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Synopsis The rational way to discover a new drug is to understand the disease mechanism and identify a target molecule, mostly a protein and design an inhibitor or an activator for the same. Alternatively, one can make a disease model and screen the compounds randomly for their action. But these high throughput screening methods need large manpower (200-300) research scientists) and time (10-12 years), which increases the cost of new drug production substantially. A systematic approach to drug designing, on the other hand, can take advantage of the developments in both the silicon world and the medicinal chemists, approach. It can not only bring down and cost and man-hours in the process but also enable us to transfer the fruits of the human genome project to mankind as many genes with therapeutic relevance are now identified. The main problem is the lack of trained manpower. This book is aimed at imparting necessary skills to a young graduate. It deals with the basics of drug discovery, molecular modeling techniques, energy based optimization using empirical and quantum chemical methods, molecular mechanics, dynamics, Monte Carlo, Genetic algorithms, use of old and new QSAR, 3D-QSAR methods such as comparative field analysis, active site analysis, receptor surface analysis, HOMOLOGY-based protein modeling, de novo ligand design using ‘growers and builders’, and 3D-database searching using different docking procedures. It also gives enough theoretical inputs for developing your own software and a brief description of the available software.