Knowledge of three-dimensional structure is a key factor in protein engineering. It is useful, for example, in predicting and understanding the functional consequences of specific substitution of one or more amino acids of the polypeptide chain. It is also necessary for the design of new effectors or analogs of the substrates of enzymes and receptors. X-ray diffraction by crystals of the biomolecule was for a long time the only method of determining three-dimensional structures. In the last 5 years, it has been joined by a new technique, two-dimensional nuclear magnetic resonance (2D NMR), which can resolve the structure of middle-sized proteins ( < 10 kilodaltons). The technique is applied on solutions whose pH, ionic strength, and temperature can be chosen and changed. The two basic measurements, COSY and NOESY, detect respectively the systems of hydrogen nuclei, or protons, coupled through covalent bonds, and those in which the interproton distances are less than 0.5 nm. A systematic strategy leads from resonance assignments of the two-dimensional spectrum to molecular modeling with constraints and finally to the determination of the molecular structure in the solution. Much sophistication is needed even today for the first task, the assignment of the resonances. Each of the COSY and NOESY spectra is a two-dimensional map, where the diagonal line is the one-dimensional spectrum, and the off-diagonal peaks indicate connectivities between protons. Peak assignment to a specific type of amino acid is based on the pattern of scalar couplings observed in the COSY spectrum. Next, the amino acids are positioned in the primary sequence, using the spatial proximities of polypeptide chain protons, as observed in the NOESY spectrum. The principal secondary structures (α helix, β sheets, etc.) are then identified by their specific connectivities. The tertiary structure is detected by NOESY connectivities between protons of different amino acids which are far apart in the primary sequence. The distance constraints from the NOESY connectivities also provide the starting point for modeling the tertiary structure. This is then refined using distance geometry and molecular dynamics algorithms. The resolution of the structures obtained with the help of recent algorithmic developments may be comparable to that provided by X-ray diffraction. The COSY measurement can be completed or substituted by other measurements, useful albeit more complex. For example, the HOHAHA experiment, currently in wide use, gives the correlations through multiple covalent bonds. Multiquanta experiments, which select systems of a given number of coupled spins, provide spectral simplification. To help with the sequential assignment, which remains a limiting step, one may substitute amino acids isotopically labeled with 15N or 13C. Nuclear magnetic resonance of these nuclei is detected either directly or by heteronuclear proton NMR. In the latter case, heteronuclear cross-peaks indicate connectivities between protons and the isotopic nuclei, 1SN and 13C. This labeling is very useful for proteins with more than 100 amino acids and for proteins exhibiting low-resolution spectra. Resolution can also be enhanced by the combination of two-dimensional experiments, giving rise to 3D NMR. The graphic representation of a three-dimensional experiment is a cube whose sections correspond to virtual two-dimensional measurements. The 3D NMR can be homonuclear or, in the case of isotopically substituted proteins, heteronuclear. The time for a single experiment reaches several days. The memory needed for data acquisition and processing is greater than for two-dimensional experiments. Large parts of the data processing, such as peak detection or the recognition of secondary structure connectivities can be automated. Two-dimensional NMR is becoming a routine technique for peptide and protein structure determination in the laboratories of the pharmaceutical firms.Key words: protein engineering, three-dimensional structure, nuclear magnetic resonance, correlated spectroscopy, nuclear Overhauser effect spectroscopy.
On the use of direct-coupling analysis with a reduced alphabet of amino acids combined with super-secondary structure motifs for protein fold prediction
