Comprehensive DEscriptors for Structural

CODESSA (we tested Version 2.6) stands for comprehensive descriptors for structural and statistical analysis. It is a conventional QSAR/QSPR program. 

Katritzky, A.R., Karelson, M., Petrukhin, R. 1994. The CODESS A PRO project Comprehensive descriptors for structural and statistical analysis. http //www.codessa-pro.com/manual/manual.htm. 

A.R. Katritzky et al., CODESSA PRO. Comprehensive DEscriptors for Structural and Statistical Analysis, University of Florida, USA, 2001-2005. http //www.codessa-pro.com. Accessed June 2007... 

Comprehensive DEscriptors for Structural and Statistical Analysis Comparative Molecular Field Analysis... 

We have evaluated three different techniques to generate QSAR models, namely Comparative Molecular Field Analysis (CoMFA), Comprehensive Descriptors for Structural and Statistical Analysis (CODESSA), and Hologram QSAR (HQSAR). More specifically they were evaluated for their utility (predictivity, speed, accuracy, and reproducibility) to predict ER binding activity quantitatively (Tong et al., 1998 Shi et al., 2001). Common to the three QSAR methods is the... 

The aforementioned macroscopic physical constants of solvents have usually been determined experimentally. However, various attempts have been made to calculate bulk properties of Hquids from pure theory. By means of quantum chemical methods, it is possible to calculate some thermodynamic properties e.g. molar heat capacities and viscosities) of simple molecular Hquids without specific solvent/solvent interactions [207]. A quantitative structure-property relationship treatment of normal boiling points, using the so-called CODESS A technique i.e. comprehensive descriptors for structural and statistical analysis), leads to a four-parameter equation with physically significant molecular descriptors, allowing rather accurate predictions of the normal boiling points of structurally diverse organic liquids [208]. Based solely on the molecular structure of solvent molecules, a non-empirical solvent polarity index, called the first-order valence molecular connectivity index, has been proposed [137]. These purely calculated solvent polarity parameters correlate fairly well with some corresponding physical properties of the solvents [137]. 

By a quantitative structure-property relationship (QSPR) analysis of a total of 45 different empirical solvent scales and 350 solvents, the direct calculation of predicted values of solvent parameters for any scale and for any previously unmeasured solvent was possible using the CODESS A program [ie. comprehensive descriptors for structural and statistical analysis) developed by Katritzky et al. [244]. The QSPR models for each of the solvent scales were constructed using only theoretical descriptors, derived solely from the molecular solvent structure. This QSPR study enabled classification of the various solvent polarity scales and ultimately allowed a unified PCA treatment of these scales. This PCA treatment, carried out with 40 solvent scales as variables (each having 40 data points for 40 solvents as objects), allowed a rational classification and grouping... 

CODESSA comprehensive descriptors for structural and statistical analysis... 

Katritzky, A.R., Lobanov, V.S., Karelson, M, Murugan, R., Grendze, M.P. and Toomey, J.E.Jr. (1996a). Comprehensive Descriptors for Structural and Statistical Analysis. 1. Correlations Between Structure and Physical Properties of Substituted Pyridines. Rev.Roum.Chim., 41, 851-867. 

Among the several CODESSA descriptors, implemented in the homonymous software CODESSA (Comprehensive DEscriptors for Structural and Statistical Analysis) [Katritzky and Gordeeva, 1993 CODESSA- Katritzky, Lobanov et al., 1996 Katritzky, Lobanov et al, 1996], are molecular weight, molecular volume, —> count descriptors, —> topological indices, charge descriptors, shadow indices, charged partial surface area descriptors, quantum-chemical descriptors, and —> electric polarization descriptors. 

The development of QSAR/QSPR on large descriptor spaces started some time ago. One of the first widely applicable programs for such modeling was CODESSA (Comprehensive DEscriptors for Structural and Statistical Analysis), developed by one of us (M.K.) and Victor Lobanov, a graduate student at that time, in collaboration with Professor Alan R. Katritzky at the University of Florida. In 1994, the first version of the program was published and assessed for the treatment of a variety of chemical and physical properties of compounds and heterocyclic compounds, in particular (1995CSR279, 1997JCICS405). 

Other recently published correlative methods for predicting Tg include the group interaction modeling (GIM) approach of Porter (42), neural networks (43-45), genetic function algorithms (46), the CODESSA (acronym for Comprehensive Descriptors for Structural and Statistical Analysis ) method (47), the energy, volume, mass (EVM) approach (48,49), correlation to the results of semiempirical quantum mechanical calculations of the electronic structure of the monomer (50), and a method that combines a thermodynamic equation-of-state based on lattice fluid theory with group contributions (51). 

CODESSA (Comprehensive Descriptors for Structures and Statistical Analysis) reports most of the descriptors designed by A. R. Katritzky, V. Lobanov, and M. Karelson (Eds.), University of Florida, Gainesville, EL, 1995. 

There have been anumber of books and reviews on topological indices, and we will mention only three books Topological Indices and Related Descriptors in QSAR and QSPR, edited by Devillers and Balaban [23] the already mentioned Comprehensive Descriptors for Structures and Statistical Analysis (CODESSA) by Katritsky et al. [8,9] and Molecular Descriptors for Chemoinformatics by Todeschini and Consonni [24,25]. For introductory information on mathematical molecular descriptors, one may consult a chapter on topological indices in The Encyclopedia of Computational Chemistry [26]. Instead of elaborating on specific molecular descriptors, we have summarized in Table 6.3 the numerous areas of physical chemistry and chemistry in general in which topological indices have found useful applications. 

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