The basis of diseases and of their treatments resides in knowledge and comprehension of the three-dimensional structures of the proteins, nucleic acids and other molecules which are involved. The availability of atomic-level structures, advances made in understanding their mechanisms, and highly efficient computational methodology which we have developed, enables us to investigate binding sites on molecular surfaces of receptors, and to dock a ligand unto a receptor surface, which will be useful in the design of potent inhibitors. We have recently developed and continue to improve highly effective descriptions of molecular surfaces that are successful and efficiently utilized for docking molecules of variable sizes. Using our sequence-order independent, computer-vision based methods, interior and surface motifs have been detected and catalogued. Using similar tools, a dataset of protein-protein interfaces was made and utilized for studies of protein associations and their comparison to protein folding. Comparisons of this dataset to a dataset of protein monomers generated earlier, illustrates the similarities and differences between the types of architectures at the interfaces and in single-chain proteins. Theoretical chemical methods are incorporated into the analyses and show that hydrophilic effects are more important than hydrophobic forces in interfaces. An efficient computational algorithm designed for cutting proteins into highly hydrophobic, compact, subdomain modules is used to produce a database of folding units that will provide deeper insights into the architecture of proteins and how they are assembled. RNA structure and function, no less important than that of proteins, is studied using thermodynamics-based algorithms for secondary structure and molecular mechanics and dynamics for three dimensional predictive modelling. Correlations drawn with experimental data from mutagenesis and NMR show successful agreement in retroviral ribosomal frameshifting. Internal ribosome entry in 5'untranslated regions (5'URT), a hallmark of picornaviruses, correlates with conserved, predicted structural elements. Similar elements are predicted in some 5'UTR's of cellular mRNA's. Refinements in predictive methods are continually developed.

Agency
National Institute of Health (NIH)
Institute
National Cancer Institute (NCI)
Type
Intramural Research (Z01)
Project #
1Z01BC008380-12
Application #
2463735
Study Section
Special Emphasis Panel (LMMB)
Project Start
Project End
Budget Start
Budget End
Support Year
12
Fiscal Year
1996
Total Cost
Indirect Cost
Name
National Cancer Institute Division of Basic Sciences
Department
Type
DUNS #
City
State
Country
United States
Zip Code
Le, Shu-Yun; Chen, Jih-H; Konings, Danielle et al. (2003) Discovering well-ordered folding patterns in nucleotide sequences. Bioinformatics 19:354-61