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Computational drug design A Guide for Computational and MedicinalChemists; a book review

David C. Young. John Wiley & Sons, Inc. Hoboken,

New Jersey. 2009. 307 p. ISBN: 978-0-470-12685-1.

Molecular modeling used to be restricted to asmall number of scientists. They wrote their own

programs, managed their own computer systemsand mended them when they broke down.Todays computer workstations are much more

powerful than that old computers and they can bepurchased relatively cheaply. It is no longernecessary for the modeler to write computer

programs and software can be obtained fromcommercial software companies and academiclaboratories. Molecular modeling can now be

performed in any laboratory or classroom.

Computational techniques, represented bymolecular modeling, play a valuable role in thedrug design process. This role makescomputational techniques important parts of asuccessful and profitable drug design process.Most importantly, drug design projects may failwithout the efforts of experts in computationalmodeling. Drug design is such a difficult problemthat every relevant technique is often utilized toits best advantage. Computational modelingtechniques have a long history of providing usefulinsights, new suggestions for molecular structuresto synthesize, and cost-effective (virtual)

experimental analysis prior to synthesis.These techniques and some useful concepts in

medicinal chemistry field are discussed in thebook Computational drug design a guide forcomputational and medicinal chemists, by DavidC. Young. In the short introduction the authordiscusses the difficulties in the process of drugdesign, the effective costs involved and thevaluable role that computational techniques playin that process. There is no one bestcomputational drug design technique, manytechniques are used at various stages of the drugdesign project, says Young.

The book is divided into three parts. (1) Thedrug design process, (2) Computational tools andtechniques and, (3) Related topics.

The first part, The drug design process, isdivided in seven chapters, where the authordescribes the properties that make a molecule agood drug, target identification, targetcharacterization, the drug design process for aknown protein target, the drug design process for

an unknown target, drug design for other targetsand compound library design.

In these first chapters it is defined useful

medicinal chemistry concepts like hits and leads,depicted some biochemical and cell-based assays,and explained about animal testing and humanclinical trials. Concepts like activity,

bioavailability, toxicity, drug side effects anddrug interactions are also described. An usefultopic about Metrics for drug-likeness deservesto be emphasized, since drug-likeness is animportant concept often discussed in themedicinal chemistry classes. The author also citesseveral recent studies related to this area,important as supplementary texts for the classes.

In the second part, Computational tools and

techniques, it is discussed homology modelbuilding, molecular mechanics, protein folding,docking, pharmacophore models, QSAR, 3D-QSAR, quantum mechanics in drug design, denovo techniques, cheminformatics and ADMET.

Some molecular modeling methodologies suchas homology modeling, docking and QSAR arevery useful in the drug design process anddeserves our attention, especially when used inmedicinal chemistry classes. In this context, Imissed the synonym of homology modeling,named comparative modeling, that the authordid not cite in the text.

The chapter on QSAR is summarized, butcontains the essential informations for a goodunderstanding of the methodology and discussesthe main descriptors used in the quantitativeanalysis. I missed the names of the 3D-QSAR

programs that the author did not mention, likeCoMFA, CoMSIA and Catalyst.

I highlight the docking chapter, where theauthor wrote with clarity. It was an easy-readingand very informative text, citing advantages anddisadvantages of the methodology.

The chapter on ADMET added newinformation to those already reviewed in the first

part, with expanding concepts.In the third part, Related topics, it is

discussed bioinformatics, simulations at thecellular and organ level, synthesis route

prediction, proteomics, prodrug approaches andfuture developments in drug design. Proteomics isone of the newest fields discussed in the textbook.The author highlighted the importance of thisfield and the human genome project.

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Computational drug design provides adescription of computational techniques and theroles that play in the drug design process. This

book covers a wide range of computational drugdesign techniques in an easily understood,nonmathematical format. The emphasis is onunderstanding how each method works, howaccurate it is, when to use it, and when not to useit.

Researchers will find this text to be anexcellent overview of the entire drug design

process. Professors of medicinal chemistry andrelated disciplines will use the texts ascomplements for the students.

Monique Arajo de BritoEmail: moniquebrito@id.uff.brDepartment of Pharmacy, Fluminense FederalUniversity, Niteri Brazil.