Mu.Ta.Lig - COST ACTION CA15135

Dr. Slavica FILIPIC

14 June 2016


General information

Name: Slavica
Surname: Filipić
Cell phone number with international prefix: + 381 63 83 80 500
Country: Serbia
Affiliation: Department of Pharmaceutical Chemistry, University of Belgrade – Faculty of Pharmacy
Gender: F T M
Year of the PhD title: 2013
Personal web page:



Previous COST participation: No Yes T


List of 10 selected publications within last 5 years

1. L. Ismaili, B. Refouvelet, M. Benchekroun, S. Brogi, M. Brindisi, S. Gemma, G. Campiani, S. Filipic, D. Agbaba, G. Esteban, M. Unzeta, K.  Nikolic, S. Butini, J. Marco-Contelles. Multitarget compounds bearing tacrine- and donepezil-like structural and functional motifs for the potential treatment of Alzheimer’s disease, Progress in Neurobiology (2016)
2. S. Filipic, D. Ruzic, J. Vucicevic, K. Nikolic, D. Agbaba. Quantitative structure-retention relationship of selected imidazoline derivatives on α1-acid glycoprotein column. Journal of Pharmaceutical and Biomedical Analysis (2016)
3. Z. Gagic, K. Nikolic, B. Ivkovic, S. Filipic, D. Agbaba. QSAR studies and design of new analogs of vitamin E with enhanced antiproliferative activity on MCF-7 breast cancer cells. Journal of  the Taiwan Institute of Chemical Engineers 59, 33-44 (2016).
4. M. Popovic, G. Popovic, S.  Filipic, K. Nikolic, D. Agbaba. The effects of micelles of differently charged surfactants on the equilibrium between (Z)- and (E)-diastereomers of five ACE inhibitors in aqueous media. Monatshefte Fur Chemie 146, 913-921 (2015)
5. O. M. Bautista-Aguilera, A. Samadi, M. Chioua, K. Nikolic, S. Filipic, D. Agbaba, E. Soriano, L. de Andrés, M. I. Rodríguez-Franco, S. Alcaro, R. R. Ramsay, F. Ortuso, M. Yañez, and J. Marco-Contelles.           N-Methyl-N-((1-methyl-5-(3-(1-(2-methylbenzyl)piperidin-4-yl)propoxy)-1H-indol-2-yl)methyl)prop-2-yn-1-amine, a New Cholinesterase and Monoamine Oxidase Dual Inhibitor J. Med. Chem., 57, 10455–10463 (2014).
6. K. Nikolic, S. Filipic, D. Agbaba,  H. Stark, Procognitive Properties of Drugs with Single and Multitargeting H3 Receptor Antagonist Activities. CNS Neuroscience & Therapeutics 20, 613–623 (2014).
7. B. Filipic, K. Nikolic, S. Filipic, B. Jovcic, D. Agbaba, J. Antic Stankovic, M. Kojic, N. Golic, Identifying the CmbT substrates specificity by using a quantitative structure–activity relationship (QSAR) study. J. Taiwan Inst. Chem. E.  45, 764-771 (2014).
8. S. Filipic, K. Nikolic, I. Vovk, M. Krizman, D. Agbaba, Quantitative structure-mobility relationship analysis of imidazoline receptor ligands in CDs-mediated CE, Electrophoresis, 34, 471–482 (2013).
9. K. Nikolic, S. Filipic, A. Smoliński, R. Kaliszan, D. Agbaba, Partial least square and hierarchical clustering in ADMET modeling: Prediction of blood – brain barrier permeation of α-Adrenergic and imidazoline receptor ligands. Journal of Pharmacy and Pharmaceutical Sciences 16, 622-647 (2013).
10. K. Nikolic, S. Filipic, D. Agbaba, Multi-target QSAR and docking study of steroids binding to corticosteroid-binding globulin and sex hormone-binding globulin. Current Computer-Aided Drug Design 8, 296-308 (2012).


Main skills and expertise (up to 5)

1. Computer-aided drug design
2. Chemometrics
3. Evaluation of physico-chemical properties by use of chromatographic and computational methods
4. Development of analytical methods for analysis of drug substances


Main equipment/facilities available in the participants’ lab (up to 5)

1. Softwares:ChemBioOffice Pro13, Gaussian09W, Simca 12+P, Dragon 6.0, Pentacle 1.0.6, FLAP 2.0.2 , ADMET Predictor, AutoDock Vina 1.1.2, Gold 5.4.0
2. NMR spectrometer 400 MHz
3. Triple quadrupole mass spectrometer with a heated electrospray ionization



Short personal activity proposal for the COST Action CA15135 (max 1000 characters)

 ·         Rational design of novel multi-target ligands as potential drugs for the treatment of complex diseases using molecular modelling, quantitative-structure activity relationships (3D-QSAR), pharmacophore modelling, virtual docking, virtual screening methods (ligand-based-virtual screening, structure-based-virtual screening) and in silico ADMET studies.·         Examination of physico-chemical and biopharmaceutical properties of multi-target ligands using in vitro parallel artificial membrane permeability assay (PAMPA), biopartitioning micellar chromatography and protein-based columns. ·         Application of partial least square regression, principal component analysis, artificial neural networks, and hierarchical clustering for quantitative structure property study of multi-target compounds. ·         Chemometry and development of analytical methods for examination of multi-target ligands. 


Work Group preference: score from 1 (preferred) to 4 (not preferred)

Work Group of the CA15135 COST Action Score
WG1: Development of new chemical entities 1
WG2: Selection of biological targets and assessment of biological data 4
WG3: Development of chemical databases 2
WG4: Development of Computational methods for multiple ligand design and discovery 1