Hierarchical virtual screening for the discovery of new molecular scaffolds in antibacterial hit identification
about
Machine-learning scoring functions to improve structure-based binding affinity prediction and virtual screeningUSR-VS: a web server for large-scale prospective virtual screening using ultrafast shape recognition techniquesistar: a web platform for large-scale protein-ligand dockingEnhancing hit identification in Mycobacterium tuberculosis drug discovery using validated dual-event Bayesian modelsDiscovery of novel GPVI receptor antagonists by structure-based repurposingUFSRAT: Ultra-fast Shape Recognition with Atom Types--the discovery of novel bioactive small molecular scaffolds for FKBP12 and 11βHSD1Low-Quality Structural and Interaction Data Improves Binding Affinity Prediction via Random Forest.Improving AutoDock Vina Using Random Forest: The Growing Accuracy of Binding Affinity Prediction by the Effective Exploitation of Larger Data Sets.Shape-based virtual screening with volumetric aligned molecular shapesMachine-learning techniques applied to antibacterial drug discoveryIdentification of novel potential antibiotics against Staphylococcus using structure-based drug screening targeting dihydrofolate reductaseFocused chemical libraries--design and enrichment: an example of protein-protein interaction chemical space.Biochemical evaluation of virtual screening methods reveals a cell-active inhibitor of the cancer-promoting phosphatases of regenerating liver.Substituting random forest for multiple linear regression improves binding affinity prediction of scoring functions: Cyscore as a case studyBayesian models for screening and TB Mobile for target inference with Mycobacterium tuberculosis.Correcting the impact of docking pose generation error on binding affinity prediction.Neural-Network Scoring Functions Identify Structurally Novel Estrogen-Receptor Ligands.Does a more precise chemical description of protein-ligand complexes lead to more accurate prediction of binding affinity?Prospective virtual screening for novel p53-MDM2 inhibitors using ultrafast shape recognition.A Bayesian Target Predictor Method based on Molecular Pairing Energies estimation.Discovery of Schaeffer's acid analogues as lead structures of mycobacterium tuberculosis type II dehydroquinase using a rational drug design approach.Computational models for neglected diseases: gaps and opportunities.Advances in the Development of Shape Similarity Methods and Their Application in Drug Discovery
P2860
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P2860
Hierarchical virtual screening for the discovery of new molecular scaffolds in antibacterial hit identification
description
2012 nî lūn-bûn
@nan
2012 թուականի Օգոստոսին հրատարակուած գիտական յօդուած
@hyw
2012 թվականի օգոստոսին հրատարակված գիտական հոդված
@hy
2012年の論文
@ja
2012年論文
@yue
2012年論文
@zh-hant
2012年論文
@zh-hk
2012年論文
@zh-mo
2012年論文
@zh-tw
2012年论文
@wuu
name
Hierarchical virtual screening ...... tibacterial hit identification
@ast
Hierarchical virtual screening ...... tibacterial hit identification
@en
Hierarchical virtual screening ...... tibacterial hit identification
@nl
type
label
Hierarchical virtual screening ...... tibacterial hit identification
@ast
Hierarchical virtual screening ...... tibacterial hit identification
@en
Hierarchical virtual screening ...... tibacterial hit identification
@nl
prefLabel
Hierarchical virtual screening ...... tibacterial hit identification
@ast
Hierarchical virtual screening ...... tibacterial hit identification
@en
Hierarchical virtual screening ...... tibacterial hit identification
@nl
P2093
P2860
P356
P1476
Hierarchical virtual screening ...... tibacterial hit identification
@en
P2093
Chris Abell
Jochen Blumberger
John B O Mitchell
Martina Mangold
Nigel I Howard
P2860
P304
P356
10.1098/RSIF.2012.0569
P577
2012-08-29T00:00:00Z