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Kirchmair J Ristic S Eder K Markt P Wolber G Laggner C Langer T 《Journal of chemical information and modeling》2007,47(6):2182-2196
In continuation of our recent studies on the quality of conformational models generated with CATALYST and OMEGA we present a large-scale survey focusing on the impact of conformational model quality and several screening parameters on pharmacophore-based and shape-based virtual high throughput screening (vHTS). Therefore, we collected known active compounds of CDK2, p38 MAPK, PPAR-gamma, and factor Xa and built a set of druglike decoys using ilib:diverse. Subsequently, we generated 3D structures using CORINA and also calculated conformational models for all compounds using CAESAR, CATALYST FAST, and OMEGA. A widespread set of 103 structure-based pharmacophore models was developed with LigandScout for virtual screening with CATALYST. The performance of both database search modes (FAST and BEST flexible database search) as well as the fit value calculation procedures (FAST and BEST fit) available in CATALYST were analyzed in terms of their ability to discriminate between active and inactive compounds and in terms of efficiency. Moreover, these results are put in direct comparison to the performance of the shape-based virtual screening platform ROCS. Our results prove that high enrichment rates are not necessarily in conflict with efficient vHTS settings: In most of the experiments, we obtained the highest yield of actives in the hit list when parameter sets for the fastest search algorithm were used. 相似文献
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In patients with depression, the use of 5-HT reuptake inhibitors can improve the condition. Machine learning methods can be used in ligand-based activity prediction processes. In order to predict SERT inhibitors, the SERT inhibitor data from the ChEMBL database was screened and pre-processed. Then 4 machine learning methods (LR, SVM, RF, and KNN) and 4 molecular fingerprints (CDK, Graph, MACCS, and PubChem) were used to build 16 prediction models. The top 5 models of accuracy (Q) in the cross-validation of training set were used to build three different ensemble learning models. In the test1 set, the VOT_CLF3 model had the largest SP (0.871), Q (0.869), AUC (0.919), and MCC (0.728). In the unbalanced test2 set, VOT_CLF3 had the largest SE (0.857), SP (0.867), Q (0.865) and MCC (0.639). VOT_CLF3 was recommended for the virtual screening process of SERT inhibitors. In addition, 12 molecular structural alerts that frequently appear in SERT inhibitors were found (P < 0.05), which provided important reference value for the design work of SERT inhibitors. 相似文献
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Prashant Revan Murumkar Vishal Prakash Zambre Mange Ram Yadav 《Journal of computer-aided molecular design》2010,24(2):143-156
A chemical feature-based pharmacophore model was developed for Tumor Necrosis Factor-α converting enzyme (TACE) inhibitors.
A five point pharmacophore model having two hydrogen bond acceptors (A), one hydrogen bond donor (D) and two aromatic rings
(R) with discrete geometries as pharmacophoric features was developed. The pharmacophore model so generated was then utilized
for in silico screening of a database. The pharmacophore model so developed was validated by using four compounds having proven
TACE inhibitory activity which were grafted into the database. These compounds mapped well onto the five listed pharmacophoric
features. This validated pharmacophore model was also used for alignment of molecules in CoMFA and CoMSIA analysis. The contour
maps of the CoMFA/CoMSIA models were utilized to provide structural insight for activity improvement of potential novel TACE
inhibitors. The pharmacophore model so developed could be used for in silico screening of any commercial/in house database
for identification of TACE inhibiting lead compounds, and the leads so identified could be optimized using the developed CoMSIA
model. The present work highlights the tremendous potential of the two mutually complementary ligand-based drug designing
techniques (i.e. pharmacophore mapping and 3D-QSAR analysis) using TACE inhibitors as prototype biologically active molecules. 相似文献
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