Cheminformatics Analysis Research Articles

The effects of cinnamaldehyde and eugenol on human adipose-derived mesenchymal stem cells viability, growth and differentiation: a cheminformatics and in vitro study.

The aim of this study was to estimate the cheminformatics and qualitative structure-activity relationship (QSAR) of cinnamaldehyde and eugenol. The effects of cinnamaldehyde and eugenol on the viability, doubling time and adipogenic or osteogenic differentiations of human adipose-derived mesenchymal stem cells (hASCs) were also investigated. QSAR and toxicity indices of cinnamaldehyde and eugenol were evaluated using cheminformatics tools including Toxtree and Toxicity Estimation Software Tool (T.E.S.T) and molinspiration server. Besides, their effects on the hASCs viability, doubling time and differentiation to adipogenic or osteogenic lineages were evaluated. Cinnamaldehyde is predicted to be more lipophilic and less toxic than eugenol. Both phytochemicals may be developmental toxicants. They probably undergo hydroxylation and epoxidation reactions by cytochrome-P450. The 2.5 µM/ml cinnamaldehyde and 0.1 µg/ml eugenol did not influence hASCs viability following 72 hr of treatment. But higher concentrations of these phytochemicals insignificantly increased hASCs doubling time till 96 hr, except 1 µg/ml eugenol for which the increase was significant. Only low concentrations of both phytochemicals were tested for their effects on the hASCs differentiation. The 2.5 µM/ml cinnamaldehyde and 0.1 µg/ml eugenol enhanced the osteogenesis and decreased the adipogenesis of hASCs meaningfully. According to the cheminformatics analysis and in vitro study, cinnamaldehyde and eugenol are biocompatible and low toxic for hASCs. Both phytochemicals may be suitable for regenerative medicine and tissue engineering when used at low concentrations, but maybe useful for neoplastic growth inhibition when used at high concentrations.

Metabolomics and Cheminformatics Analysis of Antifungal Function of Plant Metabolites.

Fusarium head blight (FHB), primarily caused by Fusarium graminearum, is a devastating disease of wheat. Partial resistance to FHB of several wheat cultivars includes specific metabolic responses to inoculation. Previously published studies have determined major metabolic changes induced by pathogens in resistant and susceptible plants. Functionality of the majority of these metabolites in resistance remains unknown. In this work we have made a compilation of all metabolites determined as selectively accumulated following FHB inoculation in resistant plants. Characteristics, as well as possible functions and targets of these metabolites, are investigated using cheminformatics approaches with focus on the likelihood of these metabolites acting as drug-like molecules against fungal pathogens. Results of computational analyses of binding properties of several representative metabolites to homology models of fungal proteins are presented. Theoretical analysis highlights the possibility for strong inhibitory activity of several metabolites against some major proteins in Fusarium graminearum, such as carbonic anhydrases and cytochrome P450s. Activity of several of these compounds has been experimentally confirmed in fungal growth inhibition assays. Analysis of anti-fungal properties of plant metabolites can lead to the development of more resistant wheat varieties while showing novel application of cheminformatics approaches in the analysis of plant/pathogen interactions.

Development of a Terpenoid Alkaloid-like Compound Library Based on the Humulene Skeleton.

Many natural terpenoid alkaloid conjugates show biological activity because their structures contain both sp3 -rich terpenoid scaffolds and nitrogen-containing alkaloid scaffolds. However, their biosynthesis utilizes a limited set of compounds as sources of the terpenoid moiety. The production of terpenoid alkaloids containing various types of terpenoid moiety may provide useful, chemically diverse compound libraries for drug discovery. Herein, we report the construction of a library of terpenoid alkaloid-like compounds based on Lewis-acid-catalyzed transannulation of humulene diepoxide and subsequent sequential olefin metathesis. Cheminformatic analysis quantitatively showed that the synthesized terpenoid alkaloid-like compound library has a high level of three-dimensional-shape diversity. Extensive pharmacological screening of the library has led to the identification of promising compounds for the development of antihypolipidemic drugs. Therefore, the synthesis of terpenoid alkaloid-like compound libraries based on humulene is well suited to drug discovery. Synthesis of terpenoid alkaloid-like compounds based on several natural terpenoids is an effective strategy for producing chemically diverse libraries.

Cheminformatics analysis of the AR agonist and antagonist datasets in PubChem.

Background As one of the largest publicly accessible databases for hosting chemical structures and biological activities, PubChem has been processing bioassay submissions from the community since 2004. With the increase in volume for the deposited data in PubChem, the diversity and wealth of information content also grows. Recently, the Tox21 program, has deposited a series of pairwise data in PubChem regarding to different mechanism of actions (MOA), such as androgen receptor (AR) agonist and antagonist datasets, to study cell toxicity. To the best of our knowledge, little work has been reported from cheminformatics study for these especially pairwise datasets, which may provide insight into the mechanism of actions of the compounds and relationship between chemical structures and functions, as well as guidance for lead compound selection and optimization. Thus, to fill the gap, we performed a comprehensive cheminformatics analysis, including scaffold analysis, matched molecular pair (MMP) analysis as well as activity cliff analysis to investigate the structural characteristics and discontinued structure–activity relationship of the individual dataset (i.e., AR agonist dataset or AR antagonist dataset) and the combined dataset (i.e., the common compounds between the AR agonist and antagonist datasets).ResultsScaffolds associated only with potential agonists or antagonists were identified. MMP-based activity cliffs, as well as a small group of compounds with dual MOA reported were recognized and analyzed. Moreover, MOA-cliff, a novel concept, was proposed to indicate one pair of structurally similar molecules which exhibit opposite MOA.ConclusionsCheminformatics methods were successfully applied to the pairwise AR datasets and the identified molecular scaffold characteristics, MMPs as well as activity cliffs might provide useful information when designing new lead compounds for the androgen receptor.Electronic supplementary materialThe online version of this article (doi:10.1186/s13321-016-0150-6) contains supplementary material, which is available to authorized users.

Are the physicochemical properties of antibacterial compounds really different from other drugs?

BackgroundIt is now widely recognized that there is an urgent need for new antibacterial drugs, with novel mechanisms of action, to combat the rise of multi-drug resistant bacteria. However, few new compounds are reaching the market. Antibacterial drug discovery projects often succeed in identifying potent molecules in biochemical assays but have been beset by difficulties in obtaining antibacterial activity. A commonly held view, based on analysis of marketed antibacterial compounds, is that antibacterial drugs possess very different physicochemical properties to other drugs, and that this profile is required for antibacterial activity.ResultsWe have re-examined this issue by performing a cheminformatics analysis of the literature data available in the ChEMBL database. The physicochemical properties of compounds with a recorded activity in an antibacterial assay were calculated and compared to two other datasets extracted from ChEMBL, marketed antibacterials and drugs marketed for other therapeutic indications. The chemical class of the compounds and Gram-negative/Gram-positive profile were also investigated. This analysis shows that compounds with antibacterial activity have physicochemical property profiles very similar to other drug classes.ConclusionsThe observation that many current antibacterial drugs lie in regions of physicochemical property space far from conventional small molecule therapeutics is correct. However, the inference that a compound must lie in one of these “outlier” regions in order to possess antibacterial activity is not supported by our analysis.Graphical abstract.Electronic supplementary materialThe online version of this article (doi:10.1186/s13321-016-0143-5) contains supplementary material, which is available to authorized users.

Cheminformatics analysis of the Chinese National Compound Library of Peking University

Cheminformatics analysis of the Chinese National Compound Library of Peking University

Modulation of Carbon Nanotubes' Perturbation to the Metabolic Activity of CYP3A4 in the Liver

The liver plays an important role in metabolizing foreign materials, such as drugs. The high accumulation of carbon nanotubes and other hydrophobic nanoparticles in the liver has raised concerns that nanoparticles may interfere with liver metabolic function. We report here that carbon nanotubes enter hepatic cells after intravenous introduction and interact with CYP enzymes, including CYP3A4. Surface chemical modifications alter the carbon nanotubes' interactions with CYP450 enzymes in human liver microsomes. They enhance, inhibit, or have no effect on the enzymatic function of CYP3A4. Using a cheminformatics analysis, certain chemical structures are identified on the surface of the carbon nanotubes that induce an enzyme inhibitory effect or prevent disruption of CYP3A4 enzymes.

A diversity-oriented synthesis strategy enabling the combinatorial-type variation of macrocyclic peptidomimetic scaffolds.

Macrocyclic peptidomimetics are associated with a broad range of biological activities. However, despite such potentially valuable properties, the macrocyclic peptidomimetic structural class is generally considered as being poorly explored within drug discovery. This has been attributed to the lack of general methods for producing collections of macrocyclic peptidomimetics with high levels of structural, and thus shape, diversity. In particular, there is a lack of scaffold diversity in current macrocyclic peptidomimetic libraries; indeed, the efficient construction of diverse molecular scaffolds presents a formidable general challenge to the synthetic chemist. Herein we describe a new, advanced strategy for the diversity-oriented synthesis (DOS) of macrocyclic peptidomimetics that enables the combinatorial variation of molecular scaffolds (core macrocyclic ring architectures). The generality and robustness of this DOS strategy is demonstrated by the step-efficient synthesis of a structurally diverse library of over 200 macrocyclic peptidomimetic compounds, each based around a distinct molecular scaffold and isolated in milligram quantities, from readily available building-blocks. To the best of our knowledge this represents an unprecedented level of scaffold diversity in a synthetically derived library of macrocyclic peptidomimetics. Cheminformatic analysis indicated that the library compounds access regions of chemical space that are distinct from those addressed by top-selling brand-name drugs and macrocyclic natural products, illustrating the value of our DOS approach to sample regions of chemical space underexploited in current drug discovery efforts. An analysis of three-dimensional molecular shapes illustrated that the DOS library has a relatively high level of shape diversity.

MCR synthesis of a tetracyclic tetrazole scaffold

Scaffold diversity is key in the ongoing exercise of discovery of novel bioactive compounds using high throughput screening (HTS). Based on the Ugi tetrazole synthesis we have designed novel bi- and tri-cyclic scaffolds featuring interesting pharmacophore properties. The compounds of the scaffold (B) are synthesizable in large diversity and numbers in two steps using (hetero)phenylethylamines, HN3, oxo components and iscyanoacetaldehyde(dimethylacetale). The chemistry is amenable to parallel synthesis and is used to enhance and fill the screening decks of the European Lead factory (ELF). Here, we are reporting full experimental details, scope and limitations of the reaction, cheminformatic analysis and the 3D structures of selected compounds.

Probing the binding site characteristics of HSA: A combined molecular dynamics and cheminformatics investigation

Human serum albumin is a remarkable protein found in high concentrations in the body. It contains at least seven distinct fatty acid binding sites and two principle sites for drugs. Its primary function is to act as a fatty acid transport system, but it also shows the capacity to bind a diverse range of acidic, neutral and zwitterionic drug molecules. In this paper we investigate the ligand binding selectivity of HSA using cheminformatics analyses and molecular dynamics simulations. We compare and contrast the known ligand binding specificities as obtained from X-ray structural data using PCA, with additional direct analyses of the seven key binding pockets using analyses derived from molecular simulations. We assess both the fatted and defatted states of HSA using 100ns simulations of the APO and HOLO forms, as well as structures containing one, three and seven myristic acid molecules. We find that differences in fatty acid binding can have a dramatic effect on the flexibility of the protein and also the pocket characteristics. We discuss how the remarkable selectivity of the HSA pockets towards both endogenous fatty acids and exogenous drug molecules is not simply controlled by bulk property effects such as ionization state and lipophilicity.

Revealing chemical reactions of coal pyrolysis with GPU-enabled ReaxFF molecular dynamics and cheminformatics analysis

The complex chemistry of coal pyrolysis is difficult to be captured by experimental techniques or simulated with the quantum mechanics computational methods. The emerging of both the large-scale coal models and the promising capability of reactive molecular dynamics (ReaxFF MD) motivated us to develop a new methodology by combining graphics processing unit (GPU)-enabled high performance computing with cheminformatics analysis in order to explore the coal pyrolysis mechanisms using ReaxFF MD. The methodology is rooted in two new software tools, GMD-Reax, the first GPU-enabled ReaxFF MD codes that make it practical to simulate large-scale models (∼10,000 atoms) on desktop workstations, and visualisation and analysis of reactive molecular dynamics (VARMD), the first software dedicated to analysis of detailed chemical reactions from the trajectories of ReaxFF MD simulation. With this methodology, reasonable product profiles and gas generation sequences of pyrolysis for bituminous coal models ranging from ∼1000 to ∼10,000 atoms (including the system with 28,351 atoms, one of the largest systems used in ReaxFF MD) have been obtained. The complex and detailed chemical reactions directly revealed by VARMD can provide further information on radical behaviours and their connection with pyrolysates. The methodology presented here offers a new and promising approach to systematically understand the complex chemical reactions in thermolysis of very complicated molecular systems.

Short Communication: Cheminformatics Analysis to Identify Predictors of Antiviral Drug Penetration into the Female Genital Tract

The exposure of oral antiretroviral (ARV) drugs in the female genital tract (FGT) is variable and almost unpredictable. Identifying an efficient method to find compounds with high tissue penetration would streamline the development of regimens for both HIV preexposure prophylaxis and viral reservoir targeting. Here we describe the cheminformatics investigation of diverse drugs with known FGT penetration using cluster analysis and quantitative structure-activity relationships (QSAR) modeling. A literature search over the 1950-2012 period identified 58 compounds (including 21 ARVs and representing 13 drug classes) associated with their actual concentration data for cervical or vaginal tissue, or cervicovaginal fluid. Cluster analysis revealed significant trends in the penetrative ability for certain chemotypes. QSAR models to predict genital tract concentrations normalized to blood plasma concentrations were developed with two machine learning techniques utilizing drugs' molecular descriptors and pharmacokinetic parameters as inputs. The QSAR model with the highest predictive accuracy had R(2)test=0.47. High volume of distribution, high MRP1 substrate probability, and low MRP4 substrate probability were associated with FGT concentrations ≥1.5-fold plasma concentrations. However, due to the limited FGT data available, prediction performances of all models were low. Despite this limitation, we were able to support our findings by correctly predicting the penetration class of rilpivirine and dolutegravir. With more data to enrich the models, we believe these methods could potentially enhance the current approach of clinical testing.

Rapid Generation of Privileged Substructure-Based Compound Libraries with Structural Diversity and Drug-Likeness

A library of privileged-substructure-based, heterocyclic compounds was constructed by a sequence of Ugi four-component reactions incorporating the indole motif and microwave-assisted cyclizations in branched pathways. Cheminformatic analysis confirmed that the library exhibited a high degree of structural diversity and good drug-likeness.

Diversity-oriented synthesis as a tool for identifying new modulators of mitosis.

The synthesis of diverse three-dimensional libraries has become of paramount importance for obtaining better leads for drug discovery. Such libraries are predicted to fare better than traditional compound collections in phenotypic screens and against difficult targets. Herein we report the diversity-oriented synthesis of a compound library using rhodium carbenoid chemistry to access structurally diverse three-dimensional molecules and show that they access biologically relevant areas of chemical space using cheminformatic analysis. High-content screening of this library for antimitotic activity followed by chemical modification identified 'Dosabulin', which causes mitotic arrest and cancer cell death by apoptosis. Its mechanism of action is determined to be microtubule depolymerization, and the compound is shown to not significantly affect vinblastine binding to tubulin; however, experiments suggest binding to a site vicinal or allosteric to Colchicine. This work validates the combination of diversity-oriented synthesis and phenotypic screening as a strategy for the discovery of biologically relevant chemical entities.

Chemical signatures and new drug targets for gametocytocidal drug development

Control of parasite transmission is critical for the eradication of malaria. However, most antimalarial drugs are not active against P. falciparum gametocytes, responsible for the spread of malaria. Consequently, patients can remain infectious for weeks after the clearance of asexual parasites and clinical symptoms. Here we report the identification of 27 potent gametocytocidal compounds (IC50 < 1 μM) from screening 5,215 known drugs and compounds. All these compounds were active against three strains of gametocytes with different drug sensitivities and geographical origins, 3D7, HB3 and Dd2. Cheminformatic analysis revealed chemical signatures for P. falciparum sexual and asexual stages indicative of druggability and suggesting potential targets. Torin 2, a top lead compound (IC50 = 8 nM against gametocytes in vitro), completely blocked oocyst formation in a mouse model of transmission. These results provide critical new leads and potential targets to expand the repertoire of malaria transmission-blocking reagents.

Short Communication: Cheminformatics Analysis to Identify Predictors of Antiviral Drug Penetration into the Female Genital Tract

Short Communication: Cheminformatics Analysis to Identify Predictors of Antiviral Drug Penetration into the Female Genital Tract

Pyrolysis of Liulin Coal Simulated by GPU-Based ReaxFF MD with Cheminformatics Analysis

In this study, the first GPU-enabled ReaxFF MD program with significantly improved performance, surpassing CPU implementations, was employed to explore the initial chemical mechanisms and product distributions in pyrolysis of Liulin coal, a bituminous coal from Shanxi, PRC. The largest coal model ever used in simulation via ReaxFF MD, the Liulin coal molecular model consisting of 28 351 atoms was constructed based on a combination of experiments and classical coal models. The ReaxFF MD simulations at temperatures of 1000–2600 K were performed for 250 ps to investigate the temperature effects on the product profile and the initial chemical reactions of the Liulin coal model pyrolysis. The generation rates of C14–C40 compounds and gas tend to equilibrate within 150–250 ps, indicating that the simulation should allow most of the thermal decomposition reactions complete and the simulated product profiles are reasonable for understanding the chemical reactions of the Liulin coal pyrolysis. The product (gas, tar, and char) evolution tendencies with time and temperature observed in the simulations are fairly in agreement with the experimental tendency reported in the literature. In particular, the evolution trends of three representative products (naphthalene, methyl-naphthalene and dimethyl-naphthalene) with temperature are very consistent with Py-GC/MS experiments. The detailed chemical reactions of the pyrolysis simulation have been generated using VARMD (Visualization and Analysis of Reactive Molecular Dynamics), which was newly created to examine the complexity of the chemical reaction network in ReaxFF MD simulation. The generation and consumption of HO· and H3C· radicals with time and temperature are reasonable and consistent both with the evolution of H2O and CH4, and with the detailed chemical reactions obtained as well. The amount of six-membered ring structures was observed to decrease with time and temperature, because of their conversion into 5-membered rings or 7–9-membered rings or even-larger-membered ring structures that will further open and decompose into small fragments. This work demonstrates a new methodology for investigating coal pyrolysis mechanism by combining GPU-enabled high-performance computing with cheminformatics analysis in ReaxFF MD.

Visualizing chemical structure-subcellular localization relationships using fluorescent small molecules as probes of cellular transport

BackgroundTo study the chemical determinants of small molecule transport inside cells, it is crucial to visualize relationships between the chemical structure of small molecules and their associated subcellular distribution patterns. For this purpose, we experimented with cells incubated with a synthetic combinatorial library of fluorescent, membrane-permeant small molecule chemical agents. With an automated high content screening instrument, the intracellular distribution patterns of these chemical agents were microscopically captured in image data sets, and analyzed off-line with machine vision and cheminformatics algorithms. Nevertheless, it remained challenging to interpret correlations linking the structure and properties of chemical agents to their subcellular localization patterns in large numbers of cells, captured across large number of images.ResultsTo address this challenge, we constructed a Multidimensional Online Virtual Image Display (MOVID) visualization platform using off-the-shelf hardware and software components. For analysis, the image data set acquired from cells incubated with a combinatorial library of fluorescent molecular probes was sorted based on quantitative relationships between the chemical structures, physicochemical properties or predicted subcellular distribution patterns. MOVID enabled visual inspection of the sorted, multidimensional image arrays: Using a multipanel desktop liquid crystal display (LCD) and an avatar as a graphical user interface, the resolution of the images was automatically adjusted to the avatar’s distance, allowing the viewer to rapidly navigate through high resolution image arrays, zooming in and out of the images to inspect and annotate individual cells exhibiting interesting staining patterns. In this manner, MOVID facilitated visualization and interpretation of quantitative structure-localization relationship studies. MOVID also facilitated direct, intuitive exploration of the relationship between the chemical structures of the probes and their microscopic, subcellular staining patterns.ConclusionMOVID can provide a practical, graphical user interface and computer-assisted image data visualization platform to facilitate bioimage data mining and cheminformatics analysis of high content, phenotypic screening experiments.

High-throughput respirometric assay identifies predictive toxicophore of mitochondrial injury

Many environmental chemicals and drugs negatively affect human health through deleterious effects on mitochondrial function. Currently there is no chemical library of mitochondrial toxicants, and no reliable methods for predicting mitochondrial toxicity. We hypothesized that discrete toxicophores defined by distinct chemical entities can identify previously unidentified mitochondrial toxicants. We used a respirometric assay to screen 1760 compounds (5μM) from the LOPAC and ChemBridge DIVERSet libraries. Thirty-one of the assayed compounds decreased uncoupled respiration, a stress test for mitochondrial dysfunction, prior to a decrease in cell viability and reduced the oxygen consumption rate in isolated mitochondria. The mitochondrial toxicants were grouped by chemical similarity and two clusters containing four compounds each were identified. Cheminformatic analysis of one of the clusters identified previously uncharacterized mitochondrial toxicants from the ChemBridge DIVERSet. This approach will enable the identification of mitochondrial toxicants and advance the prediction of mitochondrial toxicity for both drug discovery and risk assessment.

A novel quinoline derivative that inhibits mycobacterial FtsZ

High throughput phenotypic screening of large commercially available libraries through two NIH programs has produced thousands of potentially interesting hits for further development as antitubercular agents. Unfortunately, these screens do not supply target information, and further follow up target identification is required to allow optimal rational design and development of highly active and selective clinical candidates. Cheminformatic analysis of the quinoline and quinazoline hits from these HTS screens suggested a hypothesis that certain compounds in these two classes may target the mycobacterial tubulin homolog, FtsZ. In this brief communication, activity of a lead quinoline against the target FtsZ from Mycobacterium tuberculosis (Mtb) is confirmed as well as good in vitro whole cell antibacterial activity against Mtb H37Rv. The identification of a putative target of this highly tractable pharmacophore should help medicinal chemists interested in targeting FtsZ and cell division develop a rational design program to optimize this activity toward a novel drug candidate.