![Sample our Environment & Agriculture journals, sign in here to start your access, latest two full volumes FREE to you for 14 days]({"type":"image" , "src" : "/sda/5934/TOC-Subject-Sample-2021-Environment-Agriculture.jpg"})
Abstract
CORAL software has been used to build quantitative structure–activity relationships (QSARs) for the prediction of binding affinities (pEC50, i.e., minus decimal logarithm of the 50% effective concentration) of 35 potent inhibitors towards the voltage-gated potassium channel subunit Kv7.2. The pEC50 has been modelled using eight random splits, with the following representations of the molecular structure: (i) hydrogen-suppressed graph (HSG); (ii) simplified molecular input line entry system (SMILES); (iii) graph atomic orbitals (GAOs) and (iv) hybrid representation, which is HSG together with SMILES. These models have been examined using three methods, the classic scheme, balance correlation, and balance correlation with ideal slope. The QSAR model based on single optimal descriptors using SMILES provided the best accuracy for the prediction of the pEC50. The robustness of these models has been checked using parameters such as rm2, r*m2, , and using a randomization technique. The best QSAR model based on single optimal descriptors has been applied to study the in vitro structure–activity relationships of pyrazolo[1,5-a]pyrimidin-7(4H)-one derivatives as Kv7.2 modulators. The pEC50 is found to be significantly increased by the incorporation of –OH, –NO2 or –Br groups in place of one –F, whereas –NH2 has a negative effect on the pEC50 values.
Acknowledgements
The author wishes to express his gratitude to the Honourable Vice-Chancellor of Siksha ‘O’ Anusandhan University, Bhubaneswar, for extending the facility at the Centre of Excellence in Theoretical and Mathematical Sciences to conduct the present research. The author is also grateful to the authorities of the Institute of Technical Education and Research (ITER, Bhubaneswar) for their support and encouragement.