ABSTRACT
Biocomputational approaches in the rational design of bioactive proteins and peptides are driven by a general understanding of tertiary structure, electrostatic interactions, hydrogen bonding, hydrophobic interactions, desolvation effects, and cooperative motions of interacting ligands and receptors, backed up by data base searches and simulation techniques. This chapter presents a brief summary of various protein prediction strategies commonly used in computational biology, including computational approaches for predicting and energetically analyzing protein structures and for analyzing nuclear magnetic resonance (NMR) data. There is a wealth of software and methods available for computer-assisted drug design which was recently reviewed that is either the same or complementary to protein-based drug design. The design strategy incorporated NMR data, energy minimization, template forcing, and molecular dynamics. Current biocomputational approaches to peptide-based drug design combine knowledge-based systems involving crystallographic, NMR, and sequence data bases with experimentally determined constraints, conformational energy analysis, and molecular modeling.
