4D-QSAR Studies Using a New Descriptor of the Klopman Index: Antibacterial Activities of Sulfone Derivatives Containing 1, 3, 4-Oxadiazole Moiety Based on MCET Model

Abstract

In the 4D-QSAR study, nonparametric regression analysis was used to determine the adjustable constants. Using the leave One Out Cross-Validation (LOO-CV), antibacterial activities (pEC50-μM) were predicted as r loo-cv (q) = 0.979, r pred (r) = 0.911, respectively, for 27 training sets and 9 test set compounds. Also, the rm (overall) value, which indicates the closeness between the predicted and corresponding observed data, was calculated to be 0.957. The model obtained by the Molecular Conformer Electron Topological (MCET) method was compared with the q loo-cv and R non-cv values determined by the CoMFA and CoMSIA methods and more satisfactory results were obtained.

Comparison of the performance of different “local reactive descriptors” in 3D-QSAR analysis of enantioselective molecules

“…The calculation of the activity is given with the following Eq. ( 2) used in our previous study [34]: 3). In addition, the total electrostatic and covalent interactions of the positions in the P-number are calculated by Eqs.…”

“…The Klopman-Salem equation was originally given to explain the Hard-Soft Acid-Base (HSAB) [38] interactions in chemical reactions in more detail [30][31][32][33]. Klopman index was introduced and used for the first time as a new LRD to explain the interactions between L-R [34,39]. With this simplified descriptor, hard and soft interactions are considered simultaneously:…”

“…In the MCET software, we developed for 3D-QSAR research, each other different LRDs can be used in which atomic charge and frontier orbital coefficients are handled separately or both. Among them, the "Klopman index," which we introduced to the literature as a new LRD [34], is the most effective, and it was applied on 31 steroid compounds [35] to be compared with other LRDs in this study.…”

4D-QSAR Analysis of Some New Pyrrole Derivatives Using Klopman Index Descriptor

“… The equation is created based on the nonlinear interaction between L-R and the parameters on the receptor side are calculated with the Levenberg-Marquardt algorithm using LRDs at the interaction points of the ligand sides (Guzel et al, 2018). The model with the best statistical result is predicted by using the LRDs in the training set and the calculated parameters, with the LOO-CV method.…”

“…In MCET, a type of electronic property of atoms is selected, and the parameters of the receptor side belonging to the pharmacophore region are determined (Turkmenoglu et al, 2017;Yilmaz et al, 2011;Yilmaz et al, 2014). Among these, the "Klopman Index", which we have newly introduced to the literature, is a quite important descriptor (Guzel et al, 2018;Kizilcan et al, 2020;Tokat et al, 2019;Turkmenoglu and Guzel, 2018). The difference and superiority of this descriptor from others; it uses both atomic charge and frontier orbital (HOMO / LUMO) coefficients for each atom at the same time.…”