Prediction of Molecular Properties

Fundamental challenges in computational chemistry include the high computational cost of ab initio calculations in terms of time, memory, and disk space requirements difficulties that arise when standard advanced computational treatments are used to describe processes such as bond breaking determination of the best approach toward functional development in density functional theorgy, understanding the means for quantitative prediction of thermonuclear kinetics and computational chemistry treatment of transition metal systems for reliable prediction of molecular properties. This book addresses these important problems, featuring chapters by leading computational chemists and physicists. 

F. Neese, Prediction of molecular properties and molecular spectroscopy with density functional theory From fundamental theory to exchange-coupling, Coord. Chem. Rev., 253 (2009) 526-563. 

Theoretical investigations enable analysis and prediction of molecular properties when molecules are interacting with a structured environment. For this research area it is important to understand the relationship between the molecular structure, structured environments and molecular properties [2-4,32-44],... 

Studies, J. Devillers and W. Karcher, Eds., Kluwer, Dordrecht, The Netherlands, 1991, pp. 247-279. The Use of Similarity and Clustering Techniques for the Prediction of Molecular Properties. 

Such a consensus approach is reminiscent of what some computational chemists were doing in the the 1970s and 1980s when they were treating each molecule by not one, but several available semiempirical and ab initio molecular orbital methods, each of which gave different—and less than perfect—predictions of molecular properties. 

This perspective has examined the approaches to molecular modeling and drug design and emphasized their limitations. The reader should be aware, however, that these tools are daily used on many problems of therapeutic interest with increasing success. This is clearly witnessed by publications of such studies in almost every issue of current major journals. For specific application areas, such as RNA (490, 491), DNA (492-496), membrane (497-507), or peptidomimetic modeling (382, 508-513), the reader is referred to the literature. The prediction of molecular properties, such as log P and correlation between substructures and metabolism, has led to a dramatic increase in efforts to correlate adsorption, distribution (514), metabolism (515-617), and elimination (ADME) with chemical... 

Since its introduction into quantum chemistry in the late 1960s by Qzek and Paldus, " coupled cluster theory has emerged as perhaps the most reliable, yet computationally affordable method for the approximate solution of the electronic Schrodinger equation and the prediction of molecular properties. The purpose of this chapter is to provide computational chemists who seek a deeper knowledge of coupled cluster theory with the background necessary to understand the extensive literature on this important ab initio technique. 

Todeschini, R., Moro, G., Boggia, R., Bonati, L., Cosentino, U., Lasagni, M. and Pitea, D. (1997a). Modeling and Prediction of Molecular Properties. Theory of Grid-Weighted Holistic Invariant Molecular (G-WHIM) Descriptors. Chemom.Intell.Lab.Syst., 36,65-73. 

Bravi, G. Wikel, J.H. Application of MS-WHIM Descriptors 3. Prediction of Molecular Properties, Quant. Struct.-Act. Relat. 19, 39-49 (2000). 

These qualitative predictions are clearly too simple but they provide a useful zeroth-order model of the electronic structure. For example, the model predicts values for the spin-rotation parameters in the A, B, and C states of CaNH2 that are in reasonable agreement with experiment [53]. The qualitative predictions of molecular properties can also be compared with the results of ab initio calculations. The first calculations on CaNH2 [54] and related molecules such as CaBH4 were made by Ortiz... 

EHT (extended Hiickel theory) was developed by Wolfsberg and Helmholz (1952) and used widely by Hoffmann (1963) [13] to provide qualitative insights into chemical bonding, particularly for inorganic compounds. In EHT, all valence orbitals (both rr and o) are included in the molecular orbitals it is not restricted to the 7T system. This method, however, still gives poor prediction of molecular properties such as dipole moments and rotational barriers. 

In the past decade, a shift of emphasis in 1,2,3-triazine chemistry is to be noted from preparative to theoretical work. Interest in theoretical predictions of molecular properties of the parent 1 was evident from the literature over the past 40 years and has increased recently. On the other hand, benzotriazinones of type 3 receive attention primarily for the biological activity of many derivatives, and the 3-hydroxy derivative serves as a basis for active esters as coupling reagents in peptide synthesis. Via ring-chain tautomerism, 4-hydroxy-3,4-dihydrobenzotriazines derived from 12 are opened to triazenes which show cytotoxicity. 

An outline of the generalized JTE implications in electronic structure calculations is given showing the importance of this effect in both choosing the method and basis set of ab initio computation and rationalization of the results. The latter aspect is of special importance in transforming computer experiments in theoretical explanation and prediction of molecular properties. As the only source of instability and distortions of any polyatomic system the JTE serves as a general tool of (approach to) problem solving which in electronic structure calculations allow one to make conclusions based on first principles. 

W. J. Lauderdale and S. L. Rodgers, Prediction of Molecular Properties, AFAL-TR-87-063 (1987). 

The achievements in the first-principles prediction of molecular properties are very impressive and the state of the art is under constant review (see, e.g.. 

This approach works well for the precise prediction of molecular properties. However, this formula is clearly too cumbersome for routine thinking about a simple polyatomic, and a simpler, more qualitative approach is a desirable option. 

Traditional hydrocarbon conversion process models have implemented lumped kinetics schemes, where the molecules are aggregated into lumps defined by global properties, such as boiling point or solubility. Molecular information is obscured due to the multi-component nature of each lump. However, increasing environmental concerns and the desire for better control and manipulation of the process chemistry have focused attention on the molecular composition of both the feedstocks and their refined products. Modeling approaches that account for the molecular fundamentals underlying reaction of complex feeds and the subsequent prediction of molecular properties require an unprecedented level of molecular detail. 

Elaborate computational methods make reasonably accurate predictions of molecular properties, including their conformation, spectroscopic properties, and reactivity. Although these techniques tax computational resources heavily, they can be used in studies of moderately sized biological molecules. 

Pushing molecular calculations on molecules such as (H20)6 requires substantial computing resources. If the amount of computer time required for a calculation with the double zeta set is assigned a value of 1 unit, then a calculation with the hiple zeta set requires 50 units. The amount of computing time required escalates to the order of 1000 units for the quadruple zeta set and the order of 10,000 units for the quintuple zeta set. Clearly, advances in computing power are contributing significantly to our ability to provide quantitative predictions of molecular properties. 

Attempts Avere made recently to develop a set of deformation parameters, transferable between chemically similar molecules. Their application is much less time-consuming than a full electron density study and may give more realistic least-squares refinement (reduction of displacement parameters) and better predictions of molecular properties than the atomic approximation. 

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