Pan-assay Interference Compounds Research Articles

RNase P Inhibitors Identified as Aggregators.

RNase P is an essential enzyme responsible for tRNA 5'-end maturation. In most bacteria, the enzyme is a ribonucleoprotein consisting of a catalytic RNA subunit and a small protein cofactor termed RnpA. Several studies have reported small-molecule inhibitors directed against bacterial RNase P that were identified by high-throughput screenings. Using the bacterial RNase P enzymes from Thermotoga maritima, Bacillus subtilis, and Staphylococcus aureus as model systems, we found that such compounds, including RNPA2000 (and its derivatives), iriginol hexaacetate, and purpurin, induce the formation of insoluble aggregates of RnpA rather than acting as specific inhibitors. In the case of RNPA2000, aggregation was induced by Mg2+ ions. These findings were deduced from solubility analyses by microscopy and high-performance liquid chromatography (HPLC), RnpA-inhibitor co-pulldown experiments, detergent addition, and RnpA titrations in enzyme activity assays. Finally, we used a B. subtilis RNase P depletion strain, whose lethal phenotype could be rescued by a protein-only RNase P of plant origin, for inhibition zone analyses on agar plates. These cell-based experiments argued against RNase P-specific inhibition of bacterial growth by RNPA2000. We were also unable to confirm the previously reported nonspecific RNase activity of S. aureus RnpA itself. Our results indicate that high-throughput screenings searching for bacterial RNase P inhibitors are prone to the identification of "false positives" that are also termed pan-assay interference compounds (PAINS).

The Identification of Natural Products that are Predicted to Bind to the SARS‐CoV‐2 3CL Protease

Considerable attention has been paid to immunological approaches to dealing with the Covid‐19 pandemic. In addition, existing pharmaceuticals, such as the modified mononucleotide Remdesvir, have been studied in the context of the viral infection.This study looks at different classes of compounds, natural products, some already ingested by millions of people every day, and asks if there is evidence that they might bind to Covid‐19 viral proteins and possibly interfere with viral replication.In this study, the Universal Natural Products Database was used to search for compounds that bind to the SARS‐CoV‐2 3CL Protease. The database was interrogated using the Smina docking program, a branch of Autodock Vina. Those compounds that were predicted by Smina to bind better than ‐9 kcal/mole were then successively interrogated with LeDock, a program that gives results that are considerably different from Smina.The compounds with predicted binding values of ‐11 kcal/mole or lower by both programs were then studied by observing their predicted binding using several programs that enable the examination of ligand‐protein interactions.While this study identified many compounds of potential interest, this report concentrates on compounds that are commonly found in foodstuffs. Some but not all of these compounds are structurally close to those compounds that have been classified by others as Pan‐Assay Interference Compounds, PAINS.

Toward an Understanding of Pan-Assay Interference Compounds and Promiscuity: A Structural Perspective on Binding Modes.

Pan-assay interference compounds (PAINS) are promiscuous compound classes that produce false positive hits in high-throughput screenings. Yet, the mechanisms of PAINS activity are poorly understood. Although PAINS are often associated with protein reactivity, several recent studies have shown that they also mediate noncovalent interactions. Aiming at a deep understanding of PAINS promiscuity, we performed an analysis of the Protein Data Bank to characterize the binding modes of PAINS. We explored the binding mode conservation of 34 PAINS classes present in 871 ligands and among 517 protein targets. The two major findings of this work are the following: First, different PAINS classes exhibit different levels of binding mode conservation. Our novel classification of PAINS based on binding mode similarity enables a rational assessment of PAINS from a structural perspective. Second, PAINS classes with variable binding modes can bind with high affinity. The evaluation of noncovalent binding modes of PAINS-like compounds sheds light on the mechanisms of promiscuous binding. Our findings could facilitate the decisions on how to deal with PAINS and help scientists to understand why PAINS produce hits in their screenings.

Methoxy-Substituted Tyramine Derivatives Synthesis, Computational Studies and Tyrosinase Inhibitory Kinetics.

Targeting tyrosinase for melanogenesis disorders is an established strategy. Hydroxyl-substituted benzoic and cinnamic acid scaffolds were incorporated into new chemotypes that displayed in vitro inhibitory effects against mushroom and human tyrosinase for the purpose of identifying anti-melanogenic ingredients. The most active compound 2-((4-methoxyphenethyl)amino)-2-oxoethyl (E)-3-(2,4-dihydroxyphenyl) acrylate (Ph9), inhibited mushroom tyrosinase with an IC50 of 0.059 nM, while 2-((4-methoxyphenethyl)amino)-2-oxoethyl cinnamate (Ph6) had an IC50 of 2.1 nM compared to the positive control, kojic acid IC50 16700 nM. Results of human tyrosinase inhibitory activity in A375 human melanoma cells showed that compound (Ph9) and Ph6 exhibited 94.6% and 92.2% inhibitory activity respectively while the positive control kojic acid showed 72.9% inhibition. Enzyme kinetics reflected a mixed type of inhibition for inhibitor Ph9 (Ki 0.093 nM) and non-competitive inhibition for Ph6 (Ki 2.3 nM) revealed from Lineweaver–Burk plots. In silico docking studies with mushroom tyrosinase (PDB ID:2Y9X) predicted possible binding modes in the catalytic site for these active compounds. Ph9 displayed no PAINS (pan-assay interference compounds) alerts. Our results showed that compound Ph9 is a potential candidate for further development of tyrosinase inhibitors.

Parallel discovery of selective and dual inhibitors of tryptophan dioxygenases IDO1 and TDO2 with a newly-modified enzymatic assay

The expression of tryptophan catabolising enzyme indoleamine 2,3-dioxygenase 1 (IDO1) or tryptophan 2,3-dioxygenase 2 (TDO2) in cancers is associated with suppressed immunity and poor patient prognosis. Results from human clinical trials of IDO1 inhibitors have been disappointing. There is now a strong interest in the development of TDO2-selective or dual IDO1/TDO2 inhibitors that may surpass IDO1 inhibitors by providing broader efficacy and blocking constitutively-expressed hepatic TDO2. To expedite the discovery of novel TDO2-specific and dual inhibitors, an assay that enabled the efficient and accurate measurement of the inhibitory activity of compounds against both IDO1 and TDO2 enzymes, concurrently in the same experiment was established to screen 5,682 compounds that included the National Cancer Institute Diversity set 5, for inhibition of IDO1 and TDO2 activity. This screen identified 82 compounds that inhibited either IDO1, TDO2 or both enzymes > 50% at 20 µM. Thirty Pan Assay Interference compounds were removed from the list and the IC50 of the remaining 52 compounds against IDO1 and TDO2 was subsequently determined using the newly-developed concurrent assay. Ten compounds were confirmed as dual IDO1/TDO2 inhibitors having IC50 values under 50 µM against both enzymes and within 2-fold of each other. Six compounds with IC50 values between 1.39 and 8.41 µM were identified as potential TDO2-selective leads. The use of this concurrent protocol is anticipated to expedite the discovery of novel leads for dual and selective inhibitors against IDO1 and or TDO2 and speed the evaluation of novel analogues that will ensue.

Antitrypanosomal Lactones from Nectandra barbellata.

Twigs of Nectandra barbellata were extracted using a solution of the ionic liquid 1-butyl-3-methylimidazolium bromide (BMImBr) in H2O, assisted by microwave (MAE). After successive chromatographic steps, one sesquiterpene, costic acid, and three new related lactones, (R)-3(7)-Z-3-hexadec-21-enylidene-5-(hydroxymethyl)tetrahydrofuran-2-one (1), (R)-3(7)-Z-3-hexadecylidene-5-(hydroxymethyl)tetrahydrofuran-2-one (2), and (R)-3(7)-Z-3-docosylidene-5-(hydroxymethyl)tetrahydrofuran-2-one (3), were isolated. After structural elucidation using IR, UV, HRESIMS, NMR, ECD, and VCD, compounds 1-3 were tested against trypomastigote forms of Trypanosoma cruzi. The mechanism of action of bioactive isolated compounds was studied using different fluorescent-based approaches to investigate alterations of the plasma membrane, permeability/electric potential (ΔΨp), reactive oxygen species levels, mitochondria (electric membrane potential, ΔΨm/ATP levels), Ca2+ levels, and pH of the acidocalcisomes. In addition, in silico studies predicted no resemblance to pan assay interference compounds (PAINS).

C-Glucosylation as a tool for the prevention of PAINS-induced membrane dipole potential alterations

The concept of Pan-Assay Interference Compounds (PAINS) is regarded as a threat to the recognition of the broad bioactivity of natural products. Based on the established relationship between altered membrane dipole potential and transmembrane protein conformation and function, we investigate here polyphenols' ability to induce changes in cell membrane dipole potential. Ultimately, we are interested in finding a tool to prevent polyphenol PAINS-type behavior and produce compounds less prone to untargeted and promiscuous interactions with the cell membrane. Di-8-ANEPPS fluorescence ratiometric measurements suggest that planar lipophilic polyphenols—phloretin, genistein and resveratrol—act by decreasing membrane dipole potential, especially in cholesterol-rich domains such as lipid rafts, which play a role in important cellular processes. These results provide a mechanism for their labelling as PAINS through their ability to disrupt cell membrane homeostasis. Aiming to explore the role of C-glucosylation in PAINS membrane-interfering behavior, we disclose herein the first synthesis of 4-glucosylresveratrol, starting from 5-hydroxymethylbenzene-1,3-diol, via C-glucosylation, oxidation and Horner-Wadsworth-Emmons olefination, and resynthesize phloretin and genistein C-glucosides. We show that C-glucosylation generates compounds which are no longer able to modify membrane dipole potential. Therefore, it can be devised as a strategy to generate bioactive natural product derivatives that no longer act as membrane dipole potential modifiers. Our results offer a new technology towards rescuing bioactive polyphenols from their PAINS danger label through C–C ligation of sugars.

Benchmarking the mechanisms of frequent hitters: limitation of PAINS alerts

In 2010, the pan-assay interference compounds (PAINS) rule was proposed to identify false-positive compounds, especially frequent hitters (FHs), in biological screening campaigns, and has rapidly become an essential component in drug design. However, the specific mechanisms remain unknown, and the result validation and follow-up processing schemes are still unclear. In this review, a large benchmark collection of >600,000 compounds sourced from databases and the literature, including six common false-positive mechanisms, was used to evaluate the detection ability of PAINS. In addition, 400 million purchasable molecules from the ZINC database were also applied to PAINS screening. The results indicate that the PAINS rule is not suitable for the screening of all types of false-positive results and needs more improvement.

Molecular modeling of natural and synthesized inhibitors against SARS-CoV-2 spike glycoprotein

PurposeViral diseases increasingly endanger the world public health because of the transient efficacy of antiviral therapies. The novel coronavirus disease 2019 (COVID-19) has been recently identified as caused by a new type of coronaviruses. This type of coronavirus binds to the human receptor through the Spike glycoprotein (S) Receptor Binding Domain (RBD). The spike protein is found in inaccessible (closed) or accessible (open) conformations in which the accessible conformation causes severe infection. Thus, this receptor is a significant target for antiviral drug design.MethodsAn attempt was made to recognize 111 natural and synthesized compounds in order to utilize them against SARS-CoV-2 spike glycoprotein to inhibit Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) using simulation methods, such as molecular docking. The FAF-Drugs3, Pan-Assay Interference Compounds (PAINS), ADME (absorption, distribution, metabolism, excretion) databases along with Lipinski’s rules were used to evaluate the drug-like properties of the identified ligands. In order to analyze and identify the residues critical in the docking process of the spike glycoprotein, the interactions of proposed ligands with both conformations of the spike glycoprotein was simulated.ResultsThe results showed that among the available ligands, seven ligands had significant interactions with the binding site of the spike glycoprotein, in which angiotensin-converting enzyme 2 (ACE2) is bounded. Out of seven candidate molecules, six ligands exhibited drug-like characteristics. The results also demonstrated that fluorophenyl and propane groups of ligands had optimal interactions with the binding site of the spike glycoprotein.ConclusionAccording to the results, our findings indicated the ability of six ligands to prevent the binding of the SARS-CoV-2 spike glycoprotein to its cognate receptor, providing novel compounds for the treatment of COVID-19.Supplementary InformationThe online version contains supplementary material available at 10.1007/s42600-020-00122-3.

Identification of Pan-Assay INterference compoundS (PAINS) Using an MD-Based Protocol.

Pan-assay interference compounds (PAINS) are promiscuous molecules with multiple behaviors that interfere with assay readouts. Membrane PAINS are a subset of these compounds that influence the function of membrane proteins by nonspecifically perturbing the lipid membranes that surround them. Here, we describe a computational protocol to identify potential membrane PAINS molecules by calculating the effect that a given compound has on the bilayer deformation propensity.

A Potential Lead from Acacia nilotica (L.) Delile Against Hepatitis C virus - An In silico Approach

Hepatitis C virus infection is the leading cause of chronic liver disease and hepatocellular carcinoma. There is no effective vaccine for hepatitis C virus prevention despite the fact that severalvaccinesare under development. Currently, the Unites States Food and drug administration approved combination drugs for all genotypes that would help to cure the infection more quickly and efficiently than ever before. However, the high costs, development of various side effects and emergence of drug resistant strains demand the need for new anti-viral to treat different stages of the hepatitis C virus life cycle. Focussing drug candidate from herbal ingredients is the novel approach of pharmaceutical science over the past few decades. In this perspective, the present study aimed to investigate the phytochemicals present in Acacia nilotica (L.) Delile against hepatitis C virus non-structural protein3-4A serine protease. The N-terminal Protease domain of non-structural protein3 along with non-structural protein4A protein is responsible for the cleavage of four polypeptide junctions’ viz., non-structural protein3-4A, non-structural protein4A-non-structural protein4B, non-structural protein4B-non-structural protein5A and non-structural protein5A-5B that are essential for viral genome replication. Hence targeting non-structural protein3-4A blocks the replication process. Here, in silico molecular docking study was executed to estimate the efficacy ofphytochemicals along with the two Food and drug administration approved hepatitis C virus non-structural protein3-4A inhibitors-Grazoprevir and simeprevir as reference compoundsagainst the selected target. Docking results revealed that about six phytochemicals (+)-Catechin 5-Gallate, Acacetin, (+)-Mollisacacidin, Catechin, Acalinol A and Chlorogenic acid are better than the reference compounds and hence selected as hits. Further, the hit molecules were filtered through analysing druglikeness properties, pharmacokinetics, medicinal chemistry friendliness including pan assay interference compounds and Brenk structural alerts, leadlikeness and finally prediction of potential toxicity and toxic substructure to ascertain a lead molecule. The results obtained in the current study propose Acacetin as the lead molecule for further in vitro and in vivo study.

Biseugenol Exhibited Anti-Inflammatory and Anti-Asthmatic Effects in an Asthma Mouse Model of Mixed-Granulocytic Asthma.

In the present work, the anti-inflammatory and antiasthmatic potential of biseugenol, isolated as the main component from n-hexane extract from leaves of Nectandra leucantha and chemically prepared using oxidative coupling from eugenol, was evaluated in an experimental model of mixed-granulocytic asthma. Initially, in silico studies of biseugenol showed good predictions for drug-likeness, with adherence to Lipinski’s rules of five (RO5), good Absorption, Distribution, Metabolism and Excretion (ADME) properties and no alerts for Pan-Assay Interference Compounds (PAINS), indicating adequate adherence to perform in vivo assays. Biseugenol (20 mg·kg−1) was thus administered intraperitoneally (four days of treatment) and resulted in a significant reduction in both eosinophils and neutrophils of bronchoalveolar lavage fluid in ovalbumin-sensitized mice with no statistical difference from dexamethasone (5 mg·kg−1). As for lung function parameters, biseugenol (20 mg·kg−1) significantly reduced airway and tissue damping in comparison to ovalbumin group, with similar efficacy to positive control dexamethasone. Airway hyperresponsiveness to intravenous methacholine was reduced with biseugenol but was inferior to dexamethasone in higher doses. In conclusion, biseugenol displayed antiasthmatic effects, as observed through the reduction of inflammation and airway hyperresponsiveness, with similar effects to dexamethasone, on mixed-granulocytic ovalbumin-sensitized mice.

SMARTS.plus - A Toolbox for Chemical Pattern Design.

The number of publications concerning Pan‐Assay Interference Compounds and related problematic structural motifs in screening libraries is constantly growing. In consequence, filter collections are merged, extended but also critically discussed. Due to the complexity of the chemical pattern language SMARTS, an easy‐to‐use toolbox enabling every chemist to understand, design and modify chemical patterns is urgently needed. Over the past decade, we developed a series of software tools for visualizing, editing, creating, and analysing chemical patterns. Herein, we highlight how most of these tools can now be easily used as part of the novel SMARTS.plus web server (https://smarts.plus/). As a showcase, we demonstrate how researchers can apply the web server tools within minutes to derive novel SMARTS patterns for the filtering of frequent hitters from their screening libraries with only a little experience with the SMARTS language.

Targeting homologous recombination (HR) repair mechanism for cancer treatment: discovery of new potential UCHL-3 inhibitors via virtual screening, molecular dynamics and binding mode analysis

UCHL3 (ubiquitin C-terminal hydrolase-L3) is a de-ubiquitinating enzyme involved in the homologous recombination repair mechanism of double-strand breaks (DBS) of the DNA. Multiple studies indicated that UCHL3 inhibitors could be used in combination therapy with high therapeutic efficacy against cancer thus highlighting the validity of directing research against UCHL3 as a druggable target in oncology. In this study, a combination of virtual screening methods was utilized to identify new potential UCHL3 inhibitors. A series of UCHL3 ligands were identified by applying a combination of cheminformatics and molecular modeling filtration techniques to a ChemBl database of over two million small molecules viz. Lipinski's Rule of Five, Veber’s rule, pharmacophore model, Hierarchical molecular docking, Pan-assay Interference Compounds (PAINS) alerts, toxicity filter, and single-point Molecular mechanics Poisson/Boltzmann surface area (MM/PBSA) docking pose rescoring. This multi-layer filtration strategy led to the identification of twenty-one compounds as potential UCHL3 inhibitors that were subsequently subjected to a 50 ns molecular dynamics (MD) simulations predict the stability of their ligand-protein complexes. Furthermore, MM/PBSA calculations based on MD trajectories were performed, and the energy contribution per residue to the binding energy was calculated. Three compounds, 1, 2 and 3, were finally recognized as having the highest potential of being UCHL3 inhibitors. Therefore, those were used for binding mode analysis to the UCHL3 active site, leading to identification of four residues as key for binding viz. Pro8, Leu55, Val166, and Leu168. Communicated by Ramaswamy H. Sarma

Heterocyclization of 2-(2-phenylhydrazono)cyclohexane-1,3-dione to Synthesis Thiophene, Pyrazole and 1,2,4-triazine Derivatives with Anti-Tumor and Tyrosine Kinase Inhibitions.

Recently tetrahydrobenzo[b]thiazole derivatives acquired a special attention due to their wide range of pharmacological activities especially the therapeutic activities. Through the market it was found that many pharmacological drugs containing the thiazole nucleus were known. This work aimed to synthesize target molecules not only possess anti-tumor activities but also kinase inhibitors. The target molecules were obtained starting from the arylhydrazonocyclohexan-1,3-dione followed by their heterocyclization reactions to produce anticancer target molecules. The arylhydrazone derivatives 3a-c underwent different heterocyclization reactions to produce thiophene, thiazole, pyrazole and 1,2,4-triazine derivatives. The anti-proliferative activity of twenty six compounds among the synthesized compounds toward the six cancer cell lines namely A549, H460, HT-29, MKN-45, U87MG, and SMMC-7721 was studied. Anti-proliferative evaluations, tyrosine and Pim-1 kinase inhibitions were perform for most of the synthesized compounds where the varieties of substituent through the aryl ring and the thiophene moiety afforded compounds with high activities. The compounds with high anti-proliferative activity towards the cancer cell lines showed that compounds 3b, 3c, 5e, 5f, 8c, 9c, 11c, 12c, 14e, 14f and 16c were the most cytotoxic compounds. Further tests of the latter compounds toward the five tyrosine kinases c-Kit, Flt-3, VEGFR-2, EGFR, and PDGFR and Pim-1 kinase showed that compounds 3c, 5e, 5f, 8c, 9c, 12c, 14e, 14f and 16c were the most potent of the tested compounds toward the five tyrosine kinases and compounds 6d, 11a, 20b and 21e were of the highest inhibitions towards Pim-1 kinase. Pan Assay Interference Compounds (PAINS) for the most cytotoxic compounds showed zero PAINS alert and can be used as lead compounds.

MolAICal: a soft tool for 3D drug design of protein targets by artificial intelligence and classical algorithm.

Deep learning is an important branch of artificial intelligence that has been successfully applied into medicine and two-dimensional ligand design. The three-dimensional (3D) ligand generation in the 3D pocket of protein target is an interesting and challenging issue for drug design by deep learning. Here, the MolAICal software is introduced to supply a way for generating 3D drugs in the 3D pocket of protein targets by combining with merits of deep learning model and classical algorithm. The MolAICal software mainly contains two modules for 3D drug design. In the first module of MolAICal, it employs the genetic algorithm, deep learning model trained by FDA-approved drug fragments and Vinardo score fitting on the basis of PDBbind database for drug design. In the second module, it uses deep learning generative model trained by drug-like molecules of ZINC database and molecular docking invoked by Autodock Vina automatically. Besides, the Lipinski’s rule of five, Pan-assay interference compounds (PAINS), synthetic accessibility (SA) and other user-defined rules are introduced for filtering out unwanted ligands in MolAICal. To show the drug design modules of MolAICal, the membrane protein glucagon receptor and non-membrane protein SARS-CoV-2 main protease are chosen as the investigative drug targets. The results show MolAICal can generate the various and novel ligands with good binding scores and appropriate XLOGP values. We believe that MolAICal can use the advantages of deep learning model and classical programming for designing 3D drugs in protein pocket. MolAICal is freely for any nonprofit purpose and accessible at https://molaical.github.io.

Antibacterial azole derivatives: Antibacterial activity, cytotoxicity, and in silico mechanistic studies.

Azole antifungal drugs are commonly used in antifungal chemotherapy. Antibacterial effects of some topical antifungals, such as miconazole and econazole, have lately been revealed, which suggests a promising venue in antimicrobial chemotherapy. In this study, we tested an in-house azole collection with antifungal properties for their antibacterial activity to identify dual-acting hits using the broth microdilution method. The in vitro screen yielded a number of potent derivatives against gram-positive bacteria, Enterococcus faecalis and Staphylococcus aureus. Compound 73's minimum inhibitory concentration (MIC) value less than 1 μg/ml against S. aureus; however, none of the compounds showed noteworthy activity against methicillin-resistant S. aureus (MRSA). All the active compounds were found safe at their MIC values against the healthy fibroblast cells in the in vitro cytotoxicity test. Molecular docking studies of the most active compounds using a set of docking programs with flavohemoglobin (flavoHb) structure, the proposed target of the azole antifungals with antibacterial activity, presented striking similarities regarding the binding modes and interactions between the tested compounds and the antifungal drugs with crystallographic data. In addition to being noncytotoxic, the library was predicted to be drug-like and free of pan-assay interference compounds (PAINS). As a result, the current study revealed several potential azole derivatives with both antifungal and antibacterial activities. Inhibition of bacterial flavoHb was suggested as a possible mechanism of action for the title compounds.

Analysis of Nuisance Substructures and Aggregators in a Comprehensive Database of Food Chemical Compounds.

The mechanistic understanding of the biological effects of foods involves the testing of food compounds in biochemical and biological assays. Positive results in these assays can be artifactual due to some properties of the compound: namely chemical reactivity, membrane disruption, redox cycling, etc., or through the formation of colloidal aggregates. Within the drug discovery field, a wide set of so-called "nuisance" filters have been developed to identify substructures prone to assay artifacts and/or promiscuity, e.g., the pan-assay interference compounds (PAINS) and others. In the subarea of natural products, a similar concept is the so-called invalid metabolic panaceas (IMPs). Finally, tools to identify putative aggregators have also been developed. Here, we analyzed the presence of nuisance substructures, IMPs, and aggregators in a large database of food compounds (the FooDB), which should be useful to the researchers working in the field, in order to be aware of possible artifact/promiscuity issues in their assays.

Development of Functional Screens for Dietary Angiogenesis Inhibitors

Abstract Objectives We sought to develop a workflow to evaluate the anti-angiogenic potential of dietary agents in a stringent, systemic manner: 1) in vitro inhibition of angiogenesis, 2) in vivo testing of normal angiogenesis inhibition, and 3) in vivo testing of tumor prevention. Methods We used a tiered workflow for assessment of anti-angiogenic potential of dietary compounds, beginning with cell culture methods, moving to high-throughput D. rerio angiogenesis modeling and finally mouse models of angiogenesis and tumor development to identify potent dietary agents which block tumor angiogenesis. Results We identified quercetin dihydrate as an orally available inhibitor of angiogenesis and our lead candidate for further evaluation for chemoprevention of angiogenesis. Quercetin blocked in vitro sprouting angiogenesis, and displayed a dose-dependent reduction in sprouting angiogenesis in the tail regeneration model in zebrafish. Finally, quercetin implanted at reported physiologic levels blocked blood vessel growth in mouse models of angiogenesis. Conclusions We describe a workflow for systematic evaluation of dietary compounds in increasing complexity models for stringent, systematic evaluation of angiogenesis inhibition. These multi-model approaches allow for filtering of pan-assay interference compounds (PAINS) prior to in vivo screening. This workflow identified quercetin as a potent inhibitor of angiogenesis which warrants further study for chemoprevention through diet. Funding Sources National Cancer Institute Division of Cancer Prevention, National Cancer Institute Center for Cancer Research.

Design of Drug-Like Protein-Protein Interaction Stabilizers Guided By Chelation-Controlled Bioactive Conformation Stabilization.

Protein-protein interactions (PPIs) of 14-3-3 proteins are a model system for studying PPI stabilization. The complex natural product Fusicoccin A stabilizes many 14-3-3 PPIs but is not amenable for use in SAR studies, motivating the search for more drug-like chemical matter. However, drug-like 14-3-3 PPI stabilizers enabling such studies have remained elusive. An X-ray crystal structure of a PPI in complex with an extremely low potency stabilizer uncovered an unexpected non-protein interacting, ligand-chelated Mg2+ leading to the discovery of metal-ion-dependent 14-3-3 PPI stabilization potency. This originates from a novel chelation-controlled bioactive conformation stabilization effect. Metal chelation has been associated with pan-assay interference compounds (PAINS) and frequent hitter behavior, but chelation can evidently also lead to true potency gains and find use as a medicinal chemistry strategy to guide compound optimization. To demonstrate this, we exploited the effect to design the first potent, selective, and drug-like 14-3-3 PPI stabilizers.