about
Molecular Shape and Medicinal Chemistry: A PerspectiveDrug design for ever, from hype to hopeA structure-guided approach for protein pocket modeling and affinity prediction.Physical binding pocket induction for affinity prediction.QMOD: physically meaningful QSARSurface similarity-based molecular query-retrievalExtrapolative prediction using physically-based QSAR.2D-Qsar for 450 types of amino acid induction peptides with a novel substructure pair descriptor having wider scope.Iterative refinement of a binding pocket model: active computational steering of lead optimization.Does your model weigh the same as a duck?Customizing scoring functions for docking.Effects of protein conformation in docking: improved pose prediction through protein pocket adaptation.Hydrophobic similarity between molecules: a MST-based hydrophobic similarity index.NOVEL METHOD FOR MINING QSPR-RELEVANT CONFORMATIONS
P2860
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P2860
description
1994 nî lūn-bûn
@nan
1994 թուականի Դեկտեմբերին հրատարակուած գիտական յօդուած
@hyw
1994 թվականի դեկտեմբերին հրատարակված գիտական հոդված
@hy
1994年の論文
@ja
1994年論文
@yue
1994年論文
@zh-hant
1994年論文
@zh-hk
1994年論文
@zh-mo
1994年論文
@zh-tw
1994年论文
@wuu
name
A shape-based machine learning tool for drug design.
@ast
A shape-based machine learning tool for drug design.
@en
type
label
A shape-based machine learning tool for drug design.
@ast
A shape-based machine learning tool for drug design.
@en
prefLabel
A shape-based machine learning tool for drug design.
@ast
A shape-based machine learning tool for drug design.
@en
P2093
P356
P1476
A shape-based machine learning tool for drug design.
@en
P2093
R E Critchlow
R H Lathrop
T A Webster
T G Dietterich
T Lozano-Perez
P2888
P304
P356
10.1007/BF00124012
P577
1994-12-01T00:00:00Z