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1.
Chia-Yu Lai Tung-Ti Chang Mao-Feng Sun Hsin-Yi Chen Fuu-Jen Tsai Jaung-Geng Lin 《Molecular simulation》2013,39(3):250-256
The recent H1N1 (swine) influenza pandemic highlighted the urgent need of having effective anti‐viral strategies. In addition to neuraminidase inhibitors, there is another class of anti-viral drug known as M2 inhibitors that were, in the past, effective in treating seasonal influenza. However, due to the emergence of M2 inhibitor‐resistant influenza viruses, this class of drugs was not recommended for clinical usage in the latest influenza pandemic. In order to identify novel M2 inhibitors, we have performed molecular docking using a traditional Chinese medicine database (http://tcm.cmu.edu.tw/index.php). Docking and subsequent de novo designs gave 10 derivatives that have much better docking results than the control. Of these 10 derivatives, the top three, methyl isoferulate_1, genipin_1 and genipin_2, were selected for molecular dynamics simulation. During the simulation run, the top three derivatives all had stable interactions with M2 residues, Ser31 and Ala30. Methyl isoferulate_1 also has stable interaction to His37. Therefore, we recommend these three derivatives for further biomolecular experiments and clinical studies. 相似文献
2.
Tung-Ti Chang Hung-Jin Huang Kuei-Jen Lee Hsin Wei Yu Hsin-Yi Chen Fuu-Jen Tsai 《Journal of biomolecular structure & dynamics》2013,31(3):309-321
Abstract Phosphodiesterase superfamily is the key regulator of 3′,5′-cyclic guanosine monophosphate (cGMP) decomposition in human body. Phosphodiesterase-5 (PDE-5) inhibitors, sildenafil, vardenafil and tadalafil, are well known oral treatment for males with erectile dysfunction. To investigate the inhibitory effects of traditional Chinese medicine (TCM) compounds to PDE-5, we performed both ligand-based and structure-based studies on this topic. Comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) studies were conducted to construct three dimensional quantitative structure-activity relationship (3D-QSAR) models of series of known PDE-5 inhibitors. The predictive models had cross-validated, q2, and non cross-validated coefficient, r2, values of 0.791 and 0.948 for CoMFA and 0.724 and 0.908 for CoMSIA. These two 3D-QSAR models were used to predict activity of TCM compounds. Docking simulations were performed to further analyze the binding mode of training set and TCM compounds. A putative binding model was proposed based on CoMFA and CoMSIA contour maps and docking simulations; formation of pi-stacking, water bridge and specific hydrogen bonding were deemed important interactions between ligands and PDE-5. Of our TCM compounds, engeletin, satisfied our binding model, and hence, emerged as PDE-5 inhibitor candidate. Using this study as an example, we demonstrated that docking should be conducted for qualitative purposes, such as identifying protein characteristics, rather than for quantitative analyses that rank compound efficacy based on results of scoring functions. Prediction of compound activity should be reserved for QSAR analyses, and scoring functions and docking scores should be used for preliminary screening of TCM database (http://tcm.cmu.edu.tw/index.php). 相似文献
3.
A possible strategy against head and neck cancer: in silico investigation of three-in-one inhibitors
Yung-An Tsou Kuan-Chung Chen Su-Sen Chang Yeong-Ray Wen 《Journal of biomolecular structure & dynamics》2013,31(12):1358-1369
Overexpression of epidermal growth factor receptor (EGFR), Her2, and uroporphyrinogen decarboxylase (UROD) occurs in a variety of malignant tumor tissues. UROD has potential to modulate tumor response of radiotherapy for head and neck cancer, and EGFR and Her2 are common drug targets for the treatment of head and neck cancer. This study attempts to find a possible lead compound backbone from TCM Database@Taiwan (http://tcm.cmu.edu.tw/) for EGFR, Her2, and UROD proteins against head and neck cancer using computational techniques. Possible traditional Chinese medicine (TCM) lead compounds had potential binding affinities with EGFR, Her2, and UROD proteins. The candidates formed stable interactions with residues Arg803, Thr854 in EGFR, residues Thr862, Asp863 in Her2 protein, and residues Arg37, Arg41 in UROD protein, which are key residues in the binding or catalytic domain of EGFR, Her2, and UROD proteins. Thus, the TCM candidates indicated a possible molecule backbone for evolving potential inhibitors for three drug target proteins against head and neck cancer.An animated interactive 3D complement (I3DC) is available in Proteopedia at http://proteopedia.org/w/Journal:JBSD:35 相似文献
4.
Kuan-Chung Chen Yi-Ru Jian Mao-Feng Sun Tung-Ti Chang 《Journal of biomolecular structure & dynamics》2013,31(11):1207-1218
Silent information regulator 1 (Sirt1), a class III nicotinamide adenine dinucleotide dependent histone deacetylases, is important in cardioprotection, neuroprotection, metabolic disease, calorie restriction, and diseases associated with aging. Traditional Chinese Medicine (TCM) compounds from TCM Database@Taiwan (http://tcm.cmu.edu.tw/) were employed for screening potent Sirt1 agonists, and molecular dynamics (MD) simulation was implemented to simulate ligand optimum docking poses and protein structure under dynamic conditions. TCM compounds such as (S)-tryptophan-betaxanthin, 5-O-feruloylquinic acid, and RosA exhibited good binding affinity across different computational methods, and their drug-like potential were validated by MD simulation. Docking poses indicate that the carboxylic group of the three candidates generated H-bonds with residues in the protein chain from Ser441 to Lys444 and formed H-bond, π–cation interactions, or hydrophobic contacts with Phe297 and key active residue, His363. During MD, stable π–cation interactions with residues Phe273 or Arg274 were formed by (S)-tryptophan-betaxanthin and RosA. All candidates were anchored to His363 by stable π- or H-bonds. Hence, we propose (S)-tryptophan-betaxanthin, 5-O-feruloylquinic acid, and RosA as potential lead compounds that can be further tested in drug development process for diseases associated with agingAn animated interactive 3D complement (I3DC) is available in Proteopedia at http://proteopedia.org/w/Journal:JBSD:28 相似文献
5.
Uroporphyrinogen decarboxylase (UROD) has been suggested as a protectant against radiation for head and neck cancer (HNC). In this study, we employed traditional Chinese medicine (TCM) compounds from TCM nawiaT@esabataD (http://tcm.cmu.edu.tw/) to screen for drug-like candidates with potential UROD inhibition characteristics using virtual screening techniques. Isopraeroside IV, scopolin, and nodakenin exhibited the highest Dock Scores, and were predicted to have good Absorption, Distribution, Metabolism, Excretion, and Toxicity (ADMET) properties. Two common moieties, 2H-chromen-2-one and glucoside, were observed among the top TCM candidates. Cross comparison of the docking poses indicated that candidates formed stable interactions with key binding and catalytic residues of UROD through these two moieties. The 2H-chromen-2-one moiety enabled pi-cation interactions with Arg37 and H-bonds with Tyr164. The glucoside moiety was involved in forming H-bonds with Arg37 and Asp86. From our computational results, we propose isopraeroside IV, scopolin, and nodakenin as ligands that might exhibit drug-like inhibitory effects on UROD. The glucoside and 2H-chromen-2-one moieties may potentially be used for designing inhibitors of UROD. 相似文献
6.
Chang TT Huang HJ Lee KJ Yu HW Chen HY Tsai FJ Sun MF Chen CY 《Journal of biomolecular structure & dynamics》2010,28(3):309-321
Phosphodiesterase superfamily is the key regulator of 3',5'-cyclic guanosine monophosphate (cGMP) decomposition in human body. Phosphodiesterase-5 (PDE-5) inhibitors, sildenafil, vardenafil and tadalafil, are well known oral treatment for males with erectile dysfunction. To investigate the inhibitory effects of traditional Chinese medicine (TCM) compounds to PDE-5, we performed both ligand-based and structure-based studies on this topic. Comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) studies were conducted to construct three dimensional quantitative structure-activity relationship (3D-QSAR) models of series of known PDE-5 inhibitors. The predictive models had cross-validated, q(2), and non cross-validated coefficient, r(2), values of 0.791 and 0.948 for CoMFA and 0.724 and 0.908 for CoMSIA. These two 3D-QSAR models were used to predict activity of TCM compounds. Docking simulations were performed to further analyze the binding mode of training set and TCM compounds. A putative binding model was proposed based on CoMFA and CoMSIA contour maps and docking simulations; formation of pi-stacking, water bridge and specific hydrogen bonding were deemed important interactions between ligands and PDE-5. Of our TCM compounds, engeletin, satisfied our binding model, and hence, emerged as PDE-5 inhibitor candidate. Using this study as an example, we demonstrated that docking should be conducted for qualitative purposes, such as identifying protein characteristics, rather than for quantitative analyses that rank compound efficacy based on results of scoring functions. Prediction of compound activity should be reserved for QSAR analyses, and scoring functions and docking scores should be used for preliminary screening of TCM database (http://tcm.cmu.edu.tw/index.php). 相似文献
7.
Overexpression of epidermal growth factor receptor (EGFR) has been associated with cancer. Targeted inhibition of the EGFR pathway has been shown to limit proliferation of cancerous cells. Hence, we employed Traditional Chinese Medicine Database (TCM nawiaT@esabataD) (http://tcm.cmu.edu.tw) to identify potential EGFR inhibitor. Multiple Linear Regression (MLR), Support Vector Machine (SVM), Comparative Molecular Field Analysis (CoMFA), and Comparative Molecular Similarities Indices Analysis (CoMSIA) models were generated using a training set of EGFR ligands of known inhibitory activities. The top four TCM candidates based on DockScore were 2-O-caffeoyl tartaric acid, Emitine, Rosmaricine, and 2-O-feruloyl tartaric acid, and all had higher binding affinities than the control Iressa®. The TCM candidates had interactions with Asp855, Lys716, and Lys728, all which are residues of the protein kinase binding site. Validated MLR (r2 = 0.7858) and SVM (r2 = 0.8754) models predicted good bioactivity for the TCM candidates. In addition, the TCM candidates contoured well to the 3D-Quantitative Structure-Activity Relationship (3D-QSAR) map derived from the CoMFA (q2 = 0.721, r2 = 0.986) and CoMSIA (q2 = 0.662, r2 = 0.988) models. The steric field, hydrophobic field, and H-bond of the 3D-QSAR map were well matched by each TCM candidate. Molecular docking indicated that all TCM candidates formed H-bonds within the EGFR protein kinase domain. Based on the different structures, H-bonds were formed at either Asp855 or Lys716/Lys728. The compounds remained stable throughout molecular dynamics (MD) simulation. Based on the results of this study, 2-O-caffeoyl tartaric acid, Emitine, Rosmaricine, and 2-O-feruloyl tartaric acid are suggested to be potential EGFR inhibitors. 相似文献
8.
Kuan-Chung Chen Su-Sen Chang Hung-Jin Huang Tu-Liang Lin Yong-Jiang Wu 《Journal of biomolecular structure & dynamics》2013,31(6):662-683
Nowadays, the occurrence of metabolic syndrome, which is characterized by obesity and clinical disorders, has been increasing rapidly over the world. It induces several serious chronic diseases such as cardiovascular disease, dyslipidemia, gall bladder disease, hypertension, osteoarthritis, sleep apnea, stroke, and type 2 diabetes mellitus. Peroxisome proliferator-activated receptors (PPARs), which have three isoforms: PPAR-α, PPAR-γ, and PPAR-δ, are key regulators of adipogenesis, lipid and carbohydrate metabolism, and are potential drug targets for treating metabolic syndrome. The traditional Chinese medicine (TCM) compounds from TCM Database@Taiwan (http://tcm.cmu.edu.tw/) were employed to virtually screen for potential PPAR agonists, and structure-based pharmacophore models were generated to identify the key interactions for each PPAR protein. In addition, molecular dynamics (MD) simulation was performed to evaluate the stability of the PPAR–ligand complexes in a dynamic state. (S)-Tryptophan-betaxanthin and berberrubine, which have higher Dock Score than controls, form stable interactions during MD, and are further supported by the structure-based pharmacophore models in each PPAR protein. Key features include stable H-bonds with Thr279 and Ala333 of PPAR-α, with Thr252, Thr253 and Lys331 of PPAR-δ, and with Arg316 and Glu371 of PPAR-γ. Hence, we propose the top two TCM candidates as potential lead compounds in developing agonists targeting PPARs protein for treating metabolic syndrome. 相似文献
9.
Microsomal prostaglandin E2 synthase (mPGES-1) has been identified recently as a novel target for treating pain and inflammation. The aim of this study
is to understand the binding affinities of reported inhibitors for mPGES-1 and further to design potential new mPGES-1 inhibitors.
3D-QSAR-CoMFA (comparative molecular field analysis) and CoMSIA (comparative molecular similarity indices analysis) - techniques
were employed on a series of indole derivatives that act as selective mPGES-1 inhibitors. The lowest energy conformer of the
most active compound obtained from systematic conformational search was used as a template for the alignment of 32 compounds.
The models obtained were used to predict the activities of the test set of eight compounds, and the predicted values were
in good agreement with the experimental results. The 3D-QSAR models derived from the training set of 24 compounds were all
statistically significant (CoMFA; q
2 = 0.89, r
2 = 0.95, , and CoMSIA; q
2 = 0.84, r
2 = 0.93, , ). Contour plots generated for the CoMFA and CoMSIA models reveal useful clues for improving the activity of mPGES-1 inhibitors.
In particular, substitutions of an electronegative fluorine atom or a bulky hydrophilic phenoxy group at the meta or para positions of the biphenyl rings might improve inhibitory activity. A plausible binding mode between the ligands and mPGES-1
is also proposed. 相似文献
10.
11.
Amirreza Dowlati Beirami Zahra Hajimahdi 《Journal of biomolecular structure & dynamics》2019,37(11):2999-3006
A series of 26 selective COX-2 inhibitors which reported previously by our laboratory was selected to generate three-dimensional quantitative structure activity relationship (3D-QSAR) model. Active conformation of each molecule was predicted by docking studies and used for molecular alignment. Activity of 20 molecules as a train set was predicted using three methods including comparative molecular field analysis (CoMFA), CoMFA region focusing (CoMFA-RG) and comparative molecular similarity index analysis (CoMSIA). The best models of CoMFA-RG and CoMSIA revealed correlation coefficients r2 of 0.955 and 0.947, the leave one out cross-validation coefficients q2 of 0.573 and 0.574, respectively. In addition, CoMFA-RG and CoMSIA models were validated by a test set of six molecules with predicted coefficients r2pred of 0.644 and 0.799, respectively. Contour maps of generated models provided fruitful information about structural aspect of molecules that affected their COX-2 inhibitory activity. Based on three models results, steric and electrostatic properties are the most important factors in controlling the activity of the molecules. Results of CoMFA-RG and CoMSIA models were utilized to design new molecules. Comparison of experimental and predicted pIC50 values of designed molecules indicated that CoMFA-RG had the more predictive ability.
Communicated by Ramaswamy H. Sarma 相似文献
12.
13.
Chang PC Wang JD Lee MM Chang SS Tsai TY Chang KW Tsai FJ Chen CY 《Journal of biomolecular structure & dynamics》2011,29(3):471-483
Overweight and obesity are common health problems in modern society, particularly in developed countries. Excessive body mass has been linked to numerous diseases, such as cardiovascular diseases, diabetes, and cancer. Fat mass and obesity-associated protein (FTO) activity have direct impact on food intake and results in obesity. Inhibition of FTO activity may cause weight loss and reduce obese-linked health risks. We investigated the potential weight loss effects of traditional Chinese medicine (TCM), particularly by inhibiting FTO functions. Molecular docking was performed to screen TCM compounds from TCM Database@Taiwan (http://tcm.cmu.edu.tw). Three candidates were identified that contained either a tetrahydropyridine group or potent electronegative phenol group in the structure scaffold. Molecular dynamics simulation analysis of the docking poses of each complex indicated stabilizing trends in the protein-ligand complex movements. In addition, the number of hydrogen bonds increased throughout the 20 ns simulation. These results suggest that these TCM candidates could be potential FTO inhibitors through competitive inhibition. 相似文献
14.
Vascular endothselial growth factor (VEGF) and its receptor tyrosine kinase VEGFR-2 or kinase insert domain receptor (KDR)
have been identified as new promising targets for the design of novel anticancer agents. It is reported that 4-(1H-indazol-4-yl)phenylamino and aminopyrazolopyridine urea derivatives exhibit potent inhibitory activities toward KDR. To investigate
how their chemical structures relate to the inhibitory activities and to identify the key structural elements that are required
in the rational design of potential drug candidates of this class, molecular docking simulations and three-dimensional quantitative
structure-activity relationship (3D-QSAR) methods were performed on 78 4-(1H-indazol-4-yl)phenylamino and aminopyrazolopyridine urea derivatives as KDR inhibitors. Surflex-dock was used to determine
the probable binding conformations of all the compounds at the active site of KDR. As a result, multiple hydrophobic and hydrogen-bonding
interactions were found to be two predominant factors that may be used to modulate the inhibitory activities. Comparative
molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) 3D-QSAR models were developed
based on the docking conformations. The CoMFA model produced statistically significant results with the cross-validated correlation
coefficient q2 of 0.504 and the non-cross-validated correlation coefficient r2 of 0.913. The best CoMSIA model was obtained from the combination of steric, electrostatic and hydrophobic fields. Its q2 and r2 being 0.595 and 0.947, respectively, indicated that it had higher predictive ability than the CoMFA model. The predictive
abilities of the two models were further validated by 14 test compounds, giving the predicted correction coefficients rpred2 of 0.727 for CoMFA and 0.624 for CoMSIA, respectively. In addition, the CoMFA and CoMSIA models were used to guide the design
of a series of new inhibitors of this class with predicted excellent activities. Thus, these models may be used as an efficient
tool to predict the inhibitory activities and to guide the future rational design of 4-(1H-indazol-4-yl)phenylamino and aminopyrazolopyridine urea derivatives-based novel KDR inhibitors with potent activities. 相似文献
15.
3D-QSAR studies on the derivatives of 1-(3,3-diphenylpropyl)-piperidinyl amide and urea as CCR5 receptor antagonists were
performed by comparative molecular field analysis (CoMFA) and comparative molecular similarity indices (CoMSIA) methods to
rationalize the structural requirements responsible for the inhibitory activity of these compounds. The global minimum energy
conformer of the template molecule, the most active and pharmacokinetically stable molecule of the series, was obtained by
systematic search and used to build structures of the molecules in the dataset. The best predictions for the CCR5-receptor
were obtained with the CoMFA standard model (q
2 = 0.787, r
2 = 0.962) and CoMSIA model combined steric, electrostatic and hydrophobic fields (q
2 = 0.809, r
2 = 0.951). The predictive ability of CoMFA and CoMSIA were determined using a test set of 12 compounds giving predictive correlation
coefficients of 0.855 and 0.83, respectively, indicating good predictive power. Further, the robustness of the model was verified
by bootstrapping analysis. The contour maps produced by the CoMFA and CoMSIA models were used to identify the structural features
relevant to the biological activity in this series. Based on the CoMFA and CoMSIA analysis, we have identified some key features
in the series that are responsible for CCR5 antagonistic activity which may be used to design more potent 1-(3,3-diphenylpropyl)-piperidinyl
derivatives and predict their activity prior to synthesis.
Electronic supplementary material The online version of this article (doi:) contains supplementary material, which is available to authorized users. 相似文献
16.
Diabetes remains a life-threatening disease. The clinical profile of diabetic subjects is often worsened by the presence of
several long-term complications, for example neuropathy, nephropathy, retinopathy, and cataract. Comparative molecular field
analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) were performed on a series of 2,4-thiazolidinediones
derivatives as aldose reductase (ALR2) inhibitors. Molecular ligand superimposition on a template structure was finished by
the database alignment method. The 3D-QSAR models resulted from 44 molecules gave q
2 values of 0.773 and 0.817, r
2 values of 0.981 and 0.979 for CoMFA and CoMSIA, respectively. The contour maps from the models indicated that a large volume
group next to the R-substituent will increase the ALR2 inhibitory activity. In fact, adding a -CH2COOH substituent at the R-position would generate a new compound with higher predicted activity. 相似文献
17.
The Aurora kinases have been regarded as attractive targets for the development of new anticancer agents. Recently a series
of azaindole derivatives with Aurora B inhibitory activities were reported. To explore the relationship between the structures
of substituted azaindole derivatives and their inhibition of Aurora B, 3D-QSAR and molecular docking studies were performed
on a dataset of 41 compounds. 3D-QSAR, including CoMFA and CoMSIA, were applied to identify the key structures impacting their
inhibitory potencies. The CoMSIA model showed better results than CoMFA, with r
2
cv value of 0.575 and r
2
value of 0.987. 3D contour maps generated from CoMFA and CoMSIA along with the docking binding structures provided enough
information about the structural requirements for better activity. Based on the structure-activity relationship revealed by
the present study, we have designed a set of novel Aurora B inhibitors that showed excellent potencies in the developed models.
Thus, our results allowed us to design new derivatives with desired activities. 相似文献
18.
Three-dimensional quantitative structure-activity relationship (3D-QSAR) analyses using CoMFA and CoMSIA methods were conducted
on a series of fluoropyrrolidine amides as dipeptidyl peptidase IV (DP-IV) inhibitors. The selected ligands were docked into
the binding site of the 3D model of DP-IV using the GOLD software, and the possible interaction models between DP-IV and the
inhibitors were obtained. Based on the binding conformations of these fluoropyrrolidine amides and their alignment inside
the binding pocket of DP-IV, predictive 3D-QSAR models were established by CoMFA and CoMSIA analyses, which had conventional
r
2 and cross-validated coefficient values () up to 0.982 and 0.555 for CoMFA and 0.953 and 0.613 for CoMSIA, respectively. The predictive ability of these models was
validated by six compounds that were in the testing set. Structure-based investigations and the final 3D-QSAR results provide
the guide for designing new potent inhibitors. 相似文献
19.
《Journal of receptor and signal transduction research》2013,33(5):468-478
AbstractWith the purpose of designing novel chemical entities with improved inhibitory potencies against drug-resistant Mycobacterium tuberculosis, the 3D- quantitative structure–activity relationship (QSAR) studies were carried out on biphenyl analogs of the tuberculosis (TB) drug, PA-824. Anti-mycobacterial activity (MABA) was considered for the 3D-QSAR studies using the comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) approaches. The best CoMFA and CoMSIA models were found statistically significant with cross-validated coefficients (q2) of 0.784 and 0.768, respectively, and conventional coefficients (r2) of 0.823 and 0.981, respectively. The cross-validated and the external validation results revealed that both the CoMFA and CoMSIA models possesses high accommodating capacities and they would be reliable for predicting the pMIC values of new PA-824 derivatives. Based on the models and structural insights, a series of new PA-824 derivatives were designed and the anti-mycobacterial activities of the designed compounds were predicted based on the best 3D-QSAR model. The predicted data results suggest the designed compounds are more potent than existed ones. 相似文献
20.
Three-dimensional quantitative structure-activity relationship (QSAR) studies were conducted on two classes of recently explored compounds with known YopH inhibitory activities. Docking studies were employed to position the inhibitors into the YopH active site to determine the probable binding conformation. Good correlations between the predicated binding free energies and the inhibitory activities were found for two subsets of phosphate mimetics: alpha-ketocarboxylic acid and squaric acid (R2=0.70 and 0.68, respectively). The docking results also provided a reliable conformational alignment scheme for 3D-QSAR modeling. Comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) were performed based on the docking conformations, giving q2 of 0.734 and 0.754 for CoMFA and CoMSIA models, respectively. The 3D-QSAR models were significantly improved after removal of an outlier (q2=0.829 for CoMFA and q2=0.837 for CoMSIA). The predictive ability of the models was validated using a set of compounds that were not included in the training set. Mapping the 3D-QSAR models to the active site of YopH provides new insight into the protein-inhibitor interactions for this enzyme. These results should be applicable to the prediction of the activities of new YopH inhibitors, as well as providing structural implications for designing potent and selective YopH inhibitors as antiplague agents. 相似文献