The amino acid sequence of a protein uniquely determines its tertiary structure. Deciphering this relationship, the protein folding problem, has become increasingly important to molecular biologists. DNA sequencing has become routine, but structural experiments remain difficult. Two semi-empirical approaches to the folding problem have evolved: detailed energy calculations and the hierarchic condensation model. This grant focuses on the hierarchic condensation model which presumes that secondary structure is a useful computational intermediate in protein folding. We propose to study known structures. Initial efforts will be directed at deducing the rules which govern alpha-helix and beta-strand formation. Secondary structure prediction will follow an """"""""expert systems"""""""" approach which has been successfully applied to locating turns in a variety of proteins (Cohen et al (1986) Biochemistry 25, 266-275). This algorithm will be combined with procedures for exploring possible tertiary structure through the packing of secondary structure units (e.g. Cohen et al (1979) J. Molec. Biol. 132, 275-288). Methods to sort amongst the alternative structures will be developed. These methods hopefully will evolve from the study of the spatial, electrostatic and catalytic properties of proteins of known structure. Finally, these mathematical models will be applied to a variety of biologically interesting macromolecules with known amino acid sequence but unknown tertiary structure. Collaborative ventures will be established to experimentally test the predicted structures for Interleukin-1 (IL1), Interleukin-2 (IL2), and Parathyroid Hormone (PTH). Fragments of the IL1 sequence which correspond to predicted loop regions will be designed. Dr. Dinarello at Tufts will investigate the immunologic relevance and potential antagonist activity of these fragments. With Drs. Ciardelli and Smith at Dartmouth, the structure of IL2 will be examined through site directed mutagenesis. The theoretical effect of a mutation on the protein's stability and activity will be modelled and tested by circular dichroism spectroscopy and receptor binding assays. With Drs. Kuntz, Stewler and Arnaud at UCSF, the structure of PTH and chemical variants of PTH will be characterized. It is hoped that structural modelling will lead to the design of pharmacologically relevant mutant proteins.

Agency
National Institute of Health (NIH)
Institute
National Institute of General Medical Sciences (NIGMS)
Type
Research Project (R01)
Project #
5R01GM039900-03
Application #
3297167
Study Section
Special Emphasis Panel (SSS (A))
Project Start
1988-12-01
Project End
1991-11-30
Budget Start
1990-12-01
Budget End
1991-11-30
Support Year
3
Fiscal Year
1991
Total Cost
Indirect Cost
Name
University of California San Francisco
Department
Type
Schools of Medicine
DUNS #
073133571
City
San Francisco
State
CA
Country
United States
Zip Code
94143
Chandonia, John-Marc (2007) StrBioLib: a Java library for development of custom computational structural biology applications. Bioinformatics 23:2018-20
Li, Z; Chen, X; Davidson, E et al. (1994) Anti-malarial drug development using models of enzyme structure. Chem Biol 1:31-7
Harris, N L; Presnell, S R; Cohen, F E (1994) Four helix bundle diversity in globular proteins. J Mol Biol 236:1356-68
Hearst, D P; Cohen, F E (1994) GRAFTER: a computational aid for the design of novel proteins. Protein Eng 7:1411-21
Jin, L; Cohen, F E; Wells, J A (1994) Structure from function: screening structural models with functional data. Proc Natl Acad Sci U S A 91:113-7
Hunt, N G; Gregoret, L M; Cohen, F E (1994) The origins of protein secondary structure. Effects of packing density and hydrogen bonding studied by a fast conformational search. J Mol Biol 241:214-25
Ring, C S; Cohen, F E (1993) Modeling protein structures: construction and their applications. FASEB J 7:783-90
Sun, E; Cohen, F E (1993) Computer-assisted drug discovery--a review. Gene 137:127-32
Aroeti, B; Kosen, P A; Kuntz, I D et al. (1993) Mutational and secondary structural analysis of the basolateral sorting signal of the polymeric immunoglobulin receptor. J Cell Biol 123:1149-60
Presnell, S R; Cohen, F E (1993) Artificial neural networks for pattern recognition in biochemical sequences. Annu Rev Biophys Biomol Struct 22:283-98

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