Inhibition and reversal of myogenic differentiation by purine-based microtubule assembly inhibitors

Using a muscle cell differentiation screen, we have identified myoseverin from a 2,6,9-trisubsituted purine library as a purine-based microtubule binding molecule [1]. Structure-activity relation studies of myoseverin identify positions N2 and N6 to be critical for inhibiting muscle differentiation. Inhibition of microtubule polymerization induced the reversion of terminally differentiated myotubes to mononucleated cells that were responsive to both growth and differentiation conditions, without any observable cytotoxicity. Comparison of myoseverin derivatives to taxol, vinblastine, nocodazole, and colchicine identify myoseverin's effect as being selectively reversible in addition to lacking the cytotoxic effects of these non-purine-based microtubule-disrupting molecules. Myoseverin, as a purine-based microtubule inhibitor, reverted terminal muscle-differentiated cells to a state that was responsive to environmental cues. These results suggest that myoseverin may have applications in muscle regeneration and stem cell differentiation.     

Synthesis of carba-analogues of myoseverin by regioselective cross-coupling reactions of 2,6-dichloro-9-isopropylpurine

A series of 9-isopropylpurine derivatives bearing 4-methoxyphenyl, 4-methoxybenzyl, (4-methoxyphenyl)ethynyl and 2-(4-methoxyphenyl)ethyl groups in positions 2 and 6 were prepared as carba-analogues of antimitotic myoseverin. Cross-coupling reactions of 2,6-dichloro-9-isopropylpurine (1) with one equivalent of (4-methoxyphenyl)boronic acid or (4-methoxybenzyl)zinc chloride gave regioselectively the 6-substituted 2-chloropurines which were used for another cross-coupling reaction with a second equivalent of the organometallic reagent. The Sonogashira reaction of 1 with 4-(methoxyphenyl)ethyne gave 2,6-bis[(4-methoxyphenyl)ethynyl]-9-isopropylpurine that was hydrogenated to 2,6-bis[2-(4-methoxyphenyl)ethyl]-9-isopropylpurine. Regioselectivity of the couplings was proved by means of ¹H-¹⁵N HMBC experiments. 2,6-Bis[(4-methoxyphenyl)ethynyl]-9-isopropylpurine showed considerable cytostatic activity, while the other compounds were inactive.     

Compound prioritization methods increase rates of chemical probe discovery in model organisms

Preselection of compounds that are more likely to induce a phenotype can increase the efficiency and reduce the costs for model organism screening. To identify such molecules, we screened ~81,000 compounds in Saccharomyces cerevisiae and identified ~7500 that inhibit cell growth. Screening these growth-inhibitory molecules across a diverse panel of model organisms resulted in an increased phenotypic hit-rate. These data were used to build a model to predict compounds that inhibit yeast growth. Empirical and in silico application of the model enriched the discovery of bioactive compounds in diverse model organisms. To demonstrate the potential of these molecules as lead chemical probes, we used chemogenomic profiling in yeast and identified specific inhibitors of lanosterol synthase and of stearoyl-CoA 9-desaturase. As community resources, the ~7500 growth-inhibitory molecules have been made commercially available and the computational model and filter used are provided.     

Application of NMR SHAPES screening to an RNA target

Several NMR screening techniques have been developed in recent years to aid in the identification of lead drug compounds. These NMR methods have traditionally been used for protein targets, and here we examine their applicability for an RNA target. We used the SHAPES compound library to test three different NMR screening methodologies: the saturation transfer difference (STD), the 2D trNOESY, and the WaterLOGSY experiments. We found that the WaterLOGSY experiment was the most sensitive method for our RNA target, the P4P6 domain of the Tetrahymena thermophila Group I intron. Using the WaterLOGSY experiment, we found that 23 of the 112 SHAPES compounds interact with P4P6. To identify which of these 23 hits bind through nonspecific interactions, we counterscreened with a linear duplex RNA control and identified one of the SHAPES compounds as interacting with P4P6 specifically. We thus demonstrated that the WaterLOGSY experiment in combination with the SHAPES compound library can be used to efficiently find RNA binding lead compounds.     

The complex role of the triphenylmethyl motif in anticancer compounds

Compounds incorporating the triphenylmethyl motif constitute an emerging family of potent anticancer agents. Although several small molecules containing this pharmacophore have now been identified, the mechanism of cell death induction for some of these compounds is unknown. In an effort to define their mechanism of action, and to distinguish subtypes within the group of compounds containing the triphenylmethyl moiety, we have created novel triphenylmethyl-containing small molecules and have evaluated them in a battery of biological assays. Here we show that several phosphonate and phosphonochloridates possessing the triphenylmethyl motif potently induce death of multiple cancer cell lines in culture. Further assays evaluating the ability to cause cell cycle arrest, inhibit tubulin polymerization, dissociate mitochondrial-bound hexokinase in cancer cells, and inhibit calcium-dependent potassium ion channels indicate that triphenylmethyl-containing compounds can be placed into at least four distinct categories, each with a different mechanism of action.     

High throughput screening technology and the small molecules modulating aging related signals

Aging and its related diseases are severe issues in modern society. Many efforts have been made to understand the mechanisms of aging and to find the ways to prevent age-related diseases. Identifying the compounds targeting aging-related signals is a challenging work because there are so many proteins and signals involved. Recently, alone with the progresses in high throughput screening (HTS) technology, increasing numbers of small molecules targeting aging-related pathologic processes have been identified. In this review, we introduce the basic workflow, classification and assay strategies of HTS technology, and sort out known small molecules identified via HTS technology by their roles in aging related diseases, such as neural degenerative diseases, diabetes and tumors. Given the fact that application of HTS on aging research is still at an early stage, we also summarize the cellular mechanisms about aging process, paralleled with the compounds which can modulate the functions of proteins important for aging signals. Finally, we briefly discuss some advanced HTS technologies for their potent applications on the discovery of anti-aging compounds. The main purpose of this review is to provide updated and useful information to those who are interested in pharmacology and HTS technology, but not familiar with aging biology, or vice versa.     

Characterization of paint samples used in drinking water reservoirs: identification of endocrine disruptor compounds

Several migration tests are performed from various epoxy paint samples that, according to the regulation, can be used in food reservoirs such as drinking water reservoirs. The level of the organic compounds capable of producing migrations to water with special attention to endocrine disruptor compounds (EDCs) are identified and estimated by closed loop-stripping analysis (CLSA) and liquid-liquid extraction (LLE) methods coupled with gas chromatography (GC)-mass spectrometry (MS). Bisphenol A, a strong endocrine disruptor, is found in all migration experiments. Its concentration level reaches between 0.02 and 0.03 mg/cm2. The higher concentration corresponds with benzylic alcohol, which is used as a solvent and curing agent in epoxy paint. Other EDCs identified in the migration tests are phthalates, 4-nonylphenol, and t-butylphenol. The main non-EDCs identified are solvents, antioxidants, and rubber-like compounds. No great differences are found in the use of metallic plates or concrete slabs for migration experiments; only additional compounds related with the pretreatment of the concrete wall have been identified, too. In the study of a drinking water sample the same organic compounds identified in the migration test is not seen. This is probably because of the dynamic situation in a drinking water reservoir. Finally, a GC profile of a direct epoxy paint analysis is shown. The main peak identified is bisphenol A diglycidyl ether, monomer, and an active principle of the polymerization of epoxy resins based on bisphenol A. In addition, we report the recoveries of a selected group of EDCs using CLSA and LLE methods coupled with GC-MS.     

Characterization of Kimchi Flavor with Preconcentration by Head Space Solid-Phase Microextraction and Stir Bar Sorptive Extraction and Analysis by Gas Chromatography-Mass Spectrometry

Kimchi is a traditional fermented vegetable, known for its complex flavor. Herein, we compared compounds related to the kimchi flavor, identified by gas chromatography-mass spectrometry (GC-MS) with the developed solid phase microextraction (SPME) and stir bar sorptive extraction (SBSE) techniques. Although headspace-solid phase microextraction (HS-SPME) detected more volatile compounds than nondestructive-headspace-solid-phase microextraction (ND-HS-SPME), those identified by ND-HS-SPME were considered closely related to the flavor of the intact kimchi. Furthermore, direct immersion-stir bar sorptive extraction (DI-SBSE) detected more volatile and nonvolatile compounds than headspace-stir bar sorptive extraction (HS-SBSE), while more sulfur compounds were identified by HS-SBSE. Therefore, we recommend the use of the HS-SPME method using a divinylbenzene/carboxen/polydimethylsiloxane fiber for identifying compounds related to the kimchi flavor. In addition, principal component analysis showed ND-HS-SPME and HS-SBSE to be closely clustered. Overall, we estimated that the samples obtained via the nondestructive sample preparation emits fewer polar volatile flavor compounds than those obtained using the destructive sample preparation. Considering the findings presented herein, we believe that this study contributes to optimizing the flavor analysis of kimchi and other fermented vegetables.     

Discovery of a potent small molecule IL-2 inhibitor through fragment assembly

Using a site-directed fragment discovery method called tethering, we have identified a 60 nM small molecule antagonist of a cytokine/receptor interaction (IL-2/IL2Ralpha) with cell-based activity. Starting with a low micromolar hit, we employed a combination of tethering, structural biology, and computational analysis to design a focused set of 20 compounds. Eight of these compounds were at least 5-fold more active than the original hit. One of these compounds showed a 50-fold enhancement and represents the highest affinity inhibitor reported against this protein-protein target class. This method of coupling selected fragments with a low micromolar hit shows great potential for generating high-affinity lead compounds.     

Towards supramolecular polymers

The natural phenomenon of self-assembly has been used to make complex unnatural products. These new compounds have taken the form of catenanes and rotaxanes. We have identified several polymeric architectures containing the catenane and rotaxane motifs, and then described how the model structures, which we have identified and actually realized as chemical compounds, can be employed to assess the feasibility of introducing mechanical linkages into novel polymers by means of self-assembly processes.     

4-去甲斑蝥酰亚胺基丁酰苯硫脲的合成及抗惊厥活性

合成了11种γ-氨基丁酸异硫氰酯偶联去甲斑蝥素与取代苯胺目标化合物,其结构经IR、1HNMR和HR-MS测试技术确证。抗惊厥活性初步测定表明,化合物Ⅱ2、Ⅱ3和Ⅱ8显示了较强的抗惊厥活性。     

Sub-structure-based screening and molecular docking studies of potential enteroviruses inhibitors

Rhinoviruses (RV), especially Human rhinovirus (HRVs) have been accepted as the most common cause for upper respiratory tract infections (URTIs). Pleconaril, a broad spectrum anti-rhinoviral compound, has been used as a drug of choice for URTIs for over a decade. Unfortunately, for various complications associated with this drug, it was rejected, and a replacement is highly desirable. In silico screening and prediction methods such as sub-structure search and molecular docking have been widely used to identify alternative compounds. In our study, we have utilised sub-structure search to narrow down our quest in finding relevant chemical compounds. Molecular docking studies were then used to study their binding interaction at the molecular level. Interestingly, we have identified 3 residues that is worth further investigation in upcoming molecular dynamics simulation systems of their contribution in stable interaction.     

Data mining the NCI cancer cell line compound GI(50) values: identifying quinone subtypes effective against melanoma and leukemia cell classes

Using data mining techniques, we have studied a subset (1400) of compounds from the large public National Cancer Institute (NCI) compounds data repository. We first carried out a functional class identity assignment for the 60 NCI cancer testing cell lines via hierarchical clustering of gene expression data. Comprised of nine clinical tissue types, the 60 cell lines were placed into six classes-melanoma, leukemia, renal, lung, and colorectal, and the sixth class was comprised of mixed tissue cell lines not found in any of the other five classes. We then carried out supervised machine learning, using the GI(50) values tested on a panel of 60 NCI cancer cell lines. For separate 3-class and 2-class problem clustering, we successfully carried out clear cell line class separation at high stringency, p < 0.01 (Bonferroni corrected t-statistic), using feature reduction clustering algorithms embedded in RadViz, an integrated high dimensional analytic and visualization tool. We started with the 1400 compound GI(50) values as input and selected only those compounds, or features, significant in carrying out the classification. With this approach, we identified two small sets of compounds that were most effective in carrying out complete class separation of the melanoma, non-melanoma classes and leukemia, non-leukemia classes. To validate these results, we showed that these two compound sets' GI(50) values were highly accurate classifiers using five standard analytical algorithms. One compound set was most effective against the melanoma class cell lines (14 compounds), and the other set was most effective against the leukemia class cell lines (30 compounds). The two compound classes were both significantly enriched in two different types of substituted p-quinones. The melanoma cell line class of 14 compounds was comprised of 11 compounds that were internal substituted p-quinones, and the leukemia cell line class of 30 compounds was comprised of 6 compounds that were external substituted p-quinones. Attempts to subclassify melanoma or leukemia cell lines based upon their clinical cancer subtype met with limited success. For example, using GI(50) values for the 30 compounds we identified as effective against all leukemia cell lines, we could subclassify acute lymphoblastic leukemia (ALL) origin cell lines from non-ALL leukemia origin cell lines without significant overlap from non-leukemia cell lines. Based upon clustering using GI(50) values for the 60 cancer cell lines laid out by the RadViz algorithm, these two compound subsets did not overlap with clusters containing any of the NCI's 92 compounds of known mechanism of action, a few of which are quinones. Given their structural patterns, the two p-quinone subtypes we identified would clearly be expected to possess different redox potentials/substrate specificities for enzymatic reduction in vivo. These two p-quinone subtypes represent valuable information that may be used in the elucidation of pharmacophores for the design of compounds to treat these two cancer tissue types in the clinic.     

Structural bioinformatics-based identification of putative plant based lead compounds for Alzheimer Disease Therapy

Plant based lead compounds have been historically incredible as a source of therapeutic agents for various complex disorders including Alzheimer’s disease (AD). AD is one of the leading neurodegenerative disorder in which the underlying risk factors remain largely unclear and presently, there is no disease modifying treatment available. Despite its potential, to date only few compounds have entered for clinical trials. Herein, we described the identification of plant based lead compounds for treatment of AD through an integrative approach of pharmacokinetics and structure bioinformatics approach. In particular we performed screening of lead compounds from 3 traditional medicinal plants namely Withania somnifera, Bacopa monnieri and Morus alba, which are known to have potential for treatment of neurodegenerative disease. We retrieved a total of 210 plant based compounds of which 21 compounds were screened based on their pharmacokinetic properties. Further, Docking study against 7 known AD associated targets were carried out to identify the binding sites and direct interacting residues. In addition we investigate the stable and reliable binding mechanism of top such plant compounds against 3 targets through molecular docking followed by Molecular Dynamic(MD) simulation. The results obtained in the study revealed that 3 drug compounds namely Morusin (MRSN), Withanone (WTHN) and 27-Hydroxywithanolide B (HWTHN) were identified as putative lead compounds against mono amine oxidase (MAOB), Beta-secretase 1(BACE1) and phosphodiesterase 4D.     

Development of a chemical structure comparison method for integrated analysis of chemical and genomic information in the metabolic pathways

Cellular functions result from intricate networks of molecular interactions, which involve not only proteins and nucleic acids but also small chemical compounds. Here we present an efficient algorithm for comparing two chemical structures of compounds, where the chemical structure is treated as a graph consisting of atoms as nodes and covalent bonds as edges. On the basis of the concept of functional groups, 68 atom types (node types) are defined for carbon, nitrogen, oxygen, and other atomic species with different environments, which has enabled detection of biochemically meaningful features. Maximal common subgraphs of two graphs can be found by searching for maximal cliques in the association graph, and we have introduced heuristics to accelerate the clique finding and to detect optimal local matches (simply connected common subgraphs). Our procedure was applied to the comparison and clustering of 9383 compounds, mostly metabolic compounds, in the KEGG/LIGAND database. The largest clusters of similar compounds were related to carbohydrates, and the clusters corresponded well to the categorization of pathways as represented by the KEGG pathway map numbers. When each pathway map was examined in more detail, finer clusters could be identified corresponding to subpathways or pathway modules containing continuous sets of reaction steps. Furthermore, it was found that the pathway modules identified by similar compound structures sometimes overlap with the pathway modules identified by genomic contexts, namely, by operon structures of enzyme genes.     

Polypharmacology directed compound data mining: identification of promiscuous chemotypes with different activity profiles and comparison to approved drugs

Increasing evidence that many pharmaceutically relevant compounds elicit their effects through binding to multiple targets, so-called polypharmacology, is beginning to change conventional drug discovery and design strategies. In light of this paradigm shift, we have mined publicly available compound and bioactivity data for promiscuous chemotypes. For this purpose, a hierarchy of active compounds, atomic property based scaffolds, and unique molecular topologies were generated, and activity annotations were analyzed using this framework. Starting from ～35?000 compounds active against human targets with at least 1 μM potency, 33 chemotypes with distinct topology were identified that represented molecules active against at least 3 different target families. Network representations were utilized to study scaffold-target family relationships and activity profiles of scaffolds corresponding to promiscuous chemotypes. A subset of promiscuous chemotypes displayed a significant enrichment in drugs over bioactive compounds. A total of 190 drugs were identified that had on average only 2 known target annotations but belonged to the 7 most promiscuous chemotypes that were active against 8-15 target families. These drugs should be attractive candidates for polypharmacological profiling.     

Cell-active dual specificity phosphatase inhibitors identified by high-content screening

Phosphorylation of extracellular signal-regulated kinase (Erk) is tightly controlled by dual specificity phosphatases (DSPases), but few inhibitors of Erk dephosphorylation have been identified. Using a high-content, fluorescence-based cellular assay and the National Cancer Institute's 1990 agent Diversity Set, we identified ten compounds (0.5%) that significantly increased phospho-Erk cytonuclear differences in intact cells. Three of the ten positive compounds inhibited the mitogen-activated protein kinase phosphatase-3 (MKP-3/PYST-1) in vitro without affecting VHR or PTP1B phosphatases. The most potent inhibitor of MKP-3 had an IC(50) of <10 microM and inhibited MKP-3 in a novel, fluorescence-based multiparameter chemical complementation assay. These results suggest that the phospho-Erk nuclear accumulation assay may be a useful tool to discover DSPase inhibitors with biological activity.     

Synthesis and Structure–Activity Relationship of Thioacetamide-Triazoles against Escherichia coli

Infections due to Gram-negative bacteria are increasingly dangerous due to the spread of multi-drug resistant strains, emphasizing the urgent need for new antibiotics with alternative modes of action. We have previously identified a novel class of antibacterial agents, thioacetamide-triazoles, using an antifolate targeted screen and determined their mode of action which is dependent on activation by cysteine synthase A. Herein, we report a detailed examination of the anti-E. coli structure–activity relationship of the thioacetamide-triazoles. Analogs of the initial hit compounds were synthesized to study the contribution of the aryl, thioacetamide, and triazole sections. A clear structure–activity relationship was observed generating compounds with excellent inhibition values. Substitutions to the aryl ring were generally best tolerated, including the introduction of thiazole and pyridine heteroaryl systems. Substitutions to the central thioacetamide linker section were more nuanced; the introduction of a methyl branch to the thioacetamide linker substantially decreased antibacterial activity, but the isomeric propionamide and N-benzamide systems retained activity. Changes to the triazole portion of the molecule dramatically decreased the antibacterial activity, further indicating that 1,2,3-triazole is critical for potency. From these studies, we have identified new lead compounds with desirable in-vitro ADME properties and in-vivo pharmacokinetic properties.     

High-throughput kinase profiling: a more efficient approach toward the discovery of new kinase inhibitors

Selective protein kinase inhibitors have only been developed against a small number of kinase targets. Here we demonstrate that "high-throughput kinase profiling" is an efficient method for the discovery of lead compounds for established as well as unexplored kinase targets. We screened a library of 118 compounds constituting two distinct scaffolds (furan-thiazolidinediones and pyrimido-diazepines) against a panel of 353 kinases. A distinct kinase selectivity profile was observed for each scaffold. Selective inhibitors were identified with submicromolar cellular activity against PIM1, ERK5, ACK1, MPS1, PLK1-3, and Aurora A,B kinases. In addition, we identified potent inhibitors for so far unexplored kinases such as DRAK1, HIPK2, and DCAMKL1 that await further evaluation. This inhibitor-centric approach permits comprehensive assessment of a scaffold of interest and represents an efficient and general strategy for identifying new selective kinase inhibitors.