Protein Binding Profiles Research Articles

Cremophor EL Alters the Plasma Protein Binding and Pharmacokinetic Profile of Valspodar in Rats.

Cremophor EL is a nonionic surfactant widely used in pharmaceutical formulations. Nonetheless, there are several reports on the influence of this excipient on the protein binding, pharmacokinetics, and pharmacodynamics of drugs. Valspodar is an investigational non-immunosuppressive derivative of cyclosporine A, used in clinical trials for treatment of multidrug resistant tumors. The formulation of valspodar (Amdray®) contains cremophor EL and ethanol as solubilizing agents. The main aim of the current study was to assess the plasma protein binding (in vitro) and the pharmacokinetic profile of valspodar in the cremophor EL-based formulation in comparison to a cremophor EL-free formulation following intravenous (i. v.) administration to rats. Valspodar dissolved in PEG 400/ethanol (diluted in Dextrose 5%) was used as the cremophor EL-free formulation. The in vitro plasma unbound fraction (f u) of valspodar in the cremophor EL formulation was 2.3-fold higher than the PEG 400/ethanol formulation. Following a single i. v. dose of 5 mg/kg, valspodar in the cremophor EL-based formulation had around 50% lower plasma AUC compared to the PEG 400/ethanol formulation. Moreover, the cremophor EL formulation had significantly higher volume of distribution and clearance in comparison to the PEG 400-based formulation. The results highlight the significance of excipient-drug interaction that should not be overlooked during the early stages of drug development.

Integrative analysis identifies co-dependent gene expression regulation of BRG1 and CHD7 at distal regulatory sites in embryonic stem cells.

DNA binding proteins such as chromatin remodellers, transcription factors (TFs), histone modifiers and co-factors often bind cooperatively to activate or repress their target genes in a cell type-specific manner. Nonetheless, the precise role of cooperative binding in defining cell-type identity is still largely uncharacterized. Here, we collected and analyzed 214 public datasets representing chromatin immunoprecipitation followed by sequencing (ChIP-Seq) of 104 DNA binding proteins in embryonic stem cell (ESC) lines. We classified their binding sites into those proximal to gene promoters and those in distal regions, and developed a web resource called Proximal And Distal (PAD) clustering to identify their co-localization at these respective regions. Using this extensive dataset, we discovered an extensive co-localization of BRG1 and CHD7 at distal but not proximal regions. The comparison of co-localization sites to those bound by either BRG1 or CHD7 alone showed an enrichment of ESC master TFs binding and active chromatin architecture at co-localization sites. Most notably, our analysis reveals the co-dependency of BRG1 and CHD7 at distal regions on regulating expression of their common target genes in ESC. This work sheds light on cooperative binding of TF binding proteins in regulating gene expression in ESC, and demonstrates the utility of integrative analysis of a manually curated compendium of genome-wide protein binding profiles in our online resource PAD. PAD is freely available at http://pad.victorchang.edu.au/ and its source code is available via an open source GPL 3.0 license at https://github.com/VCCRI/PAD/. pengyi.yang@sydney.edu.au or j.ho@victorchang.edu.au. Supplementary data are available at Bioinformatics online.

Plasma Protein Binding Structure-Activity Relationships Related to the N-Terminus of Daptomycin.

Daptomycin is a lipopeptide antibiotic that is highly bound to plasma proteins. To date, the plasma components and structure-activity relationships responsible for the plasma protein binding profile of daptomycin remain uncharacterized. In the present study we have employed a surface plasmon resonance assay together with molecular docking techniques to investigate the plasma protein binding structure-activity relationships related to the N-terminal fatty acyl of daptomycin. Three compounds were investigated: (1) native daptomycin, which displays an N-terminal n-decanoyl fatty acid side chain, and two analogues with modifications to the N-terminal fatty acyl chain; (2) des-acyl daptomycin; and (3) acetyl-daptomycin. The surface plasmon resonance (SPR) data showed that the binding profile of native daptomycin was in the rank order human serum albumin (HSA) ≫ α-1-antitrypsin > low-density lipoprotein ≥ hemoglobin > sex hormone binding globulin > α-1-acid-glycoprotein (AGP) > hemopexin > fibrinogen > α-2-macroglobulin > β2-microglobulin > high-density lipoprotein > fibronectin > haptoglobulin > transferrin > immunoglobulin G. Notably, binding to fatty acid free HSA was greater than binding to nondelipidated HSA. SPR and ultrafiltration studies also indicated that physiological concentrations of calcium increase binding of daptomycin and acetyl-daptomycin to HSA and AGP. A molecular model of the daptomycin-human serum albumin A complex is presented that illustrates the pivotal role of the N-terminal fatty acyl chain of daptomycin for binding to drug site 1 of HSA. In proof-of-concept, the capacity of physiological cocktails of the identified plasma proteins to inhibit the antibacterial activity of daptomycin was assessed with in vitro microbiological assays. We show that HSA, α-1-antitrypsin, low-density lipoprotein, sex hormone binding globulin, α-1-acid-glycoprotein, and hemopexin are responsible for the majority of the sequestering activity in human plasma. The findings are relevant to medicinal chemistry programs focused on the development of next-generation daptomycin lipopeptides. Tailored modifications to the N-terminal fatty acyl domain of the daptomycin molecule should yield novel daptomycin lipopeptides with more ideal plasma protein binding profiles to increase the levels of active (free) drug in plasma and improved in vivo activity.

The Plasma Protein Binding Proteome of Ertapenem: A Novel Compound-Centric Proteomic Approach for Elucidating Drug–Plasma Protein Binding Interactions

Ertapenem is an important first-line carbapenem antibiotic used for the treatment of aerobic Gram-negative bacterial infections. It is the only marketed carbapenem that is highly bound to plasma proteins and displays a concentration-dependent and saturable plasma protein binding profile. To date, the plasma components responsible for sequestering ertapenems antibacterial activity remain uncharacterized. In the present study, we have employed an orthogonal, multiplatform approach, including novel compound-centric displacement proteomics and surface plasmon resonance to characterize the plasma protein binding proteome of ertapenem. In proof-of-concept, the capacity of physiological cocktails of the identified plasma proteins to inhibit the antibacterial activity of ertapenem was assessed with in vitro microbiological assays. We show that fibrinogen, complement C4, haptoglobulin, α-1-antitrypsin, fibronectin, transferrin, immunoglobulin G, hemopexin, and humans serum albumin are responsible for the majority of the sequestering activity in plasma. No binding was observed to α-1-acid-glycoprotein. The findings of this study have broad reaching implications for antibiotic drug design and for dose tailoring to suit the plasma protein levels of individual patients in order to maximize the clinical efficacy of important first-line antibiotics such as ertapenem.

The zinc‐metallothionein redox system in human retina and RPE

PurposeThe retina contains the highest concentration of zinc in the human eye and it is primarily associated with the photoreceptors and the RPE. Metallothioneins (MTs) are the main cytosolic zinc‐ion‐binding proteins, and their main roles include neuroprotection and maintenance of cellular zinc homeostasis. Zinc is the main regulator of MTs, and there is a tight control in the number of atoms of zinc bound to the MT proteins (stoichiometry), which could be related with their antioxidant and neuroprotective functions. The main purpose of this work is to study the Zn‐MT system in the RPE and retina of the human eye.MethodsWe first determined the total content of Zn by elemental mass spectrometry (i.e., ICP‐MS), in RPE and retina from post mortem human donors, and compared its quantitative distribution by bio‐imaging (i.e, laser ablation‐ICP‐MS), on cryogenic eye sections. Secondly, we carried out the quantitative speciation of zinc in the water‐soluble protein fractions of RPE and neural retina, to study its protein binding profile. Finally we studied the effects of metals (i.e., ZnSO4), inflammatory cytokines (i.e., IL1a) and glucocorticoids (i.e., dexamethasone), by ICP‐MS, in an in vitro cellular model of human RPE cells (HRPEsv).ResultsWe found preferential quantitative distribution of zinc in the RPE, followed by the retina in lesser levels. Zinc is mainly associated to high and low molecular mass proteins in both RPE and retina. Exogenous zinc, interleukin and dexamethasone increased MT proteins synthesis and induced a stoichiometric change in MT proteins in HRPEsv cells.ConclusionsThe stoichiometric transition on Zn‐MT proteins in HRPEsv and its potential implication against oxidative stress processes will be discussed.

Eravacycline Pharmacokinetics and Challenges in Defining Humanized Exposure In Vivo.

We assessed the pharmacokinetic profile of eravacycline, a novel antibiotic of the tetracycline class, and determined the dose in an immunocompetent murine thigh infection model that would provide free-drug exposure similar to that observed in humans after the administration of 1 mg/kg intravenously (i.v.) every 12 h (q12h). Eravacycline demonstrated a nonlinear protein-binding profile. The 2.5-mg/kg i.v. q12h dose in mice resulted in an area under the concentration-time curve for the free, unbound fraction of the drug of 1.64 mg · h/liter, which closely resembles the human exposure level.

Pharmacokinetics, Tissue Distribution and Protein Binding Studies of Chrysocauloflavone I in Rats.

Chrysocauloflavone I, an unfrequent biflavonoid, was purified from Selaginella doederleinii in this study. It showed cytotoxic effects on three human cancer cells, NCI-H1975, A549, and HepG-2, in vitro. In silico assessment of the physicochemical properties was performed for predicting the permeability and intestinal absorption of the tested compound. Subsequently, a rapid, sensitive, and specific high-performance liquid chromatography method was developed for determination of the compound in different biological samples to ascertain the pharmacokinetics, tissue distribution, and protein binding profiles of this active ingredient in rats. After intravenous dosing of chrysocauloflavone I at different levels (10 and 20 mg/kg), the elimination half-life was approximately 85 min, and the AUC0-∞ increased with the dose from 148.52 mg/L × min for 10 mg/kg to 399.01 mg/L × min for 20 mg/kg. After single intravenous dosing (20 mg/kg), chrysocauloflavone I was detected in all tissues studied with higher levels in the heart, blood, and lungs. The results of equilibrium dialysis indicated a very high protein binding degree (over 97%) for chrysocauloflavone I. After intragastric administration of 100 mg/kg chrysocauloflavone I to rats, no parent drug was detected in the rat plasma. This is the first report of the favorable bioactivities, plasma pharmacokinetics, tissue distribution, and protein binding profiles of the rare biflavone chrysocauloflavone I.

The AhR and NF-κB/Rel Proteins Mediate the Inhibitory Effect of 2,3,7,8-Tetrachlorodibenzo-p-Dioxin on the 3' Immunoglobulin Heavy Chain Regulatory Region.

Transcriptional regulation of the murine immunoglobulin (Ig) heavy chain gene (Igh) involves several regulatory elements including the 3'Igh regulatory region (3'IghRR), which is composed of at least 4 enhancers (hs3A, hs1.2, hs3B, and hs4). The hs1.2 and hs4 enhancers exhibit the greatest transcriptional activity and contain binding sites for several transcription factors including nuclear factor kappaB/Rel (NF-κB/Rel) proteins and the aryl hydrocarbon receptor (AhR). Interestingly, the environmental immunosuppressant 2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD), which potently inhibits antibody secretion, also profoundly inhibits 3'IghRR and hs1.2 enhancer activation induced by the B-lymphocyte activator lipopolysaccharide (LPS), but enhances LPS-induced activation of the hs4 enhancer. Within the hs1.2 and hs4 enhancers, the AhR binding site is in close proximity or overlaps an NF-κB/Rel binding site suggesting a potential reciprocal modulation of the 3'IghRR by AhR and NF-κB/Rel. The objective of the current study was to evaluate the role of NF-κB/Rel and the AhR on the 3'IghRR and its enhancers using the AhR ligand TCDD, the AhR antagonist CH223191, and toll-like receptor agonists LPS, Resiquimod (R848), or cytosine-phosphate-guanine-oligodeoxynucleotides (CpG). Utilizing the CH12.LX B-lymphocyte cell line and variants expressing either a 3'IghRR-regulated transgene reporter or an inducible IκBα (inhibitor kappa B-alpha protein) superrepressor (IκBαAA), we demonstrate an AhR- and NF-κB/Rel-dependent modulation of 3'IghRR and hs4 activity. Additionally, in mouse splenocytes or CH12.LX cells, binding within the hs1.2 and hs4 enhancer of the AhR and the NF-κB/Rel proteins RelA and RelB was differentially altered by the cotreatment of LPS and TCDD. These results suggest that the AhR and NF-κB/Rel protein binding profile within the 3'IghRR mediates the inhibitory effects of TCDD on Ig expression and therefore antibody levels.

Pharmacokinetic and protein binding profile of peptidomimetic DPP-4 inhibitor - Teneligliptin in rats using liquid chromatography-tandem mass spectrometry.

The aim of the present study is to explore pharmacokinetic and protein binding characteristics of a novel dipeptidylpeptidase-4 (DPP-4) inhibitor, teneligliptin in rats using an ultra high performance liquid chromatography-quadrupole time-of-flight mass spectrometry (UHPLC-QTOF-MS). It is required for demonstrating the high protein binding nature of teneligliptin which can be extended for drug repositioning to brain disorders. Sample preparation was accomplished through a protein precipitation procedure using acetonitrile. Separation of teneligliptin and sitagliptin (IS) from endogenous components with high selectivity and sensitivity (0.5ng/mL) was achieved within 4min using Poroshell 120 EC-C18 column (100×3.0mm, 2.7μ). A gradient mobile phase consisting of 10mM ammonium formate and acetonitrile was applied at a flow rate of 0.45mL/min. Detection of target ions [M+H](+) at m/z 427.2274 for teneligliptin and m/z 408.1258 for IS was performed in selective ion mode using positive ion electrospray ionization high resolution accurate mass spectrometry. The linearity of the method was found to be in the range of 0.5-1000ng/mL. The matrix effect was 88.7-94.5% for teneligliptin. Plasma samples were found to stable under different storage conditions. It was successfully applied to pharmacokinetic and plasma protein binding study of drug in rats. Results showed linear dose proportionality of pharmacokinetics at 0.1 and 1mg/kg and relatively high protein binding of teneligliptin (85.46 ± 0.24 %) compared with other DPP-4 inhibitors.

Human plasma protein adsorption onto alumina nanoparticles relevant to orthopedic wear.

Wear of ceramic orthopedic devices generates nanoparticles in vivo that may present a different biological character from the monolithic ceramic from which they are formed. The current work investigated protein adsorption from human plasma on alumina nanoparticles and monolithic samples representative of both wear particles and the ceramic components as implanted. A physicochemical characterization of the particles and their dispersion state was carried out, and the protein adsorption profiles were analyzed using 1D SDS-PAGE and mass spectrometry. Significant differences in protein-binding profiles were identified where the nanoparticles selectively bound known transporter proteins rather than the more highly abundant serum proteins that were observed on the monoliths. Proteins associated with opsonization of particles were seen to be present in the protein corona of the nanoparticles, which raises questions regarding the role of wear particles in periprosthetic tissue inflammation and aseptic loosening.

Population pharmacokinetics of phenytoin in critically ill children

The objective was to study the population pharmacokinetics of bound and unbound phenytoin in critically ill children, including influences on the protein binding profile. A population pharmacokinetic approach was used to analyze paired protein-unbound and total phenytoin plasma concentrations (n = 146 each) from 32 critically ill children (0.08-17 years of age) who were admitted to a pediatric hospital, primarily intensive care unit. The pharmacokinetics of unbound and bound phenytoin and the influence of possible influential covariates were modeled and evaluated using visual predictive checks and bootstrapping. The pharmacokinetics of protein-unbound phenytoin was described satisfactorily by a 1-compartment model with first-order absorption in conjunction with a linear partition coefficient parameter to describe the binding of phenytoin to albumin. The partitioning coefficient describing protein binding and distribution to bound phenytoin was estimated to be 8.22. Nonlinear elimination of unbound phenytoin was not supported in this patient group. Weight, allometrically scaled for clearance and volume of distribution for the unbound and bound compartments, and albumin concentration significantly influenced the partition coefficient for protein binding of phenytoin. The population model can be applied to estimate the fraction of unbound phenytoin in critically ill children given an individual's albumin concentration.

Large-scale integration of small molecule-induced genome-wide transcriptional responses, Kinome-wide binding affinities and cell-growth inhibition profiles reveal global trends characterizing systems-level drug action.

The Library of Integrated Network-based Cellular Signatures (LINCS) project is a large-scale coordinated effort to build a comprehensive systems biology reference resource. The goals of the program include the generation of a very large multidimensional data matrix and informatics and computational tools to integrate, analyze, and make the data readily accessible. LINCS data include genome-wide transcriptional signatures, biochemical protein binding profiles, cellular phenotypic response profiles and various other datasets for a wide range of cell model systems and molecular and genetic perturbations. Here we present a partial survey of this data facilitated by data standards and in particular a robust compound standardization workflow; we integrated several types of LINCS signatures and analyzed the results with a focus on mechanism of action (MoA) and chemical compounds. We illustrate how kinase targets can be related to disease models and relevant drugs. We identified some fundamental trends that appear to link Kinome binding profiles and transcriptional signatures to chemical information and biochemical binding profiles to transcriptional responses independent of chemical similarity. To fill gaps in the datasets we developed and applied predictive models. The results can be interpreted at the systems level as demonstrated based on a large number of signaling pathways. We can identify clear global relationships, suggesting robustness of cellular responses to chemical perturbation. Overall, the results suggest that chemical similarity is a useful measure at the systems level, which would support phenotypic drug optimization efforts. With this study we demonstrate the potential of such integrated analysis approaches and suggest prioritizing further experiments to fill the gaps in the current data.

ChIPseek, a web-based analysis tool for ChIP data.

BackgroundChromatin is a dynamic but highly regulated structure. DNA-binding proteins such as transcription factors, epigenetic and chromatin modifiers are responsible for regulating specific gene expression pattern and may result in different phenotypes. To reveal the identity of the proteins associated with the specific region on DNA, chromatin immunoprecipitation (ChIP) is the most widely used technique. ChIP assay followed by next generation sequencing (ChIP-seq) or microarray (ChIP-chip) is often used to study patterns of protein-binding profiles in different cell types and in cancer samples on a genome-wide scale. However, only a limited number of bioinformatics tools are available for ChIP datasets analysis.ResultsWe present ChIPseek, a web-based tool for ChIP data analysis providing summary statistics in graphs and offering several commonly demanded analyses. ChIPseek can provide statistical summary of the dataset including histogram of peak length distribution, histogram of distances to the nearest transcription start site (TSS), and pie chart (or bar chart) of genomic locations for users to have a comprehensive view on the dataset for further analysis. For examining the potential functions of peaks, ChIPseek provides peak annotation, visualization of peak genomic location, motif identification, sequence extraction, and comparison between datasets. Beyond that, ChIPseek also offers users the flexibility to filter peaks and re-analyze the filtered subset of peaks. ChIPseek supports 20 different genome assemblies for 12 model organisms including human, mouse, rat, worm, fly, frog, zebrafish, chicken, yeast, fission yeast, Arabidopsis, and rice. We use demo datasets to demonstrate the usage and intuitive user interface of ChIPseek.ConclusionsChIPseek provides a user-friendly interface for biologists to analyze large-scale ChIP data without requiring any programing skills. All the results and figures produced by ChIPseek can be downloaded for further analysis. The analysis tools built into ChIPseek, especially the ones for selecting and examine a subset of peaks from ChIP data, provides invaluable helps for exploring the high through-put data from either ChIP-seq or ChIP-chip. ChIPseek is freely available at http://chipseek.cgu.edu.tw.

Can sodium/hydrogen exchange inhibitors be repositioned for treating attention deficit hyperactivity disorder? An in silico approach

Medications for attention deficit hyperactivity disorder (ADHD) are only partially effective. Ideally, new treatment targets would derive from a known pathophysiology. Such data are not available for ADHD. We combine evidence for new etiologic pathways with bioinformatics data to assess the possibility that existing drugs might be repositioning for treating ADHD. We use this approach to determine if prior data implicating the sodium/hydrogen exchanger 9 gene (SLC9A9) in ADHD implicate sodium/hydrogen exchange (NHE) inhibitors as potential treatments. We assessed the potential for repositioning by assessing the similarity of drug-protein binding profiles between NHE inhibitors and drugs known to treat ADHD using the Drug Repositioning and Adverse Reaction via Chemical-Protein Interactome server. NHE9 shows a high degree of amino acid similarity between NHE inhibitor sensitive NHEs in the region of the NHE inhibitor recognition site defined for NHE1. We found high correlations in drug-protein binding profiles among most ADHD drugs. The drug-protein binding profiles of some NHE inhibitors were highly correlated with ADHD drugs whereas the profiles for a control set of nonsteroidal anti-inflammatory drugs (NSAIDs) were not. Further experimental work should evaluate if NHE inhibitors are suitable for treating ADHD.

Toward an Efficient Approach to Identify Molecular Scaffolds Possessing Selective or Promiscuous Compounds

The concept of a recurrent scaffold present in a series of structures is common in medicinal drug discovery. We present a scaffold analysis of compounds screened across 100 sequence-unrelated proteins to identify scaffolds that drive promiscuity or selectivity. Selectivity and promiscuity play a major role in traditional and poly-pharmacological drug design considerations. The collection employed here is the first publicly available data set containing the complete screening profiles of more than 15 000 compounds from different sources. In addition, no scaffold analysis of this data set has been reported. The protocol described here employs the Molecular Equivalence Index tool to facilitate the selection of Bemis-Murcko frameworks in the data set, which contain at least five compounds and Scaffold Hunter to generate a hierarchical tree of scaffolds. The annotation of the scaffold tree with protein-binding profile data enabled the successful identification of mostly highly specific compounds, due to data set constraints. We also applied this approach to a public set of 1497 small molecules screened non-uniformly across a panel of 172 protein kinases. The approach is general and can be applied to any other data sets and activity readout.

DROMPA: easy‐to‐handle peak calling and visualization software for the computational analysis and validation of ChIP‐seq data

Chromatin immunoprecipitation with high-throughput sequencing (ChIP-seq) can identify genomic regions that bind proteins involved in various chromosomal functions. Although the development of next-generation sequencers offers the technology needed to identify these protein-binding sites, the analysis can be computationally challenging because sequencing data sometimes consist of >100 million reads/sample. Herein, we describe a cost-effective and time-efficient protocol that is generally applicable to ChIP-seq analysis; this protocol uses a novel peak-calling program termed DROMPA to identify peaks and an additional program, parse2wig, to preprocess read-map files. This two-step procedure drastically reduces computational time and memory requirements compared with other programs. DROMPA enables the identification of protein localization sites in repetitive sequences and efficiently identifies both broad and sharp protein localization peaks. Specifically, DROMPA outputs a protein-binding profile map in pdf or png format, which can be easily manipulated by users who have a limited background in bioinformatics.

Gene silencing and large-scale domain structure of the E. coli genome

The H-NS chromosome-organizing protein in E. coli can stabilize genomic DNA loops, and form oligomeric structures connected to repression of gene expression. Motivated by the link between chromosome organization, protein binding and gene expression, we analyzed publicly available genomic data sets of various origins, from genome-wide protein binding profiles to evolutionary information, exploring the connections between chromosomal organization, gene-silencing, pseudo-gene localization and horizontal gene transfer. We report the existence of transcriptionally silent contiguous areas corresponding to large regions of H-NS protein binding along the genome, their position indicates a possible relationship with the known large-scale features of chromosome organization.

The restricted binding repertoire of Bcl-B leaves Bim as the universal BH3-only prosurvival Bcl-2 protein antagonist

B-cell lymphoma-2 (Bcl-2) proteins mediate intrinsic-, or mitochondrial-, initiated apoptosis. We have investigated the structure and function of the least characterized Bcl-2 family member, Bcl-B, solving the crystal structure of a Bcl-B:Bim complex to 1.9 Å resolution. Bcl-B is distinguished from other Bcl-2 family members through an insertion of an unstructured loop between helices α5 and α6. Probing Bcl-B interactions with Bcl-2 homology (BH)3 motifs using a combination of biophysical- and cell-based assays revealed a unique BH3-only protein binding profile. Bcl-B has high-affinity interactions with Bim and Bik only. Our results not only delineate the mode of action of Bcl-B but also complete our understanding of the specific interactions between BH3-only proteins and their prosurvival Bcl-2 counterparts. Notably, we conclude that Bim is the universal prosurvival antagonist as no other BH3-only protein binds all six prosurvival proteins and that Mcl-1 and Bcl-xL form a distinct prosurvival dyad.

Relating drug–protein interaction network with drug side effects

Motivation: Identifying the emergence and underlying mechanisms of drug side effects is a challenging task in the drug development process. This underscores the importance of system–wide approaches for linking different scales of drug actions; namely drug-protein interactions (molecular scale) and side effects (phenotypic scale) toward side effect prediction for uncharacterized drugs.Results: We performed a large-scale analysis to extract correlated sets of targeted proteins and side effects, based on the co-occurrence of drugs in protein-binding profiles and side effect profiles, using sparse canonical correlation analysis. The analysis of 658 drugs with the two profiles for 1368 proteins and 1339 side effects led to the extraction of 80 correlated sets. Enrichment analyses using KEGG and Gene Ontology showed that most of the correlated sets were significantly enriched with proteins that are involved in the same biological pathways, even if their molecular functions are different. This allowed for a biologically relevant interpretation regarding the relationship between drug–targeted proteins and side effects. The extracted side effects can be regarded as possible phenotypic outcomes by drugs targeting the proteins that appear in the same correlated set. The proposed method is expected to be useful for predicting potential side effects of new drug candidate compounds based on their protein-binding profiles.Supplementary information: Datasets and all results are available at http://web.kuicr.kyoto-u.ac.jp/supp/smizutan/target-effect/.Availability: Software is available at the above supplementary website.Contact: yamanishi@bioreg.kyushu-u.ac.jp, or goto@kuicr.kyoto-u.ac.jp

Data Mining of Protein-Binding Profiling Data Identifies Structural Modifications that Distinguish Selective and Promiscuous Compounds

Activity profiling of compound collections across multiple targets is increasingly being used in probe and drug discovery. Herein, we discuss an approach to systematically analyzing the structure-activity relationships of a large screening profile data with emphasis on identifying structural changes that have a significant impact on the number of proteins to which a compound binds. As a case study, we analyzed a recently released public data set of more than 15 000 compounds screened across 100 sequence-unrelated proteins. The screened compounds have different origins and include natural products, synthetic molecules from academic groups, and commercial compounds. Similar synthetic structures from academic groups showed, overall, greater promiscuity differences than do natural products and commercial compounds. The method implemented in this work readily identified structural changes that differentiated highly specific from promiscuous compounds. This approach is general and can be applied to analyze any other large-scale protein-binding profile data.