Peer-reviewed articles

R packages

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GMXPBSA in the world

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updated November 19th, 2023

26.

Assessment of the performance of the Ames MPF™ assay: A multicenter collaborative study with six coded chemicals

Spiliotopoulos D, Koelbert C, Audebert M, Barisch I, Bellet D, Constans M, Czich A, Finot F, Gervais V, Khoury L, Kirchnawy C, Kitamoto S, Le Tesson A, Malesic L, Matsuyama R, Mayrhofer E, Mouche I, Preikschat B, Prielinger L, Rainer B, Roblin C, Wäse K

2024. Mutat Res, 893:503718. DOI: 10.1016/j.mrgentox.2023.503718.

25.

Identification of a BAZ2A-bromodomain hit compound by fragment growing

Dalle Vedove A, Cazzanelli G, Batiste L, Marchand J-R, Spiliotopoulos D, Corsi J, D'Agostino V, Caflisch A, Lolli G

2022. ACS Med Chem Lett, 13(9):1434-43. DOI: 10.1021/acsmedchemlett.2c00173.

24.

Hitting a moving target: simulation and crystallography study of ATAD2 bromodomain blockers

Dolbois A, Batiste L, Wiedmer L, Dong J, Brütsch M, Huang D, Deerain N, Spiliotopoulos D, Cheng-Sánchez I, Laul E, Nevado C, Sledz P, Caflisch A

2020. ACS Med Chem Lett, 11(8):1573–80.  DOI: 10.1021/acsmedchemlett.0c00080.

23.

Assessment of the miniaturized liquid Ames Microplate Format (MPF) for a selection of the test items from the recommended list of genotoxic and non-genotoxic chemicals

Spiliotopoulos D, Koelbert C

2020. Mutat Res, 856–857:503218. DOI: 10.1016/j.mrgentox.2020.503218.

22.

Understanding the mechanism of action of pyrrolo[3,2-b]quinoxaline-derivatives as kinase inhibitors

Unzue A, Jessen-Trefzer C, Spiliotopoulos D, Gaudio E, Tarantelli C, Dong J, Zhao H, Pachmayr J, Zahler S, Bernasconi E, Sartori G, Cascione L, Bertoni F, Sledz P, Caflisch A, Nevado C

2020. RCS Med Chem, 11:665–75. DOI: 10.1039/D0MD00049C.

21.

Ligand retargeting by binding site analogy

Wiedmer L, Schärer C, Spiliotopoulos D, Hürzeler M, Sledz P, Caflisch A

2019. Eur J Med Chem, 175:107–13. DOI: 10.1016/j.ejmech.2019.04.037.

20.

Structural analysis of small molecule binding to the BAZ2A and BAZ2B bromodomains

Dalle Vedove A, Spiliotopoulos D, D'Agostino V, Marchand, J-R, Unzue A, Nevado C, Lolli G, Caflisch A

2018. ChemMedChem, 13(14):1479–87. DOI: 10.1002/cmdc.201800234.

19.

Chemical space expansion of bromodomain ligands guided by in silico virtual couplings (autocouple)

Batiste L, Unzue A, Dolbois A, Hassler F, Wang X, Deerain N, Zhu J, Spiliotopoulos D, Nevado C, Caflisch A

2018. ACS Cent Sci, 4(2):180–8. DOI: 10.1021/acscentsci.7b00401.

18.

Discovery of BAZ2A bromodomain ligands

Spiliotopoulos D, Wamhoff EC, Lolli G, Rademacher C, Caflisch A

2017. Eur J Med Chem, 139:564–72. DOI: 10.1016/j.ejmech.2017.08.028.

Also on bioRχiv!!

17.

Virtual screen to NMR (VS2NMR): Discovery of fragment hits for the CBP bromodomain

Spiliotopoulos D, Zhu J, Wamhoff EC, Deerain N, Marchand J-R, Aretz J, Rademacher C, Caflisch A

2017. Bioorg Med Chem Lett, 27(11):2472–8. DOI: 10.1016/j.bmcl.2017.04.001.

16.

dMM-PBSA: A new HADDOCK scoring function for protein-peptide docking

Spiliotopoulos D, Kastritis PL, Melquiond A, Bonvin AMJJ, Musco G, Rocchia W, Spitaleri A

2016. Front Mol Biosci, 3:46. DOI: 10.3389/fmolb.2016.00046.

15.

Fragment-based in silico screening of bromodomain ligands

Spiliotopoulos D, Caflisch A

2016. Drug Discov Today Technol, 19:81–90. DOI: 10.1016/j.ddtec.2016.06.003.

14.

Structural basis for PHDVC5HCHNSD1-C2HRNizp1 interaction: Implications for Sotos syndrome

Berardi A*, Quilici G*, Spiliotopoulos D*, Corral-Rodriguez MA, Martin-Garcia F, Degano M, Tonon G, Ghitti M, Musco G

2016. Nucl Acid Res, 44(7):3448–63. DOI: 10.1093/nar/gkw103.

13.

Fragment-based design of selective nanomolar ligands of the CREBBP bromodomain

Unzue A, Xu M, Dong J., Wiedmer L, Spiliotopoulos D, Caflisch A, Nevado C 

2016. J Med Chem, 59(4):1350–6. DOI: 10.1021/acs.jmedchem.5b00172.

12.

Discovery of CREBBP bromodomain inhibitors by high-throughput docking and hit optimization guided by Molecular Dynamics

Xu M, Unzue A, Dong J, Spiliotopoulos D, Nevado C, Caflisch A

2016. J Med Chem, 59(4):1340–9. DOI: 10.1021/acs.jmedchem.5b00171.

11.

GMXPBSA 2.1: A GROMACS tool to perform MM/PBSA and computational alanine scanning

Paissoni C, Spiliotopoulos D, Musco G, Spitaleri A

2015. Comput Phys Commun, 186:105–7. DOI: 10.1016/j.cpc.2014.09.010.

10.

Structural analysis of the binding of type I, I1/2, and II inhibitors to Eph tyrosine kinases

Dong J, Zhao H, Zhou T, Spiliotopoulos D, Rajendran C, Li XD, Huang D, Caflisch A

2014. ACS Med Chem Lett, 6(1):79–83. DOI: 10.1021/ml500355x.

9.

Molecular Dynamics simulations of bromodomains reveal binding‐site flexibility and multiple binding modes
of the natural ligand acetyl‐lysine

Spiliotopoulos D, Caflisch A

2014. Isr J Chem, 54:1084–92. DOI: 10.1002/ijch.201400009.

8.

Discovery of BRD4 bromodomain inhibitors by fragment-based high-throughput docking

Zhao H, Gartenmann L, Dong J, Spiliotopoulos D, Caflisch A

2014. Bioorg Med Chem Lett, 24(11):2493–6. DOI: 10.1016/j.bmcl.2014.04.017.

7.

GMXPBSA 2.0: A GROMACS tool to perform MM/PBSA and computational alanine scanning

Paissoni C, Spiliotopoulos D, Musco G, Spitaleri A

2014. Comput Phys Commun, 185(11):2920–9. DOI: 10.1016/j.cpc.2014.06.019.

6.

Identification of a novel de novo deletion in RAF1 associated with biventricular hypertrophy in Noonan syndrome

Sana ME, Spitaleri A, Spiliotopoulos D, Pezzoli L, Preda L, Musco G, Ferrazzi P, Iascone M

2014. Am J Med Genet A, 164(8):2069–73. DOI: 10.1002/ajmg.a.36588.

5.

muma, an R package for metabolomics univariate and multivariate statistical analysis

Gaude E, Chignola F, Spiliotopoulos D, García-Manteiga JM, Ghitti M, Spitaleri A, Mari S, Musco G

2013. Current Metabolomics, 1(2):180–9. DOI: 10.2174/2213235X11301020005.

4.

Exploring PHD fingers and H3K4me0 interactions with Molecular Dynamics simulations and binding free energy calculations: AIRE-PHD1, a case study

Spiliotopoulos D, Spitaleri A, Musco G

2013. PLoS One, 7(10):e46902. DOI: 10.1371/journal.pone.0046902.

3.

AIRE-PHD fingers are structural hubs to maintain the integrity of chromatin-associated interactome

Gaetani M, Matafora V, Saare M, Spiliotopoulos D, Mollica L, Quilici G, Chignola F, Mannella V, Zucchelli C, Peterson P, Bachi A, Musco G

2012. Nucl Acid Res, 40(22):11756–68. DOI: 10.1093/nar/gks933.

2.

A DNA-transposon-based approach to functional screening in Neural Stem cells

Albieri A, Onorati M, Calabrese G, Moiana A, Biasci D, Badaloni A, Camnasio S, Spiliotopoulos D, Ivics Z, Cattaneo E, Consalez GG

2010. J Biotechnol, 150(1):11–21

1.

An optimized experimental strategy for efficient conversion of embryonic stem (ES)-derived mouse neural stem (NS) cells into a nearly homogeneous mature neuronal population

Spiliotopoulos D*, Goffredo D*, Conti L*, Di Febo F, Toselli M, Cattaneo E

2009. Neurobiol Dis, 34(2):320–31. DOI: 10.1016/j.nbd.2009.02.007.

muma

Metabolomics Univariate and Multivariate Analysis

Gaude E, Chignola F, Spiliotopoulos D, Mari S, Spitaleri A, Ghitti M

Version:  1.4 

License:  GPL-2 

3.

Limit of detection (LOD) in nonlinear concentration-response curves, with application in in-vitro mutagenicity assays

Hothorn L, Spiliotopoulos D, Marin-Kuan M, Ritz C

zenodo, uploaded September 1st 2021. DOI:10.5281/zenodo.5356885.

2.

Similarity of multiple dose-response curves in interlaboratory studies in regulatory toxicology

Hothorn L, Spiliotopoulos D

arXiv, submitted September 25th 2020.

1.

Molecular and computational analysis of regulation of hSos1, the major activator of the proto-oncoprotein Ras

Farina M, Sacco E, Greco C, Busti S, Spiliotopoulos D, De Gioia L, Liberati D, Alberghina L, Vanoni M

International Congress ECOBIOSYS 2009 Classification and Forecasting Models, Milan.