QSAR of antimycobacterial activity of benzoxazoles by optimal SMILES-based descriptors

Nesmerak K., Toropov A. A., Toropova A. P., ERTAN BOLELLİ T., YILDIZ İ.

MEDICINAL CHEMISTRY RESEARCH, cilt.26, sa.12, ss.3203-3208, 2017 (SCI-Expanded) identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 26 Sayı: 12
  • Basım Tarihi: 2017
  • Doi Numarası: 10.1007/s00044-017-2013-8
  • Dergi Adı: MEDICINAL CHEMISTRY RESEARCH
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Sayfa Sayıları: ss.3203-3208
  • Anahtar Kelimeler: QSAR, Antimycobacterial activity, Benzoxazoles, CORAL software, SMILES, MONTE-CARLO METHOD, ACETYLCHOLINE ESTERASE INHIBITORS, MOLECULAR-STRUCTURE, MYASTHENIA-GRAVIS, ORGANIC-COMPOUNDS, CORAL, MODEL, DERIVATIVES, DESIGN, AGENTS
  • Ankara Üniversitesi Adresli: Evet

Özet

The CORAL software based on the optimal descriptors calculated with simplified molecular input-line entry system was used to build up quantitatively structure-activity relationship for the minimal inhibition concentrations against (i) Mycobacterium tuberculosis H37RV ATCC 27294 and (ii) M. tuberculosis drug resistant clinical isolate. The predictive potential of these models has been checked up with three random splits into the training, calibration, and validation sets. Although all models are quantitative, it has been found that splitting have apparent influence on the statistical quality of these models. Thus, the thesis "QSAR is a random event" is confirmed in this work.