[Prediction of ETA oligopeptides antagonists from Glycine max based on in silico proteolysis].

Oligopeptides are one of the the key pharmaceutical effective constituents of traditional Chinese medicine(TCM). Systematic study on composition and efficacy of TCM oligopeptides is essential for the analysis of material basis and mechanism of TCM. In this study, the potential anti-hypertensive oligopeptides from Glycine max and their endothelin receptor A (ETA) antagonistic activity were discovered and predicted based on in silico technologies.Main protein sequences of G. max were collected and oligopeptides were obtained using in silico gastrointestinal tract proteolysis. Then, the pharmacophore of ETA antagonistic peptides was constructed and included one hydrophobic feature, one ionizable negative feature, one ring aromatic feature and five excluded volumes. Meanwhile, three-dimensional structure of ETA was developed by homology modeling methods for further docking studies. According to docking analysis and consensus score, the key amino acid of GLN165 was identified for ETA antagonistic activity. And 27 oligopeptides from G. max were predicted as the potential ETA antagonists by pharmacophore and docking studies.In silico proteolysis could be used to analyze the protein sequences from TCM. According to combination of in silico proteolysis and molecular simulation, the biological activities of oligopeptides could be predicted rapidly based on the known TCM protein sequence. It might provide the methodology basis for rapidly and efficiently implementing the mechanism analysis of TCM oligopeptides.

Discovery of Potential Orthosteric and Allosteric Antagonists of P2Y1R from Chinese Herbs by Molecular Simulation Methods.

P2Y1 receptor (P2Y1R), which belongs to G protein-coupled receptors (GPCRs), is an important target in ADP-induced platelet aggregation. The crystal structure of P2Y1R has been solved recently, which revealed orthosteric and allosteric ligand-binding sites with the details of ligand-protein binding modes. And it suggests that P2Y1R antagonists, which recognize two distinct sites, could potentially provide an efficacious and safe antithrombotic profile. In present paper, 2D similarity search, pharmacophore based screening, and molecular docking were used to explore the potential natural P2Y1R antagonists. 2D similarity search was used to classify orthosteric and allosteric antagonists of P2Y1R. Based on the result, pharmacophore models were constructed and validated by the test set. Optimal models were selected to discover potential P2Y1R antagonists of orthosteric and allosteric sites from Traditional Chinese Medicine (TCM). And the hits were filtered by Lipinski's rule. Then molecular docking was used to refine the results of pharmacophore based screening and analyze the binding mode of the hits and P2Y1R. Finally, two orthosteric and one allosteric potential compounds were obtained, which might be used in future P2Y1R antagonists design. This work provides a reliable guide for discovering natural P2Y1R antagonists acting on two distinct sites from TCM.

Identification of potential ACAT-2 selective inhibitors using pharmacophore, SVM and SVR from Chinese herbs.

Acyl-coenzyme A cholesterol acyltransferase (ACAT) plays an important role in maintaining cellular and organismal cholesterol homeostasis. Two types of ACAT isozymes with different functions exist in mammals, named ACAT-1 and ACAT-2. Numerous studies showed that ACAT-2 selective inhibitors are effective for the treatment of hypercholesterolemia and atherosclerosis. However, as a typical endoplasmic reticulum protein, ACAT-2 protein has not been purified and revealed, so combinatorial ligand-based methods might be the optimal strategy for discovering the ACAT-2 selective inhibitors. In this study, selective pharmacophore models of ACAT-1 inhibitors and ACAT-2 inhibitors were built, respectively. The optimal pharmacophore model for each subtype was identified and utilized as queries for the Traditional Chinese Medicine Database screening. A total of 180 potential ACAT-2 selective inhibitors were obtained, which were identified using an ACAT-2 pharmacophore and not by our ACAT-1 model. Selective SVM model and bioactive SVR model were generated for further identification of the obtained ACAT-2 inhibitors. Ten compounds were finally obtained with predicted inhibitory activities toward ACAT-2. Hydrogen bond acceptor, 2D autocorrelations, GETAWAY descriptors, and BCUT descriptors were identified as key structural features for selectivity and activity of ACAT-2 inhibitors. This study provides a reasonable ligand-based approach to discover potential ACAT-2 selective inhibitors from Chinese herbs, which could help in further screening and development of ACAT-2 selective inhibitors.

[Discovery of potential ATP-sensitive potassium channel openers with potential hypotensive activity from Chinese herbs based on molecular simulation].

In this research, a combined method of ligand-based pharmacophore (LBP), structure-based pharmacophore (SBP), and molecular docking was applied for virtual screening potential ATP-sensitive potassium channel (KATP) openers from Chinese herbs. LBP models were generated by 3D-QSAR pharmacophore(hypogen) program, based on the training set composed of 48 KATP agonists. The best LBP model consisted of one hydrogen-bond acceptor, one hydrogen-bond donor, one hydrophobic feature, one aromatic ring and five excluded volumes. Besides, the correlation coefficient of training set and test set, N, and CAI value of the model were 0.876 4, 0.705 8, 3.304, and 2.616 respectively. Meanwhile, SBP models were also generated based on a 3D structure of KATP (PMID: PM0079770). The best SBP model consisted of six hydrogen-bond acceptors, eight hydrogen-bond donors, seven hydrophobic features and eighteen excluded volumes. The corresponding N and CAI value were 2.200 and 2.017. Then, the best LBP model and SBP model were applied to identify potential KATP openers from Traditional Chinese Medicine Database(TCMD), respectively. 349 hits were obtained after analyzed by drug-likeness rules. Moreover, 12 compounds with high docking scores were reserved after molecular docking evaluation. Interestingly, part of the results had been verified as hypotensive active ingredients by literatures. Therefore, this study uncovers a specific target effect contained in TCMD, and provides candidates for new KATP openers' research.

[Screen potential CYP450 2E1 inhibitors from Chinese herbal medicine based on support vector regression and molecular docking method].

Inhibition of cytochrome P450 (CYP450) enzymes is the most common reasons for drug interactions, so the study on early prediction of CYPs inhibitors can help to decrease the incidence of adverse reactions caused by drug interactions.CYP450 2E1(CYP2E1), as a key role in drug metabolism process, has broad spectrum of drug metabolism substrate. In this study, 32 CYP2E1 inhibitors were collected for the construction of support vector regression (SVR) model. The test set data were used to verify CYP2E1 quantitative models and obtain the optimal prediction model of CYP2E1 inhibitor. Meanwhile, one molecular docking program, CDOCKER, was utilized to analyze the interaction pattern between positive compounds and active pocket to establish the optimal screening model of CYP2E1 inhibitors.SVR model and molecular docking prediction model were combined to screen traditional Chinese medicine database (TCMD), which could improve the calculation efficiency and prediction accuracy. 6 376 traditional Chinese medicine (TCM) compounds predicted by SVR model were obtained, and in further verification by using molecular docking model, 247 TCM compounds with potential inhibitory activities against CYP2E1 were finally retained. Some of them have been verified by experiments. The results demonstrated that this study could provide guidance for the virtual screening of CYP450 inhibitors and the prediction of CYPs-mediated DDIs, and also provide references for clinical rational drug use.

[Virtual screening for natural CETP inhibitors by structure-based pharmacophore].

Cholesterol ester transfer protein (CETP) is a key regulator of high density lipoprotein (HDL). Owing to its important role in the reverse of cholesterol transport, CETP has become a hotspot target in modulating lipid drug design. In this paper, structure based pharmacophore (SBP) models for CETP inhibitors were built based on the protein structure 4F2A from Protein Database (PDB). The best pharmacophore contained six hydrophobic features, one hydrogen bond acceptor feature and nine excluded volume features, with the N and CAI value was 3.33 and 2.31 respectively. Then the model was used to search the traditional Chinese medicine database (TCMD) and 629 compounds originated from 315 TCM herbs were obtained. Molecular docking was also used to validate SBP by analyzing the critical amino acid residue and the interaction between potential active compounds and receptor. In this study, several TCM herbs, like Lycii Frutus and Schisandrae chinensis fructus, which contained more optimal SBP based screening results, have been reported hypolipidemic effect, and need to be studied deeply in a more focused research on herbal active constituents. Therefore, this study could provide reliable fundamental data for exploring the action mechanisms of TCM, and be applicable to identify lead candidates, which can be utilized as starting scaffolds for natural CETP inhibitors.

[Study on anti-hyperlipidemia mechanism of high frequency herb pairs by molecular docking method].

Traditional Chinese medicine (TCM) has definitely clinical effect in treating hyperlipidemia, but the action mechanism still need to be explored. Based on consulting Chinese Pharmacopoeia (2010), all the lipid-lowering Chinese patent medicines were analyzed by associated rules data mining method to explore high frequency herb pairs. The top three couplet medicines with high support degree were Puerariae Lobatae Radix-Crataegi Fructus, Salviae Miltiorrhizae Radix et Rhizoma-Crataegi Fructus, and Polygoni Multiflori Radix-Crataegi Fructus. The 20 main ingredients were selected from the herb pairs and docked with 3 key hyperlipidemia targets, namely 3-hydroxy-3-methylglutaryl coenzyme A reductase (HMG-CoA reductase), peroxisome proliferator activated receptor-α (PPAR-α ) and niemann-pick C1 like 1 (NPC1L1) to further discuss the molecular mechanism of the high frequency herb pairs, by using the docking program, LibDock. To construct evaluation rules for the ingredients of herb pairs, the root-mean-square deviation (RMSD) value between computed and initial complexes was first calculated to validate the fitness of LibDock models. Then, the key residues were also confirmed by analyzing the interactions of those 3 proteins and corresponding marketed drugs. The docking results showed that hyperin, puerarin, salvianolic acid A and polydatin can interact with two targets, and the other five compounds may be potent for at least one of the three targets. In this study, the multi-target effect of high frequency herb pairs for lipid-lowering was discussed on the molecular level, which can help further researching new multi-target anti-hyperlipidemia drug.

[Application of support vector machine approach in studying nephron toxicity of Chinese medicinal materials].

On the basis of web databases, 111 compounds with nephrotoxicity and 90 compounds without nephrotoxicity were collected as data set of nephrotoxicity discrimination model, 39 compounds with tubular necrosis and 39 compounds without tubular necrosis were collected as data set of tubular necrosis discrimination model. The 6 122 molecular descriptors, including physicochemical, charge distribution and geometrical descriptors were calculated to characterize the molecular structure of the above-mentioned compounds. CfsSubsetEval valuation method and BestFirst-D1-N5 searching method were used to select molecular descriptors. Two models with high accuracy were built based on the support vector machine (SVM) approach, respectively. Accuracy, sensitivity, specificity and matthew's correlation coefficient of the two models were all above 70%. By using 22 nephrotoxicity compounds of Chinese medicine, the nephrotoxicity discrimination model was further verified with an accuracy of 72.73%. Using the tubular necrosis discrimination model, 10 potential compounds which can cause tubular necrosis were screened from the positive results of nephrotoxicity discrimination model, 6 of them have been verified by literatures. The results demonstrated that the discrimination models can be applied to screen nephrotoxic compounds from Chinese medicinal materials, and they also offer a new research idea for the further studies on the mechanism of nephrotoxicity.

[Discovering L-type calcium channels inhibitors of antihypertensive drugs based on drug repositioning].

This study was amid to construct the pharmacophore model of L-type calcium channel antagonist in the application of screening Drugbank and TCMD. This paper repositions the approved drugs resulting from virtual screening and discusses the relocation-based drug discovery methods, screening antihypertensive drugs with L-type calcium channel function from TCMD. Qualitative hypotheses wre generated by HipHop separately on the basis of 12 compounds with antagonistic action on L-type calcium channel expressed in rabbit cardiac muscle. Datebase searching method was used to evaluate the generated hypotheses. The optimum hypothesis was used to search Drugbank and TCMD. This paper repositions the approved drugs and evaluates the antihypertensive effect of the chemical constituent of traditional Chinese medicine resulting from virtual screening by the matching score and literature. The results showed that optimum qualitative hypothesis is with six features, which were two hydrogen-bond acceptors, four hydrophobic groups, and the CAI value of 2.78. Screening Drugbank achieves 93 approved drugs. Screening TCMD achieves 285 chemical constituents of traditional Chinese medicine. It was concluded that the hypothesis is reliable and can be used to screen datebase. The approved drugs resulting from virtual screening, such as pravastatin, are potentially L-type calcium channels inhibitors. The chemical constituents of traditional Chinese medicine, such as Arctigenin III and Arctigenin are potentially antihypertensive drugs. It indicates that Drug Repositioning based on hypothesis is possible.

[Application of support vector machine in screening neurotoxic compounds from traditional Chinese medicine].

In this study, based on web database, 324 neurotoxic compounds and 234 non-neurotoxic compounds were selected as a data set for neurotoxicity discriminative model. 6 122 molecular descriptors, including charge distribution, physicochemical and geometrical descriptors,were calculated to characterize the molecular structure of neurotoxic compounds. The combination of Cfs Subset Evaluation and Best First-D1-N5 searching was used to select molecular descriptors. A discrimination model with high accuracy was built based on the support vector machine (SVM) approach. Meanwhile, the model accuracy, sensitivity and specificity were all above 80%. Besides, 30 traditional Chinese medicine compositions with neurotoxicity were set as external validation to further verify the model accuracy,with anaccuracy of 73.333%. Using the model, 13 potential neurotoxic compounds were screened from Sophorae subprostrate Radix,4 of them were verified by literatures. The results demonstrated that the discrimination model can be applied to screen neurotoxic compounds from Chinese medicinal materials.

[Discovery of potential nicotinic acid receptor agonists from Chinese herbal medicines based on molecular simulation].

Nicotinic acid could increase high density lipoprotein and reduce serum total cholesterol, low density lipoprotein cholesterol and triglycerides in human bodies, thus is frequently applied in treating low high-density lipoprotein cholesterol and hypertriglyceridemia in clinic. However, according to the findings, nicotinic acid could also cause adverse effects, such as skin flush, beside its curative effects. In this study, bioisosterism, fragment-based search and Lipinski's Rule of Five were used to preliminarily screen out potential TCM ingredients that may have similar pharmacological effects with nicotinic acid from Traditional Chinese medicine database (TCMD). Afterwards, homology modeling and flexible docking were used to further screen out potential nicotinic acid receptor agonists. As a result, eleven candidate compounds were derived from eight commonly used traditional Chinese medicines. Specifically, all of the candidate compounds' interaction with nicotinic acid receptor was similar to nicotinic acid, and their docking scores were all higher than that of nicotinic acid, but their druggability remained to be further studied. Some of the eight source traditional Chinese medicines were used to lower lipid according to literature studies, implying that they may show effect through above means. In summary, this study provides basis and reference for extracting new nicotinic acid receptor agonists from traditional Chinese medicines and improving the medication status of hyperlipidemia.