000			a
999			_c15738 _d15738
003			OSt
005			20211224104158.0
008			211224b xxu||||| |||| 00| 0 eng d
040			_aAIKTC-KRRC _cAIKTC-KRRC
100			_915054 _a PANDEY, VANDANA
245			_aCaspase-3 Inhibition Prediction of Pyrrolo[3,4-c] Quinoline-1,3-Diones Derivatives using Computational Tools
250			_aVol.83(3), May-June
260			_aMumbai _bIndian Journal of Pharmaceutical Science _c2021
300			_a504-514p.
520			_aIn the present work, two dimensional quantitative structure activity relationship, molecular docking and absorption, distribution, metabolism, excretion and toxicity analyses were performed to pyrrolo[3,4-c] quinoline-1,3-diones derivatives, previously reported as caspase-3 inhibitors. A total of one hundred fifteen compounds were used to build linear multiple linear regression (multiple linear regression) and non-linear (artificial neural networks) quantitative structure activity relationship models, using genetic algorithm as a feature selection method. Both models were thoroughly validated following Organization for economic cooperation and development principles by internal and external validation as well as the domain of application (antiphase domain). Both Genetic algorithm-multiple linear regression (Rtrain=0.88, Rtest=0.94, mape test=5.3 and rmse test=0.41) and Genetic algorithm-artificial neural network (Rtrain=0.9, Rtest=0.93, mape test=4.5 and rmse test=0.4) models are statistically robust with high external predictive ability. Molecular docking simulations were performed on selected inhibitors revealed that binding energy values are in accordance with inhibitory activity values against caspase-3, which is modulated by hydrogen bondings, Pi stacking and hydrophobic interactions. The docking studies suggest that the inhibitors bind with an allosteric site of the enzyme formed by ARG207B, SER251B, PHE250 and PHE256 of the B chain. Besides, in silico, absorption, distribution, metabolism, excretion and toxicity profiles of selected inhibitors were checked to evaluate the key pharmacokinetic, physiochemical and druglikeness features.
650		0	_94639 _aPHARMACEUTICS
773	0		_dNew Delhi _tIndian journal of pharmaceutical sciences
856			_uhttps://www.ijpsonline.com/articles/caspase3-inhibition-prediction-of-pyrrolo34c-quinoline13diones-derivatives-using-computational-tools.pdf _yClick here
942			_2ddc _cAR