Computer-aided pattern scoring - A multitarget dataset-driven workflow to predict ligands of orphan targets.

The identification of lead molecules and the exploration of novel pharmacological drug targets are major challenges of medical life sciences today. Genome-wide association studies, multi-omics, and systems pharmacology steadily reveal new protein networks, extending the known and relevant disease-modifying proteome. Unfortunately, the vast majority of the disease-modifying proteome consists of 'orphan targets' of which intrinsic ligands/substrates, (patho)physiological roles, and/or modulators are unknown. Undruggability is a major challenge in drug development today, and medicinal chemistry efforts cannot keep up with hit identification and hit-to-lead optimization studies. New 'thinking-outside-the-box' approaches are necessary to identify structurally novel and functionally distinctive ligands for orphan targets. Here we present a unique dataset that includes critical information on the orphan target ABCA1, from which a novel cheminformatic workflow - computer-aided pattern scoring (C@PS) - for the identification of novel ligands was developed. Providing a hit rate of 95.5% and molecules with high potency and molecular-structural diversity, this dataset represents a suitable template for general deorphanization studies.

Medicinal Polypharmacology in the Clinic - Translating the Polypharmacolome into Therapeutic Benefit.

Drugs with multiple targets, often annotated as 'unselective', 'promiscuous', 'multitarget', or 'polypharmacological', are widely considered in both academic and industrial research as a high risk due to the likelihood of adverse effects. However, retrospective analyses have shown that particularly approved drugs bear rich polypharmacological profiles. This raises the question whether our perception of the specificity paradigm ('one drug-one target concept') is correct - and if specifically multitarget drugs should be developed instead of being rejected. These questions provoke a paradigm shift - regarding the development of polypharmacological drugs not as a 'waste of investment', but acknowledging the existence of a 'lack of investment'. This perspective provides an insight into modern drug development highlighting latest drug candidates that have not been assessed in a broader polypharmacology-based context elsewhere embedded in a historic framework of classical and modern approved multitarget drugs. The article shall be an inspiration to the scientific community to re-consider current standards, and more, to evolve to a better understanding of polypharmacology from a challenge to an opportunity.

Medicinal polypharmacology: Exploration and exploitation of the polypharmacolome in modern drug development.

At the core of complex and multifactorial human diseases, such as cancer, metabolic syndrome, or neurodegeneration, are multiple players that cross-talk in robust biological networks which are intrinsically resilient to alterations. These multifactorial diseases are characterized by sophisticated feedback mechanisms which manifest cellular imbalance and resistance to drug therapy. By adhering to the specificity paradigm ("one target-one drug concept"), research focused for many years on drugs with very narrow mechanisms of action. This narrow focus promoted therapy ineffectiveness and resistance. However, modern drug discovery has evolved over the last years, increasingly emphasizing integral strategies for the development of clinically effective drugs. These integral strategies include the controlled engagement of multiple targets to overcome therapy resistance. Apart from the additive or even synergistic effects in therapy, multitarget drugs harbor molecular-structural attributes to explore orphan targets of which intrinsic substrates/physiological role(s) and/or modulators are unknown for future therapy purposes. We designated this multidisciplinary and translational research field between medicinal chemistry, chemical biology, and molecular pharmacology as 'medicinal polypharmacology'. Medicinal polypharmacology emerged as alternative approach to common single-targeted pharmacology stretching from basic drug and target identification processes to clinical evaluation of multitarget drugs, and the exploration and exploitation of the 'polypharmacolome' is at the forefront of modern drug development research.

HD_BPMDS: a curated binary pattern multitarget dataset of Huntington's disease-targeting agents.

The discovery of both distinctive lead molecules and novel drug targets is a great challenge in drug discovery, which particularly accounts for orphan diseases. Huntington's disease (HD) is an orphan, neurodegenerative disease of which the pathology is well-described. However, its pathophysiological background and molecular mechanisms are poorly understood. To date, only 2 drugs have been approved on the US and European markets, both of which address symptomatic aspects of this disease only. Although several hundreds of agents were described with efficacy against the HD phenotype in in vitro and/or in vivo models, a successful translation into clinical use is rarely achieved. Two major impediments are, first, the lack of awareness and understanding of the interactome-the sum of key proteins, cascades, and mediators-that contributes to HD initiation and progression; and second, the translation of the little gained knowledge into useful model systems. To counteract this lack of data awareness, we manually compiled and curated the entire modulator landscape of successfully evaluated pre-clinical small-molecule HD-targeting agents which are annotated with substructural molecular patterns, physicochemical properties, as well as drug targets, and which were linked to benchmark databases such as PubChem, ChEMBL, or UniProt. Particularly, the annotation with substructural molecular patterns expressed as binary code allowed for the generation of target-specific and -unspecific fingerprints which could be used to determine the (poly)pharmacological profile of molecular-structurally distinct molecules.

ABC Transporter C1 Prevents Dimethyl Fumarate from Targeting Alzheimer's Disease.

Alzheimer's disease (AD), the leading cause of dementia, is a growing health issue with very limited treatment options. To meet the need for novel therapeutics, existing drugs with additional preferred pharmacological profiles could be recruited. This strategy is known as 'drug repurposing'. Here, we describe dimethyl fumarate (DMF), a drug approved to treat multiple sclerosis (MS), to be tested as a candidate for other brain diseases. We used an APP-transgenic model (APPtg) of senile ß-amyloidosis mice to further investigate the potential of DMF as a novel AD therapeutic. We treated male and female APPtg mice through drinking water at late stages of ß-amyloid (Aß) deposition. We found that DMF treatment did not result in modulating effects on Aß deposition at this stage. Interestingly, we found that glutathione-modified DMF interacts with the ATP-binding cassette transporter ABCC1, an important gatekeeper at the blood-brain and blood-plexus barriers and a key player for Aß export from the brain. Our findings suggest that ABCC1 prevents the effects of DMF, which makes DMF unsuitable as a novel therapeutic drug against AD. The discovered effects of ABCC1 also have implications for DMF treatment of multiple sclerosis.

Indole Derivatives as New Structural Class of Potent and Antiproliferative Inhibitors of Monocarboxylate Transporter 1 (MCT1; SLC16A1).

The solute carrier (SLC) monocarboxylate transporter 1 (MCT1; SLC16A1) represents a promising target for the treatment of cancer; however, the MCT1 modulator landscape is underexplored with only roughly 100 reported compounds. To expand the knowledge about MCT1 modulation, we synthesized a library of 16 indole-based molecules and subjected these to a comprehensive biological assessment platform. All compounds showed functional inhibitory activities against MCT1 at low nanomolar concentrations and great antiproliferative activities against the MCT1-expressing cancer cell lines A-549 and MCF-7, while the compounds were selective over MCT4 (SLC16A4). Lead compound 24 demonstrated a greater potency than the reference compound, and molecular docking revealed strong binding affinities to MCT1. Compound 24 led to cancer cell cycle arrest as well as apoptosis, and it showed to sensitize these cancer cells toward an antineoplastic agent. Strikingly, compound 24 had also significant inhibitory power against the multidrug transporter ABCB1 and showed to reverse ABCB1-mediated multidrug resistance (MDR).

A Novel Huntington's Disease Assessment Platform to Support Future Drug Discovery and Development.

Huntington's disease (HD) is a lethal neurodegenerative disorder without efficient therapeutic options. The inefficient translation from preclinical and clinical research into clinical use is mainly attributed to the lack of (i) understanding of disease initiation, progression, and involved molecular mechanisms; (ii) knowledge of the possible HD target space and general data awareness; (iii) detailed characterizations of available disease models; (iv) better suitable models; and (v) reliable and sensitive biomarkers. To generate robust HD-like symptoms in a mouse model, the neomycin resistance cassette was excised from zQ175 mice, generating a new line: zQ175Δneo. We entirely describe the dynamics of behavioral, neuropathological, and immunohistological changes from 15-57 weeks of age. Specifically, zQ175Δneo mice showed early astrogliosis from 15 weeks; growth retardation, body weight loss, and anxiety-like behaviors from 29 weeks; motor deficits and reduced muscular strength from 36 weeks; and finally slight microgliosis at 57 weeks of age. Additionally, we collected the entire bioactivity network of small-molecule HD modulators in a multitarget dataset (HD_MDS). Hereby, we uncovered 358 unique compounds addressing over 80 different pharmacological targets and pathways. Our data will support future drug discovery approaches and may serve as useful assessment platform for drug discovery and development against HD.

A curated binary pattern multitarget dataset of focused ATP-binding cassette transporter inhibitors.

Multitarget datasets that correlate bioactivity landscapes of small-molecules toward different related or unrelated pharmacological targets are crucial for novel drug design and discovery. ATP-binding cassette (ABC) transporters are critical membrane-bound transport proteins that impact drug and metabolite distribution in human disease as well as disease diagnosis and therapy. Molecular-structural patterns are of the highest importance for the drug discovery process as demonstrated by the novel drug discovery tool 'computer-aided pattern analysis' ('C@PA'). Here, we report a multitarget dataset of 1,167 ABC transporter inhibitors analyzed for 604 molecular substructures in a statistical binary pattern distribution scheme. This binary pattern multitarget dataset (ABC_BPMDS) can be utilized for various areas. These areas include the intended design of (i) polypharmacological agents, (ii) highly potent and selective ABC transporter-targeting agents, but also (iii) agents that avoid clearance by the focused ABC transporters [e.g., at the blood-brain barrier (BBB)]. The information provided will not only facilitate novel drug prediction and discovery of ABC transporter-targeting agents, but also drug design in general in terms of pharmacokinetics and pharmacodynamics.

Physicochemistry shapes bioactivity landscape of pan-ABC transporter modulators: Anchor point for innovative Alzheimer's disease therapeutics.

Alzheimer's disease (AD) is a devastating neurological disorder characterized by the pathological accumulation of macromolecular Aß and tau leading to neuronal death. Drugs approved to treat AD may ameliorate disease symptoms, however, no curative treatment exists. Aß peptides were discovered to be substrates of adenosine triphosphate-(ATP)-binding cassette (ABC) transporters. Activators of these membrane-bound efflux proteins that promote binding and/or translocation of Aß could revolutionize AD medicine. The knowledge about ABC transporter activators is very scarce, however, the few molecules that were reported contain substructural features of multitarget (pan-)ABC transporter inhibitors. A cutting-edge strategy to obtain new drug candidates is to explore and potentially exploit the recently proposed multitarget binding site of pan-ABC transporter inhibitors as anchor point for the development of innovative activators to promote Aß clearance from the brain. Molecular associations between functional bioactivities and physicochemical properties of small-molecules are key to understand these processes. This study provides an analysis of a recently reported unique multitarget dataset for the correlation between multitarget bioactivity and physicochemistry. Six novel pan-ABC transporter inhibitors were validated containing substructural features of ABC transporter activators, which underpins the relevance of the multitarget binding site for the targeted development of novel AD diagnostics and therapeutics.

Structural feature-driven pattern analysis for multitarget modulator landscapes.

MOTIVATION: Multitargeting features of small molecules have been of increasing interest in recent years. Polypharmacological drugs that address several therapeutic targets may provide greater therapeutic benefits for patients. Furthermore, multitarget compounds can be used to address proteins of the same (or similar) protein families for their exploration as potential pharmacological targets. In addition, the knowledge of multitargeting features is of major importance in the drug selection process; particularly in ultra-large virtual screening procedures to gain high-quality compound collections. However, large-scale multitarget modulator landscapes are almost non-existent. RESULTS: We implemented a specific feature-driven computer-aided pattern analysis (C@PA) to extract molecular-structural features of inhibitors of the model protein family of ATP-binding cassette (ABC) transporters. New molecular-structural features have been identified that successfully expanded the known multitarget modulator landscape of pan-ABC transporter inhibitors. The prediction capability was biologically confirmed by the successful discovery of pan-ABC transporter inhibitors with a distinct inhibitory activity profile. AVAILABILITY AND IMPLEMENTATION: The multitarget dataset is available on the PANABC web page (http://www.panabc.info) and its use is free of charge. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Scaffold fragmentation and substructure hopping reveal potential, robustness, and limits of computer-aided pattern analysis (C@PA).

Computer-aided pattern analysis (C@PA) was recently presented as a powerful tool to predict multitarget ABC transporter inhibitors. The backbone of this computational methodology was the statistical analysis of frequently occurring molecular features amongst a fixed set of reported small-molecules that had been evaluated toward ABCB1, ABCC1, and ABCG2. As a result, negative and positive patterns were elucidated, and secondary positive substructures could be suggested that complemented the multitarget fingerprints. Elevating C@PA to a non-statistical and exploratory level, the concluded secondary positive patterns were extended with potential positive substructures to improve C@PA's prediction capabilities and to explore its robustness. A small-set compound library of known ABCC1 inhibitors with a known hit rate for triple ABCB1, ABCC1, and ABCG2 inhibition was taken to virtually screen for the extended positive patterns. In total, 846 potential broad-spectrum ABCB1, ABCC1, and ABCG2 inhibitors resulted, from which 10 have been purchased and biologically evaluated. Our approach revealed 4 novel multitarget ABCB1, ABCC1, and ABCG2 inhibitors with a biological hit rate of 40%, but with a slightly lower inhibitory power than derived from the original C@PA. This is the very first report about discovering novel broad-spectrum inhibitors against the most prominent ABC transporters by improving C@PA.

C@PA: Computer-Aided Pattern Analysis to Predict Multitarget ABC Transporter Inhibitors.

Based on literature reports of the last two decades, a computer-aided pattern analysis (C@PA) was implemented for the discovery of novel multitarget ABCB1 (P-gp), ABCC1 (MRP1), and ABCG2 (BCRP) inhibitors. C@PA included basic scaffold identification, substructure search and statistical distribution, as well as novel scaffold extraction to screen a large virtual compound library. Over 45,000 putative and novel broad-spectrum ABC transporter inhibitors were identified, from which 23 were purchased for biological evaluation. Our investigations revealed five novel lead molecules as triple ABCB1, ABCC1, and ABCG2 inhibitors. C@PA is the very first successful computational approach for the discovery of promiscuous ABC transporter inhibitors.

Rational drug design of 6-substituted 4-anilino-2-phenylpyrimidines for exploration of novel ABCG2 binding site.

In the search for novel, highly potent, and nontoxic adjuvant chemotherapeutics to resolve the major issue of ABC transporter-mediated multidrug resistance (MDR), pyrimidines were discovered as a promising compound class of modern ABCG2 inhibitors. As ABCG2-mediated MDR is a major obstacle in leukemia, pancreatic carcinoma, and breast cancer chemotherapy, adjuvant chemotherapeutics are highly desired for future clinical oncology. Very recently, docking studies of one of the most potent reversers of ABCG2-mediated MDR were reported and revealed a putative second binding pocket of ABCG2. Based on this (sub)pocket, a series of 16 differently 6-substituted 4-anilino-2-phenylpyrimidines was designed and synthesized to explore the potential increase in inhibitory activity of these ABCG2 inhibitors. The compounds were assessed for their influence on the ABCG2-mediated pheophorbide A transport, as well as the ABCB1- and ABCC1-mediated transport of calcein AM. They were additionally evaluated in MDR reversal assays to determine their half-maximal reversal concentration (EC50). The 6-substitution did not only show increased toxicity against ABCG2-overexpressing cells in combination with SN-38 but also a negative influence on cell viability in general. Nevertheless, several candidates had EC50 values in the low double-digit nanomolar concentration range, qualifying them as some of the most potent reversers of ABCG2-mediated MDR. In addition, five novel multitarget ABCB1, ABCC1, and ABCG2 inhibitors were discovered, four of them exerting their inhibitory power against the three stated transporters at least in the single-digit micromolar concentration range.

Strategies to gain novel Alzheimer's disease diagnostics and therapeutics using modulators of ABCA transporters.

Adenosine-triphosphate-(ATP)-binding cassette (ABC) transport proteins are ubiquitously present membrane-bound efflux pumps that distribute endo- and xenobiotics across intra- and intercellular barriers. Discovered over 40 years ago, ABC transporters have been identified as key players in various human diseases, such as multidrug-resistant cancer and atherosclerosis, but also neurodegenerative diseases, such as Alzheimer's disease (AD). Most prominent and well-studied are ABCB1, ABCC1, and ABCG2, not only due to their contribution to the multidrug resistance (MDR) phenotype in cancer, but also due to their contribution to AD. However, our understanding of other ABC transporters is limited, and most of the 49 human ABC transporters have been largely neglected as potential targets for novel small-molecule drugs. This is especially true for the ABCA subfamily, which contains several members known to play a role in AD initiation and progression. This review provides up-to-date information on the proposed functional background and pathological role of ABCA transporters in AD. We also provide an overview of small-molecules shown to interact with ABCA transporters as well as potential in silico, in vitro, and in vivo methodologies to gain novel templates for the development of innovative ABC transporter-targeting diagnostics and therapeutics.

Binding mode analysis of ABCA7 for the prediction of novel Alzheimer's disease therapeutics.

The adenosine-triphosphate-(ATP)-binding cassette (ABC) transporter ABCA7 is a genetic risk factor for Alzheimer's disease (AD). Defective ABCA7 promotes AD development and/or progression. Unfortunately, ABCA7 belongs to the group of 'under-studied' ABC transporters that cannot be addressed by small-molecules. However, such small-molecules would allow for the exploration of ABCA7 as pharmacological target for the development of new AD diagnostics and therapeutics. Pan-ABC transporter modulators inherit the potential to explore under-studied ABC transporters as novel pharmacological targets by potentially binding to the proposed 'multitarget binding site'. Using the recently reported cryogenic-electron microscopy (cryo-EM) structures of ABCA1 and ABCA4, a homology model of ABCA7 has been generated. A set of novel, diverse, and potent pan-ABC transporter inhibitors has been docked to this ABCA7 homology model for the discovery of the multitarget binding site. Subsequently, application of pharmacophore modelling identified the essential pharmacophore features of these compounds that may support the rational drug design of innovative diagnostics and therapeutics against AD.

Superior Pyrimidine Derivatives as Selective ABCG2 Inhibitors and Broad-Spectrum ABCB1, ABCC1, and ABCG2 Antagonists.

In the search for highly effective modulators addressing ABCG2-mediated MDR, 23 pyrimidines were synthesized and biologically assessed. Seven derivatives with (a) nitrogen- and/or halogen-containing residue(s) had extraordinary potencies against ABCG2 (IC50 < 150 nM). The compounds competitively inhibited ABCG2-mediated Hoechst 33342 transport but were not substrates of ABCG2. The most potent MDR reverser, compound 19, concentration-dependently increased SN-38-mediated cancer cell death at 11 nM (EC50), time-dependently doubled SN-38 toxicity in a period of 7 days at 10 nM, and half-maximally accelerated cell death combined with SN-38 at 17 nM. No induction of ABCG2 was observed. Furthermore, 11 pyrimidines were revealed as triple ABCB1/ABCC1/ABCG2 inhibitors. Five possessed IC50 values below 10 µM against each transporter, classifying them as some of the 50 most potent multitarget ABC transporter inhibitors. The most promising representative, compound 37, reversed ABCB1-, ABCC1-, and ABCG2-mediated MDR, making it one of the three most potent ABC transporter inhibitors and reversers of ABC transporters-mediated MDR.

Using a qPCR device to screen for modulators of ABC transporter activity: A step-by-step protocol.

INTRODUCTION: Adenosine triphosphate (ATP)-binding cassette (ABC) transporters are transmembrane proteins which actively transport a large variety of substrates across biological membranes. ABC transporter overexpression can be the underlying cause of multidrug resistance in oncology. Moreover, it has been revealed that increased ABCC1 transporter activity can ameliorate behavioural changes and Aß pathology in a rodent model of Alzheimer's disease and it is currently tested in AD patients. METHODS: Finding substances that modulate ABC transporter activity (inhibitors and activators) is of high relevance and thus, different methods have been developed to screen for potential modulators. For this purpose, we have developed a cell-based assay to measure the kinetics of ABCC1-mediated efflux of a fluorescent dye using a common qPCR device (Agilent AriaMx). RESULTS: We validated the specificity of our method with vanadate and benzbromarone controls. Furthermore, we provide a step-by-step protocol including statistical analysis of the resulting data and suggestions how to modify the protocol specifically to screen for activators of ABCC1. DISCUSSION: Our approach is biologically more relevant than cell-free assays. The continuous detection of kinetics allows for a more precise quantification compared with assays with single end-point measurements.