2009
DOI: 10.1002/jcc.21263
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QSPR modeling of enthalpies of formation for organometallic compounds by SMART‐based optimal descriptors

Abstract: A quantitative structure-property relationship (QSPR) model for the prediction of gas-phase enthalpy of formation has been developed, using as chemical information descriptors based on the SMART notation, which is an alternative to SMILES. The model is one-variable equation. The SMART-based descriptors are calculated with correlation weights of SMART attributes which are obtained by the Monte Carlo method. The model addressed organometallic compounds. Statistical characteristics of the model are the following:… Show more

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Cited by 10 publications
(2 citation statements)
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References 23 publications
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“…While the computational estimation of the molecular properties of transition metal compounds can, to some extent, be performed from low dimensionality chemical representations, such as 2D of even line notations, [154][155][156] accessing high accuracy molecular modeling methods requires the creation of 3D models. Therefore, the preparation of initial guess geometries from low dimensionality chemical representations has been a mandatory step since the early stages of molecular modeling, and a number of tools have been developed in response to this need.…”
Section: Introductionmentioning
confidence: 99%
“…While the computational estimation of the molecular properties of transition metal compounds can, to some extent, be performed from low dimensionality chemical representations, such as 2D of even line notations, [154][155][156] accessing high accuracy molecular modeling methods requires the creation of 3D models. Therefore, the preparation of initial guess geometries from low dimensionality chemical representations has been a mandatory step since the early stages of molecular modeling, and a number of tools have been developed in response to this need.…”
Section: Introductionmentioning
confidence: 99%
“…While this operation can be performed with various chemical representations, that may or may not include atomic coordinates, the evaluation of generated candidates and the identification of the most promising candidates may require the complete three-dimensional (3D) molecular structure. In fact, while analysis of two-dimensional (2D) structures, or even string-like chemical representations, , may provide good estimates of some molecular properties, high accuracy of calculated molecular properties in general can only be obtained based on 3D structures. ,, In addition, since automated design tools are likely to arrive at new chemical compounds, for which no experimental structural characterization exists, the 3D models have to be generated on-the-fly.…”
Section: Introductionmentioning
confidence: 99%