Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: The enantioselective ring-opening catalyzed by epoxide hydrolases originating from seven different sources of a series of 2,2-disubstituted oxiranes containing alkyl chains of different lengths, unsaturated (alkenyl, alkinyl) and aromatic groups as ll as electronegative heteroatoms at various positions within the side chain was analyzed by quantitative structure-activity relationships. Models for the enantioselectivity re derived with the aid of multiple linear regression analysis (MLR) using several steric and electronic (quantum chemical) descriptors. On the basis of the models derived by MLR nonlinear modeling with artificial neural networks (ANN) was also done. Good predictive performance was observed for both modeling approaches. The models also indicate that different steric and/or electronic features account for the enantioselectivities observed for the individual epoxide hydrolases.
['Simona Funar-Timofei', 'Takahiro Suzuki', 'Joachim Paier', 'Andreas Steinreiber', 'Kurt Faber', 'Walter M. F. Fabian']
I am writing a research paper on a idea Quantitative structure-activity relationships for the enantioselectivity of oxirane ring-opening catalyzed by epoxide hydrolases.
[{"from": "human", "value": "I am writing a research paper on a idea Quantitative structure-activity relationships for the enantioselectivity of oxirane ring-opening catalyzed by epoxide hydrolases."}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: The enantioselective ring-opening catalyzed by epoxide hydrolases originating from seven different sources of a series of 2,2-disubstituted oxiranes containing alkyl chains of different lengths, unsaturated (alkenyl, alkinyl) and aromatic groups as ll as electronegative heteroatoms at various positions within the side chain was analyzed by quantitative structure-activity relationships. Models for the enantioselectivity re derived with the aid of multiple linear regression analysis (MLR) using several steric and electronic (quantum chemical) descriptors. On the basis of the models derived by MLR nonlinear modeling with artificial neural networks (ANN) was also done. Good predictive performance was observed for both modeling approaches. The models also indicate that different steric and/or electronic features account for the enantioselectivities observed for the individual epoxide hydrolases."}]