Lee, Ji Young Doddareddy, Munikumar Reddy Cho, Yong Seo Choo, Hyunah Koh, Hun Yeong Kang, Jae-Hoon No, Kyoung Tai Pae, Ae Nim 2024-01-21T01:03:30Z 2024-01-21T01:03:30Z 2021-09-02 2007-05 1610-2940 https://pubs.kist.re.kr/handle/201004/134419 Comparative quantitative structure-activity relationship (QSAR) analyses of peptide deformylase (PDF) inhibitors were performed with a series of previously published (British Biotech Pharmaceuticals, Oxford, UK) reverse hydroxamate derivatives having antibacterial activity against Escherichia coli PDF, using 2D and 3D QSAR methods, comparative molecular field analysis (CoMFA), comparative molecular similarity indices analysis (CoMSIA), and hologram QSAR (HQSAR). Statistically reliable models with good predictive power were generated from all three methods (CoMFA r(2) = 0.957, q(2) = 0.569; CoMSIA r(2) = 0.924, q(2) = 0.520; HQSAR r(2) = 0.860, q(2) = 0.578). The predictive capability of these models was validated by a set of compounds that were not included in the training set. The models based on CoMFA and CoMSIA gave satisfactory predictive r(2) values of 0.687 and 0.505, respectively. The model derived from the HQSAR method showed a low predictability of 0.178 for the test set. In this study, 3D prediction models showed better predictive power than 2D models for the test set. This might be because 3D information is more important in the case of datasets containing compounds with similar skeletons. Superimposition of CoMFA contour maps in the active site of the PDF crystal structure showed a meaningful correlation between receptor-ligand binding and biological activity. The final QSAR models, along with information gathered from 3D contour and 2D contribution maps, could be useful for the design of novel active inhibitors of PDF. English SPRINGER ATOMIC PHYSICOCHEMICAL PARAMETERS DIRECTED QUANTITATIVE STRUCTURE MOLECULAR SIMILARITY INDEXES ANTIBACTERIAL ACTIVITY BB-3497 ACTINONIN IDENTIFICATION VALIDATION BINDING IRON Comparative QSAR studies on peptide deformylase inhibitors Article 10.1007/s00894-007-0175-x 1 JOURNAL OF MOLECULAR MODELING, v.13, no.5, pp.543 - 558 JOURNAL OF MOLECULAR MODELING 13 5 543 558 scie scopus 000246098500001 2-s2.0-34247592542 Biochemistry & Molecular Biology Biophysics Chemistry, Multidisciplinary Computer Science, Interdisciplinary Applications Biochemistry & Molecular Biology Biophysics Chemistry Computer Science Article ATOMIC PHYSICOCHEMICAL PARAMETERS DIRECTED QUANTITATIVE STRUCTURE MOLECULAR SIMILARITY INDEXES ANTIBACTERIAL ACTIVITY BB-3497 ACTINONIN IDENTIFICATION VALIDATION BINDING IRON PDF QSAR CoMFA CoMSIA HQSAR