This work presents contributions on distance based approaches to the generation of detailed 3 dimensional structures of proteins. New insights into protein folding obtained by traditional X-ray crystallography, NMR spectroscopy, circular dicroism and ultra-violet methods are reviewed and new methods incorporating distance-based energy functions which may be used for identifying and building protein folds. A seperate section is devoted to the latest developmentsin the use of neural networks, genetic algorithms and knowledge based approaches in the determination of fold-class predictions and protein secondary structures from sequence data. Readers: bioscientists, computer scientists.
