Screening-based translation of public research encounters painful problems

Natural compounds inhibit Monkeypox virus methyltransferase VP39 in silico studies

VP39, an essential 2'-O-RNA methyltransferase enzyme discovered in Monkeypox virus (MPXV), plays a vital role in viral RNA replication and transcription. Inhibition of the enzyme may prevent viral replication. In this context, using a combination of molecular docking and molecular dynamics (MDs) simulations, the inhibitory ability of NCI Diversity Set VII natural compounds to VP39 protein was investigated. It should be noted that the computed binding free energy of ligand via molecular docking and linear interaction energy (LIE) approaches are in good agreement with the corresponding experiments with coefficients of R = 0.72 and 0.75, respectively. NSC 319990, NSC 196515 and NSC 376254 compounds were demonstrated that can inhibit MPVX methyltransferase VP39 protein with the similar affinity compared to available inhibitor sinefungin. Moreover, nine residues involving Gln39, Gly68, Gly72, Asp95, Arg97, Val116, Asp138, Arg140 and Asn156 may be argued that they play an important role in binding process of inhibitors to VP39.Communicated by Ramaswamy H. Sarma.

Drug discovery: In silico dry data can bypass biological wet data?

The recent and extraordinary increase in computer power, along with the availability of efficient algorithms based on artificial intelligence, has prompted a large number of inexperienced scientists to challenge the complex and yet competitive world of drug discovery, by pretending to identify new hits through the sole use of computer aided drug design (CADD). Does the golden era of dry data run the risk of overshadowing the importance of wet data and, in doing so, forget that in silico and biological data need each other in successful preclinical drug discovery programmes?

On the origins of SARS-CoV-2 main protease inhibitors

In order to address the world-wide health challenge caused by the COVID-19 pandemic, the 3CL protease/SARS-CoV-2 main protease (SARS-CoV-2-Mpro) coded by its nsp5 gene became one of the biochemical targets for the design of antiviral drugs. In less than 3 years of research, 4 inhibitors of SARS-CoV-2-Mpro have actually been authorized for COVID-19 treatment (nirmatrelvir, ensitrelvir, leritrelvir and simnotrelvir) and more such as EDP-235, FB-2001 and STI-1558/Olgotrelvir or five undisclosed compounds (CDI-988, ASC11, ALG-097558, QLS1128 and H-10517) are undergoing clinical trials. This review is an attempt to picture this quite unprecedented medicinal chemistry feat and provide insights on how these cysteine protease inhibitors were discovered. Since many series of covalent SARS-CoV-2-Mpro inhibitors owe some of their origins to previous work on other proteases, we first provided a description of various inhibitors of cysteine-bearing human caspase-1 or cathepsin K, as well as inhibitors of serine proteases such as human dipeptidyl peptidase-4 or the hepatitis C protein complex NS3/4A. This is then followed by a description of the results of the approaches adopted (repurposing, structure-based and high throughput screening) to discover coronavirus main protease inhibitors.

Non-peptidic immunoproteasome β5i-selective inhibitor as potential treatment for idiopathic pulmonary fibrosis: Virtual screening, hit evolution and lead identification

The immunoproteasome has emerged as a potential therapeutic target for idiopathic pulmonary fibrosis (IPF). We report herein our efforts to discover novel non-peptidic immunoproteasome inhibitors as potential treatment for IPF. A structure-based virtual screening was initially performed and the hit compound VS-7 with an IC50 of 9.437 μM against β5i was identified. Hit evolution based on the interaction mode of VS-7 proceeded, and a potent β5i inhibitor 54 (IC50 = 8.463 nM) with favorable subunit-selective profiles was obtained. Compound 54 also imposed significant effects on the release of TNF-α and IL-6, the transcriptional activity of NF-κB, as well as TGF-β1 induced fibroblast proliferation, activation and collagen synthesis. Notably, when administered at 30 mg/kg in a bleomycin-induced IPF mouse model, compound 54 showed anti-fibrotic effects comparable to the clinical drug nintedanib. The results suggest that selective inhibition of immunoproteasome could be an effective approach to treat IPF.

On drug discovery against infectious diseases and academic medicinal chemistry contributions

This perspective is an attempt to document the problems that medicinal chemists are facing in drug discovery. It is also trying to identify relevant/possible, research areas in which academics can have an impact and should thus be the subject of grant calls. Accordingly, it describes how hit discovery happens, how compounds to be screened are selected from available chemicals and the possible reasons for the recurrent paucity of useful/exploitable results reported. This is followed by the successful hit to lead stories leading to recent and original antibacterials which are, or about to be, used in human medicine. Then, illustrated considerations and suggestions are made on the possible inputs of academic medicinal chemists. This starts with the observation that discovering a "good" hit in the course of a screening campaign still rely on a lot of luck - which is within the reach of academics -, that the hit to lead process requires a lot of chemistry and that if public-private partnerships can be important throughout these stages, they are absolute requirements for clinical trials. Concerning suggestions to improve the current hit success rate, one academic input in organic chemistry would be to identify new and pertinent chemical space, design synthetic accesses to reach these and prepare the corresponding chemical libraries. Concerning hit to lead programs on a given target, if no new hits are available, previously reported leads along with new structural data can be pertinent starting points to design, prepare and assay original analogues. In conclusion, this text is an actual plea illustrating that, in many countries, academic research in medicinal chemistry should be more funded, especially in the therapeutic area neglected by the industry. At the least, such funds would provide the intensive to secure series of hopefully relevant chemical entities which appears to often lack when considering the results of academic as well as industrial screening campaigns.

Genetic validation of Aspergillus fumigatus phosphoglucomutase as a viable therapeutic target in invasive aspergillosis

Aspergillus fumigatus is the causative agent of invasive aspergillosis, an infection with mortality rates of up to 50%. The glucan-rich cell wall of A. fumigatus is a protective structure that is absent from human cells and is a potential target for antifungal treatments. Glucan is synthesized from the donor uridine diphosphate glucose, with the conversion of glucose-6-phosphate to glucose-1-phosphate by the enzyme phosphoglucomutase (PGM) representing a key step in its biosynthesis. Here, we explore the possibility of selectively targeting A. fumigatus PGM (AfPGM) as an antifungal treatment strategy. Using a promoter replacement strategy, we constructed a conditional pgm mutant and revealed that pgm is required for A. fumigatus growth and cell wall integrity. In addition, using a fragment screen, we identified the thiol-reactive compound isothiazolone fragment of PGM as targeting a cysteine residue not conserved in the human ortholog. Furthermore, through scaffold exploration, we synthesized a para-aryl derivative (ISFP10) and demonstrated that it inhibits AfPGM with an IC50 of 2 μM and exhibits 50-fold selectivity over the human enzyme. Taken together, our data provide genetic validation of PGM as a therapeutic target and suggest new avenues for inhibiting AfPGM using covalent inhibitors that could serve as tools for chemical validation.

Promoting GAINs (Give Attention to Limitations in Assays) over PAINs Alerts: no PAINS, more GAINs

Many concepts and guidelines in medicinal chemistry have been introduced to aid in successful drug discovery and development. An example is the concept of Pan-Assay Interference Compounds (PAINS) and the elimination of such nuisance compounds from high-throughput screening (HTS) libraries. PAINs, along with other guidelines in medicinal chemistry, are like double-edged swords. If used appropriately, they may be beneficial for drug discovery and development. However, rigid and blind use of such concepts can hinder productivity. In this perspective, we introduce GAINS (give attention to limitations in assays) and highlight its relevance for successful drug discovery.

Gains from no real PAINS: Where 'Fair Trial Strategy' stands in the development of multi-target ligands

Compounds that selectively modulate multiple targets can provide clinical benefits and are an alternative to traditional highly selective agents for unique targets. High-throughput screening (HTS) for multitarget-directed ligands (MTDLs) using approved drugs, and fragment-based drug design has become a regular strategy to achieve an ideal multitarget combination. However, the unexpected presence of pan-assay interference compounds (PAINS) suspects in the development of MTDLs frequently results in nonspecific interactions or other undesirable effects leading to artefacts or false-positive data of biological assays. Publicly available filters can help to identify PAINS suspects; however, these filters cannot comprehensively conclude whether these suspects are "bad" or innocent. Additionally, these in silico approaches may inappropriately label a ligand as PAINS. More than 80% of the initial hits can be identified as PAINS by the filters if appropriate biochemical tests are not used resulting in false positive data that are unacceptable for medicinal chemists in manuscript peer review and future studies. Therefore, extensive offline experiments should be used after online filtering to discriminate "bad" PAINS and avoid incorrect evaluation of good scaffolds. We suggest that the use of "Fair Trial Strategy" to identify interesting molecules in PAINS suspects to provide certain structure‒function insight in MTDL development.

Docking Screens of Noncovalent Interaction Motifs of the Human Subtype-D2 Receptor-75 Schizophrenia Antipsychotic Complexes with Physicochemical Appraisal of Antipsychotics

Chemoinformatics appraisal and molecular docking were employed to investigate 225 complexes of 75 schizophrenia antipsychotics with the dopamine receptor subtypes D2R, D3R, and D4R. Considering the effective noncovalent interactions in the subtype-D2 receptor selectivity of antipsychotics, this study evaluated the possible physicochemical properties of ligands underlying the design of safer and more effective antipsychotics. The pan-assay interference compounds (PAINs) include about 25% of typical antipsychotics and 5% of atypicals. Popular antipsychotics like haloperidol, clozapine, risperidone, and aripiprazole are not PAINs. They have stronger interactions with D2R and D4R, but their interactions with D3R are slightly weaker, which is similar to the behavior of dopamine. In contrast to typical antipsychotics, atypical antipsychotics exhibit more noncovalent interactions with D4R than with D2R. These results suggest that selectivity to D2R and D4R comes from the synergy between hydrophobic and hydrogen-bonding interactions through their concomitant occurrence in the form of a hydrogen-bonding site adorned with hydrophobic contacts in antipsychotic-receptor complexes. All the antipsychotics had more synergic interactions with D2R and D4R in comparison with D3R. The atypical antipsychotics made a good distinction between the subtype D2 receptors with high selectivity to D4R. Among the popular antipsychotics, haloperidol, clozapine, and risperidone have hydrophobic-hydrogen-bonding synergy with D4R, while aripiprazole profits with D2R. The most important residue participating in the synergic interactions was threonine for D2R and cysteine for D4R. This work could be useful in informing and guiding future drug discovery and development studies aimed at receptor-specific antipsychotics.

Oximes: Novel Therapeutics with Anticancer and Anti-Inflammatory Potential

Oximes have been studied for decades because of their significant roles as acetylcholinesterase reactivators. Over the last twenty years, a large number of oximes have been reported with useful pharmaceutical properties, including compounds with antibacterial, anticancer, anti-arthritis, and anti-stroke activities. Many oximes are kinase inhibitors and have been shown to inhibit over 40 different kinases, including AMP-activated protein kinase (AMPK), phosphatidylinositol 3-kinase (PI3K), cyclin-dependent kinase (CDK), serine/threonine kinases glycogen synthase kinase 3 α/β (GSK-3α/β), Aurora A, B-Raf, Chk1, death-associated protein-kinase-related 2 (DRAK2), phosphorylase kinase (PhK), serum and glucocorticoid-regulated kinase (SGK), Janus tyrosine kinase (JAK), and multiple receptor and non-receptor tyrosine kinases. Some oximes are inhibitors of lipoxygenase 5, human neutrophil elastase, and proteinase 3. The oxime group contains two H-bond acceptors (nitrogen and oxygen atoms) and one H-bond donor (OH group), versus only one H-bond acceptor present in carbonyl groups. This feature, together with the high polarity of oxime groups, may lead to a significantly different mode of interaction with receptor binding sites compared to corresponding carbonyl compounds, despite small changes in the total size and shape of the compound. In addition, oximes can generate nitric oxide. This review is focused on oximes as kinase inhibitors with anticancer and anti-inflammatory activities. Oximes with non-kinase targets or mechanisms of anti-inflammatory activity are also discussed.

Brief Guide: Experimental Strategies for High-Quality Hit Selection from Small-Molecule Screening Campaigns

Small-molecule screening is a powerful approach to identify modulators of either specific biological targets or cellular pathways with phenotypic endpoints. A myriad of assay technologies are available to assess the activity of enzymes, monitor protein-protein interactions, measure transcription factor activity in reporter assays, or detect cellular features and activities using high-content imaging. A common challenge during small-molecule screening is, however, the presence of hit compounds generating assay interference, thereby producing false-positive hits. Thus, efforts are needed to uncover such interferences to prioritize high-quality hits for further analysis. This process encompasses (1) computational approaches to flag undesirable compounds, and (2) the use of experimental approaches like counter, orthogonal, and cellular fitness screens to identify and eliminate artifacts. In this brief guide, we provide an overview for first-time users, highlighting experimental screening strategies to prioritize high-quality bioactive hits from high-throughput screening/high-content screening (HTS/HCS) campaigns.

Nuisance compounds in cellular assays

Compounds that exhibit assay interference or undesirable mechanisms of bioactivity ("nuisance compounds") are routinely encountered in cellular assays, including phenotypic and high-content screening assays. Much is known regarding compound-dependent assay interferences in cell-free assays. However, despite the essential role of cellular assays in chemical biology and drug discovery, there is considerably less known about nuisance compounds in more complex cell-based assays. In our view, a major obstacle to realizing the full potential of chemical biology will not just be difficult-to-drug targets or even the sheer number of targets, but rather nuisance compounds, due to their ability to waste significant resources and erode scientific trust. In this review, we summarize our collective academic, government, and industry experiences regarding cellular nuisance compounds. We describe assay design strategies to mitigate the impact of nuisance compounds and suggest best practices to efficiently address these compounds in complex biological settings.

Computational and Experimental Studies Reveal That Thymoquinone Blocks the Entry of Coronaviruses Into In Vitro Cells

INTRODUCTION

Since December 2019, severe acute respiratory syndrome-related coronavirus-2 (SARS-CoV-2) has caused the coronavirus disease 2019 (COVID-19) pandemic in China and worldwide. New drugs for the treatment of COVID-19 are in urgent need. Considering the long development time for new drugs, the identification of promising inhibitors from FDA-approved drugs is an imperative and valuable strategy. Recent studies have shown that the S1 and S2 subunits of the spike protein of SARS-CoV-2 utilize human angiotensin-converting enzyme 2 (hACE2) as the receptor to infect human cells.

METHODS

We combined molecular docking and surface plasmon resonance (SPR) to identify potential inhibitors for ACE2 from available commercial medicines. We also designed coronavirus pseudoparticles that contain the spike protein assembled onto green fluorescent protein or luciferase reporter gene-carrying vesicular stomatitis virus core particles.

RESULTS

We found that thymoquinone, a phytochemical compound obtained from the plant Nigella sativa, is a potential drug candidate. SPR analysis confirmed the binding of thymoquinone to ACE2. We found that thymoquinone can inhibit SARS-CoV-2, SARS-CoV, and NL63 pseudoparticles infecting HEK293-ACE2 cells, with half-maximal inhibitory concentrations of 4.999, 7.598, and 6.019 μM, respectively. The SARS-CoV-2 pseudoparticle inhibition had half-maximal cytotoxic concentration of 35.100 μM and selection index = 7.020.

CONCLUSION

Thymoquinone is a potential broad-spectrum inhibitor for the treatment of coronavirus infections.

Personal Accounts of Australian Drug Discovery at the Public–Private Interface

The public–private interface is a vibrant and invigorating stage for drug discovery and can allow for relatively higher risk but more rewarding research. Although adequate resourcing is a perennial challenge, persistence, optimism, and flexibility will pay dividends and can allow for a thoroughly rewarding career. In this account of chronological research experiences, selected examples are used to support this contention.

A Review of the Antimalarial, Antitrypanosomal, and Antileishmanial Activities of Natural Compounds Isolated From Nigerian Flora

The West African country Nigeria features highly diverse vegetation and climatic conditions that range from rain forest bordering the Atlantic Ocean in the South to the Desert (Sahara) at the Northern extreme. Based on data from the World Conservation Monitoring Center of the United Nations Environmental Protection, Nigeria, with ~5,000 documented vascular plants, ranks amongst the top 50 countries in terms of biodiversity. Such a rich biodiversity implies that the country is rich in diverse secondary metabolites-natural products/unique chemicals produced by the plant kingdom to confer selective advantages to them. Like many tropical countries, Nigeria is also endemic to numerous infectious diseases particularly those caused by parasitic pathogens. These phytochemicals have been exploited for the treatment of diseases and as a result, a new branch of chemistry, natural product chemistry, has evolved, to try to reproduce and improve the therapeutic qualities of particular phytochemicals. In this review, we have compiled a compendium of natural products, isolated from Nigerian flora, that have been reported to be effective against certain protozoan parasites with the aim that it will stimulate interests for further investigations, and give impetus to the development of the natural products into registered drugs. In total 93 structurally characterized natural compounds have been identified with various levels of anti-parasite activity mainly from Nigerian plants. The synthesis protocol and molecular target for some of these natural anti-parasite agents have been established. For instance, the anti-plasmodial compound fagaronine (7), a benzophenanthridine alkaloid from Fagara zanthoxyloides has been successfully synthesized in the laboratory, and the anti-trypanosomal compound azaanthraquinone (55) elicits its effect by inhibiting mitochondrial electron transfer in trypanosomes. This review also discusses the barriers to developing approved drugs from phytochemicals, and the steps that should be taken in order to accelerate the development of new antiparasitics from the highlighted compounds.

Bioprospecting for Antibacterial Drugs: a Multidisciplinary Perspective on Natural Product Source Material, Bioassay Selection and Avoidable Pitfalls

Bioprospecting is the exploration, extraction and screening of biological material and sometimes indigenous knowledge to discover and develop new drugs and other products. Most antibiotics in current clinical use (eg. β-lactams, aminoglycosides, tetracyclines, macrolides) were discovered using this approach, and there are strong arguments to reprioritize bioprospecting over other strategies in the search for new antibacterial drugs. Academic institutions should be well positioned to lead the early stages of these efforts given their many thousands of locations globally and because they are not constrained by the same commercial considerations as industry. University groups can lack the full complement of knowledge and skills needed though (eg. how to tailor screening strategy to biological source material). In this article, we review three key aspects of the bioprospecting literature (source material and in vitro antibacterial and toxicity testing) and present an integrated multidisciplinary perspective on (a) source material selection, (b) legal, taxonomic and other issues related to source material, (c) cultivation methods, (d) bioassay selection, (e) technical standards available, (f) extract/compound dissolution, (g) use of minimum inhibitory concentration and selectivity index values to identify progressible extracts and compounds, and (h) avoidable pitfalls. The review closes with recommendations for future study design and information on subsequent steps in the bioprospecting process.

Action plan for hit identification (APHID): KAT6A as a case study

Here, we describe our action plan for hit identification (APHID) that guides the process of hit triage, with elimination of less tractable hits and retention of more tractable hits. We exemplify the process with reference to our high-throughput screening (HTS) campaign against the enzyme, KAT6A, that resulted in successful identification of a tractable hit. We hope that APHID could serve as a useful, concise and digestible guide for those involved in HTS and hit triage, especially those that are relatively new to this exciting and continually evolving technology.

Natural allosteric modulators and their biological targets: molecular signatures and mechanisms

Covering: 2008 to 2018Over the last decade more than two hundred single natural products were confirmed as natural allosteric modulators (alloNPs) of proteins. The compounds are presented and discussed with the support of a chemical space, constructed using a principal component analysis (PCA) of molecular descriptors from chemical compounds of distinct databases. This analysis showed that alloNPs are dispersed throughout the majority of the chemical space defined by natural products in general. Moreover, a cluster of alloNPs was shown to occupy a region almost devoid of allosteric modulators retrieved from a dataset composed mainly of synthetic compounds, further highlighting the importance to explore the entire natural chemical space for probing allosteric mechanisms. The protein targets which alloNPs bind to comprised 81 different proteins, which were classified into 5 major groups, with enzymes, in particular hydrolases, being the main representative group. The review also brings a critical interpretation on the mechanisms by which alloNPs display their molecular action on proteins. In the latter analysis, alloNPs were classified according to their final effect on the target protein, resulting in 3 major categories: (i) local alteration of the orthosteric site; (ii) global alteration in protein dynamics that change function; and (iii) oligomer stabilisation or protein complex destabilisation via protein-protein interaction in sites distant from the orthosteric site. G-protein coupled receptors (GPCRs), which use a combination of the three types of allosteric regulation found, were also probed by natural products. In summary, the natural allosteric modulators reviewed herein emphasise their importance for exploring alternative chemotherapeutic strategies, potentially pushing the boundaries of the druggable space of pharmacologically relevant drug targets.

Ebola Virus Bayesian Machine Learning Models Enable New in Vitro Leads

We have previously described the first Bayesian machine learning models from FDA-approved drug screens, for identifying compounds active against the Ebola virus (EBOV). These models led to the identification of three active molecules in vitro: tilorone, pyronaridine, and quinacrine. A follow-up study demonstrated that one of these compounds, tilorone, has 100% in vivo efficacy in mice infected with mouse-adapted EBOV at 30 mg/kg/day intraperitoneal. This suggested that we can learn from the published data on EBOV inhibition and use it to select new compounds for testing that are active in vivo. We used these previously built Bayesian machine learning EBOV models alongside our chemical insights for the selection of 12 molecules, absent from the training set, to test for in vitro EBOV inhibition. Nine molecules were directly selected using the model, and eight of these molecules possessed a promising in vitro activity (EC50 < 15 μM). Three further compounds were selected for an in vitro evaluation because they were antimalarials, and compounds of this class like pyronaridine and quinacrine have previously been shown to inhibit EBOV. We identified the antimalarial drug arterolane (IC50 = 4.53 μM) and the anticancer clinical candidate lucanthone (IC50 = 3.27 μM) as novel compounds that have EBOV inhibitory activity in HeLa cells and generally lack cytotoxicity. This work provides further validation for using machine learning and medicinal chemistry expertize to prioritize compounds for testing in vitro prior to more costly in vivo tests. These studies provide further corroboration of this strategy and suggest that it can likely be applied to other pathogens in the future.

Discorhabdin N, a South African Natural Compound, for Hsp72 and Hsc70 Allosteric Modulation: Combined Study of Molecular Modeling and Dynamic Residue Network Analysis

The human heat shock proteins (Hsps), predominantly Hsp72 and Hsp90, have been strongly implicated in various critical stages of oncogenesis and progression of human cancers. While drug development has extensively focused on Hsp90 as a potential anticancer target, much less effort has been put against Hsp72. This work investigated the therapeutic potential of Hsp72 and its constitutive isoform, Hsc70, via in silico-based screening against the South African Natural Compounds Database (SANCDB). A comparative modeling approach was used to obtain nearly full-length 3D structures of the closed conformation of Hsp72 and Hsc70 proteins. Molecular docking of SANCDB compounds identified one potential allosteric modulator, Discorhabdin N, binding to the allosteric β substrate binding domain (SBDβ) back pocket, with good binding affinities in both cases. This allosteric region was identified in one of our previous studies. Subsequent all-atom molecular dynamics simulations and free energy calculations exhibited promising protein⁻ligand association characteristics, indicative of strong binding qualities. Further, we utilised dynamic residue network analysis (DRN) to highlight protein regions actively involved in cross-domain communication. Most residues identified agreed with known allosteric signal regulators from literature, and were further investigated for the purpose of deducing meaningful insights into the allosteric modulation properties of Discorhabdin N.

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.

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.

Data Sets Representative of the Structures and Experimental Properties of FDA-Approved Drugs

Presented here are several data sets that gather information collected from the labels of the FDA approved drugs: their molecular structures and those of the described active metabolites, their associated pharmacokinetics and pharmacodynamics data, and the history of their marketing authorization by the FDA. To date, 1852 chemical structures have been identified with a molecular weight less than 2000 of which 492 are or have active metabolites. To promote the sharing of data, the original web server was upgraded for browsing the database and downloading the data sets (http://chemoinfo.ipmc.cnrs.fr/edrug3d). It is believed that the multidimensional chemistry-oriented collections are an essential resource for a thorough analysis of the current drug chemical space. The data sets are envisioned as being used in a wide range of endeavors that include drug repurposing, drug design, privileged structures analyses, structure-activity relationship studies, and improving of absorption, distribution, metabolism, and elimination predictive models.

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

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

A novel compound which sensitizes BRAF wild-type melanoma cells to vemurafenib in a TRIM16-dependent manner

There is an urgent need for better therapeutic options for advanced melanoma patients, particularly those without the BRAFV600E/K mutation. In melanoma cells, loss of TRIM16 expression is a marker of cell migration and metastasis, while the BRAF inhibitor, vemurafenib, induces melanoma cell growth arrest in a TRIM16-dependent manner. Here we identify a novel small molecule compound which sensitized BRAF wild-type melanoma cells to vemurafenib. High throughput, cell-based, chemical library screening identified a compound (C012) which significantly reduced melanoma cell viability, with limited toxicity for normal human fibroblasts. When combined with the BRAFV600E/K inhibitor, vemurafenib, C012 synergistically increased vemurafenib potency in 5 BRAFWT and 4 out of 5 BRAFV600E human melanoma cell lines (Combination Index: CI < 1), and, dramatically reduced colony forming ability. In addition, this drug combination was significantly anti-tumorigenic in vivo in a melanoma xenograft mouse model. The combination of vemurafenib and C012 markedly increased expression of TRIM16 protein, and knockdown of TRIM16 significantly reduced the growth inhibitory effects of the vemurafenib and C012 combination. These findings suggest that the combination of C012 and vemurafenib may have therapeutic potential for the treatment of melanoma, and, that reactivation of TRIM16 may be an effective strategy for patients with this disease.

Small molecule targeting of PTPs in cancer

Protein tyrosine phosphatases (PTPs) undeniably have a central role in the development and progression of human cancers. Historically, however, PTPs have not been viewed as privileged drug targets, and progress on identifying potent, selective, and cell-active small molecule PTP inhibitors has suffered accordingly. This situation is rapidly changing, however, due to biochemical advances in the study of PTPs and recent small molecule screening campaigns, which have identified potent and mechanistically diverse lead structures. These compounds are facilitating the exploration of the fundamental cellular processes controlled by PTPs in cancers, and could form the inflection point for new therapeutic paradigms for the treatment of a range of cancers. Herein, we review recent advances in the discovery and biological annotation of cancer-relevant small molecule PTP inhibitors.

New Approaches to Difficult Drug Targets: The Phosphatase Story

The drug discovery landscape is littered with promising therapeutic targets that have been abandoned because of insufficient validation, historical screening failures, and inferior chemotypes. Molecular targets once labeled as “undruggable” or “intractable” are now being more carefully interrogated, and while they remain challenging, many target classes are appearing more approachable. Protein tyrosine phosphatases represent an excellent example of a category of molecular targets that have emerged as druggable, with several small molecules and antibodies recently becoming available for further development. In this review, we examine some of the diseases that are associated with protein tyrosine phosphatase dysfunction and use some prototype contemporary strategies to illustrate approaches that are being used to identify small molecules targeting this enzyme class.

Computational modeling of the bat HKU4 coronavirus 3CLpro inhibitors as a tool for the development of antivirals against the emerging Middle East respiratory syndrome (MERS) coronavirus

The Middle East respiratory syndrome coronavirus (MERS‐CoV) is an emerging virus that poses a major challenge to clinical management.

The 3C‐like protease (3CL^pro) is essential for viral replication and thus represents a potential target for antiviral drug development. Presently, very few data are available on MERS‐CoV 3CL^pro inhibition by small molecules. We conducted extensive exploration of the pharmacophoric space of a recently identified set of peptidomimetic inhibitors of the bat HKU4‐CoV 3CL^pro. HKU4‐CoV 3CL^pro shares high sequence identity (81%) with the MERS‐CoV enzyme and thus represents a potential surrogate model for anti‐MERS drug discovery. We used 2 well‐established methods: Quantitative structure‐activity relationship (QSAR)‐guided modeling and docking‐based comparative intermolecular contacts analysis. The established pharmacophore models highlight structural features needed for ligand recognition and revealed important binding‐pocket regions involved in 3CL^pro‐ligand interactions. The best models were used as 3D queries to screen the National Cancer Institute database for novel nonpeptidomimetic 3CL^pro inhibitors. The identified hits were tested for HKU4‐CoV and MERS‐CoV 3CL^pro inhibition. Two hits, which share the phenylsulfonamide fragment, showed moderate inhibitory activity against the MERS‐CoV 3CL^pro and represent a potential starting point for the development of novel anti‐MERS agents. To the best of our knowledge, this is the first pharmacophore modeling study supported by in vitro validation on the MERS‐CoV 3CL^pro.

Highlights

MERS‐CoV is an emerging virus that is closely related to the bat HKU4‐CoV.

3CL^pro is a potential drug target for coronavirus infection.

HKU4‐CoV 3CL^pro is a useful surrogate model for the identification of MERS‐CoV 3CL^pro enzyme inhibitors.

dbCICA is a very robust modeling method for hit identification.

The phenylsulfonamide scaffold represents a potential starting point for MERS coronavirus 3CL^pro inhibitors development.

Inhibition of delta-secretase improves cognitive functions in mouse models of Alzheimer's disease

δ-secretase, also known as asparagine endopeptidase (AEP) or legumain, is a lysosomal cysteine protease that cleaves both amyloid precursor protein (APP) and tau, mediating the amyloid-β and tau pathology in Alzheimer's disease (AD). Here we report the therapeutic effect of an orally bioactive and brain permeable δ-secretase inhibitor in mouse models of AD. We performed a high-throughput screen and identified a non-toxic and selective δ-secretase inhibitor, termed compound 11, that specifically blocks δ-secretase but not other related cysteine proteases. Co-crystal structure analysis revealed a dual active site-directed and allosteric inhibition mode of this compound class. Chronic treatment of tau P301S and 5XFAD transgenic mice with this inhibitor reduces tau and APP cleavage, ameliorates synapse loss and augments long-term potentiation, resulting in protection of memory. Therefore, these findings demonstrate that this δ-secretase inhibitor may be an effective clinical therapeutic agent towards AD.

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

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

Incorporation of Privileged Structures into Bevirimat Can Improve Activity against Wild-Type and Bevirimat-Resistant HIV-1

Two "privileged fragments", caffeic acid and piperazine, were integrated into bevirimat producing new derivatives with improved activity against HIV-1/NL4-3 and NL4-3/V370A carrying the most prevalent bevirimat-resistant polymorphism. The activity of one of these, 18c, was increased by 3-fold against NL4-3 and 51-fold against NL4-3/V370A. Moreover, 18c is a maturation inhibitor with improved metabolic stability. Our study suggested that integration of privileged motifs into promising natural product skeletons is an effective strategy for discovering potent derivatives.

Determining the Degree of Promiscuity of Extensively Assayed Compounds

In the context of polypharmacology, an emerging concept in drug discovery, promiscuity is rationalized as the ability of compounds to specifically interact with multiple targets. Promiscuity of drugs and bioactive compounds has thus far been analyzed computationally on the basis of activity annotations, without taking assay frequencies or inactivity records into account. Most recent estimates have indicated that bioactive compounds interact on average with only one to two targets, whereas drugs interact with six or more. In this study, we have further extended promiscuity analysis by identifying the most extensively assayed public domain compounds and systematically determining their promiscuity. These compounds were tested in hundreds of assays against hundreds of targets. In our analysis, assay promiscuity was distinguished from target promiscuity and separately analyzed for primary and confirmatory assays. Differences between the degree of assay and target promiscuity were surprisingly small and average and median degrees of target promiscuity of 2.6 to 3.4 and 2.0 were determined, respectively. Thus, target promiscuity remained at a low level even for most extensively tested active compounds. These findings provide further evidence that bioactive compounds are less promiscuous than drugs and have implications for pharmaceutical research. In addition to a possible explanation that drugs are more extensively tested for additional targets, the results would also support a “promiscuity enrichment model” according to which promiscuous compounds might be preferentially selected for therapeutic efficacy during clinical evaluation to ultimately become drugs.

Novel diversity-oriented synthesis-derived respiratory syncytial virus inhibitors identified via a high throughput replicon-based screen

Respiratory syncytial virus (RSV) infections affect millions of children and adults every year. Despite the significant disease burden, there are currently no safe and effective vaccines or therapeutics. We employed a replicon-based high throughput screen combined with live-virus triaging assays to identify three novel diversity-oriented synthesis-derived scaffolds with activity against RSV. One of these small molecules is shown to target the RSV polymerase (L protein) to inhibit viral replication and transcription; the mechanisms of action of the other small molecules are currently unknown. The compounds described herein may provide attractive inhibitors for lead optimization campaigns.

Feeling Nature's PAINS: Natural Products, Natural Product Drugs, and Pan Assay Interference Compounds (PAINS)

We have previously reported on classes of compounds that can interfere with bioassays via a number of different mechanisms and termed such compounds Pan Assay INterference compoundS, or PAINS. These compounds were defined on the basis of high-throughput data derived from vendor-supplied synthetics. The question therefore arises whether the concept of PAINS is relevant to compounds of natural origin. Here, it is shown that this is indeed the case, but that the context of the biological readout is an important factor that must be brought into consideration.

Focus on PAINS: false friends in the quest for selective anti-protozoal lead structures from Nature?

Pan-assay interference compounds (PAINS) are molecules showing promising but deceptive activities in various biochemical screenings mainly due to unselective interactions with the target.

Non-stoichiometric inhibition in integrated lead finding - a literature review

INTRODUCTION

Non-stoichiometric inhibition summarizes different mechanisms by which low-molecular weight compounds can reproducibly inhibit high-throughput screening (HTS) and other lead finding assays without binding to a structurally defined site on their molecular target. This disqualifies such molecules from optimization by medicinal chemistry, and therefore their rapid elimination from screening hit lists is essential for productive and effective drug discovery.

AREAS COVERED

This review covers recent literature that either investigates the various mechanisms behind non-stoichiometric inhibition or suggests assays and readouts to identify them. In addition, combination of the various methods to distill promising molecules out of raw primary hit lists step-by-step is considered. Emerging technologies to demonstrate target engagement in cells are also discussed.

EXPERT OPINION

Over the last few years, awareness of non-stoichiometric inhibitors within screening libraries and HTS hit lists has considerably increased, not only in the pharmaceutical industry but also in the academic drug discovery community. This has resulted in a variety of methods to detect and handle such compounds. These range from in silico approaches to flag suspicious compounds, and counterassays to measure non-stoichiometric inhibition, to biophysical methods that positively demonstrate stoichiometric binding. In addition, novel technologies to verify target engagement within cells are becoming available. While still a time- and resource-consuming nuisance, non-stoichiometric inhibitors therefore do not fundamentally jeopardize the discovery of low molecular weight lead and drug candidates. Rather, they should be viewed as a manageable issue that with appropriate expertise can be overcome through integration of the above-mentioned approaches.