Some observations on classical QSAR John G. Topliss Perspectives Part I. Quantitative Structure-Activity Relationships Pages: 253 - 268
Partial Least Squares (PLS): Its strengths and limitations Richard D. Cramer III Perspectives Part I. Quantitative Structure-Activity Relationships Pages: 269 - 278
New approaches to QSAR: Neural networks and machine learning Ross D. KingJonathan D. HirstMichael J. E. Sternberg Perspectives Part I. Quantitative Structure-Activity Relationships Pages: 279 - 290
Three-dimensional models for integral membrane proteins: Possibilities and pitfalls Maria KontoyianniTerry P. Lybrand Perspectives Part II. Molecular Modeling Pages: 291 - 300
A good ligand is hard to find: Automated docking methods Jeffrey M. BlaneyJ. Scott Dixon Perspectives Part II. Molecular Modeling Pages: 301 - 319
Why are binding-site models more complicated than molecules? G. M. CrippenM. P. BradleyW. W. Richardson Perspectives Part II. Molecular Modeling Pages: 321 - 328
Seeing our way to drug design Arthur J. OlsonGarrett M. Morris Perspectives Part III. Hardware And Software Pages: 329 - 344
Supercomputing and drug discovery research Donald B. BoydSamuel A. F. Milosevich Perspectives Part III. Hardware And Software Pages: 345 - 358
The effect of workstation technology on methods in drug design and discovery David C. SpellmeyerWilliam C. Swope Perspectives Part III. Hardware And Software Pages: 359 - 370
Structure-based drug design (SBDD): Every structure tells a story... Siegfried H. ReichStephen E. Webber Perspectives Part IV. Empirical Support For Theoretical Studies Pages: 371 - 390
Modern NMR spectroscopy of proteins and peptides in solution and its relevance to drug design E. R. P. ZuiderwegS. R. van DorenA. Majumdar Perspectives Part IV. Empirical Support For Theoretical Studies Pages: 391 - 417