Baroni M - Search Results

1

Getting Insights into Structural and Energetic Properties of Reciprocal Peptide-Protein Interactions.

Trisciuzzi D, Siragusa L, Baroni M, Autiero I, Nicolotti O, Cruciani G. Trisciuzzi D, et al. Among authors: baroni m. J Chem Inf Model. 2022 Feb 28;62(4):1113-1125. doi: 10.1021/acs.jcim.1c01343. Epub 2022 Feb 11. J Chem Inf Model. 2022. PMID: 35148095

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: baroni m. J Med Chem. 2004 Feb 12;47(4):907-14. doi: 10.1021/jm030972s. J Med Chem. 2004. PMID: 14761192

3

Chemometric studies on the bactericidal activity of quinolones via an extended VolSurf approach.

Cianchetta G, Mannhold R, Cruciani G, Baroni M, Cecchetti V. Cianchetta G, et al. Among authors: baroni m. J Med Chem. 2004 Jun 3;47(12):3193-201. doi: 10.1021/jm030986y. J Med Chem. 2004. PMID: 15163198

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. J Chem Inf Model. 2007 Mar-Apr;47(2):279-94. doi: 10.1021/ci600253e. J Chem Inf Model. 2007. PMID: 17381166

5

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: baroni m. 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

6

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: baroni m. J Chem Inf Model. 2010 Jan;50(1):155-69. doi: 10.1021/ci9003317. J Chem Inf Model. 2010. PMID: 19919042

7

FLAP: GRID molecular interaction fields in virtual screening. validation using the DUD data set.

Cross S, Baroni M, Carosati E, Benedetti P, Clementi S. Cross S, et al. Among authors: baroni m. J Chem Inf Model. 2010 Aug 23;50(8):1442-50. doi: 10.1021/ci100221g. J Chem Inf Model. 2010. PMID: 20690627

8

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: baroni m. J Chem Inf Model. 2010 Aug 23;50(8):1451-65. doi: 10.1021/ci100113p. J Chem Inf Model. 2010. PMID: 20726601

9

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: baroni m. 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

10

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: baroni m. 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

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