Reliable prediction of lipophilicity in organic compounds involves molecular descriptors determination. In this work, the lipophilicity of a set of twenty-three molecules has been determined using up to eleven quantum...Reliable prediction of lipophilicity in organic compounds involves molecular descriptors determination. In this work, the lipophilicity of a set of twenty-three molecules has been determined using up to eleven quantum various descriptors calculated by means of quantum chemistry methods. According to Quantitative Structure Property Relationship (QSPR) methods, a first set of fourteen molecules was used as training set whereas a second set of nine molecules was used as test set. Calculations made at AM1 and HF/6-311++G theories levels have led to establish a QSPR relation able to predict molecular lipophilicity with over 95% confidence.展开更多
The reactivity parameters,Q and e,in the Q-e scheme reflect the reactivities of a monomer(or a radical)in free-radical copolymerizations.By applying multiple linear regression(MLR)analysis,the optimal quantitative str...The reactivity parameters,Q and e,in the Q-e scheme reflect the reactivities of a monomer(or a radical)in free-radical copolymerizations.By applying multiple linear regression(MLR)analysis,the optimal quantitative structure-activity relationship(QSAR)model for the reactivity parameter lnQ was developed based on five descriptors(NAF,NOF,EαLUMO,EβHOMO,and EβLUMO)and 69 monomers with the root mean square(rms)error of 0.61.The optimal MLR model of the parameter e obtained from five descriptors(TOcl,NpN,NSO,EαHOMO and DH)and 68 monomers produced rms error of 0.42.Compared with previous models,the two optimal MLR models in this paper show satisfactory statistical characteristics.The feasibility of combining 2D descriptors obtained from the monomers and 3D descriptors calculated from the radical structures(formed from monomers+H )to predict parameters Q and e has been demonstrated.展开更多
基金supported by the National Key Research Program of China (2022YFA1503101)the National Natural Science Foundation of China (22173067)+3 种基金the Science and Technology Development Fund, Macao SAR (FDCT, 0024/2022/ITP)the Collaborative Innovation Center of Suzhou Nano Science & Technology, Priority Academic Program Development of Jiangsu Higher Education Institutions (PAPD)the 111 Projectthe Joint International Research Laboratory of Carbon-Based Functional Materials and Devices。
文摘Reliable prediction of lipophilicity in organic compounds involves molecular descriptors determination. In this work, the lipophilicity of a set of twenty-three molecules has been determined using up to eleven quantum various descriptors calculated by means of quantum chemistry methods. According to Quantitative Structure Property Relationship (QSPR) methods, a first set of fourteen molecules was used as training set whereas a second set of nine molecules was used as test set. Calculations made at AM1 and HF/6-311++G theories levels have led to establish a QSPR relation able to predict molecular lipophilicity with over 95% confidence.
基金supported by the National Natural Science Foundation of China(No.21472040)the Scientific Research Fund of Hunan Education Department(Nos.16A047 and 18A344)the Open Project Program of Hunan Provincial Key Laboratory of Environmental Catalysis & Waste Regeneration(Hunan Institute of Engineering)(2018KF11)
文摘The reactivity parameters,Q and e,in the Q-e scheme reflect the reactivities of a monomer(or a radical)in free-radical copolymerizations.By applying multiple linear regression(MLR)analysis,the optimal quantitative structure-activity relationship(QSAR)model for the reactivity parameter lnQ was developed based on five descriptors(NAF,NOF,EαLUMO,EβHOMO,and EβLUMO)and 69 monomers with the root mean square(rms)error of 0.61.The optimal MLR model of the parameter e obtained from five descriptors(TOcl,NpN,NSO,EαHOMO and DH)and 68 monomers produced rms error of 0.42.Compared with previous models,the two optimal MLR models in this paper show satisfactory statistical characteristics.The feasibility of combining 2D descriptors obtained from the monomers and 3D descriptors calculated from the radical structures(formed from monomers+H )to predict parameters Q and e has been demonstrated.
