow multiple parallel reactions to be rapidly performed in 96-well microtitre plates. By scrutinizing every aspect of the traditional method and making appropriate modifications it has been possible to considerably reduce the time, risk of sample loss and complexity of footprinting, whilst dramatically increasing the yield of data (30-fold). A semi-automated analysis system has also been developed to present footprinting data as an estimate of the binding affinity of each tested compound to any base pair in the assessed DNA sequence, giving an intuitive ‘one compound–one line’ scheme. Here, we demonstrate the screening capabilities of the 96-well assay and the subsequent data analysis using a series of six pyrrolobenzodiazepine-polypyrrole compounds and human Topoisomerase II alpha promoter DNA. The dramatic increase in throughput, quantified data and decreased handling time allow, for the first time, DNase I footprinting to be used as a screening tool to assess DNA-binding agents.     

Mitochondria–plasma membrane interactions and communication

Mitochondria are known as the powerhouses of eukaryotic cells; however, they perform many other functions besides oxidative phosphorylation, including Ca²⁺ homeostasis, lipid metabolism, antiviral response, and apoptosis. Although other hypotheses exist, mitochondria are generally thought as descendants of an α-proteobacteria that adapted to the intracellular environment within an Asgard archaebacteria, which have been studied for decades as an organelle subdued by the eukaryotic cell. Nevertheless, several early electron microscopy observations hinted that some mitochondria establish specific interactions with certain plasma membrane (PM) domains in mammalian cells. Furthermore, recent findings have documented the direct physical and functional interaction of mitochondria and the PM, the organization of distinct complexes, and their communication through vesicular means. In yeast, some molecular players mediating this interaction have been elucidated, but only a few works have studied this interaction in mammalian cells. In addition, mitochondria can be translocated among cells through tunneling nanotubes or by other mechanisms, and free, intact, functional mitochondria have been reported in the blood plasma. Together, these findings challenge the conception of mitochondria as organelles subdued by the eukaryotic cell. This review discusses the evidence of the mitochondria interaction with the PM that has been long disregarded despite its importance in cell function, pathogenesis, and evolution. It also proposes a scheme of mitochondria–PM interactions with the intent to promote research and knowledge of this emerging pathway that promises to shift the current paradigms of cell biology.     

UPA, a universal protein array system for quantitative detection of protein–protein, protein–DNA, protein–RNA and protein–ligand interactions

Protein–protein interactions have been widely used to study gene expression pathways and may be considered as a new approach to drug discovery. Here I report the development of a universal protein array (UPA) system that provides a sensitive, quantitative, multi-purpose, effective and easy technology to determine not only specific protein–protein interactions, but also specific interactions of proteins with DNA, RNA, ligands and other small chemicals. (i) Since purified proteins are used, the results can be easily interpreted. (ii) UPA can be used multiple times for different targets, making it economically affordable for most laboratories, hospitals and biotechnology companies. (iii) Unlike DNA chips or DNA microarrays, no additional instrumentation is required. (iv) Since the UPA uses active proteins (without denaturation and renaturation), it is more sensitive compared with most existing methods. (v) Because the UPA can analyze hundreds (even thousands on a protein microarray) of proteins in a single experiment, it is a very effective method to screen proteins as drug targets in cancer and other human diseases.     

Widespread autogenous mRNA–protein interactions detected by CLIP-seq

Autogenous interactions between mRNAs and the proteins they encode are implicated in cellular feedback-loop regulation, but their extent and mechanistic foundation are unclear. It was recently hypothesized that such interactions may be common, reflecting the role of intrinsic nucleobase–amino acid affinities in shaping the genetic code''s structure. Here we analyze a comprehensive set of CLIP-seq experiments involving multiple protocols and report on widespread autogenous interactions across different organisms. Specifically, 230 of 341 (67%) studied RNA-binding proteins (RBPs) interact with their own mRNAs, with a heavy enrichment among high-confidence hits and a preference for coding sequence binding. We account for different confounding variables, including physical (overexpression and proximity during translation), methodological (difference in CLIP protocols, peak callers and cell types) and statistical (treatment of null backgrounds). In particular, we demonstrate a high statistical significance of autogenous interactions by sampling null distributions of fixed-margin interaction matrices. Furthermore, we study the dependence of autogenous binding on the presence of RNA-binding motifs and structured domains in RBPs. Finally, we show that intrinsic nucleobase–amino acid affinities favor co-aligned binding between mRNA coding regions and the proteins they encode. Our results suggest a central role for autogenous interactions in RBP regulation and support the possibility of a fundamental connection between coding and binding.     

Cold spots are universal in protein–protein interactions

Proteins interact with each other through binding interfaces that differ greatly in size and physico‐chemical properties. Within the binding interface, a few residues called hot spots contribute the majority of the binding free energy and are hence irreplaceable. In contrast, cold spots are occupied by suboptimal amino acids, providing possibility for affinity enhancement through mutations. In this study, we identify cold spots due to cavities and unfavorable charge interactions in multiple protein–protein interactions (PPIs). For our cold spot analysis, we first use a small affinity database of PPIs with known structures and affinities and then expand our search to nearly 4000 homo‐ and heterodimers in the Protein Data Bank (PDB). We observe that cold spots due to cavities are present in nearly all PPIs unrelated to their binding affinity, while unfavorable charge interactions are relatively rare. We also find that most cold spots are located in the periphery of the binding interface, with high‐affinity complexes showing fewer centrally located colds spots than low‐affinity complexes. A larger number of cold spots is also found in non‐cognate interactions compared to their cognate counterparts. Furthermore, our analysis reveals that cold spots are more frequent in homo‐dimeric complexes compared to hetero‐complexes, likely due to symmetry constraints imposed on sequences of homodimers. Finally, we find that glycines, glutamates, and arginines are the most frequent amino acids appearing at cold spot positions. Our analysis emphasizes the importance of cold spot positions to protein evolution and facilitates protein engineering studies directed at enhancing binding affinity and specificity in a wide range of applications.     

Visualization and characterization of RNA–protein interactions in living cells

RNA–protein interactions are the structural and functional basis of significant numbers of RNA molecules. RNA–protein interaction assays though, still mainly depend on biochemical tests in vitro. Here, we establish a convenient and reliable RNA fluorescent three-hybrid (rF3H) method to detect/interrogate the interactions between RNAs and proteins in cells. A GFP tagged highly specific RNA trap is constructed to anchor the RNA of interest to an artificial or natural subcellular structure, and RNA–protein interactions can be detected and visualized by the enrichment of RNA binding proteins (RBPs) at these structures. Different RNA trapping systems are developed and detection of RNA–protein complexes at multiple subcellular structures are assayed. With this new toolset, interactions between proteins and mRNA or noncoding RNAs are characterized, including the interaction between a long noncoding RNA and an epigenetic modulator. Our approach provides a flexible and reliable method for the characterization of RNA–protein interactions in living cells.     

Recent developments of sequence-based prediction of protein–protein interactions

The identification of protein–protein interactions (PPIs) can lead to a better understanding of cellular functions and biological processes of proteins and contribute to the design of drugs to target disease-causing PPIs. In addition, targeting host–pathogen PPIs is useful for elucidating infection mechanisms. Although several experimental methods have been used to identify PPIs, these methods can yet to draw complete PPI networks. Hence, computational techniques are increasingly required for the prediction of potential PPIs, which have never been seen experimentally. Recent high-performance sequence-based methods have contributed to the construction of PPI networks and the elucidation of pathogenetic mechanisms in specific diseases. However, the usefulness of these methods depends on the quality and quantity of training data of PPIs. In this brief review, we introduce currently available PPI databases and recent sequence-based methods for predicting PPIs. Also, we discuss key issues in this field and present future perspectives of the sequence-based PPI predictions.     

SARS‐CoV‐2–host proteome interactions for antiviral drug discovery

Treatment options for COVID‐19, caused by SARS‐CoV‐2, remain limited. Understanding viral pathogenesis at the molecular level is critical to develop effective therapy. Some recent studies have explored SARS‐CoV‐2–host interactomes and provided great resources for understanding viral replication. However, host proteins that functionally associate with SARS‐CoV‐2 are localized in the corresponding subnetwork within the comprehensive human interactome. Therefore, constructing a downstream network including all potential viral receptors, host cell proteases, and cofactors is necessary and should be used as an additional criterion for the validation of critical host machineries used for viral processing. This study applied both affinity purification mass spectrometry (AP‐MS) and the complementary proximity‐based labeling MS method (BioID‐MS) on 29 viral ORFs and 18 host proteins with potential roles in viral replication to map the interactions relevant to viral processing. The analysis yields a list of 693 hub proteins sharing interactions with both viral baits and host baits and revealed their biological significance for SARS‐CoV‐2. Those hub proteins then served as a rational resource for drug repurposing via a virtual screening approach. The overall process resulted in the suggested repurposing of 59 compounds for 15 protein targets. Furthermore, antiviral effects of some candidate drugs were observed in vitro validation using image‐based drug screen with infectious SARS‐CoV‐2. In addition, our results suggest that the antiviral activity of methotrexate could be associated with its inhibitory effect on specific protein–protein interactions.     

Sulfotyrosine residues: Interaction specificity determinants for extracellular protein–protein interactions

Tyrosine sulfation, a post-translational modification, can determine and often enhance protein–protein interaction specificity. Sulfotyrosyl residues (sTyrs) are formed by the enzyme tyrosyl-protein sulfotransferase during protein maturation in the Golgi apparatus and most often occur singly or as a cluster within a six-residue span. With both negative charge and aromatic character, sTyr facilitates numerous atomic contacts as visualized in binding interface structural models, thus there is no discernible binding site consensus. Found exclusively in secreted proteins, in this review, we discuss the four broad sequence contexts in which sTyr has been observed: first, a solitary sTyr has been shown to be critical for diverse high-affinity interactions, such as between peptide hormones and their receptors, in both plants and animals. Second, sTyr clusters within structurally flexible anionic segments are essential for a variety of cellular processes, including coreceptor binding to the HIV-1 envelope spike protein during virus entry, chemokine interactions with receptors, and leukocyte rolling cell adhesion. Third, a subcategory of sTyr clusters is found in conserved acidic sequences termed hirudin-like motifs that enable proteins to interact with thrombin; consequently, many proven and potential therapeutic proteins derived from blood-consuming invertebrates depend on sTyrs for their activity. Finally, several proteins that interact with collagen or similar proteins contain one or more sTyrs within an acidic residue array. Refined methods to direct sTyr incorporation in peptides synthesized both in vitro and in vivo, together with continued advances in mass spectrometry and affinity detection, promise to accelerate discoveries of sTyr occurrence and function.     

High‐throughput metabolomics predicts drug–target relationships for eukaryotic proteins

Chemical probes are important tools for understanding biological systems. However, because of the huge combinatorial space of targets and potential compounds, traditional chemical screens cannot be applied systematically to find probes for all possible druggable targets. Here, we demonstrate a novel concept for overcoming this challenge by leveraging high‐throughput metabolomics and overexpression to predict drug–target interactions. The metabolome profiles of yeast treated with 1,280 compounds from a chemical library were collected and compared with those of inducible yeast membrane protein overexpression strains. By matching metabolome profiles, we predicted which small molecules targeted which signaling systems and recovered known interactions. Drug–target predictions were generated across the 86 genes studied, including for difficult to study membrane proteins. A subset of those predictions were tested and validated, including the novel targeting of GPR1 signaling by ibuprofen. These results demonstrate the feasibility of predicting drug–target relationships for eukaryotic proteins using high‐throughput metabolomics.     

By-passing selection: direct screening for antibody–antigen interactions using protein arrays

We have developed a system to identify highly specific antibody–antigen interactions by protein array screening. This removes the need for selection using animal immunisation or in vitro techniques such as phage or ribosome display. We screened an array of 27 648 human foetal brain proteins with 12 well-expressed antibody fragments that had not previously been exposed to any antigen. Four highly specific antibody–antigen pairs were identified, including three antibodies that bind proteins of unknown function. The target proteins were expressed at a very low copy number on the array, emphasising the unbiased nature of the screen. The specificity and sensitivity of binding demonstrates that this ‘naive’ screening approach could be applied to the high throughput isolation of specific antibodies against many different targets in the human proteome.     

Modulation of angiogenesis with siRNA inhibitors for novel therapeutics

Cancer and many other serious diseases are characterized by the uncontrolled growth of new blood vessels. Recently, RNA interference (RNAi) has reinvigorated the therapeutic prospects for inhibiting gene expression and promises many advantages over binding inhibitors, including high specificity, which is essential for targeted therapeutics. This article describes the latest developments using small-interfering RNA (siRNA) inhibitors to downregulate various angiogenic and tumor-associated factors, both in cell-culture assays and in animal disease models. The majority of research efforts are currently focused on understanding gene function, as well as proof-of-concept for siRNA-mediated anti-angiogenesis. The prospects for siRNA therapeutics, both advantages and looming hurdles, are evaluated.     

INDI: a computational framework for inferring drug interactions and their associated recommendations

Inferring drug–drug interactions (DDIs) is an essential step in drug development and drug administration. Most computational inference methods focus on modeling drug pharmacokinetics, aiming at interactions that result from a common metabolizing enzyme (CYP). Here, we introduce a novel prediction method, INDI (INferring Drug Interactions), allowing the inference of both pharmacokinetic, CYP‐related DDIs (along with their associated CYPs) and pharmacodynamic, non‐CYP associated ones. On cross validation, it obtains high specificity and sensitivity levels (AUC (area under the receiver‐operating characteristic curve)?0.93). In application to the FDA adverse event reporting system, 53% of the drug events could potentially be connected to known (41%) or predicted (12%) DDIs. Additionally, INDI predicts the severity level of each DDI upon co‐administration of the involved drugs, suggesting that severe interactions are abundant in the clinical practice. Examining regularly taken medications by hospitalized patients, 18% of the patients receive known or predicted severely interacting drugs and are hospitalized more frequently. Access to INDI and its predictions is provided via a web tool at http://www.cs.tau.ac.il/～bnet/software/INDI , facilitating the inference and exploration of drug interactions and providing important leads for physicians and pharmaceutical companies alike.     

Investigating the pharmacodynamic durability of GalNAc–siRNA conjugates

One hallmark of trivalent N-acetylgalactosamine (GalNAc)-conjugated siRNAs is the remarkable durability of silencing that can persist for months in preclinical species and humans. Here, we investigated the underlying biology supporting this extended duration of pharmacological activity. We found that siRNA accumulation and stability in acidic intracellular compartments is critical for long-term activity. We show that functional siRNA can be liberated from these compartments and loaded into newly generated Argonaute 2 protein complexes weeks after dosing, enabling continuous RNAi activity over time. Identical siRNAs delivered in lipid nanoparticles or as GalNAc conjugates were dose-adjusted to achieve similar knockdown, but only GalNAc–siRNAs supported an extended duration of activity, illustrating the importance of receptor-mediated siRNA trafficking in the process. Taken together, we provide several lines of evidence that acidic intracellular compartments serve as a long-term depot for GalNAc–siRNA conjugates and are the major contributor to the extended duration of activity observed in vivo.     

SLX4–XPF mediates DNA damage responses to replication stress induced by DNA–protein interactions

The DNA damage response (DDR) has a critical role in the maintenance of genomic integrity during chromosome replication. However, responses to replication stress evoked by tight DNA–protein complexes have not been fully elucidated. Here, we used bacterial LacI protein binding to lacO arrays to make site-specific replication fork barriers on the human chromosome. These barriers induced the accumulation of single-stranded DNA (ssDNA) and various DDR proteins at the lacO site. SLX4–XPF functioned as an upstream factor for the accumulation of DDR proteins, and consequently, ATR and FANCD2 were interdependently recruited. Moreover, LacI binding in S phase caused underreplication and abnormal mitotic segregation of the lacO arrays. Finally, we show that the SLX4–ATR axis represses the anaphase abnormality induced by LacI binding. Our results outline a long-term process by which human cells manage nucleoprotein obstacles ahead of the replication fork to prevent chromosomal instability.     

Acid-degradable cationic dextran particles for the delivery of siRNA therapeutics

We report a new acid-sensitive, biocompatible, and biodegradable microparticulate delivery system, spermine modified acetalated-dextran (Spermine-Ac-DEX), which can be used to efficiently encapsulate siRNA. These particles demonstrated efficient gene knockdown in HeLa-luc cells with minimal toxicity. This knockdown was comparable to that obtained using Lipofectamine, a commercially available transfection reagent generally limited to in vitro use due to its high toxicity.