Identifying biologically active compound classes using phenotypic screening data and sampling statistics

Scoring the activity of compounds in phenotypic high-throughput assays presents a unique challenge because of the limited resolution and inherent measurement error of these assays. Techniques that leverage the structural similarity of compounds within an assay can be used to improve the hit-recovery rate from screening data. A technique is presented that uses clustering and sampling statistics to predict likely compound activity by scoring entire structural classes. A set of phenotypic assays performed against a commercially available compound library was used as a test set. Using the class-scoring technique, the resultant activity prediction scores were more reproducible than individual assay measurements, and class scoring recovered known active compounds more efficiently than individual assay measurements because class scoring had fewer false positives. Known biologically active compounds were recovered 87% of the time using class scores, suggesting a low false-negative rate that compared well to individual assay measurements. In addition, many weak and potentially novel classes of active compounds, overlooked by individual assay measurements, were suggested.     

Rapid aryl hydrocarbon receptor based polymerase chain reaction screening assay for polychlorinated dibenzo-p-dioxins and furans in soil and sediment

A method for the estimation of polychlorinated dibenzo-p-dioxin and furan (PCCD/F) toxicity equivalent quotient (TEQ) of soil and sediment matrices is described. The method includes extraction, isolation of the PCDD/Fs from interfering compounds, such as polychlorinated biphenyls (PCBs) and polycyclic aromatic hydrocarbons (PAHs), and measurement of PCDD/F using the PROCEPT aryl hydrocarbon (AhR) receptor based polymerase chain reaction (PCR) assay. The values obtained using the PROCEPT assay correlate well with reference TEQ values generated from gas chromatography-high resolution mass spectrometry (GC-HRMS), with a linearity coefficient (R(2)) of 0.94. Applied in a screening mode at 50pg/g PCDD/F TEQ, the PROCEPT assay yielded five false positive results (2.6%) and no false negative results for 196 analyses of spiked soils and environmental samples obtained from US EPA Superfund sites.     

A Mix‐and‐Read Fluorescence Strategy for the Switch‐On Probing of Kinase Activity Based on an Aptameric‐Peptide/Graphene‐Oxide Platform

Protein kinase plays a vital role in regulating signal‐transduction pathways and its simple and quick detection is highly desirable because traditional kinase assays typically rely on a time‐consuming kinase‐phosphorylation process (ca. 1 h). Herein, we report a new and rapid fluorescence‐based sensing platform for probing the activity of protein kinase that is based on the super‐quenching capacity of graphene oxide (GO) nanosheets and specific recognition of the aptameric peptide (FITC‐IP₂₀). On the GO/peptide platform, the fluorescence quenching of FITC‐IP₂₀ that is adsorbed onto GO can be restored by selective binding of active protein kinase to the aptameric peptide, thereby resulting in the fast switch‐on detection of kinase activity (ca. 15 min). The feasibility of this method has been demonstrated by the sensitive measurement of the activity of cAMP‐dependent protein kinase (PKA), with a detection limit of 0.053 mU μL^?1. This assay technique was also successfully applied to the detection of kinase activation in cell lysate.     

Fluorescent detection of protein kinase based on zirconium ions-immobilized magnetic nanoparticles

We report here an affinity separation-based fluorometric method for monitoring the activity and inhibition of protein kinase. In this assay, when the fluorescein isothiocyanate (FITC) labeled substrate peptides (S-peptide) are phosphorylated by kinase, the product peptides (P-peptide) will be adsorbed and concentrated onto the surface of Zr⁴⁺-immobilized nitrilotriacetic acid-coated magnetic nanoparticles (Zr-NTA MNPs) through the chelation of Zr⁴⁺ and phosphate groups. After magnetic separation, the fluorescence intensity of the homogeneous solution changes dramatically. Hence the fluorescence response allows this MNPs-based method to easily probe kinase activity by a spectrometer. The feasibility of the method has been demonstrated by sensitive measurement of the activity of cAMP-dependent protein kinase (PKA) with a low detection limit (0.5 mU μL⁻¹). Moreover, the system is successfully applied to estimate the IC₅₀ value of PKA inhibitor H-89 and detect the Forskolin/3-isobutyl-1-methylxanthine (IBMX) stimulated activation of PKA in cell lysate. Additionally, Zr-NTA MNPs are reusable by stripping Zr⁴⁺ ions from NTA-coated MNPs and rechelating again. This method, which relies on the surface-functionalized MNPs, presents a promising candidate for simple and cost-effective assay of kinase activity and inhibitor screening.     

Cell-active dual specificity phosphatase inhibitors identified by high-content screening

Phosphorylation of extracellular signal-regulated kinase (Erk) is tightly controlled by dual specificity phosphatases (DSPases), but few inhibitors of Erk dephosphorylation have been identified. Using a high-content, fluorescence-based cellular assay and the National Cancer Institute's 1990 agent Diversity Set, we identified ten compounds (0.5%) that significantly increased phospho-Erk cytonuclear differences in intact cells. Three of the ten positive compounds inhibited the mitogen-activated protein kinase phosphatase-3 (MKP-3/PYST-1) in vitro without affecting VHR or PTP1B phosphatases. The most potent inhibitor of MKP-3 had an IC(50) of <10 microM and inhibited MKP-3 in a novel, fluorescence-based multiparameter chemical complementation assay. These results suggest that the phospho-Erk nuclear accumulation assay may be a useful tool to discover DSPase inhibitors with biological activity.     

Harnessing Protein-Ligand Interaction Fingerprints to Predict New Scaffolds of RIPK1 Inhibitors

Necroptosis has emerged as an exciting target in oncological, inflammatory, neurodegenerative, and autoimmune diseases, in addition to acute ischemic injuries. It is known to play a role in innate immune response, as well as in antiviral cellular response. Here we devised a concerted in silico and experimental framework to identify novel RIPK1 inhibitors, a key necroptosis factor. We propose the first in silico model for the prediction of new RIPK1 inhibitor scaffolds by combining docking and machine learning methodologies. Through the data analysis of patterns in docking results, we derived two rules, where rule #1 consisted of a four-residue signature filter, and rule #2 consisted of a six-residue similarity filter based on docking calculations. These were used in consensus with a machine learning QSAR model from data collated from ChEMBL, the literature, in patents, and from PubChem data. The models allowed for good prediction of actives of >90, 92, and 96.4% precision, respectively. As a proof-of-concept, we selected 50 compounds from the ChemBridge database, using a consensus of both molecular docking and machine learning methods, and tested them in a phenotypic necroptosis assay and a biochemical RIPK1 inhibition assay. A total of 7 of the 47 tested compounds demonstrated around 20–25% inhibition of RIPK1’s kinase activity but, more importantly, these compounds were discovered to occupy new areas of chemical space. Although no strong actives were found, they could be candidates for further optimization, particularly because they have new scaffolds. In conclusion, this screening method may prove valuable for future screening efforts as it allows for the exploration of new areas of the chemical space in a very fast and inexpensive manner, therefore providing efficient starting points amenable to further hit-optimization campaigns.     

Modeling and benchmark data set for the inhibition of c-Jun N-terminal kinase-3

The goal of this paper is to present and describe a novel 2D- and 3D-QSAR (quantitative structure-activity relationship) binary classification data set for the inhibition of c-Jun N-terminal kinase-3 with previously unpublished activities for a diverse set of compounds. JNK3 is an important pharmaceutical target because it is involved in many neurological disorders. Accordingly, the development of JNK3 inhibitors has gained increasing interest. 2D and 3D versions of the data set were used, consisting of 313 (70 actives) and 249 (60 actives) compounds, respectively. All compounds, for which activity was only determined for the racemate, were removed from the 3D data set. We investigated the diversity of the data sets by an agglomerative clustering with feature trees and show that the data set contains several different scaffolds. Furthermore, we show that the benchmarks can be tackled with standard supervised learning algorithms with a convincing performance. For the 2D problem, a random decision forest classifier achieves a Matthew's correlation coefficient of 0.744, the 3D problem could be modeled with a Matthew's correlation coefficient of 0.524 with 3D pharmacophores and a support vector machine. The performance of both data sets was evaluated within a nested 10-fold cross-validation. We therefore suggest that the data set is a reasonable basis for generating QSAR models for JNK3 because of its diverse composition and the performance of the classifiers presented in this study.     

Fluorescence resonance energy transfer assay for high-throughput screening of ADAMTS1 inhibitors

A disintegrin and metalloprotease with thrombospondin type I motifs-1 (ADAMTS1) plays a crucial role in inflammatory joint diseases and its inhibitors are potential candidates for anti-arthritis drugs. For the purposes of drug discovery, we reported the development and validation of fluorescence resonance energy transfer (FRET) assay for high-throughput screening (HTS) of the ADAMTS1 inhibitors. A FRET substrate was designed for a quantitative assay of ADAMTS1 activity and enzyme kinetics studies. The assay was developed into a 50-μL, 384-well assay format for high throughput screening of ADAMTS1 inhibitors with an overall Z' factor of 0.89. ADAMTS1 inhibitors were screened against a diverse library of 40,960 total compounds with the established HTS system. Four structurally related hits, naturally occurring compounds, kuwanon P, kuwanon X, albafuran C and mulberrofuran J, extracted from the Chinese herb Morus alba L., were identified for further investigation. The results suggest that this FRET assay is an excellent tool, not only for measurement of ADAMTS1 activity but also for discovery of novel ADAMTS1 inhibitors with HTS.     

Lead hopping using SVM and 3D pharmacophore fingerprints

The combination of 3D pharmacophore fingerprints and the support vector machine classification algorithm has been used to generate robust models that are able to classify compounds as active or inactive in a number of G-protein-coupled receptor assays. The models have been tested against progressively more challenging validation sets where steps are taken to ensure that compounds in the validation set are chemically and structurally distinct from the training set. In the most challenging example, we simulate a lead-hopping experiment by excluding an entire class of compounds (defined by a core substructure) from the training set. The left-out active compounds comprised approximately 40% of the actives. The model trained on the remaining compounds is able to recall 75% of the actives from the "new" lead series while correctly classifying >99% of the 5000 inactives included in the validation set.     

Virtual screening and rational drug design method using structure generation system based on 3D-QSAR and docking

An efficient virtual and rational drug design method is presented. It combines virtual bioactive compound generation with 3D-QSAR model and docking. Using this method, it is possible to generate a lot of highly diverse molecules and find virtual active lead compounds. The method was validated by the study of a set of anti-tumor drugs. With the constraints of pharmacophore obtained by DISCO implemented in SYBYL 6.8, 97 virtual bioactive compounds were generated, and their anti-tumor activities were predicted by CoMFA. Eight structures with high activity were selected and screened by the 3D-QSAR model. The most active generated structure was further investigated by modifying its structure in order to increase the activity. A comparative docking study with telomeric receptor was carried out, and the results showed that the generated structures could form more stable complexes with receptor than the reference compound selected from experimental data. This investigation showed that the proposed method was a feasible way for rational drug design with high screening efficiency.     

Virtual screening and rational drug design method using structure generation system based on 3D-QSAR and docking

An efficient virtual and rational drug design method is presented. It combines virtual bioactive compound generation with 3D-QSAR model and docking. Using this method, it is possible to generate a lot of highly diverse molecules and find virtual active lead compounds. The method was validated by the study of a set of anti-tumor drugs. With the constraints of pharmacophore obtained by DISCO implemented in SYBYL 6.8, 97 virtual bioactive compounds were generated, and their anti-tumor activities were predicted by CoMFA. Eight structures with high activity were selected and screened by the 3D-QSAR model. The most active generated structure was further investigated by modifying its structure in order to increase the activity. A comparative docking study with telomeric receptor was carried out, and the results showed that the generated structures could form more stable complexes with receptor than the reference compound selected from experimental data. This investigation showed that the proposed method was a feasible way for rational drug design with high screening efficiency.     

Cu2＋和铜锌超氧化物歧化酶作用的光谱学研究

利用邻苯三酚自氧化法监测在磷酸盐缓冲体系中Cu^2＋对猪肝铜锌超氧化物歧化酶(CuZnSOD)活力的影响, 认为Cu^2＋与猪肝CuZnSOD存在直接相互作用. 通过荧光光谱方法研究了这种相互作用, 内源荧光的猝灭实验表明Cu^2＋与CuZnSOD形成1∶1型稳定配合物; 荧光猝灭的动力学分析表明配合物形成过程由两个独立步骤完成: 第一步是双分子快速缔合过程, 形成了结合疏松的配合物, 第二步是单分子慢速过程, 即松散的配合物“异构化”成为结合紧密的配合物. FTIR和CD证实相互作用过程伴随了蛋白分子构象的变化.     

Comparison of luminescence ADP production assay and radiometric scintillation proximity assay for Cdc7 kinase

Several assay technologies have been successfully adapted and used in HTS to screen for protein kinase inhibitors; however, emerging comparative analysis studies report very low hit overlap between the different technologies, which challenges the working assumption that hit identification is not dependent on the assay method of choice. To help address this issue, we performed two screens on the cancer target, Cdc7-Dbf4 heterodimeric protein kinase, using a direct assay detection method measuring [(33)P]-phosphate incorporation into the substrate and an indirect method measuring residual ADP production using luminescence. We conducted the two screens under similar conditions, where in one, we measured [(33)P]-phosphate incorporation using scintillation proximity assay (SPA), and in the other, we detected luminescence signal of the ATP-dependent luciferase after regenerating ATP from residual ADP (LUM). Surprisingly, little or no correlation were observed between the positives identified by the two methods; at a threshold of 30% inhibition, 25 positives were identified in the LUM screen whereas the SPA screen only identified two positives, Tannic acid and Gentian violet, with Tannic acid being common to both. We tested 20 out of the 25 positive compounds in secondary confirmatory study and confirmed 12 compounds including Tannic acid as Cdc7-Dbf4 kinase inhibitors. Gentian violet, which was only positive in the SPA screen, inhibited luminescence detection and categorized as a false positive. This report demonstrates the strong impact in detection format on the success of a screening campaign and the importance of carefully designed confirmatory assays to eliminate those compounds that target the detection part of the assay.     

Fluorescence resonance energy transfer between polyphenolic compounds and riboflavin indicates a possible accessory photoreceptor function for some polyphenolic compounds

The photoreceptive extreme tip of the wheat coleoptile exhibits intense green-yellow fluorescence under UV light, suggesting the presence of UV-absorbing materials. Fluorescence spectra of the intact coleoptile tip and tip homogenate showed the presence of the known photoreceptor pigments flavin and carotene, and a preponderance of phenolic compounds. Absorption spectra and fluorescence spectra of various phenolic compounds showed close overlap with the absorption and fluorescence spectra of the wheat coleoptile tip homogenate. Fluorescence spectra of several phenolic compounds showed close overlap with the absorption bands of flavin, carotene and pterine, suggesting possible energy transduction from phenols to these photoreceptors. Excitation of gentisic acid and ferulic acid with 340 nm light in the presence of flavin showed enhancement of flavin fluorescence in a concentration- and viscosity-dependent fashion, indicating fluorescence resonance energy transfer between them and riboflavin. Furthermore, several phenolic compounds tested generated superoxide anion on excitation at 340 nm, suggesting that superoxide-dependent signal cascades could operate in a polyphenol-mediated pathway. Phenolic compounds thus may act as accessory photoreceptors bringing about excitation energy transfer to the reactive photoreceptor molecules, or they may take over the function of the normal photoreceptor in genetic mutations lacking the system, or both processes may occur. The responses of plants to UV-B and UV-A light in mutants may be explained in terms of various phenolics acting as energy transducers in photoreceptor functioning.