A common mechanism underlying promiscuous inhibitors from virtual and high-throughput screening

Stabilization of amyloidogenic immunoglobulin light chains by small molecules

In Ig light-chain (LC) amyloidosis (AL), the unique antibody LC protein that is secreted by monoclonal plasma cells in each patient misfolds and/or aggregates, a process leading to organ degeneration. As a step toward developing treatments for AL patients with substantial cardiac involvement who have difficulty tolerating existing chemotherapy regimens, we introduce small-molecule kinetic stabilizers of the native dimeric structure of full-length LCs, which can slow or stop the amyloidogenicity cascade at its origin. A protease-coupled fluorescence polarization-based high-throughput screen was employed to identify small molecules that kinetically stabilize LCs. NMR and X-ray crystallographic data demonstrate that at least one structural family of hits bind at the LC-LC dimerization interface within full-length LCs, utilizing variable-domain residues that are highly conserved in most AL patients. Stopping the amyloidogenesis cascade at the beginning is a proven strategy to ameliorate postmitotic tissue degeneration.

Binding Assays for Bromodomain Proteins: Their Utility in Drug Discovery in Oncology and Inflammatory Disease

Bromodomains are protein domains that recognize acetylated lysine residues and are important for recruiting a large number of protein and multiprotein complexes to sites of lysine acetylation. They play an important role in chromatin biology and are popular targets for drug discovery. Compound screening in this area requires the use of biochemical assays to assess the binding potency of potential drug candidates. Foremost among the efforts to target bromodomains are those aimed at identifying compounds that interact with the bromodomain and extra-terminal domain (BET) family of bromodomain-containing proteins (BRD2, BRD3, BRD4, and BRDT). Inhibitors of these proteins are under clinical development for a large variety of oncologic indications. Described in this unit are several assays to assess the binding potency and selectivity within the BET protein family. Included are AlphaScreen, fluorescence polarization, and thermal shift assays. The strengths and weaknesses of each assay are discussed. © 2018 by John Wiley & Sons, Inc.

The Light and Dark Sides of Virtual Screening: What Is There to Know?

Virtual screening consists of using computational tools to predict potentially bioactive compounds from files containing large libraries of small molecules. Virtual screening is becoming increasingly popular in the field of drug discovery as in silico techniques are continuously being developed, improved, and made available. As most of these techniques are easy to use, both private and public organizations apply virtual screening methodologies to save resources in the laboratory. However, it is often the case that the techniques implemented in virtual screening workflows are restricted to those that the research team knows. Moreover, although the software is often easy to use, each methodology has a series of drawbacks that should be avoided so that false results or artifacts are not produced. Here, we review the most common methodologies used in virtual screening workflows in order to both introduce the inexperienced researcher to new methodologies and advise the experienced researcher on how to prevent common mistakes and the improper usage of virtual screening methodologies.

The Light and Dark Sides of Virtual Screening: What Is There to Know?

Virtual screening consists of using computational tools to predict potentially bioactive compounds from files containing large libraries of small molecules. Virtual screening is becoming increasingly popular in the field of drug discovery as in silico techniques are continuously being developed, improved, and made available. As most of these techniques are easy to use, both private and public organizations apply virtual screening methodologies to save resources in the laboratory. However, it is often the case that the techniques implemented in virtual screening workflows are restricted to those that the research team knows. Moreover, although the software is often easy to use, each methodology has a series of drawbacks that should be avoided so that false results or artifacts are not produced. Here, we review the most common methodologies used in virtual screening workflows in order to both introduce the inexperienced researcher to new methodologies and advise the experienced researcher on how to prevent common mistakes and the improper usage of virtual screening methodologies.

Small Molecules Targeting the Flavivirus E Protein with Broad-Spectrum Activity and Antiviral Efficacy in Vivo

Vaccines and antivirals to combat dengue, Zika, and other flavivirus pathogens present a major, unmet medical need. Vaccine development has been severely challenged by the antigenic diversity of these viruses and the propensity of non-neutralizing, cross-reactive antibodies to facilitate cellular infection and increase disease severity. As an alternative, direct-acting antivirals targeting the flavivirus envelope protein, E, have the potential to act via an analogous mode of action without the risk of antibody-dependent enhancement of infection and disease. We previously discovered that structurally diverse small molecule inhibitors of the dengue virus E protein exhibit varying levels of antiviral activity against other flaviviruses in cell culture. Here, we demonstrate that the broad-spectrum activity of several cyanohydrazones against dengue, Zika, and Japanese encephalitis viruses is due to specific inhibition of E-mediated membrane fusion during viral entry and provide proof of concept for pharmacological inhibition of E as an antiviral strategy in vivo.

Ultra-large library docking for discovering new chemotypes

Despite intense interest in expanding chemical space, libraries containing hundreds-of-millions to billions of diverse molecules have remained inaccessible. Here we investigate structure-based docking of 170 million make-on-demand compounds from 130 well-characterized reactions. The resulting library is diverse, representing over 10.7 million scaffolds that are otherwise unavailable. For each compound in the library, docking against AmpC β-lactamase (AmpC) and the D4 dopamine receptor were simulated. From the top-ranking molecules, 44 and 549 compounds were synthesized and tested for interactions with AmpC and the D4 dopamine receptor, respectively. We found a phenolate inhibitor of AmpC, which revealed a group of inhibitors without known precedent. This molecule was optimized to 77 nM, which places it among the most potent non-covalent AmpC inhibitors known. Crystal structures of this and other AmpC inhibitors confirmed the docking predictions. Against the D4 dopamine receptor, hit rates fell almost monotonically with docking score, and a hit-rate versus score curve predicted that the library contained 453,000 ligands for the D4 dopamine receptor. Of 81 new chemotypes discovered, 30 showed submicromolar activity, including a 180-pM subtype-selective agonist of the D4 dopamine receptor.

Promiscuous Ligands from Experimentally Determined Structures, Binding Conformations, and Protein Family-Dependent Interaction Hotspots

Compound promiscuity is often attributed to nonspecific binding or assay artifacts. On the other hand, it is well-known that many pharmaceutically relevant compounds are capable of engaging multiple targets in vivo, giving rise to polypharmacology. To explore and better understand promiscuous binding characteristics of small molecules, we have searched X-ray structures (and very few qualifying solution structures) for ligands that bind to multiple distantly related or unrelated target proteins. Experimental structures of a given ligand bound to different targets represent high-confidence data for exploring promiscuous binding events. A total of 192 ligands were identified that formed crystallographic complexes with proteins from different families and for which activity data were available. These "multifamily" compounds included endogenous ligands and were often more polar than other bound compounds and active in the submicromolar range. Unexpectedly, many promiscuous ligands displayed conserved or similar binding conformations in different active sites. Others were found to conformationally adjust to binding sites of different architectures. A comprehensive analysis of ligand-target interactions revealed that multifamily ligands frequently formed different interaction hotspots in binding sites, even if their bound conformations were similar, thus providing a rationale for promiscuous binding events at the molecular level of detail. As a part of this work, all multifamily ligands we have identified and associated activity data are made freely available.

Resonant waveguide grating based assays for colloidal aggregate detection and promiscuity characterization in natural products

Small molecules, including natural compounds, in aqueous buffer that self-associate into colloidal aggregates is the main cause of false results in the early stage of drug discovery. Here we reported resonant waveguide grating (RWG) based assays to identify natural compound aggregation and characterize its influence on membrane receptors in living cells. We first applied a cell-free aggregation assay to determine compound critical aggregation concentration (CAC) values. Then we characterized the aggregators' influence on membrane receptors using three types of dynamic mass redistribution (DMR) assays. Results showed that colloidal aggregates may cause false activity in DMR desensitization assays; some of the false activities can be implied by the large response in DMR agonism assays and can further be identified by DMR antagonism assays. Furthermore, the aggregation mechanism was confirmed by addition of 0.025% tween-80, with cell signals attenuated and potency decreased. Finally, these observations were used for aggregate examination and promiscuity investigation of a traditional herbal medicine, Rhodiola rosea, which ultimately led to the revealing of the true target and reduced the risk of a bioactivity tracking process at the very first stage. This study highlights that the RWG based assays can be used as practical tools to distinguish between real and false hits to provide reliable results in the early stage of drug discovery.

Resonant waveguide grating based assays to eliminate colloidal aggregate induced false activity involving natural products.

How to Prepare a Compound Collection Prior to Virtual Screening

Virtual screening is a well-established technique that has proven to be successful in the identification of novel biologically active molecules, including drug repurposing. Whether for ligand-based or for structure-based virtual screening, a chemical collection needs to be properly processed prior to in silico evaluation. Here we describe our step-by-step procedure for handling very large collections (up to billions) of compounds prior to virtual screening.

Assessing molecular interactions with biophysical methods using the validation cross

There are numerous methods for studying molecular interactions. However, each method gives rise to false negative- or false positive binding results, stemming from artifacts of the scientific equipment or from shortcomings of the experimental format. To validate an initial positive binding result, additional methods need to be applied to cover the shortcomings of the primary experiment. The aim of such a validation procedure is to exclude as many artifacts as possible to confirm that there is a true molecular interaction that meets the standards for publishing or is worth investing considerable resources for follow-up activities in a drug discovery project. To simplify this validation process, a graphical scheme — the validation cross — can be used. This simple graphic is a powerful tool for identifying blind spots of a binding hypothesis, for selecting the most informative combination of methods to reveal artifacts and, in general, for understanding more thoroughly the nature of a validation process. The concept of the validation cross was originally introduced for the validation of protein–ligand interactions by NMR in drug discovery. Here, an attempt is made to expand the concept to further biophysical methods and to generalize it for binary molecular interactions.

Celastrol Promotes Weight Loss in Diet-Induced Obesity by Inhibiting the Protein Tyrosine Phosphatases PTP1B and TCPTP in the Hypothalamus

Celastrol is a natural pentacyclic triterpene used in traditional Chinese medicine with significant weight-lowering effects. Celastrol-administered mice at 100 μg/kg decrease food consumption and body weight via a leptin-dependent mechanism, yet its molecular targets in this pathway remain elusive. Here, we demonstrate in vivo that celastrol-induced weight loss is largely mediated by the inhibition of leptin negative regulators protein tyrosine phosphatase (PTP) 1B (PTP1B) and T-cell PTP (TCPTP) in the arcuate nucleus (ARC) of the hypothalamus. We show in vitro that celastrol binds reversibly and inhibits noncompetitively PTP1B and TCPTP. NMR data map the binding site to an allosteric site in the catalytic domain that is in proximity of the active site. By using a panel of PTPs implicated in hypothalamic leptin signaling, we show that celastrol additionally inhibited PTEN and SHP2 but had no activity toward other phosphatases of the PTP family. These results suggest that PTP1B and TCPTP in the ARC are essential for celastrol's weight lowering effects in adult obese mice.

Development of a high-content imaging assay for screening compound aggregation

Aggregated compounds can promiscuously and nonspecifically associate with proteins resulting in either false inhibition or activation of many different protein target classes. We developed a high-content imaging assay in a 384-well format using fluorescently labeled target proteins and an Operetta cell imager to screen for compound aggregates that interact with target proteins. The high-throughput assay can not only directly detect the interaction between compound aggregators and the target of interest, but also determine the critical aggregation concentration (CAC) of a given promiscuous small molecule.

Discovery of Immunologically Inspired Small Molecules That Target the Viral Envelope Protein

Dengue virus is a major human pathogen that infects over 390 million people annually leading to approximately 500 000 hospitalizations due to severe dengue. Since the only marketed vaccine, Dengvaxia, has recently been shown to increase disease severity in those lacking natural immunity, antivirals to prevent or treat dengue  infection represent a large, unmet medical need. Small molecules that target the dengue virus envelope protein, E, on the surface of the virion could act analogously to antibodies by engaging E extracellularly to block infection; however, a shortage of target-based assays suitable for screening and medicinal chemistry studies has limited efforts in this area. Here we demonstrate that the dengue E protein offers a tractable drug target for preventing dengue infection by developing a target-based assay using a recombinantly expressed dengue serotype 2 E protein. We performed a high-throughput screen of ∼20 000 compounds followed by secondary assays to confirm target-binding and antiviral activity and counter-screens to exclude compounds with nonspecific activities. These efforts yielded eight distinct chemical leads that inhibit dengue infection by binding to E and preventing E-mediated membrane fusion with potencies equal to or greater than previously described small molecule inhibitors of E. We show that a subset of these compounds inhibit viruses representative of the other three dengue serotypes and Zika virus. This work provides tools for discovery and optimization of direct-acting antivirals against dengue E and shows that this approach may be useful in developing antivirals with broad-spectrum activity against other flavivirus pathogens.

Triaryl Pyrazole Toll-Like Receptor Signaling Inhibitors: Structure-Activity Relationships Governing Pan- and Selective Signaling Inhibitors

The immune system uses members of the toll-like receptor (TLR) family to recognize a variety of pathogen- and host-derived molecules in order to initiate immune responses. Although TLR-mediated, pro-inflammatory immune responses are essential for host defense, prolonged and exaggerated activation can result in inflammation pathology that manifests in a variety of diseases. Therefore, small-molecule inhibitors of the TLR signaling pathway might have promise as anti-inflammatory drugs. We previously identified a class of triaryl pyrazole compounds that inhibit TLR signaling by modulation of the protein-protein interactions essential to the pathway. We have now systematically examined the structural features essential for inhibition of this pathway, revealing characteristics of compounds that inhibited all TLRs tested (pan-TLR signaling inhibitors) as well as compounds that selectively inhibited certain TLRs. These findings reveal interesting classes of compounds that could be optimized for particular inflammatory diseases governed by different TLRs.

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.

Be Aware of Aggregators in the Search for Potential Human ecto-5'-Nucleotidase Inhibitors

Promiscuous inhibition due to aggregate formation has been recognized as a major concern in drug discovery campaigns. Here, we report some aggregators identified in a virtual screening (VS) protocol to search for inhibitors of human ecto-5′-nucleotidase (ecto-5′-NT/CD73), a promising target for several diseases and pathophysiological events, including cancer, inflammation and autoimmune diseases. Four compounds (A, B, C and D), selected from the ZINC-11 database, showed IC₅₀ values in the micromolar range, being at the same time computationally predicted as potential aggregators. To confirm if they inhibit human ecto-5′-NT via promiscuous mechanism, forming aggregates, enzymatic assays were done in the presence of 0.01% (v/v) Triton X-100 and an increase in the enzyme concentration by 10-fold. Under both experimental conditions, these four compounds showed a significant decrease in their inhibitory activities. To corroborate these findings, turbidimetric assays were performed, confirming that they form aggregate species. Additionally, aggregation kinetic studies were done by dynamic light scattering (DLS) for compound C. None of the identified aggregators has been previously reported in the literature. For the first time, aggregation and promiscuous inhibition issues were systematically studied and evaluated for compounds selected by VS as potential inhibitors for human ecto-5′-NT. Together, our results reinforce the importance of accounting for potential false-positive hits acting by aggregation in drug discovery campaigns to avoid misleading assay results.

Modeling Small-Molecule Reactivity Identifies Promiscuous Bioactive Compounds

Scientists rely on high-throughput screening tools to identify promising small-molecule compounds for the development of biochemical probes and drugs. This study focuses on the identification of promiscuous bioactive compounds, which are compounds that appear active in many high-throughput screening experiments against diverse targets but are often false-positives which may not be easily developed into successful probes. These compounds can exhibit bioactivity due to nonspecific, intractable mechanisms of action and/or by interference with specific assay technology readouts. Such "frequent hitters" are now commonly identified using substructure filters, including pan assay interference compounds (PAINS). Herein, we show that mechanistic modeling of small-molecule reactivity using deep learning can improve upon PAINS filters when modeling promiscuous bioactivity in PubChem assays. Without training on high-throughput screening data, a deep learning model of small-molecule reactivity achieves a sensitivity and specificity of 18.5% and 95.5%, respectively, in identifying promiscuous bioactive compounds. This performance is similar to PAINS filters, which achieve a sensitivity of 20.3% at the same specificity. Importantly, such reactivity modeling is complementary to PAINS filters. When PAINS filters and reactivity models are combined, the resulting model outperforms either method alone, achieving a sensitivity of 24% at the same specificity. However, as a probabilistic model, the sensitivity and specificity of the deep learning model can be tuned by adjusting the threshold. Moreover, for a subset of PAINS filters, this reactivity model can help discriminate between promiscuous and nonpromiscuous bioactive compounds even among compounds matching those filters. Critically, the reactivity model provides mechanistic hypotheses for assay interference by predicting the precise atoms involved in compound reactivity. Overall, our analysis suggests that deep learning approaches to modeling promiscuous compound bioactivity may provide a complementary approach to current methods for identifying promiscuous compounds.

Mechanism of Selective Enzyme Inhibition through Uncompetitive Regulation of an Allosteric Agonist

Classical uncompetitive inhibitors are potent pharmacological modulators of enzyme function. Since they selectively target enzyme-substrate complexes (E:S), their inhibitory potency is amplified by increasing substrate concentrations. Recently, an unconventional uncompetitive inhibitor, called CE3F4R, was discovered for the exchange protein activated by cAMP isoform 1 (EPAC1). Unlike conventional uncompetitive inhibitors, CE3F4R is uncompetitive with respect to an allosteric effector, cAMP, as opposed to the substrate (i.e., CE3F4R targets the E:cAMP rather than the E:S complex). However, the mechanism of CE3F4R as an uncompetitive inhibitor is currently unknown. Here, we elucidate the mechanism of CE3F4R's action using NMR spectroscopy. Due to limited solubility and line broadening, which pose major challenges for traditional structural determination approaches, we resorted to a combination of protein- and ligand-based NMR experiments to comparatively analyze EPAC mutations, inhibitor analogs, and cyclic nucleotide derivatives that trap EPAC at different stages of activation. We discovered that CE3F4R binds within the EPAC cAMP-binding domain (CBD) at a subdomain interface distinct from the cAMP binding site, acting as a wedge that stabilizes a cAMP-bound mixed-intermediate. The mixed-intermediate includes attributes of both the apo/inactive and cAMP-bound/active states. In particular, the intermediate targeted by CE3F4R traps a CBD's hinge helix in its inactive conformation, locking EPAC into a closed domain topology that restricts substrate access to the catalytic domain. The proposed mechanism of action also explains the isoform selectivity of CE3F4R in terms of a single EPAC1 versus EPAC2 amino acid difference that destabilizes the active conformation of the hinge helix.

Feature optimization in high dimensional chemical space: statistical and data mining solutions

Objectives

The primary goal of this experiment is to prioritize molecular descriptors that control the activity of active molecules that could reduce the dimensionality produced during the virtual screening process. It also aims to: (1) develop a methodology for sampling large datasets and the statistical verification of the sampling process, (2) apply screening filter to detect molecules with polypharmacological or promiscuous activity.

Results

Sampling from large a dataset and its verification were done by applying Z-test. Molecular descriptors were prioritized using principal component analysis (PCA) by eliminating the least influencing ones. The original dimensions were reduced to one-twelfth by the application of PCA. There was a significant improvement in statistical parameter values of virtual screening model which in turn resulted in better screening results. Further improvement of screened results was done by applying Eli Lilly MedChem rules filter that removed molecules with polypharmacological or promiscuous activity. It was also shown that similarities in the activity of compounds were due to the molecular descriptors which were not apparent in prima facie structural studies.

Electronic supplementary material

The online version of this article (10.1186/s13104-018-3535-y) contains supplementary material, which is available to authorized users.

The A-Z of Zika drug discovery

Despite the recent outbreak of Zika virus (ZIKV), there are still no approved treatments, and early-stage compounds are probably many years away from approval. A comprehensive A-Z review of the recent advances in ZIKV drug discovery efforts is presented, highlighting drug repositioning and computationally guided compounds, including discovered viral and host cell inhibitors. Promising ZIKV molecular targets are also described and discussed, as well as targets belonging to the host cell, as new opportunities for ZIKV drug discovery. All this knowledge is not only crucial to advancing the fight against the Zika virus and other flaviviruses but also helps us prepare for the next emerging virus outbreak to which we will have to respond.

cat-ELCCA: catalyzing drug discovery through click chemistry

Click chemistry has emerged as a powerful tool in our arsenal for unlocking new biology. This includes its utility in both chemical biology and drug discovery. An emerging application of click chemistry is in the development of biochemical assays for high-throughput screening to identify new chemical probes and drug leads. This Feature Article will discuss the advancements in click chemistry that were necessary for the development of a new class of biochemical assay, catalytic enzyme-linked click chemistry assay or cat-ELCCA. Inspired by enzyme immunoassays, cat-ELCCA was designed as a click chemistry-based amplification assay where bioorthogonally-tagged analytes and enzymes are used in place of the enzyme-linked secondary antibodies used in immunoassays. The result is a robust assay format with demonstrated applicability in several important areas of biology and drug discovery, including post-translational modifications, pre-microRNA maturation, and protein-protein and RNA-protein interactions. Through the use of cat-ELCCA and other related click chemistry-based assays, new chemical probes for interrogating promising drug targets have been discovered. These examples will be discussed, in addition to a future outlook on the impact of this approach in probe and drug discovery.

Targeting a hidden site on class A beta-lactamases

Increasing resistance against available orthosteric beta-lactamase inhibitors necessitates the search for novel and powerful inhibitor molecules. In this respect, allosteric inhibitors serve as attractive alternatives. Here, we examine the structural basis of inhibition in a hidden, druggable pocket in TEM-1 beta-lactamase. Based on crystallographic evidence that 6-cyclohexyl-1-hexyl-β-D-maltoside (CYMAL-6) binds to this site, first we determined the kinetic mechanism of inhibition by CYMAL-6. Activity measurements with CYMAL-6 showed that it competitively inhibits the wild type enzyme. Interestingly, it exhibits a steep dose-response curve with an IC50 of 100 μM. The IC50 value changes neither with different enzyme concentration nor with incubation of the enzyme with the inhibitor, showing that inhibition is not aggregation-based. The presence of the same concentrations of CYMAL-6 does not influence the activity of lactate dehydrogenase, further confirming the specificity of CYMAL-6 for TEM-1 beta-lactamase. Then, we identified compounds with high affinity to this allosteric site by virtual screening using Glide and Schrödinger Suite. Virtual screening performed with 500,000 drug like compounds from the ZINC database showed that top scoring compounds interact with the hydrophobic pocket that forms between H10 and H11 helices and with the catalytically important Arg244 residue through pi-cation interactions. Discovery of novel chemical scaffolds that target this allosteric site will pave the way for a new avenue in the design of new antimicrobials.

Determination of Affinity and Residence Time of Potent Drug-Target Complexes by Label-free Biosensing

Prolonged drug-target occupancy has become increasingly important in lead optimization, and biophysical assays that measure residence time are in high demand. Here we report a practical label-free assay methodology that provides kinetic and affinity measurements suitable for most target classes without long preincubations and over comparatively short sample contact times. The method, referred to as a "chaser" assay, has been applied to three sets of unrelated kinase/inhibitor panels in order to measure the residence times, where correlation with observed efficacy was suspected. A lower throughput chaser assay measured a residence time of 3.6 days ±3.4% (95% CI) and provided single digit pM sensitivity. A higher throughput chaser methodology enabled a maximum capacity of 108 compounds in duplicate/day with an upper residence time limit of 9 h given an assay dissociation time of 34 min.

Extracting Compound Profiling Matrices from Screening Data

Compound profiling matrices record assay results for compound libraries tested against panels of targets. In addition to their relevance for exploring structure-activity relationships, such matrices are of considerable interest for chemoinformatic and chemogenomic applications. For example, profiling matrices provide a valuable data resource for the development and evaluation of machine learning approaches for multitask activity prediction. However, experimental compound profiling matrices are rare in the public domain. Although they are generated in pharmaceutical settings, they are typically not disclosed. Herein, we present an algorithm for the generation of large profiling matrices, for example, containing more than 100 000 compounds exhaustively tested against 50 to 100 targets. The new methodology is a variant of biclustering algorithms originally introduced for large-scale analysis of genomics data. Our approach is applied here to assays from the PubChem BioAssay database and generates profiling matrices of increasing assay or compound coverage by iterative removal of entities that limit coverage. Weight settings control final matrix size by preferentially retaining assays or compounds. In addition, the methodology can also be applied to generate matrices enriched with active entries representing above-average assay hit rates.

In vitro Antichlamydial Activity of 1,2,3,5-Tetrasubstituted Pyrrole Derivatives

BACKGROUND

Chlamydia is a group of bacterial pathogens distributed worldwide that can lead to serious reproductive and other health problems. The rise of antibiotic-resistant pathogens promotes the development of novel antichlamydial agents. The aim of this study is to assess in vitro antichlamydial activity of our previously synthesized 1,2,3,5- tetrasubstituted pyrroles.

METHODS

The derivatives were screened for their antichlamydial activity against three Chlamydia strains by calculating IC50 values using concentration-response inhibition data between 1 and 32 μM. The action of the compounds on Chlamydia elementary body (EB) infectivity and the impact of the chemicals' administration time on their antichlamydial effect were evaluated to reveal the inhibitory mechanism.

RESULTS

Some of the compounds moderately inhibited the Chlamydia strains. Compound 10 exhibited the strongest inhibitory activity, with IC50 values from 4.34 to 5.83 μM. These pyrrole derivatives inhibited Chlamydia infection by reducing EB infectivity during the early stage and disturbing Chlamydia growth by targeting the early-to-middle stage prior to 12 h of the chlamydial life cycle.

CONCLUSION

Our findings highlight the potential of 1,2,3,5-tetrasubstituted pyrrole derivatives as promising lead molecules for the development of antichlamydial agents.

ALARM NMR for HTS triage and chemical probe validation

Nonspecific target engagement by test compounds and purported chemical probes is a significant source of assay interference and promiscuous bioactivity in high-throughput screening (HTS) and chemical biology. Most counter-screens for thiol-reactive compounds utilize mass spectrometry or fluorescence detection, and non-proteinaceous reporters like glutathione that may not always approximate the reactivity of protein side-chains. By contrast, a La assay to detect reactive molecules by nuclear magnetic resonance (ALARM NMR) is an industry-developed protein-based [¹H-¹³C]-heteronuclear multiple quantum coherence (HMQC) NMR counter-screen to identify nonspecific protein interactions by test compounds by reporting their tendencies to modulate the human La antigen conformation. This Current Protocol is a users-guide to the production of the ¹³C-labeled La antigen reporter protein, the reaction of test compounds with this reporter protein, as well as the collection and analysis of characteristic NMR spectra. Combined with other assay interference counter-screens, this assay will enhance chemical biology by helping researchers better prioritize chemical matter and which will increase the number of tractable HTS screening actives and aid in the development of better chemical probes.

Colloidal aggregation: from screening nuisance to formulation nuance

It is well known that small molecule colloidal aggregation is a leading cause of false positives in early drug discovery. Colloid-formers are diverse and well represented among corporate and academic screening decks, and even among approved drugs. Less appreciated is how colloid formation by drug-like compounds fits into the wider understanding of colloid physical chemistry. Here we introduce the impact that colloidal aggregation has had on early drug discovery, and then turn to the physical and thermodynamic driving forces for small molecule colloidal aggregation, including the particulate nature of the colloids, their critical aggregation concentration-governed formation, their mechanism of protein adsorption and subsequent inhibition, and their sensitivity to detergent. We describe methods that have been used extensively to both identify aggregate-formers and to study and control their physical chemistry. While colloidal aggregation is widely recognized as a problem in early drug discovery, we highlight the opportunities for exploiting this phenomenon in biological milieus and for drug formulation.

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.

Structure-based discovery of selective positive allosteric modulators of antagonists for the M2 muscarinic acetylcholine receptor

The orthosteric binding sites of the five muscarinic acetylcholine receptor (mAChR) subtypes are highly conserved, making the development of selective antagonists challenging. The allosteric sites of these receptors are more variable, allowing one to imagine allosteric modulators that confer subtype selectivity, which would reduce the major off-target effects of muscarinic antagonists. Accordingly, a large library docking campaign was prosecuted seeking unique positive allosteric modulators (PAMs) for antagonists, ultimately revealing a PAM that substantially potentiates antagonist binding leading to subtype selectivity at the M₂ mAChR. This study supports the feasibility of discovering PAMs that can convert an armamentarium of potent but nonselective G-protein–coupled receptor (GPCR) antagonist drugs into subtype-selective reagents.

Subtype-selective antagonists for muscarinic acetylcholine receptors (mAChRs) have long been elusive, owing to the highly conserved orthosteric binding site. However, allosteric sites of these receptors are less conserved, motivating the search for allosteric ligands that modulate agonists or antagonists to confer subtype selectivity. Accordingly, a 4.6 million-molecule library was docked against the structure of the prototypical M₂ mAChR, seeking molecules that specifically stabilized antagonist binding. This led us to identify a positive allosteric modulator (PAM) that potentiated the antagonist N-methyl scopolamine (NMS). Structure-based optimization led to compound ’628, which enhanced binding of NMS, and the drug scopolamine itself, with a cooperativity factor (α) of 5.5 and a K_B of 1.1 μM, while sparing the endogenous agonist acetylcholine. NMR spectral changes determined for methionine residues reflected changes in the allosteric network. Moreover, ’628 slowed the dissociation rate of NMS from the M₂ mAChR by 50-fold, an effect not observed at the other four mAChR subtypes. The specific PAM effect of ’628 on NMS antagonism was conserved in functional assays, including agonist stimulation of [³⁵S]GTPγS binding and ERK 1/2 phosphorylation. Importantly, the selective allostery between ’628 and NMS was retained in membranes from adult rat hypothalamus and in neonatal rat cardiomyocytes, supporting the physiological relevance of this PAM/antagonist approach. This study supports the feasibility of discovering PAMs that confer subtype selectivity to antagonists; molecules like ’628 can convert an armamentarium of potent but nonselective GPCR antagonist drugs into subtype-selective reagents, thus reducing their off-target effects.

A printable hydrogel microarray for drug screening avoids false positives associated with promiscuous aggregating inhibitors

A significant problem in high-throughput drug screening is the disproportionate number of false hits associated with drug candidates that form colloidal aggregates. Such molecules, referred to as promiscuous inhibitors, nonspecifically inhibit multiple enzymes and are thus not useful as potential drugs. Here, we report a printable hydrogel-based drug-screening platform capable of non-ambiguously differentiating true enzyme inhibitors from promiscuous aggregating inhibitors, critical for accelerating the drug discovery process. The printed hydrogels can both immobilize as well as support the activity of entrapped enzymes against drying or treatment with a protease or chemical denaturant. Furthermore, the printed hydrogel can be applied in a high-throughput microarray-based screening platform (consistent with current practice) to rapidly ( <25 min) and inexpensively identify only clinically promising lead compounds with true inhibitory potential as well as to accurately quantify the dose–response relationships of those inhibitors, all while using 95% less sample than required for a solution assay.

False positive results significantly slow down the drug discovery process. Here, the authors developed a gel serving as a screening platform in which enzymes can be stored, stabilized, and protected from most of the compounds that typically cause these misleading results.

Rce1: mechanism and inhibition

Ras converting enzyme 1 (Rce1) is an integral membrane endoprotease localized to the endoplasmic reticulum that mediates the cleavage of the carboxyl-terminal three amino acids from CaaX proteins, whose members play important roles in cell signaling processes. Examples include the Ras family of small GTPases, the γ-subunit of heterotrimeric GTPases, nuclear lamins, and protein kinases and phosphatases. CaaX proteins, especially Ras, have been implicated in cancer, and understanding the post-translational modifications of CaaX proteins would provide insight into their biological function and regulation. Many proteolytic mechanisms have been proposed for Rce1, but sequence alignment, mutational studies, topology, and recent crystallographic data point to a novel mechanism involving a glutamate-activated water and an oxyanion hole. Studies using in vivo and in vitro reporters of Rce1 activity have revealed that the enzyme cleaves only prenylated substrates and the identity of the a₂ amino residue in the Ca₁a₂X sequence is most critical for recognition, preferring Ile, Leu, or Val. Substrate mimetics can be somewhat effective inhibitors of Rce1 in vitro. Small-molecule inhibitor discovery is currently limited by the lack of structural information on a eukaryotic enzyme, but a set of 8-hydroxyquinoline derivatives has demonstrated an ability to mislocalize all three mammalian Ras isoforms, giving optimism that potent, selective inhibitors might be developed. Much remains to be discovered regarding cleavage specificity, the impact of chemical inhibition, and the potential of Rce1 as a therapeutic target, not only for cancer, but also for other diseases.

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.

X-ray-Structure-Based Identification of Compounds with Activity against Targets from Different Families and Generation of Templates for Multitarget Ligand Design

Compounds with multitarget activity (promiscuity) are increasingly sought in drug discovery. However, promiscuous compounds are often viewed controversially in light of potential assay artifacts that may give rise to false-positive activity annotations. We have reasoned that the strongest evidence for true multitarget activity of small molecules would be provided by experimentally determined structures of ligand-target complexes. Therefore, we have carried out a systematic search of currently available X-ray structures for compounds forming complexes with different targets. Rather unexpectedly, 1418 such crystallographic ligands were identified, including 702 that formed complexes with targets from different protein families (multifamily ligands). About half of these multifamily ligands originated from the medicinal chemistry literature, making it possible to consider additional target annotations and search for analogues. From 168 distinct series of analogues containing one or more multifamily ligands, 133 unique analogue-series-based scaffolds were isolated that can serve as templates for the design of new compounds with multitarget activity. As a part of our study, all of the multifamily ligands we have identified and the analogue-series-based scaffolds are made freely available.

Reconstitution of Staphylococcus aureus Lipoteichoic Acid Synthase Activity Identifies Congo Red as a Selective Inhibitor

Lipoteichoic acid (LTA) is an anionic surface polymer that is essential for normal growth of Staphylococcus aureus, making the LTA polymerase, LTA synthase (LtaS), a proposed drug target for combating Staphylococcal infections. LtaS is a polytopic membrane protein with five membrane-spanning helices and an extracellular domain, and it uses phosphatidylglycerol to assemble a glycerol phosphate chain on a glycosylated diacylglycerol membrane anchor. We report here the first reconstitution of LtaS polymerization activity and show that the azo dye Congo red inhibits this enzyme both in vitro and in cells. Related azo dyes and the previously reported LtaS inhibitor 1771 have weak or no in vitro inhibitory activity. Synthetic lethality with mutant strains known to be nonviable in the absence of LTA confirms selective inhibition by Congo red. As the only validated LtaS inhibitor, Congo red can serve as a probe to understand how inhibiting lipoteichoic acid biosynthesis affects cell physiology and may also guide the discovery of more potent inhibitors for use in treating S. aureus infections.