A major goal of structural biology is to understand how molecules recognize and interact with one another. Comprehension of the details of protein interactions would enhance the understanding of numerous biological processes, as well as provide a sounder basis for drug design. Learning about molecular interactions has been the goal of many of our studies, particularly through the use of coarse-grained models. Extracting interaction energies from structures, together with the general forms of the overall energy distributions represents one of our major efforts. During this period we have collected interaction energies for interactions between separate proteins (intermolecular) and compared them to those for intramolecular cases. The results of the comparison depend strongly on the reference state, i.e., whether the interacting pairs are formed by replacing water interactions or by replacing other residue interactions. In the former case, the intermolecular and intramolecular potentials are extremely similar, because of the dominant effect of water interactions. We have also investigated alternative ways to extract short-range interaction energies from protein structures and combined them with long-range potentials to improve threading. Surprisingly the short-range interaction terms are similarly effective as the long-range terms, and when combined the gains in threading performance are relatively small. In new studies we have been studying the most extremely conserved parts of proteins and have shown that these comprise a small fraction of the structure, typically 6 ? 10 residues. At the same time we are also investigating the correlations of various molecular properties, such as packing, with the sequence conserved regions. Understanding the physical basis in structure for sequence conservation would enable us to make some critical predictions of protein cores from sequences alone.Another goal of molecular biology is to understand molecular mechanisms. Protein structures combined with conventional molecular dynamics have not been so informative about these. We are investigating protein dynamics with a new coarse-grained model having only one point per residue. This new approach represents a simplest way to infer functional behavior from structures. It considers fluctuations about known protein structures based on a Gaussian network model. This procedure is being shown to sample satisfactorily the distribution of atomic fluctuations about the native conformation in proteins, and to yield remarkably good agreement with crystallographic temperature factors and hydrogen exchange data, for a broad variety of proteins and nucleic acid structures. Although this method is simple, results are intuitive and compelling. The approach yields a series of modes of motion, typically hinge bending motions, including even the slowest, most global motions. This opens new and exciting prospects for comprehending the functional dynamics of extremely large, even supra- molecular structures. Examples of our studies with this approach include: 1) subunit communications within tryptophan synthase; 2) reverse transcriptase in which we showed how the anti-correlations between the motions of the fingers/thumb binding site and the ribonuclease H site could lead to a step-wise processing mechanism; 3) t-RNA free and bound to its cognate synthetase; and 4) topoisomerase II in trying to infer connections between individual modes of motion and the enzyme?s functional steps. Other studies underway include the GroEl-GroES protein chaperone system (about 8800 residues) which is an extremely large system that demonstrates the power of the approach and some other nucleic acid binding proteins. This approach is being applied to investigate binding sites, typically the most flexible regions, but also to investigate the more rigid hinges and folding nuclei for a broad variety of proteins.Z01 BC 08370-16 - databases, molecular interactions, molecular models, protein folding, protein structure, supercomputing,

Agency
National Institute of Health (NIH)
Institute
National Cancer Institute (NCI)
Type
Intramural Research (Z01)
Project #
1Z01BC008370-16
Application #
6289198
Study Section
Special Emphasis Panel (LECB)
Project Start
Project End
Budget Start
Budget End
Support Year
16
Fiscal Year
1999
Total Cost
Indirect Cost
Name
National Cancer Institute Division of Basic Sciences
Department
Type
DUNS #
City
State
Country
United States
Zip Code