Small molecule-facilitated degradation of ANO1 protein: a new targeting approach for anticancer therapeutics.

ANO1, a calcium-activated chloride channel, is highly expressed and amplified in human cancers and is a critical survival factor in these cancers. The ANO1 inhibitor CaCCinh-A01 decreases proliferation of ANO1-amplified cell lines; however, the mechanism of action remains elusive. We explored the mechanism behind the inhibitory effect of CaCCinh-A01 on cell proliferation using a combined experimental and in silico approach. We show that inhibition of ANO1 function is not sufficient to diminish proliferation of ANO1-dependent cancer cells. We report that CaCCinh-A01 reduces ANO1 protein levels by facilitating endoplasmic reticulum-associated, proteasomal turnover of ANO1. Washout of CaCCinh-A01 rescued ANO1 protein levels and resumed cell proliferation. Proliferation of newly derived CaCCinh-A01-resistant cell pools was not affected by CaCCinh-A01 as compared with the parental cells. Consistently, CaCCinh-A01 failed to reduce ANO1 protein levels in these cells, whereas ANO1 currents were still inhibited by CaCCinh-A01, indicating that CaCCinh-A01 inhibits cell proliferation by reducing ANO1 protein levels. Furthermore, we employed in silico methods to elucidate novel biological functions of ANO1 inhibitors. Specifically, we derived a pharmacophore model to describe inhibitors capable of promoting ANO1 degradation and report new inhibitors of ANO1-dependent cell proliferation. In summary, our data demonstrate that inhibition of the channel activity of ANO1 is not sufficient to inhibit ANO1-dependent cell proliferation, indicating that the role of ANO1 in cancer only partially depends on its function as a channel. Our results provide an impetus for gaining a deeper understanding of ANO1 modulation in cells and introduce a new targeting approach for antitumor therapy in ANO1-amplified cancers.

FOCUS--Development of a Global Communication and Modeling Platform for Applied and Computational Medicinal Chemists.

Communication of data and ideas within a medicinal chemistry project on a global as well as local level is a crucial aspect in the drug design cycle. Over a time frame of eight years, we built and optimized FOCUS, a platform to produce, visualize, and share information on various aspects of a drug discovery project such as cheminformatics, data analysis, structural information, and design. FOCUS is tightly integrated with internal services that involve-among others-data retrieval systems and in-silico models and provides easy access to automated modeling procedures such as pharmacophore searches, R-group analysis, and similarity searches. In addition, an interactive 3D editor was developed to assist users in the generation and docking of close analogues of a known lead. In this paper, we will specifically concentrate on issues we faced during development, deployment, and maintenance of the software and how we continually adapted the software in order to improve usability. We will provide usage examples to highlight the functionality as well as limitations of FOCUS at the various stages of the development process. We aim to make the discussion as independent of the software platform as possible, so that our experiences can be of more general value to the drug discovery community.

Automated ligand- and structure-based protocol for in silico prediction of human serum albumin binding.

Plasma protein binding has a profound impact on the pharmacokinetic and pharmacodynamic properties of many drug candidates and is thus an integral component of drug discovery. Nevertheless, extant methods to examine small-molecule interactions with plasma protein have various limitations, thus creating a need for alternative methods. Herein we present a comprehensive and cross-validated in silico workflow for the prediction of small-molecule binding to Human Serum Albumin (HSA), the most ubiquitous plasma protein. This protocol reliably predicts small-molecule interactions with HSA, including a binding affinity calculation using multiple linear regression methods, binding site prediction using a naive-Bayes classifier, and a three-dimensional binding pose using induced fit docking. Furthermore, this workflow is implemented in a portable and automated format that can be downloaded and used by other end users, either as is or with customization.

Development of isoform selective PI3-kinase inhibitors as pharmacological tools for elucidating the PI3K pathway.

Using a parallel synthesis approach to target a non-conserved region of the PI3K catalytic domain a pan-PI3K inhibitor 1 was elaborated to provide alpha, delta and gamma isoform selective Class I PI3K inhibitors 21, 24, 26 and 27. The compounds had good cellular activity and were selective against protein kinases and other members of the PI3K superfamily including mTOR and DNA-PK.

The design, synthesis and structure-activity relationships of novel isoindoline-based histone deacetylase inhibitors.

The design, synthesis and biological evaluation of a novel series of isoindoline-based hydroxamates is described. Several analogs were shown to inhibit HDAC1 with IC(50) values in the low nanomolar range and inhibit cellular proliferation of HCT116 human colon cancer cells in the sub-micromolar range. The cellular potency of compound 17e was found to have greater in vitro anti-proliferative activity than several compounds in late stage clinical trials for the treatment of cancer. The in vitro safety profiles of selected compounds were assessed and shown to be suitable for further lead optimization.

Avoidance of the Ames test liability for aryl-amines via computation.

Aryl-amines are commonly used synthons in modern drug discovery, however a minority of these chemical templates have the potential to cause toxicity through mutagenicity. The toxicity mostly arises through a series of metabolic steps leading to a reactive electrophilic nitrenium cation intermediate that reacts with DNA nucleotides causing mutation. Highly detailed in silico calculations of the energetics of chemical reactions involved in the metabolic formation of nitrenium cations have been performed. This allowed a critical assessment of the accuracy and reliability of using a theoretical formation energy of the DNA-reactive nitrenium intermediate to correlate with the Ames test response. This study contains the largest data set reported to date, and presents the in silico calculations versus the in vitro Ames response data in the form of beanplots commonly used in statistical analysis. A comparison of this quantum mechanical approach to QSAR and knowledge-based methods is also reported, as well as the calculated formation energies of nitrenium ions for thousands of commercially available aryl-amines generated as a watch-list for medicinal chemists in their synthetic optimization strategies.

Human HDAC isoform selectivity achieved via exploitation of the acetate release channel with structurally unique small molecule inhibitors.

Herein we report the discovery of a family of novel yet simple, amino-acid derived class I HDAC inhibitors that demonstrate isoform selectivity via access to the internal acetate release channel. Isoform selectivity criteria is discussed on the basis of X-ray crystallography and molecular modeling of these novel inhibitors bound to HDAC8, potentially revealing insights into the mechanism of enzymatic function through novel structural features revealed at the atomic level.

Antibacterial and Solubility Optimization of Thiomuracin A.

Synthetic studies of the antimicrobial secondary metabolite thiomuracin A (1) provided access to analogues in the Northern region (C2-C10). Selective hydrolysis of the C10 amide of lead compound 2 and subsequent derivatization led to novel carbon- and nitrogen-linked analogues (e.g., 3) which improved antibacterial potency across a panel of Gram-positive organisms. In addition, congeners with improved physicochemical properties were identified which proved efficacious in murine sepsis and hamster C. difficile models of disease. Optimal efficacy in the hamster model of C. difficile was achieved with compounds that possessed both potent antibacterial activity and high aqueous solubility.

The chemical tuning of a weak zinc binding motif for histone deacetylase using electronic effects.

The hydroxamic acid moiety is an effective metal-binding warhead for a variety of metalloenzyme targets of interest in drug-discovery. For the zinc-containing histone deacetylase enzymes in particular, this chemical group has been widely incorporated and studied in the clinic. An alternative chemical functionality for binding zinc is the α-aminocarbonyl motif, which has been shown to bind to histone deacetylase enzymes. The current article explores the minimal binding site theoretical approach combined with structural knowledge to explore the ideal chemical substitution pattern of the α-aminocarbonyl motif within HDAC8. The metal-binding strength of the group is predicted to be highly tunable to chemical substitution at the carbonyl and the α-amino carbon. A fixed receptor model approach with a dispersion-corrected density functional, clearly discerned the effect of different substituents at both these positions using either a flexible or partially fixed ligand optimized in the presence of a fixed receptor model of the HDAC8 binding site. An electron donating substituent such as methyl at the C(α) in combination with NMe(2) substitution at the carbonyl position, similar to observed crystal structures, result in the optimal energetic profile for binding the zinc atom in the HDAC8 enzyme.

Discovery of LFF571: an investigational agent for Clostridium difficile infection.

Clostridium difficile (C. difficile) is a Gram positive, anaerobic bacterium that infects the lumen of the large intestine and produces toxins. This results in a range of syndromes from mild diarrhea to severe toxic megacolon and death. Alarmingly, the prevalence and severity of C. difficile infection are increasing; thus, associated morbidity and mortality rates are rising. 4-Aminothiazolyl analogues of the antibiotic natural product GE2270 A (1) were designed, synthesized, and optimized for the treatment of C. difficile infection. The medicinal chemistry effort focused on enhancing aqueous solubility relative to that of the natural product and previous development candidates (2, 3) and improving antibacterial activity. Structure-activity relationships, cocrystallographic interactions, pharmacokinetics, and efficacy in animal models of infection were characterized. These studies identified a series of dicarboxylic acid derivatives, which enhanced solubility/efficacy profile by several orders of magnitude compared to previously studied compounds and led to the selection of LFF571 (4) as an investigational new drug for treating C. difficile infection.

Identification of elongation factor G as the conserved cellular target of argyrin B.

Argyrins, produced by myxobacteria and actinomycetes, are cyclic octapeptides with antibacterial and antitumor activity. Here, we identify elongation factor G (EF-G) as the cellular target of argyrin B in bacteria, via resistant mutant selection and whole genome sequencing, biophysical binding studies and crystallography. Argyrin B binds a novel allosteric pocket in EF-G, distinct from the known EF-G inhibitor antibiotic fusidic acid, revealing a new mode of protein synthesis inhibition. In eukaryotic cells, argyrin B was found to target mitochondrial elongation factor G1 (EF-G1), the closest homologue of bacterial EF-G. By blocking mitochondrial translation, argyrin B depletes electron transport components and inhibits the growth of yeast and tumor cells. Further supporting direct inhibition of EF-G1, expression of an argyrin B-binding deficient EF-G1 L693Q variant partially rescued argyrin B-sensitivity in tumor cells. In summary, we show that argyrin B is an antibacterial and cytotoxic agent that inhibits the evolutionarily conserved target EF-G, blocking protein synthesis in bacteria and mitochondrial translation in yeast and mammalian cells.

An investigation into pharmaceutically relevant mutagenicity data and the influence on Ames predictive potential.

BACKGROUND: In drug discovery, a positive Ames test for bacterial mutation presents a significant hurdle to advancing a drug to clinical trials. In a previous paper, we discussed success in predicting the genotoxicity of reagent-sized aryl-amines (ArNH2), a structure frequently found in marketed drugs and in drug discovery, using quantum mechanics calculations of the energy required to generate the DNA-reactive nitrenium intermediate (ArNH:+). In this paper we approach the question of what molecular descriptors could improve these predictions and whether external data sets are appropriate for further training. RESULTS: In trying to extend and improve this model beyond this quantum mechanical reaction energy, we faced considerable difficulty, which was surprising considering the long history and success of QSAR model development for this test. Other quantum mechanics descriptors were compared to this reaction energy including AM1 semi-empirical orbital energies, nitrenium formation with alternative leaving groups, nitrenium charge, and aryl-amine anion formation energy. Nitrenium formation energy, regardless of the starting species, was found to be the most useful single descriptor. External sets used in other QSAR investigations did not present the same difficulty using the same methods and descriptors. When considering all substructures rather than just aryl-amines, we also noted a significantly lower performance for the Novartis set. The performance gap between Novartis and external sets persists across different descriptors and learning methods. The profiles of the Novartis and external data are significantly different both in aryl-amines and considering all substructures. The Novartis and external data sets are easily separated in an unsupervised clustering using chemical fingerprints. The chemical differences are discussed and visualized using Kohonen Self-Organizing Maps trained on chemical fingerprints, mutagenic substructure prevalence, and molecular weight. CONCLUSIONS: Despite extensive work in the area of predicting this particular toxicity, work in designing and publishing more relevant test sets for compounds relevant to drug discovery is still necessary. This work also shows that great care must be taken in using QSAR models to replace experimental evidence. When considering all substructures, a random forest model, which can inherently cover distinct neighborhoods, built on Novartis data and previously reported external data provided a suitable model.

Atomic-scale characterization of conformational changes in the preQ1 riboswitch aptamer upon ligand binding.

Riboswitches are mRNA structural elements that act as intracellular sensors of small-molecule metabolites. By undergoing conformational changes capable of modulating translation or terminating transcription, riboswitches are able to play a role in regulating the concentration of essential metabolites in the cell. Computer-guided fluorescence experiments were carried out to interrogate molecular dynamics and conformational changes in the minimal riboswitch aptamer that binds 7-aminomethyl-7-deazaguanine (preQ1). Our combined experimental results and computational analysis suggest that the preQ1 riboswitch apo form is structured but shows no evidence of a ligand-binding pocket. Simulations of the apo and bound forms indicate a large conformational change is triggered by the breaking of the Watson-Crick base pairing of nucleotides G11 and C31 upon preQ1 removal, followed by collapse of the pocket due to interfering π-stacking. Computational predictions of local aptamer dynamics were validated by fluorescence experiments employing 2-aminopurine substitutions. In-line probing reactions confirmed that fluorophore-labeled riboswitches retain similar higher-order structural features as the unlabeled aptamer upon ligand binding, although their affinity for the ligand is reduced by the introduction of the fluorescent reporter.

Antibacterial optimization of 4-aminothiazolyl analogues of the natural product GE2270 A: identification of the cycloalkylcarboxylic acids.

4-Aminothiazolyl analogues of the antibiotic natural product GE2270 A (1) were designed, synthesized, and optimized for their activity against Gram positive bacterial infections. Optimization efforts focused on improving the physicochemical properties (e.g., aqueous solubility and chemical stability) of the 4-aminothiazolyl natural product template while improving the in vitro and in vivo antibacterial activity. Structure-activity relationships were defined, and the solubility and efficacy profiles were improved over those of previous analogues and 1. These studies identified novel, potent, soluble, and efficacious elongation factor-Tu inhibitors, which bear cycloalkylcarboxylic acid side chains, and culminated in the selection of development candidates amide 48 and urethane 58.

Optimization of the in vitro cardiac safety of hydroxamate-based histone deacetylase inhibitors.

Histone deacetylase (HDAC) inhibitors have shown promise in treating various forms of cancer. However, many HDAC inhibitors from diverse structural classes have been associated with QT prolongation in humans. Inhibition of the human ether a-go-go related gene (hERG) channel has been associated with QT prolongation and fatal arrhythmias. To determine if the observed cardiac effects of HDAC inhibitors in humans is due to hERG blockade, a highly potent HDAC inhibitor devoid of hERG activity was required. Starting with dacinostat (LAQ824), a highly potent HDAC inhibitor, we explored the SAR to determine the pharmacophores required for HDAC and hERG inhibition. We disclose here the results of these efforts where a high degree of pharmacophore homology between these two targets was discovered. This similarity prevented traditional strategies for mitigating hERG binding/modulation from being successful and novel approaches for reducing hERG inhibition were required. Using a hERG homology model, two compounds, 11r and 25i, were discovered to be highly efficacious with weak affinity for the hERG and other ion channels.

Conformational refinement of hydroxamate-based histone deacetylase inhibitors and exploration of 3-piperidin-3-ylindole analogues of dacinostat (LAQ824).

Inspired by natural product HDAC inhibitors, we prepared a series of conformationally restrained HDAC inhibitors based on the hydroxamic acid dacinostat (LAQ824, 7). Several scaffolds with improved biochemical and cellular potency, as well as attenuated hERG inhibition, were identified, suggesting that the introduction of molecular rigidity is a viable strategy to enhance HDAC binding and mitigate hERG liability. Further SAR studies around a 3-piperidin-3-ylindole moiety resulted in the discovery of compound 30, for which a unique conformation was speculated to contribute to overcoming increased lipophilicity and attenuating hERG binding. Separation of racemate 30 afforded 32, the R enantiomer, which demonstrated improved potency in both enzyme and cellular assays compared to dacinostat.

Application of non-parametric regression to quantitative structure-activity relationships.

Several non-parametric regressors have been applied to modelling quantitative structure-activity relationship (QSAR) data. Performances were benchmarked against multilinear regression and the nonlinear method of smoothing splines. Variable selection was explored through systematic combinations of different variables and combinations of principal components. For the training set examined--539 inhibitors of the tyrosine kinase, Syk--the best two-descriptor model had a 5-fold cross-validated q2 of 0.43. This was generated by a multi-variate Nadaraya-Watson kernel estimator. A subsequent, independent, test set of 371 similar chemical entities showed the model had some predictive power. Other approaches did not perform as well. A modest increase in predictive ability can be achieved with three descriptors, but the resulting model is less easy to visualise. We conclude that non-parametric regression offers a potentially powerful approach to identifying predictive, low-dimensional QSARs.