Pan-assay Interference Compounds Research Articles

High-throughput screening campaigns against a PI3Kα isoform bearing the H1047R mutation identified potential inhibitors with novel scaffolds.

The phosphatidylinositol 3-kinase (PI3K) pathway is involved in many cellular functions including cell growth, metabolism, and transformation. Hyperactivation of this pathway contributes to tumorigenesis, therefore, PI3K is a major target for anticancer drug discovery. Since the PI3Kα isoform is implicated mostly in cancer, we conducted a high-throughputscreening (HTS) campaign using a 3-step PI3K homogenous time-resolved fluorescence assay against this isoform bearing the H1047R mutation. A total of 288,000 synthetic and natural product-derived compounds were screened and of which, we identified 124 initial hits that were further selected by considering the predicted binding mode, relationship to known pan-assay interference compounds and previous descriptions as a lipid kinase inhibitor. A total of 24 compounds were then tested for concentration-dependent responses. These hit compounds provide novel scaffolds that can potentially be optimized to create novel PI3K inhibitors.

Investigating the Behavior of Published PAINS Alerts Using a Pharmaceutical Company Data Set.

Biochemical assay interference is becoming increasingly recognized as a significant waste of resource in drug discovery, both in industry and academia. A seminal publication from Baell and Holloway raised the awareness of this issue, and they published a set of alerts to identify what they described as PAINS (pan-assay interference compounds). These alerts have been taken up by drug discovery groups, even though the original paper had a somewhat limited data set. Here, we have taken Lilly’s far larger internal data set to assess the PAINS alerts on four criteria: promiscuity (over six assay formats including AlphaScreen), compound stability, cytotoxicity, and presence of a high Hill slope as a surrogate for non-1:1 protein–ligand binding. It was found that only three of the alerts show pan-assay promiscuity, and the alerts appear to encode primarily AlphaScreen promiscuous molecules. Although not enriching for pan-assay promiscuity, many of the alerts do encode molecules that are unstable, show cytotoxicity, and increase the prevalence of high Hill slopes.

Nuisance Compounds, PAINS Filters, and Dark Chemical Matter in the GSK HTS Collection

High-throughput screening (HTS) hits include compounds with undesirable properties. Many filters have been described to identify such hits. Notably, pan-assay interference compounds (PAINS) has been adopted by the community as the standard term to refer to such filters, and very useful guidelines have been adopted by the American Chemical Society (ACS) and subsequently triggered a healthy scientific debate about the pitfalls of draconian use of filters. Using an inhibitory frequency index, we have analyzed in detail the promiscuity profile of the whole GlaxoSmithKline (GSK) HTS collection comprising more than 2 million unique compounds that have been tested in hundreds of screening assays. We provide a comprehensive analysis of many previously published filters and newly described classes of nuisance structures that may serve as a useful source of empirical information to guide the design or growth of HTS collections and hit triaging strategies.

New fluorescence-based high-throughput screening assay for small molecule inhibitors of tyrosyl-DNA phosphodiesterase 2 (TDP2)

Tyrosyl-DNA phosphodiesterase 2 (TDP2) repairs topoisomerase II (TOP2) mediated DNA damages and causes resistance to TOP2-targeted cancer therapy. Inhibiting TDP2 could sensitize cancer cells toward TOP2 inhibitors. However, potent TDP2 inhibitors with favorable physicochemical properties are not yet reported. Therefore, there is a need to search for novel molecular scaffolds capable of inhibiting TDP2. We report herein a new simple, robust, homogenous mix-and-read fluorescence biochemical assay based using humanized zebrafish TDP2 (14M_zTDP2), which provides biochemical and molecular structure basis for TDP2 inhibitor discovery. The assay was validated by screening a preselected library of 1600 compounds (Z′ ≥ 0.72) in a 384-well format, and by running in parallel gel-based assays with fluorescent DNA substrates. This library was curated via virtual high throughput screening (vHTS) of 460,000 compounds from Chembridge Library, using the crystal structure of the novel surrogate protein 14M_zTDP2. From this primary screening, we selected the best 32 compounds (2% of the library) to further assess their TDP2 inhibition potential, leading to the IC50 determination of 10 compounds. Based on the dose-response curve profile, pan-assay interference compounds (PAINS) structure identification, physicochemical properties and efficiency parameters, two hit compounds, 11a and 19a, were tested using a novel secondary fluorescence gel-based assay. Preliminary structure-activity relationship (SAR) studies identified guanidine derivative 12a as an improved hit with a 6.4-fold increase in potency over the original HTS hit 11a. This study highlights the importance of the development of combination approaches (biochemistry, crystallography and high throughput screening) for the discovery of TDP2 inhibitors.

Exploring the novel heterocyclic derivatives as lead molecules for design and development of potent anticancer agents

This paper deals with in silico evaluation of newly proposed heterocyclic derivatives in search of potential anticancer activity. Best possible drug candidates have been proposed using a rational approach employing a pipeline of computational techniques namely MetaPrint2D prediction, molinspiration, cheminformatics, Osiris Data warrior, AutoDock and iGEMDOCK. Lazar toxicity prediction, AdmetSAR predictions, and targeted docking studies were also performed. 27 heterocyclic derivatives were selected for bioactivity prediction and drug likeness score on the basis of Lipinski's rule, Viber rule, Ghose filter, leadlikeness and Pan Assay Interference Compounds (PAINS) rule. Bufuralol, Sunitinib, and Doxorubicin were selected as reference standard drug for the comparison of molecular descriptors and docking. Bufuralol is a known non-selective adreno-receptor blocking agent. Studies showed that beta blockers are also used against different types of cancers. Sunitinib is well known Food and Drug administration (FDA) approved pyrrole containing tyrosine kinase inhibitor and our proposed molecules possess similarities with both drug and doxorubicin is another moiety having anticancer activity. All heterocyclic derivatives were found to obey the drug filters except standard drug Doxorubicin. Bioactivity score of the compounds was predicted for drug targets including enzymes, nuclear receptors, kinase inhibitors, G protein-coupled receptor (GPCR) ligands and ion channel modulators. Absorption, distribution, metabolism and toxicity (ADMET) prediction of all proposed compound showed good Blood-brain barrier (BBB) penetration, Human intestinal absorption (HIA), Caco-2 cell permeability except compound-11 and was found to have no AdmetSAR toxicity as well as carcinogenic effect. Compounds 1–9 were slightly mutagenic while compound 2, 11, 20 and 21 showed carcinogenic effect according to Lazar toxicity prediction. Rests of the compounds were predicted to have no side effect. Molecular docking was performed with vascular endothelial growth factor receptor-2(VEGFR2) and glutathione S-transferase-1 (GSTP1) because both are common cancer causing proteins. Sunitinib and Doxorubicin possess great affinity to inhibit these cancers causing protein. Self-organizing map (SOM) was used to depict data in a simple 2D presentation. Our studies justify that good oral bioavailability and therapeutic efficacy of 10, 12–19 and 22–27 compounds can be considered as potential anticancer agents.

Hit Dexter: A Machine-Learning Model for the Prediction of Frequent Hitters.

False-positive assay readouts caused by badly behaving compounds-frequent hitters, pan-assay interference compounds (PAINS), aggregators, and others-continue to pose a major challenge to experimental screening. There are only a few in silico methods that allow the prediction of such problematic compounds. We report the development of Hit Dexter, two extremely randomized trees classifiers for the prediction of compounds likely to trigger positive assay readouts either by true promiscuity or by assay interference. The models were trained on a well-prepared dataset extracted from the PubChem Bioassay database, consisting of approximately 311 000 compounds tested for activity on at least 50 proteins. Hit Dexter reached MCC and AUC values of up to 0.67 and 0.96 on an independent test set, respectively. The models are expected to be of high value, in particular to medicinal chemists and biochemists who can use Hit Dexter to identify compounds for which extra caution should be exercised with positive assay readouts. Hit Dexter is available as a free web service at http://hitdexter.zbh. uni-hamburg.de.

In Vitro, In Silico, and In Vivo Analyses of Novel Aromatic Amidines against Trypanosoma cruzi.

Five bis-arylimidamides were assayed as anti-Trypanosoma cruzi agents by in vitro, in silico, and in vivo approaches. None were considered to be pan-assay interference compounds. They had a favorable pharmacokinetic landscape and were active against trypomastigotes and intracellular forms, and in combination with benznidazole, they gave no interaction. The most selective agent (28SMB032) tested in vivo led to a 40% reduction in parasitemia (0.1 mg/kg of body weight/5 days intraperitoneally) but without mortality protection. In silico target fishing suggested DNA as the main target, but ultrastructural data did not match.

Development and Validation of 2D Difference Intensity Analysis for Chemical Library Screening by Protein-Detected NMR Spectroscopy.

An academic chemical screening approach was developed by using 2D protein-detected NMR, and a 352-chemical fragment library was screened against three different protein targets. The approach was optimized against two protein targets with known ligands: CXCL12 and BRD4. Principal component analysis reliably identified compounds that induced nonspecific NMR crosspeak broadening but did not unambiguously identify ligands with specific affinity (hits). For improved hit detection, a novel scoring metric-difference intensity analysis (DIA)-was devised that sums all positive and negative intensities from 2D difference spectra. Applying DIA quickly discriminated potential ligands from compounds inducing nonspecific NMR crosspeak broadening and other nonspecific effects. Subsequent NMR titrations validated chemotypes important for binding to CXCL12 and BRD4. A novel target, mitochondrial fission protein Fis1, was screened, and six hits were identified by using DIA. Screening these diverse protein targets identified quinones and catechols that induced nonspecific NMR crosspeak broadening, hampering NMR analyses, but are currently not computationally identified as pan-assay interference compounds. The results established a streamlined screening workflow that can easily be scaled and adapted as part of a larger screening pipeline to identify fragment hits and assess relative binding affinities in the range of 0.3-1.6 mm. DIA could prove useful in library screening and other applications in which NMR chemical shift perturbations are measured.

X-ray Structures of Target-Ligand Complexes Containing Compounds with Assay Interference Potential.

Pan assay interference compounds (PAINS) have become a paradigm for compound classes that might cause artifacts in biological assays. PAINS-defining substructures are typically contained in larger compounds. We have systematically examined X-ray structures of protein-ligand complexes for compounds containing PAINS motifs. In 2874 X-ray structures, 1107 unique ligands with PAINS substructures belonging to 70 different classes were identified. PAINS most frequently detected in crystallographic ligands included a number of prominent candidates such as quinones, catechols, or Mannich bases. However, on the basis of X-ray data, the presence of specific ligand-target interactions and reactivity under assay conditions were not mutually exclusive. In some instances, reactivity of ligands was likely responsible for complex formation. Different categories of PAINS-containing ligands were distinguished, which aided in the interpretation of specific interactions versus potential assay artifacts. Careful consideration of structural data adds another dimension to the analysis of interference compounds.

Seven Year Itch: Pan-Assay Interference Compounds (PAINS) in 2017-Utility and Limitations.

Pan-Assay Interference Compounds (PAINS) are very familiar to medicinal chemists who have spent time fruitlessly trying to optimize these nonprogressible compounds. Electronic filters formulated to recognize PAINS can process hundreds and thousands of compounds in seconds and are in widespread current use to identify PAINS in order to exclude them from further analysis. However, this practice is fraught with danger because such black box treatment is simplistic. Here, we outline for the first time all necessary considerations for the appropriate use of PAINS filters.

Comment on The Ecstasy and Agony of Assay Interference Compounds.

2017 , 57 , 387 - 390 ) is examined critically. When assessing assay hits from screening, it is important to draw a distinction between false positives, that have no effect on target function, and compounds that affect target function through an undesirable mechanism of action. Observation of frequent-hitter behavior for a compound should be regarded as circumstantial evidence, rather than definitive proof, that the compound has interfered with assay readouts or acted through an undesirable mechanism of action. The applicability domain of published (Baell and Holloway J. Med. Chem. 2010 , 53 , 2719 - 2740 ) Pan Assay INterference compoundS (PAINS) filters is limited by the narrow scope of the proprietary data used to derive them. It is suggested that journal guidelines for authors should not prescribe, as those for the Journal of Medicinal Chemistry appear to do, that activity in assays reported for compounds that match PAINS filters be treated any differently from that for compounds that do not match PAINS filters. It is argued that use of models based on proprietary data in the evaluation of manuscripts would contradict the editorial policy of any journal that deemed the use of proprietary data to be unacceptable in modeling studies.

In silico identification of inhibitors of ribose 5-phosphate isomerase from Trypanosoma cruzi using ligand and structure based approaches

Chagas disease, caused by the protozoan Trypanosoma cruzi, affects approximately seven million people, mainly in Latin America, and causes about 7000 deaths annually. The available treatments are unsatisfactory and search for more effective drugs against this pathogen is critical. In this context, the ribose 5-phosphate isomerase (Rpi) enzyme is a potential drug target mainly due to its function in the pentose phosphate pathway and its essentiality (previously shown in other trypanosomatids). In this study, we propose novel potential inhibitors for the Rpi of T. cruzi (TcRpi) based on a computer-aided approach, including structure-based and ligand-based pharmacophore modeling. Along with a substructural and similarity search, the selected pharmacophore hypotheses were used to screen the purchasable subset of the ZINC Database, yielding 20,183 candidate compounds. These compounds were submitted to molecular docking studies in the TcRpi and Human Rpi (HsRpi) active sites in order to identify potential selective inhibitors for the T. cruzi enzyme. After the molecular docking and ADME-T (absorption, distribution, metabolism, excretion and toxicity)/PAINS (pan-assay interference compounds) screenings, 211 molecules were selected as potential TcRpi inhibitors. Out of these, three compounds – ZINC36975961, ZINC63480117, and ZINC43763931 – were submitted to molecular dynamics simulations and two of them – ZINC36975961 and ZINC43763931- had good performance and made interactions with important active site residues over all the simulation time. These compounds could be considered potential TcRpi inhibitors candidates and also may be used as leads for developing new TcRpi inhibitors.

Photoactivation provides a mechanistic explanation for pan-assay interference behaviour of 2-aminopyrroles in lipoxygenase inhibition

Human 15-lipoxygenase-1 (h-15-LOX-1) is a promising drug target in inflammation and cancer. In this study substitution-oriented screening (SOS) has been used to identify compounds with a 2-aminopyrrole scaffold as inhibitors for h-15-LOX-1. The observed structure activity relationships (SAR) proved to be relatively flat. IC50's for the most potent inhibitor of the series did not surpass 6.3 μM and the enzyme kinetics demonstrated uncompetitive inhibition. Based on this, we hypothesized that the investigated 2-aminopyrroles are pan assay interference compounds (PAINS) with photoactivation via a radical mechanism. Our results demonstrated clear photoactivation of h-15-LOX-1 inhibition under UV and visible light. In addition, the investigated 2-aminopyrroles decreased viability of cultured human hepatocarcinoma cells HCC-1.2 in a dose-dependent manner with LD50 ranging from 0.55 ± 0.15 μM (21B10) to 2.75 ± 0.91 μM (22). Taken together, this indicates that photoactivation can play an important role in the biological activity of compounds with a 2-amino-pyrrole scaffold as investigated here.

How Frequently Are Pan-Assay Interference Compounds Active? Large-Scale Analysis of Screening Data Reveals Diverse Activity Profiles, Low Global Hit Frequency, and Many Consistently Inactive Compounds.

Undetected pan-assay interference compounds (PAINS) with false-positive activities in assays often propagate through medicinal chemistry programs and compromise their outcomes. Although a large number of PAINS have been classified, often on the basis of individual studies or chemical experience, little has been done so far to systematically assess their activity profiles. Herein we report a large-scale analysis of the behavior of PAINS in biological screening assays. More than 23 000 extensively tested compounds containing PAINS substructures were detected, and their hit rates were determined. Many consistently inactive compounds were identified. The hit frequency was low overall, with median values of two to five hits for PAINS tested in hundreds of assays. Only confined subsets of PAINS produced abundant hits. The same PAINS substructure was often found in consistently inactive and frequently active compounds, indicating that the structural context in which PAINS occur modulates their effects.

Phantom PAINS: Problems with the Utility of Alerts for Pan-Assay INterference CompoundS.

The use of substructural alerts to identify Pan-Assay INterference compoundS (PAINS) has become a common component of the triage process in biological screening campaigns. These alerts, however, were originally derived from a proprietary library tested in just six assays measuring protein–protein interaction (PPI) inhibition using the AlphaScreen detection technology only; moreover, 68% (328 out of the 480 alerts) were derived from four or fewer compounds. In an effort to assess the reliability of these alerts as indicators of pan-assay interference, we performed a large-scale analysis of the impact of PAINS alerts on compound promiscuity in bioassays using publicly available data in PubChem. We found that the majority (97%) of all compounds containing PAINS alerts were actually infrequent hitters in AlphaScreen assays measuring PPI inhibition. We also found that the presence of PAINS alerts, contrary to expectations, did not reflect any heightened assay activity trends across all assays in PubChem including AlphaScreen, luciferase, beta-lactamase, or fluorescence-based assays. In addition, 109 PAINS alerts were present in 3570 extensively assayed, but consistently inactive compounds called Dark Chemical Matter. Finally, we observed that 87 small molecule FDA-approved drugs contained PAINS alerts and profiled their bioassay activity. Based on this detailed analysis of PAINS alerts in nonproprietary compound libraries, we caution against the blind use of PAINS filters to detect and triage compounds with possible PAINS liabilities and recommend that such conclusions should be drawn only by conducting orthogonal experiments.

The Essential Medicinal Chemistry of Curcumin.

Curcumin is a constituent (up to ∼5%) of the traditional medicine known as turmeric. Interest in the therapeutic use of turmeric and the relative ease of isolation of curcuminoids has led to their extensive investigation. Curcumin has recently been classified as both a PAINS (pan-assay interference compounds) and an IMPS (invalid metabolic panaceas) candidate. The likely false activity of curcumin in vitro and in vivo has resulted in >120 clinical trials of curcuminoids against several diseases. No double-blinded, placebo controlled clinical trial of curcumin has been successful. This manuscript reviews the essential medicinal chemistry of curcumin and provides evidence that curcumin is an unstable, reactive, nonbioavailable compound and, therefore, a highly improbable lead. On the basis of this in-depth evaluation, potential new directions for research on curcuminoids are discussed.

Activity profiles of analog series containing pan assay interference compounds

Shown is the distribution of activity profiles (color-coded bars) of analog series containing PAINS substructures in a heatmap.

PAIN-less identification and evaluation of small molecule inhibitors against protein tyrosine phosphatase 1B.

A highly miniaturized biochemical assay was set up to test a focused set of natural products against the enzymatic activity of protein tyrosine phosphatase 1B (PTP1B). The screen resulted in the identification of the natural product alkaloids, berberine and palmatine as well as α-tocopheryl succinate (α-TOS) as potential inhibitors of PTP1B. In a second step, several read-out and counter assays were applied to confirm the observed inhibitory activity of the identified hits and to remove false positives which target the enzymatic activity of PTP1B by a non-specific mechanism, also known as PAINS (pan-assay interference compounds). Both, berberine and palmatine were identified as false positives which interfered with the assay read-out. Using NMR spectroscopy, self-association via stacking interactions was detected for berberine in aqueous media, which may also contribute to the non-specific inhibition of PTP1B. α-TOS was confirmed as a novel reversible and competitive inhibitor of PTP1B. A concise structure-activity relationship study identified the carboxyl group and the saturated phytyl-side chain as being critical for PTP1B inhibition.

Antitrypanosomal activity and evaluation of the mechanism of action of dehydrodieugenol isolated from Nectandra leucantha (Lauraceae) and its methylated derivative against Trypanosoma cruzi

BackgroundFrom a previous screening of Brazilian biodiversity for antiprotozoal activity, the hexane extract from leaves of Nectandra leucantha (Nees & Mart.) (Lauraceae) demonstrated activity against Trypanosoma cruzi. Chromatographic separation of this extract afforded bioactive dehydrodieugenol (1). Furthermore, methylated derivative 2 (dehydrodieugenol dimethyl ether) was prepared and also tested against T. cruzi. PurposeTo examine the therapeutical potential of compounds 1 and 2 against T. cruzi as well as to elucidate the mechanism of action of bioactive compound 1 against T. cruzi. Methods/Study designCrude hexane extract from leaves was subjected to chromatographic steps to afford bioactive compound 1. In order to analyze the effect of additional methyl group in the antiparasitic activity of 1, derivative 2 was prepared (both are no pan-assay interference compounds - PAINS). These compounds were evaluated in vitro against T. cruzi (trypomastigote and amastigote forms) and analyzed for the potential effect in host cells through the production of nitric oxide and reactive oxygen species. Finally, the plasma membrane effect of the most potent compound 1 was investigated in T. cruzi trypomastigotes. ResultsCompounds 1 and 2 displayed activity against amastigotes of T. cruzi. Although both compounds promoted activity against intracellular amastigotes, the production of nitric oxide and reactive oxygen species of host cells were unaltered, suggesting an antiparasitic activity other than host cell activation. Considering 1 the most effective compound against T. cruzi, the interference in the plasma membrane of the trypomastigotes was investigated using the fluorescent probe SYTOX® Green. After a short-term incubation, the fluidity and integrity of the plasma membrane was completely altered, suggesting it as a primary target for compound 1 in T. cruzi. ConclusionCompounds 1 and 2 selectively eliminated the intracellular parasites without host cell activation and could be important scaffolds for the search of new hit compounds.

Highly Promiscuous Small Molecules from Biological Screening Assays Include Many Pan-Assay Interference Compounds but Also Candidates for Polypharmacology.

In PubChem screening assays, 466 highly promiscuous compounds were identified that were examined for known pan-assay interference compounds (PAINS) and aggregators using publicly available filters. These filters detected 210 PAINS and 67 aggregators. Compounds passing the filters included additional PAINS that were not detected, mostly due to tautomerism, and a variety of other potentially reactive compounds currently not encoded as PAINS. For a subset of compounds passing the filters, there was no evidence of potential artifacts. These compounds are considered candidates for further exploring multitarget activities and the molecular basis of polypharmacology.