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Geometry-Corrected Quadratic Optimization Algorithm for NDDO-Descendant Semiempirical Models
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DOI：10.1021/acs.jctc.4c01070.png)
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摘要
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The long-held assumption that the optimization of parameters for NDDO-descendant semiempirical methods may be performed without precise geometry optimization is assessed in detail; the relevant equations for the analytical evaluation of the geometry-corrected derivatives of molecular properties that account for changes in the optimum geometry are then presented. The first and second derivatives calculated from our implementation of MNDO are used for a limited reparameterization of 1,113 CHNO molecules taken from the PM7 training set, demonstrating an improvement over the PARAM program used in the optimization of parameters for the PMx methods.
Keyword:
PARAMETERS
MNDO
APPROXIMATIONS
AM1
EXTENSION
DERIVATIVES
PM3
期刊
IF:
5.5
论文数:
1.1W
被引数:
5.4W
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