Cruciani G - Search Results

1

High-throughput virtual screening of proteins using GRID molecular interaction fields.

Sciabola S, Stanton RV, Mills JE, Flocco MM, Baroni M, Cruciani G, Perruccio F, Mason JS. Sciabola S, et al. Among authors: cruciani g. J Chem Inf Model. 2010 Jan;50(1):155-69. doi: 10.1021/ci9003317. J Chem Inf Model. 2010. PMID: 19919042

2

Conformer- and alignment-independent model for predicting structurally diverse competitive CYP2C9 inhibitors.

Afzelius L, Zamora I, Masimirembwa CM, Karlén A, Andersson TB, Mecucci S, Baroni M, Cruciani G. Afzelius L, et al. Among authors: cruciani g. J Med Chem. 2004 Feb 12;47(4):907-14. doi: 10.1021/jm030972s. J Med Chem. 2004. PMID: 14761192

3

Hydrogen bonding interactions of covalently bonded fluorine atoms: from crystallographic data to a new angular function in the GRID force field.

Carosati E, Sciabola S, Cruciani G. Carosati E, et al. Among authors: cruciani g. J Med Chem. 2004 Oct 7;47(21):5114-25. doi: 10.1021/jm0498349. J Med Chem. 2004. PMID: 15456255

4

A common reference framework for analyzing/comparing proteins and ligands. Fingerprints for Ligands and Proteins (FLAP): theory and application.

Baroni M, Cruciani G, Sciabola S, Perruccio F, Mason JS. Baroni M, et al. Among authors: cruciani g. J Chem Inf Model. 2007 Mar-Apr;47(2):279-94. doi: 10.1021/ci600253e. J Chem Inf Model. 2007. PMID: 17381166

5

New and original pKa prediction method using grid molecular interaction fields.

Milletti F, Storchi L, Sforna G, Cruciani G. Milletti F, et al. Among authors: cruciani g. J Chem Inf Model. 2007 Nov-Dec;47(6):2172-81. doi: 10.1021/ci700018y. Epub 2007 Oct 2. J Chem Inf Model. 2007. PMID: 17910431

6

Targeting the conformational transitions of MDM2 and MDMX: insights into dissimilarities and similarities of p53 recognition.

Macchiarulo A, Giacchè N, Carotti A, Baroni M, Cruciani G, Pellicciari R. Macchiarulo A, et al. Among authors: cruciani g. J Chem Inf Model. 2008 Oct;48(10):1999-2009. doi: 10.1021/ci800146m. Epub 2008 Oct 1. J Chem Inf Model. 2008. PMID: 18826207

7

Molecular interaction fields and 3D-QSAR studies of p53-MDM2 inhibitors suggest additional features of ligand-target interaction.

Dezi C, Carotti A, Magnani M, Baroni M, Padova A, Cruciani G, Macchiarulo A, Pellicciari R. Dezi C, et al. Among authors: cruciani g. J Chem Inf Model. 2010 Aug 23;50(8):1451-65. doi: 10.1021/ci100113p. J Chem Inf Model. 2010. PMID: 20726601

8

GRID-based three-dimensional pharmacophores II: PharmBench, a benchmark data set for evaluating pharmacophore elucidation methods.

Cross S, Ortuso F, Baroni M, Costa G, Distinto S, Moraca F, Alcaro S, Cruciani G. Cross S, et al. Among authors: cruciani g. J Chem Inf Model. 2012 Oct 22;52(10):2599-608. doi: 10.1021/ci300154n. Epub 2012 Sep 21. J Chem Inf Model. 2012. PMID: 22970854

9

GRID-based three-dimensional pharmacophores I: FLAPpharm, a novel approach for pharmacophore elucidation.

Cross S, Baroni M, Goracci L, Cruciani G. Cross S, et al. Among authors: cruciani g. J Chem Inf Model. 2012 Oct 22;52(10):2587-98. doi: 10.1021/ci300153d. Epub 2012 Sep 21. J Chem Inf Model. 2012. PMID: 22970894

10

BioGPS descriptors for rational engineering of enzyme promiscuity and structure based bioinformatic analysis.

Ferrario V, Siragusa L, Ebert C, Baroni M, Foscato M, Cruciani G, Gardossi L. Ferrario V, et al. Among authors: cruciani g. PLoS One. 2014 Oct 29;9(10):e109354. doi: 10.1371/journal.pone.0109354. eCollection 2014. PLoS One. 2014. PMID: 25353170 Free PMC article.

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