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Items: 16

1.

Regulatory T-cell Genes Drive Altered Immune Microenvironment in Adult Solid Cancers and Allow for Immune Contextual Patient Subtyping.

Brouwer-Visser J, Cheng WY, Bauer-Mehren A, Maisel D, Lechner K, Andersson E, Dudley JT, Milletti F.

Cancer Epidemiol Biomarkers Prev. 2018 Jan;27(1):103-112. doi: 10.1158/1055-9965.EPI-17-0461. Epub 2017 Nov 13.

PMID:
29133367
2.

Identification of Short Hydrophobic Cell-Penetrating Peptides for Cytosolic Peptide Delivery by Rational Design.

Schmidt S, Adjobo-Hermans MJ, Kohze R, Enderle T, Brock R, Milletti F.

Bioconjug Chem. 2017 Feb 15;28(2):382-389. doi: 10.1021/acs.bioconjchem.6b00535. Epub 2016 Dec 14.

PMID:
27966361
3.

Detecting Cytosolic Peptide Delivery with the GFP Complementation Assay in the Low Micromolar Range.

Schmidt S, Adjobo-Hermans MJ, Wallbrecher R, Verdurmen WP, Bovée-Geurts PH, van Oostrum J, Milletti F, Enderle T, Brock R.

Angew Chem Int Ed Engl. 2015 Dec 7;54(50):15105-8. doi: 10.1002/anie.201505913. Epub 2015 Oct 30.

PMID:
26515694
4.

Novel chemistry for undruggable targets.

Milletti F, Sawyer TK.

Eur J Med Chem. 2015 Apr 13;94:458. doi: 10.1016/j.ejmech.2015.02.015. Epub 2015 Feb 13. No abstract available.

PMID:
25735718
5.

Quantifying the probability of clinical trial success from scientific articles.

Joshi V, Milletti F.

Drug Discov Today. 2014 Oct;19(10):1514-7. doi: 10.1016/j.drudis.2014.06.013. Epub 2014 Jun 20.

PMID:
24955839
6.

Chemogenomics in drug discovery: computational methods based on the comparison of binding sites.

Vulpetti A, Kalliokoski T, Milletti F.

Future Med Chem. 2012 Oct;4(15):1971-9. doi: 10.4155/fmc.12.147. Review.

PMID:
23088277
7.

Targeted kinase selectivity from kinase profiling data.

Milletti F, Hermann JC.

ACS Med Chem Lett. 2012 Mar 14;3(5):383-6. doi: 10.1021/ml300012r. eCollection 2012 May 10.

8.

Cell-penetrating peptides: classes, origin, and current landscape.

Milletti F.

Drug Discov Today. 2012 Aug;17(15-16):850-60. doi: 10.1016/j.drudis.2012.03.002. Epub 2012 Mar 23. Review.

PMID:
22465171
9.

Progress in the prediction of pKa values in proteins.

Alexov E, Mehler EL, Baker N, Baptista AM, Huang Y, Milletti F, Nielsen JE, Farrell D, Carstensen T, Olsson MH, Shen JK, Warwicker J, Williams S, Word JM.

Proteins. 2011 Dec;79(12):3260-75. doi: 10.1002/prot.23189. Epub 2011 Oct 15. Review.

10.

Predicting polypharmacology by binding site similarity: from kinases to the protein universe.

Milletti F, Vulpetti A.

J Chem Inf Model. 2010 Aug 23;50(8):1418-31. doi: 10.1021/ci1001263.

PMID:
20666497
11.

Extending pKa prediction accuracy: high-throughput pKa measurements to understand pKa modulation of new chemical series.

Milletti F, Storchi L, Goracci L, Bendels S, Wagner B, Kansy M, Cruciani G.

Eur J Med Chem. 2010 Sep;45(9):4270-9. doi: 10.1016/j.ejmech.2010.06.026. Epub 2010 Jun 23.

PMID:
20633962
12.

Tautomer preference in PDB complexes and its impact on structure-based drug discovery.

Milletti F, Vulpetti A.

J Chem Inf Model. 2010 Jun 28;50(6):1062-74. doi: 10.1021/ci900501c.

PMID:
20515065
13.

In silico pKa prediction and ADME profiling.

Cruciani G, Milletti F, Storchi L, Sforna G, Goracci L.

Chem Biodivers. 2009 Nov;6(11):1812-21. doi: 10.1002/cbdv.200900153.

PMID:
19937818
14.

Predicting protein pK(a) by environment similarity.

Milletti F, Storchi L, Cruciani G.

Proteins. 2009 Aug 1;76(2):484-95. doi: 10.1002/prot.22363.

PMID:
19241472
15.

Tautomer enumeration and stability prediction for virtual screening on large chemical databases.

Milletti F, Storchi L, Sforna G, Cross S, Cruciani G.

J Chem Inf Model. 2009 Jan;49(1):68-75. doi: 10.1021/ci800340j.

PMID:
19123923
16.

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

Milletti F, Storchi L, Sforna G, Cruciani G.

J Chem Inf Model. 2007 Nov-Dec;47(6):2172-81. Epub 2007 Oct 2.

PMID:
17910431

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