Phytol Promotes the Formation of Slow-Twitch Muscle Fibers through PGC-1α/miRNA but Not Mitochondria Oxidation.

Phytol is a side chain of chlorophyll belonging to the side-chain double terpenoid. When animals consume food rich in chlorophyll, phytol can be broken down to phytanic acid after digestion. It was reported that feeding animals with different varieties and levels of forage could significant improve pH and marbling score of steer and lamb carcasses, but the internal mechanism for this is still not reported.

Identification and biochemical characterization of DC07090 as a novel potent small molecule inhibitor against human enterovirus 71 3C protease by structure-based virtual screening.

Hand, foot and mouth disease (HFMD) is a serious, highly contagious disease. HFMD caused by Enterovirus 71 (EV71), results in severe complications and even death. The pivotal role of EV71 3C in the viral life cycle makes it an attractive target for drug discovery and development to treat HFMD.

Wedelolactone metabolism in rats through regioselective glucuronidation catalyzed by uridine diphosphate-glucuronosyltransferases 1As (UGT1As).

Background: Wedelolactone (WEL), a medicinal plant-derived coumestan, has been reported to exhibit a diverse range of pharmacological activities. However, the metabolism and disposition of WEL remain unexplored.

Purpose: The present study aims to investigate the metabolism of WEL in rats and identify the enzymes responsible for forming major WEL metabolites.

A novel small-molecule compound targeting CD147 inhibits the motility and invasion of hepatocellular carcinoma cells.

CD147, a type I transmembrane glycoprotein, is highly expressed in various cancer types and plays important roles in tumor progression, especially by promoting the motility and invasion of hepatocellular carcinoma (HCC) cells. These crucial roles make CD147 an attractive target for therapeutic intervention in HCC, but no small-molecule inhibitors of CD147 have been developed to date. To identify a candidate inhibitor, we used a pharmacophore model derived from the structure of CD147 to virtually screen over 300,000 compounds.

Combinatorial Pharmacophore Modeling of Multidrug and Toxin Extrusion Transporter 1 Inhibitors: a Theoretical Perspective for Understanding Multiple Inhibitory Mechanisms.

A combinatorial pharmacophore (CP) model for Multidrug and toxin extrusion 1 (MATE1/SLC47A1) inhibitors was developed based on a data set including 881 compounds. The CP model comprises four individual pharmacophore hypotheses, HHR1, DRR, HHR2 and AAAP, which can successfully identify the MATE1 inhibitors with an overall accuracy around 75%. The model emphasizes the importance of aromatic ring and hydrophobicity as two important structural determinants for MATE1 inhibition.

In silico ADME/T modelling for rational drug design.

In recent decades, in silico absorption, distribution, metabolism, excretion (ADME), and toxicity (T) modelling as a tool for rational drug design has received considerable attention from pharmaceutical scientists, and various ADME/T-related prediction models have been reported. The high-throughput and low-cost nature of these models permits a more streamlined drug development process in which the identification of hits or their structural optimization can be guided based on a parallel investigation of bioavailability and safety, along with activity. However, the effectiveness of these tools is highly dependent on their capacity to cope with needs at different stages, e.

Combinatorial Pharmacophore-Based 3D-QSAR Analysis and Virtual Screening of FGFR1 Inhibitors.

The fibroblast growth factor/fibroblast growth factor receptor (FGF/FGFR) signaling pathway plays crucial roles in cell proliferation, angiogenesis, migration, and survival. Aberration in FGFRs correlates with several malignancies and disorders. FGFRs have proved to be attractive targets for therapeutic intervention in cancer, and it is of high interest to find FGFR inhibitors with novel scaffolds.

TarPred: a web application for predicting therapeutic and side effect targets of chemical compounds.

Motivation: Discovering the relevant therapeutic targets for drug-like molecules, or their unintended 'off-targets' that predict adverse drug reactions, is a daunting task by experimental approaches alone. There is thus a high demand to develop computational methods capable of detecting these potential interacting targets efficiently.

Results: As biologically annotated chemical data are becoming increasingly available, it becomes feasible to explore such existing knowledge to identify potential ligand-target interactions.

Identifying novel selective non-nucleoside DNA methyltransferase 1 inhibitors through docking-based virtual screening.

The DNA methyltransferases (DNMTs) found in mammals include DNMT1, DNMT3A, and DNMT3B and are attractive targets in cancer chemotherapy. DNMT1 was the first among the DNMTs to be characterized, and it is responsible for maintaining DNA methylation patterns. A number of DNMT inhibitors have been reported, but most of them are nucleoside analogs that can lead to toxic side effects and lack specificity.

Differential gene expression pattern in hypothalamus of chickens during fasting-induced metabolic reprogramming: functions of glucose and lipid metabolism in the feed intake of chickens.

Fasting-induced hypothalamic metabolic reprogramming is involved in regulating energy homeostasis and appetite in mammals, but this phenomenon remains unclear in poultry. In this study, the expression patterns of a panel of genes related to neuropeptides, glucose, and lipid metabolism enzymes in the hypothalamus of chickens during fasting and refeeding were characterized by microarray analysis and quantitative PCR. Results showed that 48 h of fasting upregulated (P < 0.

In Silico target fishing: addressing a "Big Data" problem by ligand-based similarity rankings with data fusion.

Background: Ligand-based in silico target fishing can be used to identify the potential interacting target of bioactive ligands, which is useful for understanding the polypharmacology and safety profile of existing drugs. The underlying principle of the approach is that known bioactive ligands can be used as reference to predict the targets for a new compound.

Results: We tested a pipeline enabling large-scale target fishing and drug repositioning, based on simple fingerprint similarity rankings with data fusion.

Estimation of acute oral toxicity in rat using local lazy learning.

Background: Acute toxicity means the ability of a substance to cause adverse effects within a short period following dosing or exposure, which is usually the first step in the toxicological investigations of unknown substances. The median lethal dose, LD50, is frequently used as a general indicator of a substance's acute toxicity, and there is a high demand on developing non-animal-based prediction of LD50. Unfortunately, it is difficult to accurately predict compound LD50 using a single QSAR model, because the acute toxicity may involve complex mechanisms and multiple biochemical processes.

In silico site of metabolism prediction for human UGT-catalyzed reactions.

Motivation: The human uridine diphosphate-glucuronosyltransferase enzyme family catalyzes the glucuronidation of the glycosyl group of a nucleotide sugar to an acceptor compound (substrate), which is the most common conjugation pathway that serves to protect the organism from the potential toxicity of xenobiotics. Moreover, it could affect the pharmacological profile of a drug. Therefore, it is important to identify the metabolically labile sites for glucuronidation.