Publications 2014

  1. Chilmończyk, Z.; Bojarski, A. J.; Sylte, I. Ligand-directed trafficking of receptor stimulus. Pharmacol Rep 2014, 66, 1011-1021 (http://www.ncbi.nlm.nih.gov/pubmed/25443729)
  2. Salerno, L.; Pittalà, V.; Modica, M. N.; Siracusa, M. A.; Intagliata, S.; Cagnotto, A.; Salmona, M.; Kurczab, R.; Bojarski, A. J.; Romeo, G. Structure-activity relationships and molecular modeling studies of novel arylpiperazinylalkyl 2-benzoxazolones and 2-benzothiazolones as 5-HT7 and 5-HT1A receptor ligands. Eur J Med Chem 201485, 716-726 (http://www.ncbi.nlm.nih.gov/pubmed/25128671)
  3. Waszkielewicz, A. M.; Pytka, K.; Rapacz, A.; Wełna, E.; Jarzyna, M.; Satała, G.; Bojarski, A. J. ; Sapa, J.; Zmudzki, P.; Filipek, B.; Marona, H. Synthesis and Evaluation of Antidepressant-like activity of some 4-substituted 1-(2-methoxyphenyl)piperazine derivatives. Chem. Biol. Drug Des. 2014, Epub ahead of print (http://www.ncbi.nlm.nih.gov/pubmed/25048712)
  4. Śmieja, M.; Warszycki, D.; Tabor, J.; Bojarski A. J. Asymmetric clustering index in a case study of 5-HT1A receptor ligands. PLoS One 20149, e102069 (http://www.ncbi.nlm.nih.gov/pubmed/25019251)
  5. Zajdel, P.; Partyka, A.; Marciniec, K.; Bojarski, A. J.; Pawlowski, M.; Wesolowska, A. Quinoline- and isoquinoline-sulfonamide analogs of aripiprazole: novel antipsychotic agents? Future. Med. Chem. 2014, 6, 57-75 (http://www.ncbi.nlm.nih.gov/pubmed/24358948).
  6. Witek, J.; Smusz, S.; Rataj, K.; Mordalski, S.; Bojarski, A. J. An application of machine learning methods to structural interaction fingerprints–a case study of kinase inhibitors. Bioorg. Med. Chem. Lett.  2014, 24, 580-585 (http://www.ncbi.nlm.nih.gov/pubmed/24374279)
  7. Sagnes, C.; Fournet, G.; Satala, G.; Bojarski, A. J. ; Joseph, B. New 1-arylindoles based serotonin 5-HT antagonists. Synthesis and binding evaluation studies. Eur. J. Med. Chem. 2014, 75C, 159-168 (http://www.ncbi.nlm.nih.gov/pubmed/24531229)
  8. Gabrielsen, M.; Kurczab, R.; Siwek, A.; Wolak, M.; Ravna, A. W.; Kristiansen, K.; Kufareva, I.; Abagyan, R.; Nowak, G.; Chilmonczyk, Z.; Sylte, I.; Bojarski, A. J. Identification of novel serotonin transporter compounds by virtual screening. J. Chem. Inf. Model. 2014, 54, 933-944 (http://www.ncbi.nlm.nih.gov/pubmed/24521202)
  9. Canale, V.; Guzik, P.; Kurczab, R.; Verdie, P.; Satala, G.; Kubica, B.; Pawlowski, M.; Martinez, J.; Subra, G.; Bojarski, A. J.; Zajdel, P. Solid-supported synthesis, molecular modeling, and biological activity of long-chain arylpiperazine derivatives with cyclic amino acid amide fragments as 5-HT and 5-HT receptor ligands. Eur. J Med. Chem. 2014, 78, 10-22 (http://www.ncbi.nlm.nih.gov/pubmed/24675176)
  10. Handzlik, J.; Bojarski, A. J.; Satala, G.; Kubacka, M. ; Sadek, B.; Ashoor, A.; Siwek, A.; Wiecek, M.; Kucwaj, K.; Filipek, B.; Kiec-Kononowicz, K. SAR-studies on the importance of aromatic ring topologies in search for selective 5-HT(7) receptor ligands among phenylpiperazine hydantoin derivatives. Eur. J Med. Chem. 2014, 78, 324-339 (http://www.ncbi.nlm.nih.gov/pubmed/24691057)
  11. Chłoń-Rzepa, G.; Zmudzki, P.; Pawlowski, M.; Wesolowska, A.; Satala, G.; Bojarski, A. J.; Jabłoński, M.; Kalinowska-Tłuścik, J. New 7-arylpiperazinylalkyl-8-morpholin-4-yl-purine-2, 6-dione derivatives with anxiolytic activity–Synthesis, crystal structure and structure–activity study. J. Mol. Struc. 2014, 1067, 243-251 (http://www.sciencedirect.com/science/article/pii/S0022286014002865)
  12. Marciniec, K.; Latocha, M.; Boryczka, S.; Kurczab, R. Synthesis, molecular docking study, and evaluation of the antiproliferative action of a new group of propargylthio- and propargylselenoquinolines. Med. Chem. Res. 2014, 23, 3468-3477 (http://link.springer.com/article/10.1007%2Fs00044-014-0922-3)
  13. Kurczab, R.; Smusz, S. ; Bojarski, A. J. The influence of negative training set size on machine learning-based virtual screening. J. Cheminform. 2014, 6:32, 1-9 (http://www.ncbi.nlm.nih.gov/pubmed/24976867)
  14. Rataj, K.; Witek, J.; Mordalski, S.; Kosciolek, T.; Bojarski, A. J. Impact of template choice on homology model efficiency in virtual screening. J. Chem. Inf. Model. 2014, 54, 1661-1668 (http://www.ncbi.nlm.nih.gov/pubmed/24813470)