| Rank |
Title |
Journal |
Year |
PubWeight™‹?› |
|
1
|
Predictive QSAR modeling workflow, model applicability domains, and virtual screening.
|
Curr Pharm Des
|
2007
|
2.41
|
|
2
|
QSAR modeling of the blood-brain barrier permeability for diverse organic compounds.
|
Pharm Res
|
2008
|
1.46
|
|
3
|
Quantitative structure-activity relationship analysis of functionalized amino acid anticonvulsant agents using k nearest neighbor and simulated annealing PLS methods.
|
J Med Chem
|
2002
|
1.18
|
|
4
|
Combinatorial QSAR modeling of P-glycoprotein substrates.
|
J Chem Inf Model
|
2006
|
1.16
|
|
5
|
A novel automated lazy learning QSAR (ALL-QSAR) approach: method development, applications, and virtual screening of chemical databases using validated ALL-QSAR models.
|
J Chem Inf Model
|
2006
|
1.16
|
|
6
|
Development and validation of k-nearest-neighbor QSPR models of metabolic stability of drug candidates.
|
J Med Chem
|
2003
|
1.06
|
|
7
|
Development of quantitative structure-binding affinity relationship models based on novel geometrical chemical descriptors of the protein-ligand interfaces.
|
J Med Chem
|
2006
|
1.05
|
|
8
|
Integrative chemical-biological read-across approach for chemical hazard classification.
|
Chem Res Toxicol
|
2013
|
1.01
|
|
9
|
Quantitative structure-activity relationship analysis of pyridinone HIV-1 reverse transcriptase inhibitors using the k nearest neighbor method and QSAR-based database mining.
|
J Comput Aided Mol Des
|
2005
|
0.99
|
|
10
|
Combinatorial QSAR of ambergris fragrance compounds.
|
J Chem Inf Comput Sci
|
2004
|
0.98
|
|
11
|
Novel ligands for the human histamine H1 receptor: synthesis, pharmacology, and comparative molecular field analysis studies of 2-dimethylamino-5-(6)-phenyl-1,2,3,4-tetrahydronaphthalenes.
|
Bioorg Med Chem
|
2006
|
0.97
|
|
12
|
Application of predictive QSAR models to database mining: identification and experimental validation of novel anticonvulsant compounds.
|
J Med Chem
|
2004
|
0.96
|
|
13
|
Discovery of novel antimalarial compounds enabled by QSAR-based virtual screening.
|
J Chem Inf Model
|
2013
|
0.93
|
|
14
|
A novel two-step hierarchical quantitative structure-activity relationship modeling work flow for predicting acute toxicity of chemicals in rodents.
|
Environ Health Perspect
|
2009
|
0.93
|
|
15
|
Antitumor agents. 213. Modeling of epipodophyllotoxin derivatives using variable selection k nearest neighbor QSAR method.
|
J Med Chem
|
2002
|
0.92
|
|
16
|
Does rational selection of training and test sets improve the outcome of QSAR modeling?
|
J Chem Inf Model
|
2012
|
0.88
|
|
17
|
Differentiation of AmpC beta-lactamase binders vs. decoys using classification kNN QSAR modeling and application of the QSAR classifier to virtual screening.
|
J Comput Aided Mol Des
|
2008
|
0.86
|
|
18
|
Quantitative structure-property relationship modeling of remote liposome loading of drugs.
|
J Control Release
|
2011
|
0.85
|
|
19
|
Combinatorial QSAR modeling of specificity and subtype selectivity of ligands binding to serotonin receptors 5HT1E and 5HT1F.
|
J Chem Inf Model
|
2008
|
0.83
|
|
20
|
Development, validation, and use of quantitative structure-activity relationship models of 5-hydroxytryptamine (2B) receptor ligands to identify novel receptor binders and putative valvulopathic compounds among common drugs.
|
J Med Chem
|
2010
|
0.80
|
|
21
|
Application of quantitative structure-activity relationship models of 5-HT1A receptor binding to virtual screening identifies novel and potent 5-HT1A ligands.
|
J Chem Inf Model
|
2014
|
0.76
|
|
22
|
QSAR modeling of alpha-campholenic derivatives with sandalwood odor.
|
J Chem Inf Comput Sci
|
2003
|
0.75
|