Customer Reviews
an excellent introduction - By: , 10 Sep 2004 
This is a very lucid introduction to chemoinformatics. It covers all the main topics: 2D & 3D representations of chemical structure, pharmacophore searching, descriptor generation, chemometric techiniques (Principal Component Analysis & Partial Least Squares), QSAR model building, similarity searching, diversity analysis & molecule selection, & combinatorial library design.
Additionally, there are sections on virtual screening & on data-mining of high-throughput screening, which are slightly weaker than the other material. In the former case, sections on filters, drug-likeness, docking & ADMET prediction, hangs together rather uneasily. The docking section, while communicating the basics, is perhaps a little too light on detail.
The HTS chapter considers classification techniques as separate from regression (which is coveredin the QSAR chapter), covering neural networks & decision trees, as well as linear discriminant analysis & briefly mentioning Support Vector Machines. I would question whether LDA is suitable for analysis of HTS data (the example given is from 1974 & only considers 20 molecules!), likewise for SVMs (due to speed issues). And certainly, SVMs & NNs can be used for regression.
One other thing - the jacket design sports a horrendously naff typeface. Please change this for the next edition, Kluwer!
However, these are minor quibbles. The authors have packed a large amount of information (with plenty of references) into a small volume, without sacrificing readability. An admirable achievement, & highly recommended for anyone seeking a good overview or entry point into the field.
A comprehensive introduction - By: Hugo Kubinyi, 18 Aug 2003 Chemical structures are a symbolic "language" that has developed about 150 years ago. For the specialist, the structures do not only encode the connectivity of atoms but they also provide information, via the recognition of functional groups, on synthetic accessibility, chemical reactivity, & various other molecular properties. However, for a computer, this symbolic language has to be translated. This is one application of chemoinformatics, to store & retrieve structural informationin various ways. Some other ones, becoming more & more important because of the vast amount of compounds being synthesised & testedin drug research, are the calculation of different molecular properties, the comparison of molecules by their mutual similarity, the selection of sets of compounds with the highest dissimilarity, & various strategies for the enrichment of compound libraries, especially combinatorial libraries, with promising candidates for biological testing.
The book by Leach & Gillet is a comprehensive introduction into the field, well balancedin its presentation of the underlying theories & a critical discussion of scope & limitations of the individual approaches.
In an introductory chapter, the representation & manipulation of 2D molecular structure (i.e., by the computer) is described, including structure searching & substructure searching. The next chapter deals with the generation, representation & manipulation of 3D structures; pharmacophore generation & pharmacophore searches are treated as well as the flexibility of molecules. 2D & 3D descriptors are describedin an extra chapter, which is the basis of the discussion of computational models, like QSAR & molecular field analyses. Two more chapters discuss similarity methods & the selection of diverse sets of compounds; a small section of each chapter is dedicated to a comparison & evaluation of the individual methods. A chapter on the analysis of high-throughput screening data discusses data visualisation & data mining methods. Virtual screening is becoming more & more important, due to the vast number of compounds that could be synthesised & tested. Correspondingly, a chapter on this topic discusses the concept of "drug-likeness", different computational filters, ligand docking & scoring, & the prediction of ADMET (absorption, distribution, metabolism, elimination, & toxicity) properties. The final chapter deals with library designin combinatorial chemistry. Two short appendices, one on matrices, eigenvectors & eigenvalues, & another one on conformation, energy calculations & energy surfaces, present details which could not be includedin the text. Very helpful is a short section on recommendations for further reading (sorted by chapters), followed by the list of references for all chapters (25 pages), & the keyword index (9 pages).
Leach & Gillet have been successful to compile an introductory text which is easy to read & understand, & is of special value for the newcomer as well as for the practitioner. The individual chapters treat all important aspects of chemoinformaticsin a well-balanced manner,in scientific detail but without too much theory. To me, the comments on limitations & various pitfalls, which reflect the long practical experience of these two outstanding scientists, are the most important aspect of the book. Too many people use modellingin a "blind" manner, without being aware of the problems behind the individual methods. This can be avoided by studying this book.
Correspondingly, this chemoinformatics book is highly recommended as an introductory text for students & all scientists who deal with molecular modelling, combinatorial chemistry, high-throughput, structure-activity relationships, & drug research,in general.
