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Ivanka Tsakovska
Researcher at Bulgarian Academy of Sciences
Publications - 63
Citations - 1167
Ivanka Tsakovska is an academic researcher from Bulgarian Academy of Sciences. The author has contributed to research in topics: Chemistry & Medicine. The author has an hindex of 16, co-authored 52 publications receiving 906 citations.
Papers
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Journal ArticleDOI
Cytotoxicity and Microbicidal Activity of Commonly Used Organic Solvents: A Comparative Study and Application to a Standardized Extract from Vaccinium macrocarpon.
Yana Ilieva,Lyudmila Dimitrova,Maya M. Zaharieva,Mila Kaleva,Petko Alov,Ivanka Tsakovska,Tania Pencheva,Ivanka Pencheva-El Tibi,Hristo Najdenski,Ilza Pajeva +9 more
TL;DR: In this paper, the cytotoxicity and microbicidal capacity of seven organic solvents commonly applied for studying plant extracts and bioactive compounds were systematically investigated based on international standards.
Journal ArticleDOI
Molecular determinants of PPARγ partial agonism and related in silico/in vivo studies of natural saponins as potential type 2 diabetes modulators.
Merilin Al Sharif,Petko Alov,Antonia Diukendjieva,Vessela Vitcheva,Rumyana Simeonova,Ilina Krasteva,Aleksandar Shkondrov,Ivanka Tsakovska,Ilza Pajeva +8 more
TL;DR: In silico studies, strongly suggest possible involvement of PPARγ-mediated mechanisms in the in vivo antidiabetic and antioxidant effects of PSM from A. corniculatus Bieb.
Book ChapterDOI
InterCriteria Analysis Implementation for Exploration of the Performance of Various Docking Scoring Functions
Ivanka Tsakovska,Petko Alov,Nikolay Ikonomov,Vassia Atanassova,Peter Vassilev,Olympia Roeva,Dessislava Jereva,Krassimir T. Atanassov,Ilza Pajeva,Tania Pencheva +9 more
TL;DR: New software capabilities, implemented in order to apply ICrA to in silico drug design, are presented and a case study of InterCriteria Analysis is implemented to explore the performance of various scoring functions in docking.
Journal ArticleDOI
Molecular Modeling of P-Glycoprotein and Related Drugs
TL;DR: This paper summarizes the results from molecular modeling of various multidrug resistance (MDR) modulators and the MDR protein P-glycoprotein (P-gp) and highly predictive 3D-QSAR models obtained that can be used for anti-MDR activity prediction.
Journal ArticleDOI
QSAR and 3D QSAR of inhibitors of the epidermal growth factor receptor
TL;DR: This article reports quantitative structure–activity relationships (QSAR) and 3D QSAR models of 134 structurally diverse inhibitors of the epidermal growth factor receptor (EGFR) tyrosine kinase to show consistent results.