title: Knowledge-based model building of proteins: concepts and examples.
abstract: We describe how to build protein models from structural templates. Methods to identify structural similarities between proteins in cases of significant, moderate to low, or virtually absent sequence similarity are discussed. The detection and evaluation of structural relationships is emphasized as a central aspect of protein modeling, distinct from the more technical aspects of model building. Computational techniques to generate and complement comparative protein models are also reviewed. Two examples, P-selectin and gp39, are presented to illustrate the derivation of protein model structures and their use in experimental studies.
authors.affiliation: Bristol-Myers Squibb, Pharmaceutical Research Institute, Seattle, Washington 98121.
authors.forename: J
authors.initials: J
authors.lastname: Bajorath
authors.forename: R
authors.initials: R
authors.lastname: Stenkamp
authors.forename: A
authors.initials: A
authors.lastname: Aruffo
mesh_terms: D000595:Amino Acid Sequence; D023201:CD40 Ligand; D003198:Computer Simulation; D008562:Membrane Glycoproteins / Q000737:chemistry; D008958:Models, Molecular; D008969:Molecular Sequence Data; D019007:P-Selectin; D010980:Platelet Membrane Glycoproteins / Q000737:chemistry; D011487:Protein Conformation; D011506:Proteins / Q000737:chemistry*; D017386:Sequence Homology, Amino Acid
chemical_list: D008562:Membrane Glycoproteins; D019007:P-Selectin; D010980:Platelet Membrane Glycoproteins; D011506:Proteins; D023201:CD40 Ligand