Three Dimensional QSAR : Applications in Pharmacology and Toxicology

With numerous examples and more than 1,000 references, this book presents the most recent QSAR methods and illustrates their scope, advantages, and limitations. It offers extended comparisons of 2.5D methods in which the 3D information is masked by data preprocessing and emphasizes the synergy of various aspects of chemoinformatics, including neural networks, genetic algorithms, support vector machines, data mining, and pharmacophore detection. The authors include actual calculations of the thermodynamic cycle and free energy perturbations. They also present the basic principles of molecular modeling methods and recent statistical/mathematical approaches.

As a result of new statistical and mathematical approaches, improved visualization tools, and recognition by international regulatory groups, quantitative structure-activity relationships (QSARs) now play important roles in pharmacology for the design of new drugs as well as in toxicology and ecotoxicology for hazard identification and risk assessment. Providing up-to-date coverage of the field, Three Dimensional QSAR: Applications in Pharmacology and Toxicology presents the most recent QSAR methods and illustrates their scope, advantages, and limitations.

Part I
The first part of the book addresses CoMFA and related methods, such as CoMSIA, FLUFF, SOMFA. It also describes shape-, surface-, and volume-based approaches, including MSA, excluded volume, LIV, HASL, receptor surface model, COMPASS, and CoMSA.

Part II
Focusing on methods that use 3D information, the second part covers autocorrelation methods, such as GRIND; similarity-based methods, including similarity matrices and quantum similarity indices; and quantitative spectroscopic data–activity relationships. Some applications in data mining are also explored.

Part III
The third part deals with post-3D models. The authors discuss the adaptation of the receptor and simultaneous presence of several conformers or solvation mechanisms.

Part IV
The final part presents receptor-related approaches as well as docking and free energy calculations, which are treated at various levels. This part concerns the extensive sampling of phase space and approximate methods, such as linear interaction energy, Poisson–Boltzmann, and generalized Born models. A case study covering several parallel approaches is also developed.

An appendix offers the basic principles of modeling and statistical tools routinely required in QSAR methodologies, includi