Oncology exploration: charting cancer medicinal chemistry space

DataPype: A Fully Automated Unified Software Platform for Computer-Aided Drug Design

With the advent of computer-aided drug design (CADD), traditional physical testing of thousands of molecules has now been replaced by target-focused drug discovery, where potentially bioactive molecules are predicted by computer software before their physical synthesis. However, despite being a significant breakthrough, CADD still faces various limitations and challenges. The increasing availability of data on small molecules has created a need to streamline the sourcing of data from different databases and automate the processing and cleaning of data into a form that can be used by multiple CADD software applications. Several standalone software packages are available to aid the drug designer, each with its own specific application, requiring specialized knowledge and expertise for optimal use. These applications require their own input and output files, making it a challenge for nonexpert users or multidisciplinary discovery teams. Here, we have developed a new software platform called DataPype, which wraps around these different software packages. It provides a unified automated workflow to search for hit compounds using specialist software. Additionally, multiple virtual screening packages can be used in the one workflow, and if different ways of looking at potential hit compounds all predict the same set of molecules, we have higher confidence that we should make or purchase and test the molecules. Importantly, DataPype can run on computer servers, speeding up the virtual screening for new compounds. Combining access to multiple CADD tools within one interface will enhance the early stage of drug discovery, increase usability, and enable the use of parallel computing.

Stereoselective Synthesis and Application of Gibberellic Acid-Derived Aminodiols

A series of gibberellic acid-based aminodiols was designed and synthesized from commercially available gibberellic acid. Exposure of gibberellic acid to hydrochloric acid under reflux conditions resulted in aromatization followed by rearrangement to form allo-gibberic acid. The key intermediate, ethyl allo-gibberate, was prepared according to literature methods. Epoxidation of key intermediate and subsequent ring-opening of the corresponding epoxide with different nucleophiles resulted in N-substituted aminodiols. The regioselective ring closure of N-benzyl-substituted aminodiol with formaldehyde was also investigated. All aminodiol derivatives were well characterized using modern spectroscopic techniques and evaluated for their antiproliferative activity against a panel of human cancer cell lines. In addition, structure–activity relationships were examined by assessing substituent effects on the aminodiol systems. The results indicated that aminodiols containing aromatic rings on their nitrogen substituents displayed significant cytotoxic effects. Among these agents, N-naphthylmethyl-substituted aminodiols were found to be the most potent candidates in this series. One of these molecules exhibited a modest cancer selectivity determined by non-cancerous fibroblast cells. A docking study was also made to exploit the observed results.

"Click" reaction mediated synthesis of costunolide and dehydrocostuslactone derivatives and evaluation of their cytotoxic activity

As part of pharmacological-phytochemical integrated studies on medicinal plants from Indian flora, costunolide (1) and dehydrocostus lactone (2), were isolated as major phytochemicals from Saussurea lappa, a plant traditionally used in different Asian systems of medicine. A series of 1,4-disubstituted-1,2,3-triazoles conjugates were synthesized through diastereo selective Michael addition followed by regioselective Huisgen 1,3-dipolar cycloaddition reactions. All these triazolyl derivatives (5a-5j) & (7a-7j) were well characterized using modern spectroscopic techniques and evaluated for their anticancer activity against a panel of five human cancerous celllines. The results indicated that all the analogs displayed moderate cytotoxic activity.

Compound high-quality criteria: a new vision to guide the development of drugs, current situation

For several decades, the pharmaceutical industry has suffered due to major issues such as reductions of the number of FDA approved drugs and biologics. Several analyses have been highlighted that the 'druglikeness' is one of the strategies to improve succeed rates of screening such as, for instance, high-throughput screening (HTS), and then hits (as starting point), leads and clinical candidates. It is clear that the improvement of compound quality accelerates the drug discovery projects. The monitoring of several indices to avoid 'molecular obesity' (ADMET problems) of final drugs from good-quality 'low-fat' starting points represents today a powerful strategy of optimization process. The development of the new guides to find drugs highlighting attempts at improving the attrition rate from hits to final medicines by focusing on how to improve the druggability of hits, leads and drugs during the drug discovery process represents a key approach to design next better generation of medicines.

Design, synthesis and anti-proliferative activities of novel 7′-O-substituted schisantherin A derivatives

A series of schisantherin A (1) derivatives were efficiently synthesized utilizing Yamaguchi esterification (2,4,6-trichlorobenzoyl chloride, Et₃N, THF, DMAP, toluene) at the C-7′ position of the schisantherin A core.

Mappability of drug-like space: towards a polypharmacologically competent map of drug-relevant compounds

Intuitive, visual rendering--mapping--of high-dimensional chemical spaces (CS), is an important topic in chemoinformatics. Such maps were so far dedicated to specific compound collections--either limited series of known activities, or large, even exhaustive enumerations of molecules, but without associated property data. Typically, they were challenged to answer some classification problem with respect to those same molecules, admired for their aesthetical virtues and then forgotten--because they were set-specific constructs. This work wishes to address the question whether a general, compound set-independent map can be generated, and the claim of "universality" quantitatively justified, with respect to all the structure-activity information available so far--or, more realistically, an exploitable but significant fraction thereof. The "universal" CS map is expected to project molecules from the initial CS into a lower-dimensional space that is neighborhood behavior-compliant with respect to a large panel of ligand properties. Such map should be able to discriminate actives from inactives, or even support quantitative neighborhood-based, parameter-free property prediction (regression) models, for a wide panel of targets and target families. It should be polypharmacologically competent, without requiring any target-specific parameter fitting. This work describes an evolutionary growth procedure of such maps, based on generative topographic mapping, followed by the validation of their polypharmacological competence. Validation was achieved with respect to a maximum of exploitable structure-activity information, covering all of Homo sapiens proteins of the ChEMBL database, antiparasitic and antiviral data, etc. Five evolved maps satisfactorily solved hundreds of activity-based ligand classification challenges for targets, and even in vivo properties independent from training data. They also stood chemogenomics-related challenges, as cumulated responsibility vectors obtained by mapping of target-specific ligand collections were shown to represent validated target descriptors, complying with currently accepted target classification in biology. Therefore, they represent, in our opinion, a robust and well documented answer to the key question "What is a good CS map?"

Addressing the Right Targets in Oncology

Translating existing and emerging knowledge of cancer biology into effective novel therapies remains a great challenge in drug discovery. A firm understanding of the target biology, confidence in the supporting preclinical research, and access to diverse chemical matter is required to lower attrition rates and prosecute targets effectively. Understanding past successes and failures will aid in refining this process to deliver further therapeutic benefit to patients. In this review, we suggest that early oncology drug discovery should focus on selection and prosecution of cancer targets with strong disease biology rather than on more chemically “druggable” targets with only modest disease-linkage. This approach offers higher potential benefit but also increases the need for innovative and alternative approaches. These include using different methods to validate novel targets and identify chemical matter, as well as raising the standards and our interpretation of the scientific literature. The combination of skills required for this emphasizes the need for broader early collaborations between academia and industry.

Synthesis, antiproliferative and anti-inflammatory activities of some novel 6-aryl-2-(p-(methanesulfonyl)phenyl)-4,5-dihydropyridazi-3(2H)-ones

Sixteen new 6-aryl-2-(p-(methanesulfonyl)phenyl)-4,5-dihydropyridazi-3(2H)-ones (2a-p) were synthesized and tested for in vitro anticancer and in vivo anti-inflammatory activities. Eleven (2b, 2d, 2e-j and 2m-p) of the obtained compounds were screened for their antiproliferative activity towards 60 human cancer cell lines by the National Cancer Institute (USA). Compound 2f showed remarkable activity with GI50 less than 1 μM on 36 human tumor cell lines and has been referred to Biological Evaluation Committee (NCI) for advance study. Compound 2g also displayed promising antiproliferative activity against 20 different cell lines with GI50 less than 1 μM. Compounds 2k and 2n were found to have a comparable anti-inflammatory activity to that of standard drug etoricoxib in carrageenan-induced rat hind paw edema model at 5 h.

Synthesis, anticancer, and antibacterial activities of piplartine derivatives on cell cycle regulation and growth inhibition

A series of piplartine derivatives were synthesized via Baylis-Hillman reaction and evaluated for anticancer and antibacterial activities. The cytotoxicity of these compounds was examined in two different human tumor cell lines, IMR-32 and HeLa. The antibacterial activity was examined in Staphylococcus aureus and Pseudomonas aeruginosa. The results showed that compounds 2b, 2e, and 2j were found to be the most active compounds, which displayed line no cytotoxicity, but G2-M cell cycle arrest in tumor cells, and showed cytostatic effects in bacteria.

Exploring DNA topoisomerase I ligand space in search of novel anticancer agents

DNA topoisomerase I (Top1) is over-expressed in tumour cells and is an important target in cancer chemotherapy. It relaxes DNA torsional strain generated during DNA processing by introducing transient single-strand breaks and allowing the broken strand to rotate around the intermediate Top1 – DNA covalent complex. This complex can be trapped by a group of anticancer agents interacting with the DNA bases and the enzyme at the cleavage site, preventing further topoisomerase activity. Here we have identified novel Top1 inhibitors as potential anticancer agents by using a combination of structure- and ligand-based molecular modelling methods. Pharmacophore models have been developed based on the molecular characteristics of derivatives of the alkaloid camptothecin (CPT), which represent potent antitumour agents and the main group of Top1 inhibitors. The models generated were used for in silico screening of the National Cancer Institute (NCI, USA) compound database, leading to the identification of a set of structurally diverse molecules. The strategy is validated by the observation that amongst these molecules are several known Top1 inhibitors and agents cytotoxic against human tumour cell lines. The potential of the untested hits to inhibit Top1 activity was further evaluated by docking into the binding site of a Top1 – DNA complex, resulting in a selection of 10 compounds for biological testing. Limited by the compound availability, 7 compounds have been tested in vitro for their Top1 inhibitory activity, 5 of which display mild to moderate Top1 inhibition. A further compound, found by similarity search to the active compounds, also shows mild activity. Although the tested compounds display only low in vitro antitumour activity, our approach has been successful in the identification of structurally novel Top1 inhibitors worthy of further investigation as potential anticancer agents.

Visual characterization and diversity quantification of chemical libraries: 1. creation of delimited reference chemical subspaces

High-throughput screening (HTS) is a well-established technology which can test up to several million compounds in a few weeks. Despite these appealing capabilities, available resources and high costs may limit the number of molecules screened, making diversity analysis a method of choice to design and prioritize screening libraries. With a constantly increasing number of molecules available for screening, chemical space has become a key concept for visualizing, analyzing, and comparing chemical libraries. In this first article, we present a new method to build delimited reference chemical subspaces (DRCS). A set of 16 million screening compounds from 73 chemical providers has been gathered, resulting in a database of 6.63 million standardized and unique molecules. These molecules have been used to create three DRCS using three different sets of chemical descriptors. A robust principal component analysis model for each space has been obtained, whereby molecules are projected in a reduced two-dimensional viewable space. The specificity of our approach is that each reduced space has been delimited by a representative contour encompassing a very large proportion of molecules and reflecting its overall shape. The methodology is illustrated by mapping and comparing various chemical libraries. Several tools used in these studies are made freely available, thus enabling any user to compute DRCS matching specific requirements.

Identification of agents that induce apoptosis of multicellular tumour spheroids: enrichment for mitotic inhibitors with hydrophobic properties

Cell-based anticancer drug screening generally utilizes rapidly proliferating tumour cells grown as monolayer cultures. Hit compounds from such screens are not necessarily effective on hypoxic and slowly proliferating cells in 3-D tumour tissue. The aim of this study was to examine the potential usefulness of 3-D cultured tumour cells for anticancer drug screening. We used colon carcinoma multicellular spheroids containing hypoxic and quiescent cells in core areas for this purpose. Three libraries (∼11 000 compounds) were screened using antiproliferative activity and/or apoptosis as end-points. Screening of monolayer and spheroid cultures was found to identify different sets of hit compounds. Spheroid screening enriched for hydrophobic compounds: median XLogP values of 4.3 and 4.4 were observed for the hits in two independent screening campaigns. Mechanistic analysis revealed that the majority of spheroid screening hits were microtubuli inhibitors. One of these inhibitors was examined in detail and found to be effective against non-dividing cells in the hypoxic centres of spheroids. Spheroid screening represents a conceptually new strategy for anticancer drug discovery. Our findings have implications for drug library design and hit selection in projects aimed to develop drugs for the treatment of solid tumours.

Rational methods for the selection of diverse screening compounds

Traditionally a pursuit of large pharmaceutical companies, high-throughput screening assays are becoming increasingly common within academic and government laboratories. This shift has been instrumental in enabling projects that have not been commercially viable, such as chemical probe discovery and screening against high-risk targets. Once an assay has been prepared and validated, it must be fed with screening compounds. Crafting a successful collection of small molecules for screening poses a significant challenge. An optimized collection will minimize false positives while maximizing hit rates of compounds that are amenable to lead generation and optimization. Without due consideration of the relevant protein targets and the downstream screening assays, compound filtering and selection can fail to explore the great extent of chemical diversity and eschew valuable novelty. Herein, we discuss the different factors to be considered and methods that may be employed when assembling a structurally diverse compound collection for screening. Rational methods for selecting diverse chemical libraries are essential for their effective use in high-throughput screens.

Design and synthesis of novel tetrahydro-2H-Pyrano[3,2-c]pyridazin-3(6H)-one derivatives as potential anticancer agents

Polyfunctional tetrahydro-2H-pyrano[3,2-c]pyridazin-3(6H)-one derivatives were synthesized and biologically evaluated as novel anticancer agents. These motifs were produced by a five-step reaction sequence in which the Achmatowicz oxidative cyclization, is the basic core for such synthesis. Compounds 15f, 16c, and 16d showed antiproliferative activity against the SK-BR-3 breast cancer cell line. Importantly, 16c and 16d showed the highest efficacy, being approximately 30-fold more potent against SK-BR-3 (IC50 0.21 and 0.15 μM, respectively) compared to other cancer cell lines tested. In addition, 16c and 16d displayed about 295 fold less toxicity against normal breast cell line MCF10A compared to SK-BR-3 breast cancer cells. These compounds form the foundation for further investigation in our continuing efforts to develop potent anticancer agents.

Synthesis and biological evaluation of cytotoxic activity of novel anthracene L-rhamnopyranosides

A series of anthracene L-rhamnopyranosides were designed and synthesized in a practical way and their cytotoxic activity was examined in vitro. Most compounds exhibited both potent cytotoxicity against several tumor cell lines and high DNA binding capacity. The preliminary results showed that subtle modifications of rhamnosyl moiety in anthracene rhamnosides with acetyl group had a selective toxicity for different tumor cells and the displacement of C-10 carbonyl group in emodin by acetylmethylene group was helpful to improve the inhibitory activity. Lipophilicity of the anthracene glycosides was not a crucial factor for cytotoxicity and most molecules with good cytotoxicity could inhibit the catalytic activity of Top2alpha.

Factor analysis of proton MR spectroscopic imaging data in HIV infection: metabolite-derived factors help identify infection and dementia

PURPOSE

To develop a relevant pathophysiologic model of human immunodeficiency virus (HIV)-associated dementia by studying regional variations in metabolite levels measured with magnetic resonance (MR) spectroscopic imaging and their relationship to immunologic measures and cognitive dysfunction.

MATERIALS AND METHODS

This was a HIPAA-compliant, institutional review board-approved study involving written informed consent. Distributions of N-acetylaspartate (NAA), choline (Cho), and creatine (Cr) concentrations in 94 subjects (20 seronegative controls and 74 HIV-positive subjects; 34 of the HIV-positive subjects having HIV-associated dementia; 63 men, 31 women; mean age, 40 years) were determined with proton (hydrogen 1 [(1)H]) MR spectroscopic imaging. HIV-positive subjects underwent neuropsychological testing and blood and cerebrospinal fluid (CSF) analysis. Factor analysis was utilized to determine associations between metabolites across regions. Analysis of variance and t tests were used to isolate differences between cohorts.

RESULTS

A "Cho factor" differentiated seronegative controls from HIV-infected cohorts, indicating elevated Cho levels across deep gray and white matter regions of HIV-positive individuals. An "NAA factor" differentiated those with dementia from those without and correlated best with psychomotor and executive function tests. A "Cr factor" indicated Cr elevations correlated with CSF monocyte chemoattractant protein-1 levels. NAA and Cr factor scores were strongly weighted to metabolite changes in white matter regions.

CONCLUSION

These results highlight the importance of white matter involvement in HIV-associated dementia and support the current pathogenesis model of glial cell proliferation in HIV infection, denoted by regional Cho elevations, and neuronal dysfunction and/or death, denoted by NAA decreases, associated with dementia. Factor analysis of MR spectroscopic imaging data is a useful method for determining regional metabolic variations in HIV infection and its neuropsychological correlates.

Identification of a novel topoisomerase inhibitor effective in cells overexpressing drug efflux transporters

Background

Natural product structures have high chemical diversity and are attractive as lead structures for discovery of new drugs. One of the disease areas where natural products are most frequently used as therapeutics is oncology.

Method and Findings

A library of natural products (NCI Natural Product set) was screened for compounds that induce apoptosis of HCT116 colon carcinoma cells using an assay that measures an endogenous caspase-cleavage product. One of the apoptosis-inducing compounds identified in the screen was thaspine (taspine), an alkaloid from the South American tree Croton lechleri. The cortex of this tree is used for medicinal purposes by tribes in the Amazonas basin. Thaspine was found to induce conformational activation of the pro-apoptotic proteins Bak and Bax, mitochondrial cytochrome c release and mitochondrial membrane permeabilization in HCT116 cells. Analysis of the gene expression signature of thaspine-treated cells suggested that thaspine is a topoisomerase inhibitor. Inhibition of both topoisomerase I and II was observed using in vitro assays, and thaspine was found to have a reduced cytotoxic effect on a cell line with a mutated topoisomerase II enzyme. Interestingly, in contrast to the topoisomerase II inhibitors doxorubicin, etoposide and mitoxantrone, thaspine was cytotoxic to cell lines overexpressing the PgP or MRP drug efflux transporters. We finally show that thaspine induces wide-spread apoptosis in colon carcinoma multicellular spheroids and that apoptosis is induced in two xenograft mouse models in vivo.

Conclusions

The alkaloid thaspine from the cortex of Croton lechleri is a dual topoisomerase inhibitor effective in cells overexpressing drug efflux transporters and induces wide-spread apoptosis in multicellular spheroids.

Integration of ligand and structure-based virtual screening for the identification of the first dual targeting agent for heat shock protein 90 (Hsp90) and tubulin

We describe the discovery of a novel indazole-based scaffold that represents the "first-in-class" dual Hsp90/tubulin binding compound. Individual known ligands for both targets shared similar 3',4',5'-trimethoxyphenyl cores, and from this it was hypothesized that application of an integrated ligand and structure-based virtual screening (VS) workflow could yield a single scaffold with dual binding affinity. Following validation of the VS protocol, we successfully identified a novel dual inhibitor, sourced from a commercial screening collection of 160 000 compounds.

Factor analysis reveals differences in brain metabolism in macaques with SIV/AIDS and those with SIV-induced encephalitis

MRS has often been used to study metabolic processes in the HIV-infected brain. However, it remains unclear how changes in individual metabolites are related to one another in this context of virus-induced central nervous system dysfunction. We used factor analysis (FA) to identify patterns of metabolite distributions from an MRS study of healthy macaques and those infected with simian immunodeficiency virus (SIV) which were moribund with AIDS. FA summarized the correlations from nine metabolites into three main factors. Factor 3 identified patterns that discern healthy animals from those with SIV/AIDS. Factor 2 was able to differentiate between animals that had encephalitis and those moribund with AIDS but lacking encephalitis. Specifically, Factor 2 was able to distinguish animals with moderate to severe encephalitis from animals with mild or no encephalitis as well as uninfected controls. FA not only confirmed the involvement of neuronal metabolites (N-acetylaspartate and glutamate) in disease severity, but also detected changes in creatine and myo-inositol that have not been observed in the SIV macaque model previously. These results suggest that the divergent pathways of N-acetylaspartate and creatine in this disease may enable the commonly reported ratio N-acetylaspartate/creatine to be a more sensitive marker of disease severity.

Improving the drug selection and development process for combination devices

Combination devices are at the interface of both pharmaceutical and medical device research. While there have been several notable successes in bringing combination devices to market there are drug selection criteria that both the pharmaceutical and medical device companies need to consider. A successful combination device creates a product that has efficacy greater than the sum of the parts. However, failure to address some aspects of the drug or biologic properties in enough detail could result in a suboptimal product, creating a challenging legacy for future iterations. This review addresses the many dimensions including opportunities and challenges of combination device development from both the device and pharmaceutical perspectives.

In silico pharmacology for drug discovery: applications to targets and beyond

Computational (in silico) methods have been developed and widely applied to pharmacology hypothesis development and testing. These in silico methods include databases, quantitative structure-activity relationships, similarity searching, pharmacophores, homology models and other molecular modeling, machine learning, data mining, network analysis tools and data analysis tools that use a computer. Such methods have seen frequent use in the discovery and optimization of novel molecules with affinity to a target, the clarification of absorption, distribution, metabolism, excretion and toxicity properties as well as physicochemical characterization. The first part of this review discussed the methods that have been used for virtual ligand and target-based screening and profiling to predict biological activity. The aim of this second part of the review is to illustrate some of the varied applications of in silico methods for pharmacology in terms of the targets addressed. We will also discuss some of the advantages and disadvantages of in silico methods with respect to in vitro and in vivo methods for pharmacology research. Our conclusion is that the in silico pharmacology paradigm is ongoing and presents a rich array of opportunities that will assist in expediating the discovery of new targets, and ultimately lead to compounds with predicted biological activity for these novel targets.

A cell-based molecular transport simulator for pharmacokinetic prediction and cheminformatic exploration

In the body, cell monolayers serve as permeability barriers, determining transport of molecules from one organ or tissue compartment to another. After oral drug administration, for example, transport across the epithelial cell monolayer lining the lumen of the intestine determines the fraction of drug in the gut that is absorbed by the body. By modeling passive transcellular transport properties in the presence of an apical to basolateral concentration gradient, we demonstrate how a computational, cell-based molecular transport simulator can be used to define a physicochemical property space occupied by molecules with desirable permeability and intracellular retention characteristics. Considering extracellular domains of cell surface receptors located on the opposite side of a cell monolayer as a drug's desired site of action, simulation of transcellular transport can be used to define the physicochemical properties of molecules with maximal transcellular permeability but minimal intracellular retention. Arguably, these molecules would possess very desirable features: least likely to exhibit nonspecific toxicity, metabolism, and side effects associated with high (undesirable) intracellular accumulation; and most likely to exhibit favorable bioavailability and efficacy associated with maximal rates of transport across cells and minimal intracellular retention, resulting in (desirable) accumulation at the extracellular site of action. Simulated permeability values showed good correlations with PAMPA, Caco-2, and intestinal permeability measurements, without "training" the model and without resorting to statistical regression techniques to "fit" the data. Therefore, cell-based molecular transport simulators could be useful in silico screening tools for chemical genomics and drug discovery.

Computer-aided drug discovery and development (CADDD): in silico-chemico-biological approach

It is generally recognized that drug discovery and development are very time and resources consuming processes. There is an ever growing effort to apply computational power to the combined chemical and biological space in order to streamline drug discovery, design, development and optimization. In biomedical arena, computer-aided or in silico design is being utilized to expedite and facilitate hit identification, hit-to-lead selection, optimize the absorption, distribution, metabolism, excretion and toxicity profile and avoid safety issues. Commonly used computational approaches include ligand-based drug design (pharmacophore, a 3D spatial arrangement of chemical features essential for biological activity), structure-based drug design (drug-target docking), and quantitative structure-activity and quantitative structure-property relationships. Regulatory agencies as well as pharmaceutical industry are actively involved in development of computational tools that will improve effectiveness and efficiency of drug discovery and development process, decrease use of animals, and increase predictability. It is expected that the power of CADDD will grow as the technology continues to evolve.

Application of data mining approaches to drug delivery

Computational approaches play a key role in all areas of the pharmaceutical industry from data mining, experimental and clinical data capture to pharmacoeconomics and adverse events monitoring. They will likely continue to be indispensable assets along with a growing library of software applications. This is primarily due to the increasingly massive amount of biology, chemistry and clinical data, which is now entering the public domain mainly as a result of NIH and commercially funded projects. We are therefore in need of new methods for mining this mountain of data in order to enable new hypothesis generation. The computational approaches include, but are not limited to, database compilation, quantitative structure activity relationships (QSAR), pharmacophores, network visualization models, decision trees, machine learning algorithms and multidimensional data visualization software that could be used to improve drug delivery after mining public and/or proprietary data. We will discuss some areas of unmet needs in the area of data mining for drug delivery that can be addressed with new software tools or databases of relevance to future pharmaceutical projects.