Computational-experimental chemistry relationship

The proposed volume provides basic information as well as the details of computational and computational-experimental studies improving our knowledge on functioning of alive, different properties of drugs, and predictions of new medicines. Whenever it is possible the interplay between the theory and the experiment is provided. The unique feature of the book is the fact that such different in principles computational techniques as quantum-chemical and molecular dynamic approaches on one hand and quantitative structure-activity relationships on another hand are considered inside one volume. The reviews presented in the volume cover main tendencies and priorities in apphcation of computational methods of quantum chemistry, molecular dynamics and chemoinformatics to solve the tasks of pharmacy and medicine. 

Other simple geometrical descriptors are interatomic distances between pairs of atoms s and t. Interatomic distances are devided into intramolecular interatomic distances, i.e. distances between any pair of atoms (s, t) within the molecule, and intermo-lecular interatomic distances, i.e. distances between atoms of a molecule and atoms of a receptor structure, a reference compound or another molecule. While classical computational chemistry describes molecular geometry in terms of three-dimensional Cartesian coordinates or internal coordinates, the -> distance geometry (DG) method takes the interatomic distances as the fundamental coordinates of molecules, exploiting their close relationship to experimental quantities and molecular energies. 

Empirical QSPR Correlations In quantitative structure property relationship (QSPR) methods, physical properties are correlated with molecular descriptors that characterize the molecular and electronic structure of the molecule. Large amounts of experimental data are used to statistically determine the most significant descriptors to be used in the correlation and their contributions. The resultant correlations are simple to apply if the descriptors are available. Descriptors must generally be generated by the user with computational chemistry software, although the DIPPR 801 database now contains a table of molecular descriptors for most of the compounds in it. QSPR methods are often very accurate for specific families of compounds for which the correlation was developed, but extrapolation problems are even more of an issue than with GC methods. 

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