S
Svetoslav Slavov
Researcher at Food and Drug Administration
Publications - 42
Citations - 1455
Svetoslav Slavov is an academic researcher from Food and Drug Administration. The author has contributed to research in topics: Quantitative structure–activity relationship & Toxicophore. The author has an hindex of 16, co-authored 41 publications receiving 1267 citations. Previous affiliations of Svetoslav Slavov include Tallinn University of Technology & University of Tartu.
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Journal ArticleDOI
Quantitative Correlation of Physical and Chemical Properties with Chemical Structure: Utility for Prediction
Alan R. Katritzky,Minati Kuanar,Svetoslav Slavov,C. Dennis Hall,Mati Karelson,Iiris Kahn,Dimitar A. Dobchev +6 more
Journal ArticleDOI
CERAPP: Collaborative Estrogen Receptor Activity Prediction Project
Kamel Mansouri,Ahmed Abdelaziz,Aleksandra Rybacka,Alessandra Roncaglioni,Alexander Tropsha,Alexandre Varnek,Alexey V. Zakharov,Andrew Worth,Ann M. Richard,Christopher M. Grulke,Daniela Trisciuzzi,Denis Fourches,Dragos Horvath,Emilio Benfenati,Eugene N. Muratov,Eva Bay Wedebye,Francesca Grisoni,Giuseppe Felice Mangiatordi,Giuseppina M. Incisivo,Huixiao Hong,Hui W. Ng,Igor V. Tetko,Ilya A. Balabin,Jayaram Kancherla,Jie Shen,Julien Burton,Marc C. Nicklaus,Matteo Cassotti,Nikolai Georgiev Nikolov,Orazio Nicolotti,Patrik L. Andersson,Qingda Zang,Regina Politi,Richard D. Beger,Roberto Todeschini,Ruili Huang,Sherif Farag,Sine Abildgaard Rosenberg,Svetoslav Slavov,Xin Hu,Richard S. Judson +40 more
TL;DR: This project demonstrated the possibility to screen large libraries of chemicals using a consensus of different in silico approaches and the efficacy of using predictive computational models trained on high-throughput screening data to evaluate thousands of chemicals for ER-related activity and prioritize them for further testing.
Journal ArticleDOI
Synthesis and bioassay of improved mosquito repellents predicted from chemical structure.
Alan R. Katritzky,Zuoquan Wang,Svetoslav Slavov,Maia Tsikolia,Dimitar A. Dobchev,Novruz G. Akhmedov,C. Dennis Hall,Ulrich R. Bernier,Gary G. Clark,Kenneth J. Linthicum +9 more
TL;DR: Mosquito repellency data on acylpiperidines derived from the U.S. Department of Agriculture archives were modeled by using molecular descriptors calculated by CODESSA PRO software and a artificial neural network model was developed to predict the repellent activity of novel compounds of similar structures.
Journal ArticleDOI
Correlation of blood–brain penetration using structural descriptors
Alan R. Katritzky,Minati Kuanar,Svetoslav Slavov,Svetoslav Slavov,Dimitar A. Dobchev,Dimitar A. Dobchev,Dan C. Fara,Mati Karelson,Mati Karelson,William E. Acree,Vitaly P. Solov'ev,Alexandre Varnek +11 more
TL;DR: Experimental blood-brain partition coefficients (logBB) for a diverse set of 113 drug molecules are correlated with computed structural descriptors using CODESSA-PRO and ISIDA programs to give statistically significant QSAR models based respectively, on molecular and on fragment descriptors.