Gabriele Cruciani
Gabriele Cruciani
Verified email at unipg.it
TitleCited byYear
Molecular fields in quantitative structure–permeation relationships: the VolSurf approach
G Cruciani, P Crivori, PA Carrupt, B Testa
Journal of Molecular Structure: THEOCHEM 503 (1-2), 17-30, 2000
6072000
GRid-INdependent descriptors (GRIND): a novel class of alignment-independent three-dimensional molecular descriptors
M Pastor, G Cruciani, I McLay, S Pickett, S Clementi
Journal of medicinal chemistry 43 (17), 3233-3243, 2000
5172000
Generating optimal linear PLS estimations (GOLPE): an advanced chemometric tool for handling 3D‐QSAR problems
M Baroni, G Costantino, G Cruciani, D Riganelli, R Valigi, S Clementi
Quantitative Structure‐Activity Relationships 12 (1), 9-20, 1993
5101993
Predicting blood− brain barrier permeation from three-dimensional molecular structure
P Crivori, G Cruciani, PA Carrupt, B Testa
Journal of medicinal chemistry 43 (11), 2204-2216, 2000
4862000
VolSurf: a new tool for the pharmacokinetic optimization of lead compounds
G Cruciani, M Pastor, W Guba
European Journal of Pharmaceutical Sciences 11, S29-S39, 2000
4252000
MetaSite: understanding metabolism in human cytochromes from the perspective of the chemist
G Cruciani, E Carosati, B De Boeck, K Ethirajulu, C Mackie, T Howe, ...
Journal of medicinal chemistry 48 (22), 6970-6979, 2005
4182005
Antileishmanial chalcones: Statistical design, synthesis, and three-dimensional quantitative structure− activity relationship analysis
SF Nielsen, SB Christensen, G Cruciani, A Kharazmi, T Liljefors
Journal of Medicinal Chemistry 41 (24), 4819-4832, 1998
3531998
A common reference framework for analyzing/comparing proteins and ligands. Fingerprints for Ligands and Proteins (FLAP): theory and application
M Baroni, G Cruciani, S Sciabola, F Perruccio, JS Mason
Journal of chemical information and modeling 47 (2), 279-294, 2007
3232007
Progress in predicting human ADME parameters in silico
S Ekins, CL Waller, PW Swaan, G Cruciani, SA Wrighton, JH Wikel
Journal of pharmacological and toxicological methods 44 (1), 251-272, 2000
2852000
New and Original pKa Prediction Method Using Grid Molecular Interaction Fields
F Milletti, L Storchi, G Sforna, G Cruciani
Journal of chemical information and modeling 47 (6), 2172-2181, 2007
2282007
Hydrogen bonding interactions of covalently bonded fluorine atoms: from crystallographic data to a new angular function in the GRID force field
E Carosati, S Sciabola, G Cruciani
Journal of medicinal chemistry 47 (21), 5114-5125, 2004
2092004
GRID/CPCA: a new computational tool to design selective ligands
MA Kastenholz, M Pastor, G Cruciani, EEJ Haaksma, T Fox
Journal of medicinal chemistry 43 (16), 3033-3044, 2000
1992000
Computational approaches to identifying and characterizing protein binding sites for ligand design
S Henrich, OMH Salo‐Ahen, B Huang, FF Rippmann, G Cruciani, ...
Journal of Molecular Recognition: An Interdisciplinary Journal 23 (2), 209-219, 2010
1902010
Comparative molecular field analysis using GRID force-field and GOLPE variable selection methods in a study of inhibitors of glycogen phosphorylase b
G Cruciani, KA Watson
Journal of medicinal chemistry 37 (16), 2589-2601, 1994
1781994
Predicting drug metabolism: a site of metabolism prediction tool applied to the cytochrome P450 2C9
I Zamora, L Afzelius, G Cruciani
Journal of medicinal chemistry 46 (12), 2313-2324, 2003
1722003
Smart region definition: A new way to improve the predictive ability and interpretability of three-dimensional quantitative structure− activity relationships
M Pastor, G Cruciani, S Clementi
Journal of medicinal chemistry 40 (10), 1455-1464, 1997
1621997
Predictive ability of regression models. Part I: Standard deviation of prediction errors (SDEP)
G Cruciani, M Baroni, S Clementi, G Costantino, D Riganelli, ...
Journal of Chemometrics 6 (6), 335-346, 1992
1321992
Vitamin E: Emerging aspects and new directions
F Galli, A Azzi, M Birringer, JM Cook-Mills, M Eggersdorfer, J Frank, ...
Free Radical Biology and Medicine 102, 16-36, 2017
1252017
Predictive ability of regression models. Part II: Selection of the best predictive PLS model
M Baroni, S Clementi, G Cruciani, G Costantino, D Riganelli, E Oberrauch
Journal of chemometrics 6 (6), 347-356, 1992
1221992
Principal properties for aromatic substituents. A multivariate approach for design in QSAR
B Skagerberg, D Bonelli, S Clementi, G Cruciani, C Ebert
Quantitative Structure‐Activity Relationships 8 (1), 32-38, 1989
1151989
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Articles 1–20