Image_3_In Vitro and In Vivo Antitumor Activity of Cucurbitacin C, a Novel Natural Product From Cucumber.tif

Cucurbitacin C (CuC), a novel analogue of triterpenoids cucurbitacins, confers a bitter taste in cucumber. Genes and signaling pathways responsive for biosynthesis of CuC have been identified in the recent years. In the present study, we explored the anti-cancer effects of CuC against human cancers in vitro and in vivo. CuC inhibited proliferation and clonogenic potential of multiple cancer cells in a dose-dependent manner. Low-dose CuC treatment induced cell cycle arrest at G1 or G2/M stage in different cancer lines, whereas high-dose treatment of CuC caused apoptosis in cancer cells. PI3K-Akt signaling pathway was found to be one of the major pathways involved in CuC-induced cell growth arrest and apoptosis by RNA-Seq and Western blotting. Mechanistic dissection further confirmed that CuC effectively inhibited the Akt signaling by inhibition of Akt phosphorylation at Ser473. In vivo CuC treatment (0.1 mg/kg body weight) effectively inhibited growth of cancer cell-derived xenograft tumors in athymic nude mice and caused significant apoptosis. Our findings for the first time demonstrated the potential therapeutic significance of CuC against human cancers.</p

Mechanism of the All‑α to All‑β Conformational Transition of RfaH-CTD: Molecular Dynamics Simulation and Markov State Model

The C-terminal domain of the bacterial transcription antiterminator RfaH undergoes a dramatic all-α-helix to all-β-barrel transition when released from its N-terminal domain. These two distinct folding patterns correspond to different functions: the all-α state acts as an essential regulator of transcription to ensure RNA polymerase binding, whereas the all-β state operates as an activator of translation by interacting with the ribosomal protein S10 and recruits ribosomal mRNA. Accordingly, this drastic conformational change enables RfaH to physically couple the transcription and translation processes in gene expression. To understand the mechanism behind this extraordinary functionally relevant structural transition, we constructed Markov state models using an adaptive seeding method. The constructed models highlight several parallel folding pathways with heterogeneous molecular mechanisms, which reveal the folding kinetics and atomic details of the conformational transition

Knowledge-Based Scoring Functions in Drug Design: 3. A Two-Dimensional Knowledge-Based Hydrogen-Bonding Potential for the Prediction of Protein–Ligand Interactions

Hydrogen bonding is a key contributor to the molecular recognition between ligands and their host molecules in biological systems. Here we develop a novel orientation-dependent hydrogen bonding potential based on the geometric characteristics of hydrogen bonds observed in 44,585 protein–ligand complexes. We find a close correspondence between the empirical knowledge and the energy landscape inferred from the distribution of HBs. A scoring function based on the resultant hydrogen-bonding potentials discriminates native protein–ligand structures from incorrectly docked decoys with remarkable predictive power

Combinatorial Pharmacophore Modeling of Organic Cation Transporter 2 (OCT2) Inhibitors: Insights into Multiple Inhibitory Mechanisms

Organic cation transporter 2 (OCT2) is responsible for the entry step of many drugs in renal elimination, of which the changing activity may cause unwanted drug–drug interactions (DDIs). To develop drugs with favorable safety profile and provide instruction for rational clinical drug administration, it is of great interest to investigate the multiple mechanisms of OCT2 inhibition. In this study, we designed a combinatorial scheme to screen the optimum combination of pharmacophores from a pool of hypotheses established based on 162 OCT2 inhibitors. Among them, one single pharmacophore hypothesis represents a potential binding mode that may account for one unique inhibitory mechanism, and the obtained pharmacophore combination describes the multimechanisms of OCT2 inhibition. The final model consists of four individual pharmacophores, i.e., DHPR18, APR2, PRR5 and HHR4. Given a query ligand, it is considered as an inhibitor if it matches at least one of the hypotheses, or a noninhibitor if it fails to match any of four hypotheses. Our combinatorial pharmacophore model performs reasonably well to discriminate inhibitors and noninhibitors, yielding an overall accuracy around 0.70 for a test set containing 81 OCT2 inhibitors and 218 noninhibitors. Intriguingly, we found that the number of matched hypotheses was positively correlated with inhibition rate, which coincides with the pharmacophore modeling result of P-gp substrate binding. Further analysis suggested that the hypothesis PRR5 was responsible for competitive inhibition of OCT2, and other hypotheses were important for interaction between the inhibitor and OCT2. In light of the results, a hypothetical model for inhibiting transporting mediated by OCT2 was proposed

Image_2_In Vitro and In Vivo Antitumor Activity of Cucurbitacin C, a Novel Natural Product From Cucumber.tif

Cucurbitacin C (CuC), a novel analogue of triterpenoids cucurbitacins, confers a bitter taste in cucumber. Genes and signaling pathways responsive for biosynthesis of CuC have been identified in the recent years. In the present study, we explored the anti-cancer effects of CuC against human cancers in vitro and in vivo. CuC inhibited proliferation and clonogenic potential of multiple cancer cells in a dose-dependent manner. Low-dose CuC treatment induced cell cycle arrest at G1 or G2/M stage in different cancer lines, whereas high-dose treatment of CuC caused apoptosis in cancer cells. PI3K-Akt signaling pathway was found to be one of the major pathways involved in CuC-induced cell growth arrest and apoptosis by RNA-Seq and Western blotting. Mechanistic dissection further confirmed that CuC effectively inhibited the Akt signaling by inhibition of Akt phosphorylation at Ser473. In vivo CuC treatment (0.1 mg/kg body weight) effectively inhibited growth of cancer cell-derived xenograft tumors in athymic nude mice and caused significant apoptosis. Our findings for the first time demonstrated the potential therapeutic significance of CuC against human cancers.</p

Image_1_In Vitro and In Vivo Antitumor Activity of Cucurbitacin C, a Novel Natural Product From Cucumber.tif

Cucurbitacin C (CuC), a novel analogue of triterpenoids cucurbitacins, confers a bitter taste in cucumber. Genes and signaling pathways responsive for biosynthesis of CuC have been identified in the recent years. In the present study, we explored the anti-cancer effects of CuC against human cancers in vitro and in vivo. CuC inhibited proliferation and clonogenic potential of multiple cancer cells in a dose-dependent manner. Low-dose CuC treatment induced cell cycle arrest at G1 or G2/M stage in different cancer lines, whereas high-dose treatment of CuC caused apoptosis in cancer cells. PI3K-Akt signaling pathway was found to be one of the major pathways involved in CuC-induced cell growth arrest and apoptosis by RNA-Seq and Western blotting. Mechanistic dissection further confirmed that CuC effectively inhibited the Akt signaling by inhibition of Akt phosphorylation at Ser473. In vivo CuC treatment (0.1 mg/kg body weight) effectively inhibited growth of cancer cell-derived xenograft tumors in athymic nude mice and caused significant apoptosis. Our findings for the first time demonstrated the potential therapeutic significance of CuC against human cancers.</p

Computational Screening for Active Compounds Targeting Protein Sequences: Methodology and Experimental Validation

The three-dimensional (3D) structures of most protein targets have not been determined so far, with many of them not even having a known ligand, a truly general method to predict ligand–protein interactions in the absence of three-dimensional information would be of great potential value in drug discovery. Using the support vector machine (SVM) approach, we constructed a model for predicting ligand–protein interaction based only on the primary sequence of proteins and the structural features of small molecules. The model, trained by using 15 000 ligand–protein interactions between 626 proteins and over 10 000 active compounds, was successfully used in discovering nine novel active compounds for four pharmacologically important targets (i.e., GPR40, SIRT1, p38, and GSK-3β). To our knowledge, this is the first example of a successful sequence-based virtual screening campaign, demonstrating that our approach has the potential to discover, with a single model, active ligands for any protein

Conformational Transition and Energy Landscape of ErbB4 Activated by Neuregulin1β: One Microsecond Molecular Dynamics Simulations

ErbB4, a receptor tyrosine kinase of the ErbB family, plays crucial roles in cell growth and differentiation, especially in the development of the heart and nervous system. Ligand binding to its extracellular region could modulate the activation process. To understand the mechanism of ErbB4 activation induced by ligand binding, we performed one microsecond molecular dynamics (MD) simulations on the ErbB4 extracellular region (ECR) with and without its endogenous ligand neuregulin1β (NRG1β). The conformational transition of the ECR-ErbB4/NRG1β complex from a tethered inactive conformation to an extended active-like form has been observed, while such large and function-related conformational change has not been seen in the simulation on the ECR-ErbB4, suggesting that ligand binding is indeed the active inducing force for the conformational transition and further dimerization. On the basis of MD simulations and principal component analysis, we constructed a rough energy landscape for the conformational transition of ECR-ErbB4/NRG1β complex, suggesting that the conformational change from the inactive state to active-like state involves a stable conformation. The energy barrier for the tether opening was estimated as ∼2.7 kcal/mol, which is very close to the experimental value (1–2 kcal/mol) reported for ErbB1. On the basis of the simulation results, an atomic mechanism for the ligand-induced activation of ErbB4 was postulated. The present MD simulations provide a new insight into the conformational changes underlying the activation of ErbB4

Estimation of Carcinogenicity Using Molecular Fragments Tree

Carcinogenicity is an important toxicological endpoint that poses high concern to drug discovery. In this study, we developed a method to extract structural alerts (SAs) and modulating factors of carcinogens on the basis of statistical analyses. First, the Gaston algorithm, a frequent subgraph mining method, was used to detect substructures that occurred at least six times. Then, a molecular fragments tree was built and pruned to select high-quality SAs. The <i>p</i>-value of the parent node in the tree and that of its children nodes were compared, and the nodes that had a higher statistical significance in binomial tests were retained. Finally, modulating factors that suppressed the toxic effects of SAs were extracted by three self-defining rules. The accuracy of the 77 SAs plus four SA/modulating factor pairs model for the training set, and the test set was 0.70 and 0.65, respectively. Our model has higher predictive ability than Benigni’s model, especially in the test set. The results highlight that this method is preferable in terms of prediction accuracy, and the selected SAs are useful for prediction as well as interpretation. Moreover, our method is convenient to users in that it can extract SAs from a database using an automated and unbiased manner that does not rely on a priori knowledge of mechanism of action

PDTD: a web-accessible protein database for drug target identification-1

Describing the drug target. Not all fields are shown.<p><b>Copyright information:</b></p><p>Taken from "PDTD: a web-accessible protein database for drug target identification"</p><p>http://www.biomedcentral.com/1471-2105/9/104</p><p>BMC Bioinformatics 2008;9():104-104.</p><p>Published online 19 Feb 2008</p><p>PMCID:PMC2265675.</p><p></p