Pan-assay interference compounds (PAINS) that may not be too painful for chemical biology projects

Design and Diversity Analysis of Chemical Libraries in Drug Discovery

Chemical libraries and compound data sets are among the main inputs to start the drug discovery process at universities, research institutes, and the pharmaceutical industry. The approach used in the design of compound libraries, the chemical information they possess, and the representation of structures, play a fundamental role in the development of studies: chemoinformatics, food informatics, in silico pharmacokinetics, computational toxicology, bioinformatics, and molecular modeling to generate computational hits that will continue the optimization process of drug candidates. The prospects for growth in drug discovery and development processes in chemical, biotechnological, and pharmaceutical companies began a few years ago by integrating computational tools with artificial intelligence methodologies. It is anticipated that it will increase the number of drugs approved by regulatory agencies shortly.

Terminators or Guardians? Design, Synthesis, and Cytotoxicity Profiling of Chalcone-Sulfonamide Hybrids

With a "less is more" philosophy, a series of 15 chalcone-sulfonamide hybrids were designed anticipating synergistic anticancer activity. The aromatic sulfonamide moiety was included as a known direct inhibitor of carbonic anhydrase IX activity through its zinc chelating property. The chalcone moiety was incorporated as an electrophilic stressor to indirectly inhibit carbonic anhydrase IX cellular activity. Screening by the Developmental Therapeutics Program of the National Cancer Institute, NCI-60, revealed that 12 derivatives were potent inhibitors of cancer cell growth in multiple cell lines and were promoted to the five-dose screen. The cancer cell growth inhibition profile indicated sub- to two-digit micromolar potency (GI₅₀ down to 0.3 μM and LC₅₀ as low as 4 μM) against colorectal carcinoma cells, in particular. Unexpectedly, most compounds demonstrated low to moderate potency as direct inhibitors of carbonic anhydrase catalytic activity in vitro, with 4d being the most potent, having an average Ki value of 4 μM. Compound 4j showed ca. six-fold selectivity to carbonic anhydrase IX over the other tested isoforms in vitro. Cytotoxicity of both 4d and 4j in live HCT116, U251, and LOX IMVI cells under hypoxic conditions confirmed their targeting of carbonic anhydrase activity. Elevation of oxidative cellular stress was stipulated from the increase in Nrf2 and ROS levels in 4j-treated colorectal carcinoma, HCT116, cells compared to the control. Compound 4j arrested the cell cycle of HCT116 cells at the G1/S phase. In addition, both 4d and 4j showed up to 50-fold cancer cell selectivity compared to the non-cancerous HEK293T cells. Accordingly, this study presents 4d and 4j being new, synthetically accessible, simplistically designed derivatives as potential candidates to be further developed as anticancer therapeutics.

A new ChEMBL dataset for the similarity-based target fishing engine FastTargetPred: Annotation of an exhaustive list of linear tetrapeptides

Drug discovery often requires the identification of off-targets as the binding of a compound to targets other than the intended target(s) can be beneficial in some cases or detrimental in other situations (e.g., binding to anti-targets). Such investigations are also of importance during the early stage of a project, for example when the target is not known (e.g., phenotypic screening). Target identification can be performed in-vitro, but various in-silico methods have also been developed in recent years to facilitate target identification and help generate ideas. FastTargetPred is one such approach, it is a freely available Python/C program that attempts to predict putative macromolecular targets (i.e., target fishing) for a single input small molecule query or an entire compound collection using established chemical similarity search approaches. Indeed, the putative macromolecular target(s) of a small chemical compound can be predicted by identifying ligands that are known experimentally to bind to some targets and that are structurally similar to the input query chemical compound. Therefore, this type of target fishing approach relies on a large collection of experimentally validated macromolecule-chemical compound binding data. The small chemical compounds can be described as molecular fingerprints encoding their structural characteristics as a vector. The published version of FastTargetPred used ligand-target binding data extracted from the release 25 (2019) of the ChEMBL database. Here we provide a new dataset for FastTargetPred extracted from the last ChEMBL release, namely, at the time of writing, ChEMBL29 (2021). Four fingerprints were computed (ECFP4, ECFP6, MACCS and PL) for the extracted compound dataset (714,780 unique ChEMBL29 compounds while the entire ChEMBL29 database contained about 2.1 million compounds). However, it was not possible to compute fingerprints for 19 molecules because of their unusual chemistry (complex macrocycles). These data files were then prepared so as to be compatible with FastTargetPred requirements. The 714,761 ChEMBL chemical compounds with computed fingerprints hit 6,477 macromolecular targets based on the selected criteria. For these ChEMBL compounds a ChEMBL target ID is reported and these target IDs were matched with the corresponding UniProt IDs. Thus, when available, the UniProt ID is provided, the protein UniProt name, the gene name, the organism as well as annotated involvement in diseases, gene ontology data, and cross-references to the Reactome pathway database. As short peptides can be of interest for drug discovery and chemical biology endeavours, we were interested in attempting to predict putative macromolecular targets for a previously reported exhaustive combination of peptides containing four natural amino acids (i.e., 20 × 20 × 20 × 20 = 160,000 linear tetrapeptides) using FastTargetPred and the presently generated ChEMBL29 dataset. With the parameters used, putative targets are reported for 63,944 unique query peptides. These target predictions are provided in two different searchable files with hyperlinks to the ChEMBL, UniProt and Reactome databases.

Thiosemicarbazone derivatives: Evaluation as cruzipain inhibitors and molecular modeling study of complexes with cruzain

The development of cruzipain inhibitors represents one of the most attractive challenges in the search for drugs for the treatment of Chagas disease. A recombinant form of this enzyme, cruzain, has been crystallized with numerous inhibitors, excluding thiosemicarbazones. These compounds have been established as potent inhibitors of cruzain, although there is very little data in the literature of thiosemicarbazones tested on cruzipain. In this work, we present the results of the evaluation of eleven thiosemicarbazones on cruzipain, isolated from T. cruzi epimastigotes, six of them previously evaluated on cruzain. For these latter, we studied through computational methods, the mode of interaction with the active site of cruzain and the contribution of geometric parameters to the possible mechanism of action involved in the observed inhibition. Finally, from some geometric parameters analyzed on modeled TSC-cruzain complexes, a semi-quantitative relationship was established that could explain the inhibitory activity of thiosemicarbazones on cruzipain, the enzyme actually present in the parasite.

Redox active or thiol reactive? Optimization of rapid screens to identify less evident nuisance compounds

Compounds that exhibit assay interference or undesirable mechanisms of bioactivity are routinely encountered in assays at various stages of drug discovery. We observed that assays for the investigation of thiol-reactive and redox-active compounds have not been collected in a comprehensive review. Here, we review these assays and subject them to experimental optimization to improve their reliability. We demonstrate the usefulness of our assay cascade by assaying a library of bioactive compounds, chemical probes, and a set of approved drugs. These high-throughput assays should complement the array of wet-lab and in silico assays during the initial stages of hit discovery campaigns to pursue only hit compounds with tractable mechanisms of action. Teaser: We provide an overview of assays to detect redox active and thiol reactive compounds and the robust protocols for identification of nuisance compounds during early stages of drug discovery programs.

The Fellowship of Privileged Scaffolds-One Structure to Inhibit Them All

Over the past few years, the application of privileged structure has emerged as a powerful approach to the discovery of new biologically active molecules. Privileged structures are molecular scaffolds with binding properties to the range of different biological targets. Moreover, privileged structures typically exhibit good drug-like properties, thus assuring more drug-like properties of modified compound. Our main objective is to discuss the privileged structures used for the development of antiviral agents.

Natural Products-Based Drug Design against SARS-CoV-2 Mpro 3CLpro

Coronavirus disease 2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has received global attention due to the serious threat it poses to public health. Since the outbreak in December 2019, millions of people have been affected and its rapid global spread has led to an upsurge in the search for treatment. To discover hit compounds that can be used alone or in combination with repositioned drugs, we first analyzed the pharmacokinetic and toxicological properties of natural products from Brazil's semiarid region. After, we analyzed the site prediction and druggability of the SARS-CoV-2 main protease (Mpro), followed by docking and molecular dynamics simulation. The best SARS-CoV-2 Mpro complexes revealed that other sites were accessed, confirming that our approach could be employed as a suitable starting protocol for ligand prioritization, reinforcing the importance of catalytic cysteine-histidine residues and providing new structural data that could increase the antiviral development mainly against SARS-CoV-2. Here, we selected 10 molecules that could be in vitro assayed in response to COVID-19. Two compounds (b01 and b02) suggest a better potential for interaction with SARS-CoV-2 Mpro and could be further studied.

Insights on Dengue and Zika NS5 RNA-dependent RNA polymerase (RdRp) inhibitors

Over recent years, many outbreaks caused by (re)emerging RNA viruses have been reported worldwide, including life-threatening Flaviviruses, such as Dengue (DENV) and Zika (ZIKV). Currently, there is only one licensed vaccine against Dengue, Dengvaxia®. However, its administration is not recommended for children under nine years. Still, there are no specific inhibitors available to treat these infectious diseases. Among the flaviviral proteins, NS5 RNA-dependent RNA polymerase (RdRp) is a metalloenzyme essential for viral replication, suggesting that it is a promising macromolecular target since it has no human homolog. Nowadays, several NS5 RdRp inhibitors have been reported, while none inhibitors are currently in clinical development. In this context, this review constitutes a comprehensive work focused on RdRp inhibitors from natural, synthetic, and even repurposing sources. Furthermore, their main aspects associated with the structure-activity relationship (SAR), proposed mechanisms of action, computational studies, and other topics will be discussed in detail.

Small-Molecule Inhibitors of the Coronavirus Spike: ACE2 Protein-Protein Interaction as Blockers of Viral Attachment and Entry for SARS-CoV-2

Inhibitors of the protein-protein interaction (PPI) between the SARS-CoV-2 spike protein and human ACE2 (hACE2), which acts as a ligand-receptor pair that initiates the viral attachment and cellular entry of this coronavirus causing the ongoing COVID-19 pandemic, are of considerable interest as potential antiviral agents. While blockade of such PPIs with small molecules is more challenging than that with antibodies, small-molecule inhibitors (SMIs) might offer alternatives that are less strain- and mutation-sensitive, suitable for oral or inhaled administration, and more controllable/less immunogenic. Here, we report the identification of SMIs of this PPI by screening our compound library focused around the chemical space of organic dyes. Among promising candidates identified, several dyes (Congo red, direct violet 1, Evans blue) and novel druglike compounds (DRI-C23041, DRI-C91005) inhibited the interaction of hACE2 with the spike proteins of SARS-CoV-2 as well as SARS-CoV with low micromolar activity in our cell-free ELISA-type assays (IC50's of 0.2-3.0 μM), whereas control compounds, such as sunset yellow FCF, chloroquine, and suramin, showed no activity. Protein thermal shift assays indicated that the SMIs of interest identified here bind SARS-CoV-2-S and not hACE2. While dyes seemed to be promiscuous inhibitors, DRI-C23041 showed some selectivity and inhibited the entry of two different SARS-CoV-2-S expressing pseudoviruses into hACE2-expressing cells in a concentration-dependent manner with low micromolar IC50's (6-7 μM). This provides proof-of-principle evidence for the feasibility of small-molecule inhibition of PPIs critical for SARS-CoV-2 attachment/entry and serves as a first guide in the search for SMI-based alternative antiviral therapies for the prevention and treatment of diseases caused by coronaviruses in general and COVID-19 in particular.

Iron Acquisition Systems of Gram-negative Bacterial Pathogens Define TonB-Dependent Pathways to Novel Antibiotics

Iron is an indispensable metabolic cofactor in both pro- and eukaryotes, which engenders a natural competition for the metal between bacterial pathogens and their human or animal hosts. Bacteria secrete siderophores that extract Fe3+ from tissues, fluids, cells, and proteins; the ligand gated porins of the Gram-negative bacterial outer membrane actively acquire the resulting ferric siderophores, as well as other iron-containing molecules like heme. Conversely, eukaryotic hosts combat bacterial iron scavenging by sequestering Fe3+ in binding proteins and ferritin. The variety of iron uptake systems in Gram-negative bacterial pathogens illustrates a range of chemical and biochemical mechanisms that facilitate microbial pathogenesis. This document attempts to summarize and understand these processes, to guide discovery of immunological or chemical interventions that may thwart infectious disease.

Deconstructing Noncovalent Kelch-like ECH-Associated Protein 1 (Keap1) Inhibitors into Fragments to Reconstruct New Potent Compounds

Targeting the protein-protein interaction (PPI) between nuclear factor erythroid 2-related factor 2 (Nrf2) and Kelch-like ECH-associated protein 1 (Keap1) is a potential therapeutic strategy to control diseases involving oxidative stress. Here, six classes of known small-molecule Keap1-Nrf2 PPI inhibitors were dissected into 77 fragments in a fragment-based deconstruction reconstruction (FBDR) study and tested in four orthogonal assays. This gave 17 fragment hits of which six were shown by X-ray crystallography to bind in the Keap1 Kelch binding pocket. Two hits were merged into compound 8 with a 220-380-fold stronger affinity (K_i = 16 μM) relative to the parent fragments. Systematic optimization resulted in several novel analogues with K_i values of 0.04-0.5 μM, binding modes determined by X-ray crystallography, and enhanced microsomal stability. This demonstrates how FBDR can be used to find new fragment hits, elucidate important ligand-protein interactions, and identify new potent inhibitors of the Keap1-Nrf2 PPI.

QSAR Models for Active Substances against Pseudomonas aeruginosa Using Disk-Diffusion Test Data

Pseudomonas aeruginosa is a Gram-negative bacillus included among the six “ESKAPE” microbial species with an outstanding ability to “escape” currently used antibiotics and developing new antibiotics against it is of the highest priority. Whereas minimum inhibitory concentration (MIC) values against Pseudomonas aeruginosa have been used previously for QSAR model development, disk diffusion results (inhibition zones) have not been apparently used for this purpose in the literature and we decided to explore their use in this sense. We developed multiple QSAR methods using several machine learning algorithms (support vector classifier, K nearest neighbors, random forest classifier, decision tree classifier, AdaBoost classifier, logistic regression and naïve Bayes classifier). We used four sets of molecular descriptors and fingerprints and three different methods of data balancing, together with the “native” data set. In total, 32 models were built for each set of descriptors or fingerprint and balancing method, of which 28 were selected and stacked to create meta-models. In terms of balanced accuracy, the best performance was provided by KNN, logistic regression and decision tree classifier, but the ensemble method had slightly superior results in nested cross-validation.

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.

The diverse mechanisms and anticancer potential of naphthoquinones

Cancer is one of the leading causes of death around the world and although the different clinical approaches have helped to increase survival rates, incidence is still high and so its mortality. Chemotherapy is the only approach which is systemic, reaching cancer cells in all body tissues and the search for new potent and selective drugs is still an attractive field within cancer research. Naphthoquinones, natural and synthetic, have garnered much attention in the scientific community due to their pharmacological properties, among them anticancer action, and potential therapeutic significance. Many mechanisms of action have been reported which also depend on structural differences among them. Here, we describe some of the most relevant mechanisms of action reported so far for naphthoquinones and highlight novel targets which are being described in the literature. Furthermore, we gather some of the most impressive efforts done by researchers to harness the anticancer properties of these compounds through specifically designed structural modifications.

Design, synthesis, and evaluation of chalcone analogues incorporate α,β-Unsaturated ketone functionality as anti-lung cancer agents via evoking ROS to induce pyroptosis

Chalcone, a natural structure, demonstrates many pharmacological activities including anticancer, and one promising mechanism is to modulate the generation of ROS. It has been known that pyroptosis is associated with anticancer effects, whereas there is fewer researches about ROS-mediated pyroptosis triggered by chemotherapy drugs. Moreover, incorporation of a α,β-unsaturated ketone unit into chalcone may be an effective strategy for development of chemotherapy drugs. Hence, a number of chalcone analogues bearing a α,β-unsaturated ketone were synthesized from chalcone analogues 1 with modest anticancer activities as the lead compound. Structure-activity relationship (SAR) studies confirmed the function of α,β-unsaturated ketone to improve anticancer activity. Notably, compound 8, bearing a α,β-unsaturated ketone, is the most potent inhibitor of cancer, with IC₅₀ values on NCI-H460, A549 and H1975 cells of 2.3 ± 0.3, 3.2 ± 0.0 and 5.7 ± 1.4 μM, respectively. Besides, 8 showed antiproliferative ability against NCI-H460 cells in a time- and concentration-dependent manner through modulating ROS to induce caspase-3-mediated pyroptosis, and displayed a better safety profile in vivo. Overall, these results demonstrated that compound 8 is a candidate agent and a potential lead compound for development of chemotherapy drugs, and can be used as a probe to further examine the mechanism of ROS-dependent pyroptosis.

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.

Computer-Aided Discovery and Characterization of Novel Ebola Virus Inhibitors

The Ebola virus (EBOV) causes severe human infection that lacks effective treatment. A recent screen identified a series of compounds that block EBOV-like particle entry into human cells. Using data from this screen, quantitative structure-activity relationship models were built and employed for virtual screening of a ∼17 million compound library. Experimental testing of 102 hits yielded 14 compounds with IC₅₀ values under 10 μM, including several sub-micromolar inhibitors, and more than 10-fold selectivity against host cytotoxicity. These confirmed hits include FDA-approved drugs and clinical candidates with non-antiviral indications, as well as compounds with novel scaffolds and no previously known bioactivity. Five selected hits inhibited BSL-4 live-EBOV infection in a dose-dependent manner, including vindesine (0.34 μM). Additional studies of these novel anti-EBOV compounds revealed their mechanisms of action, including the inhibition of NPC1 protein, cathepsin B/L, and lysosomal function. Compounds identified in this study are among the most potent and well-characterized anti-EBOV inhibitors reported to date.

Application of Virtual Screening Approaches for the Identification of Small Molecule Inhibitors of the Methyllysine Reader Protein Spindlin1

Computer-based approaches represent a powerful tool which helps to identify and optimize lead structures in the process of drug discovery. Computer-aided drug design techniques (CADD) encompass a large variety of methods which are subdivided into structure-based (SBDD) and ligand-based drug design (LBDD) methods. Several approaches have been successfully used over the last three decades in different fields. Indeed also in the field of epigenetics, virtual screening (VS) studies and structure-based approaches have been applied to identify novel chemical modulators of epigenetic targets as well as to predict the binding mode of active ligands and to study the protein dynamics.In this chapter, an iterative VS approach using both SBDD and LBDD methods, which was successful in identifying Spindlin1 inhibitors, will be described. All protocol steps, starting from structure-based pharmacophore modeling, protein and database preparation along with docking and similarity search, will be explained in details.

Discovery of antimicrobial compounds targeting bacterial type FAD synthetases

The increase of bacterial strains resistant to most of the available antibiotics shows a need to explore novel antibacterial targets to discover antimicrobial drugs. Bifunctional bacterial FAD synthetases (FADSs) synthesise the flavin mononucleotide (FMN) and flavin adenine dinucleotide (FAD). These cofactors act in vital processes as part of flavoproteins, making FADS an essential enzyme. Bacterial FADSs are potential antibacterial targets because of differences to mammalian enzymes, particularly at the FAD producing site. We have optimised an activity-based high throughput screening assay targeting Corynebacterium ammoniagenes FADS (CaFADS) that identifies inhibitors of its different activities. We selected the three best high-performing inhibitors of the FMN:adenylyltransferase activity (FMNAT) and studied their inhibition mechanisms and binding properties. The specificity of the CaFADS hits was evaluated by studying also their effect on the Streptococcus pneumoniae FADS activities, envisaging differences that can be used to discover species-specific antibacterial drugs. The antimicrobial effect of these compounds was also evaluated on C. ammoniagenes, S. pneumoniae, and Mycobacterium tuberculosis cultures, finding hits with favourable antimicrobial properties.

Chalcone Derivatives: Promising Starting Points for Drug Design

Medicinal chemists continue to be fascinated by chalcone derivatives because of their simple chemistry, ease of hydrogen atom manipulation, straightforward synthesis, and a variety of promising biological activities. However, chalcones have still not garnered deserved attention, especially considering their high potential as chemical sources for designing and developing new effective drugs. In this review, we summarize current methodological developments towards the design and synthesis of new chalcone derivatives and state-of-the-art medicinal chemistry strategies (bioisosterism, molecular hybridization, and pro-drug design). We also highlight the applicability of computer-assisted drug design approaches to chalcones and address how this may contribute to optimizing research outputs and lead to more successful and cost-effective drug discovery endeavors. Lastly, we present successful examples of the use of chalcones and suggest possible solutions to existing limitations.