Quantum mechanics derived descriptors

The need to reduce the number of variables was recognized at about the same time that quantum mechanically derived descriptors proliferated in QSAR. " An early procedure, designed to eliminate the smallest number... 

Enoch SJ (2010)The use of quantum mechanics derived descriptors in computational toxicology. In Puzyn T et al (ed) Challenges and advances in computational chemistry and physics, vol 8. Springer Science pp 24-27... 

T values are useful descriptors for measuring the electron-donating or -accepting properties of the substituent in aromatic and nonaromatic systems quantum mechanically derived charges or energies can also be used for this... 

VAMP can be used with Tsar to provide quantum mechanically calculated descriptors for QSAR. Apart from molecular properties such as dipole, quadrupole, and octupole moments, ionization potential, electron affinity, polarizability (calculated as a default in VAMP by a variational method), etc., atomic properties such as Coulson-, Mulliken-, or MEP-derived charges, chemical shifts and atomic dipoles and quadrupoles, VAMP can also calculate surface electrostatic descriptors introduced by Politzer, and is useful for QSARs and QSPRs involving intermolecular interactions. Many of these descriptors can be exported directly into Tsar for analysis by classical regression techniques or artificial neural nets. ... 

The MEP at the molecular surface has been used for many QSAR and QSPR applications. Quantum mechanically calculated MEPs are more detailed and accurate at the important areas of the surface than those derived from net atomic charges and are therefore usually preferable [Ij. However, any of the techniques based on MEPs calculated from net atomic charges can be used for full quantum mechanical calculations, and vice versa. The best-known descriptors based on the statistics of the MEP at the molecular surface are those introduced by Murray and Politzer [44]. These were originally formulated for DFT calculations using an isodensity surface. They have also been used very extensively with semi-empirical MO techniques and solvent-accessible surfaces [1, 2]. The charged polar surface area (CPSA) descriptors proposed by Stanton and Jurs [45] are also based on charges derived from semi-empirical MO calculations. 

Breindl et. al. published a model based on semi-empirical quantum mechanical descriptors and back-propagation neural networks [14]. The training data set consisted of 1085 compounds, and 36 descriptors were derived from AMI and PM3 calculations describing electronic and spatial effects. The best results with a standard deviation of 0.41 were obtained with the AMl-based descriptors and a net architecture 16-25-1, corresponding to 451 adjustable parameters and a ratio of 2.17 to the number of input data. For a test data set a standard deviation of 0.53 was reported, which is quite close to the training model. 

A descriptor for the 3D arrangement of atoms in a molceulc can be derived in a similar manner. The Cartesian coordinates of the atoms in a molecule can be calculated by semi-empirical quantum mechanical or molecular mechanics (force field) methods, For larger data sets, fast 3D structure generators are available that combine data- and rule-driven methods to calculate Cartesian coordinates from the connection table of a molecule (e.g., CORINA [10]). 

MolSurf parameters [33] are descriptors derived from quantum mechanical calculations. These descriptors are computed at a surface of constant electron density, with which a very fine description of the properties of a molecule at the Van der Waals surface can be obtained. They describe various electrostatic properties such as hydrogen-bonding strengths and polarizability, as well as Lewis base and acid strengths. MolSurf parameters are computed using the following protocol. 

Recent progress in computational hardware and the development of efficient algorithms have assisted the routine development of molecular quantum-mechanical calculations. New semiempirical methods calculate realistic quantum-chemical molecular quantities in a relatively short computational time frame. Quantum-chemical calculations are thus an attractive source for molecular descriptors that can express all of the electronic and geometric properties of molecules and their interactions. Quantum-chemical methods can be applied to QSARs by direct derivation of electronic descriptors from the molecular wave function. 

Estimation methods for reductive transformations (e.g., dehalogenation or nitro reduction reactions) are limited because it is not yet possible to predict the rates of reductive transformations quantitatively. The choice of appropriate descriptors is complicated by the variability in rate-limiting steps with contaminant structure and environmental conditions. Most QSARs for reduction reactions have been developed as diagnostic tools to determine reduction mechanisms and pathways. So far, only a few of these QSARs provide sufficiently precise predictions and are sufficiently general in scope that they might be useful to predict environmental fate (Tratnyek et al. 2003). They mostly use LFER-type correlations or quantum-chemically derived parameters (e.g., Peijnenburg et al., 1991 Rorije et al., 1995 Scherer et al., 1998 Tratnyek and Macalady, 2000) and many of them are compiled in a recent review by Tratnyek et al. (2003). 

An additional consideration on the choice of descriptor for diversity analyses is the speed with which the descriptor can be calculated since diversity studies are often applied to the huge numbers of compounds (potentially millions) that characterise combinatorial libraries. Thus, some computationally expensive descriptors such as field-based descriptors [28] or descriptors derived from quantum mechanics [29] are not appropriate for diversity studies. 

This chapter provides a tutorial focused on the uses of quantum mechanical descriptors in linear free energy relationships (LFERs). Often, LFERs derived with empirically based (i.e., experimental) descriptors are superior in quality to those derived with quantum mechanical descriptors. However, theoretically based LFERs have some advantages including ease of calculation. The QM... 

The predictive power, robustness, and reliability of the QSAR/QSPR models depend critically on the use of appropriate molecular descriptors. A myriad of descriptors, either empirical or those calculated on the basis of the molecular structure alone ( theoretical descriptors), have been developed both for the predictive and cognitive purposes [1,2]. Many of those descriptors are based directly on the results of quantum-mechanical calculations or can be derived from the electronic wave function or electrostatic field of the molecule. It is the purpose of the present chapter to give an overview of such molecular descriptors, together with some key applications. 

Considering all the above mentioned fundamental nature of the physico-chemical process of protonation and its probable relationship with the quantum mechanical descriptors, we suggest an ansatz for the computation of the proton affinity in terms of these theoretical descriptors. The physico-chemical process and the energetic effect must entail the above stated four parameters. To derive an explicit relation to compute the proton affinity in terms of the above stated descriptors, we suggest... 

A large class of the molecular descriptors can be derived from the results of the quantum mechanical calculations (1996CR1027,2004MI10). The solution of the Schrodinger equation... 

The PSP approach [39-43] is a novel predictive thermodynamic framework, which combines elements from the solubility parameter approach [112,114,116,126] detailed earlier, the solvatochromic/ LSER approach [127-133], and the COSMO-RS theory of solutions [134-136]. It retains the simplicity of the solubility parameter approach, it uses molecular descriptors that can be mapped one to one to the Abraham/LSER descriptors, and these descriptors are derived from the moments of the a-profiles of the quantum mechanics-based COSMO-RS model. Because of this combination, the PSP approach has a broader range of applications compared to each of the earlier three... 

Eventually, we proposed an our own index based on the SF descriptor (SFLAI, Source Function Local Aromaticity Index) for quantifying the degree of aromaticity of 6-membered rings (6MRs) in polycyclic systems. Analogously to the SF analysis of electron delocalization, such an index might prove to be particularly useful for application to experimentally-derived ED s, as, at variance with other commonly employed quantum-mechanical (local) aromaticity descriptors, it does not require the knowledge of the pair density. 

We have launched a search of identifying the preferred site of attack by the bio-molecules (bacteria) on the mesoionic derivatives. We have also tried to predict the nature of the reaction that will be preferred by the biologically active mesoionic compounds molecules while attaching with the biomolecules in terms of local quantum mechanical descriptors. Thus we hopefully predict the reactive site in the mesoionic heterocycles and also the mechanism of the reaction that will be preferred by these compounds while entering into reaction with the biomolecules. 

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