Systematic exploitation of multiple receptor conformations for virtual ligand screening
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New insights for drug design from the X-ray crystallographic structures of G-protein-coupled receptorsIn silico assessment of potential druggable pockets on the surface of α1-antitrypsin conformersCan the energy gap in the protein-ligand binding energy landscape be used as a descriptor in virtual ligand screening?A structure-based model for predicting serum albumin bindingThe Art of Compiling Protein Binding Site Ensembles.Pocketome: an encyclopedia of small-molecule binding sites in 4DImplicit ligand theory: rigorous binding free energies and thermodynamic expectations from molecular docking.Rational prediction with molecular dynamics for hit identificationInduced fit docking, and the use of QM/MM methods in dockingComputational methods for the design of potent aromatase inhibitors.Latest developments in molecular docking: 2010-2011 in review.Flexible receptor docking for drug discovery.Understanding the challenges of protein flexibility in drug design.A cross docking pipeline for improving pose prediction and virtual screening performance.PeptiSite: a structural database of peptide binding sites in 4D.New pockets in dengue virus 2 surface identified by molecular dynamics simulation.Exploring the PDE5 H-pocket by ensemble docking and structure-based design and synthesis of novel β-carboline derivatives.Structure-based predictions of activity cliffs.In silico approach for the discovery of new PPARγ modulators among plant-derived polyphenolsLigand-biased ensemble receptor docking (LigBEnD): a hybrid ligand/receptor structure-based approach.Development and Application of a Virtual Screening Protocol for the Identification of Multitarget Fragments.Dynamic Docking: A Paradigm Shift in Computational Drug Discovery.ProSelection: A Novel Algorithm to Select Proper Protein Structure Subsets for in Silico Target Identification and Drug Discovery Research.Binding pose and affinity prediction in the 2016 D3R Grand Challenge 2 using the Wilma-SIE method.Optimization of compound ranking for structure-based virtual ligand screening using an established FRED-Surflex consensus approach.Ensemble-based virtual screening: identification of a potential allosteric inhibitor of Bcr-Abl.Binding mode similarity measures for ranking of docking poses: a case study on the adenosine A2A receptor.Advances in the Development of Shape Similarity Methods and Their Application in Drug DiscoveryEmpirical Scoring Functions for Structure-Based Virtual Screening: Applications, Critical Aspects, and Challenges
P2860
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P2860
Systematic exploitation of multiple receptor conformations for virtual ligand screening
description
2011 nî lūn-bûn
@nan
2011 թուականին հրատարակուած գիտական յօդուած
@hyw
2011 թվականին հրատարակված գիտական հոդված
@hy
2011年の論文
@ja
2011年論文
@yue
2011年論文
@zh-hant
2011年論文
@zh-hk
2011年論文
@zh-mo
2011年論文
@zh-tw
2011年论文
@wuu
name
Systematic exploitation of multiple receptor conformations for virtual ligand screening
@ast
Systematic exploitation of multiple receptor conformations for virtual ligand screening
@en
Systematic exploitation of multiple receptor conformations for virtual ligand screening
@nl
type
label
Systematic exploitation of multiple receptor conformations for virtual ligand screening
@ast
Systematic exploitation of multiple receptor conformations for virtual ligand screening
@en
Systematic exploitation of multiple receptor conformations for virtual ligand screening
@nl
prefLabel
Systematic exploitation of multiple receptor conformations for virtual ligand screening
@ast
Systematic exploitation of multiple receptor conformations for virtual ligand screening
@en
Systematic exploitation of multiple receptor conformations for virtual ligand screening
@nl
P2860
P50
P1433
P1476
Systematic exploitation of multiple receptor conformations for virtual ligand screening
@en
P2093
Andrea Cavalli
Manuel Rueda
P2860
P304
P356
10.1371/JOURNAL.PONE.0018845
P407
P577
2011-01-01T00:00:00Z