TOUCHSTONE: an ab initio protein structure prediction method that uses threading-based tertiary restraints

Abstract

The successful prediction of protein structure from amino acid sequence requires two features: an efficient conformational search algorithm and an energy function with a global minimum in the native state. As a step toward addressing both issues, a threading-based method of secondary and tertiary restraint prediction has been developed and applied to ab initio folding. Such restraints are derived by extracting consensus contacts and local secondary structure from at least weakly scoring structures that, in some cases, can lack any global similarity to the sequence of interest. Furthermore, to generate representative protein structures, a reduced lattice-based protein model is used with replica exchange Monte Carlo to explore conformational space. We report results on the application of this methodology, termed TOUCHSTONE, to 65 proteins whose lengths range from 39 to 146 residues. For 47 (40) proteins, a cluster centroid whose rms deviation from native is below 6.5 (5) A is found in one of the five lowest energy centroids. The number of correctly predicted proteins increases to 50 when atomic detail is added and a knowledge-based atomic potential is combined with clustered and nonclustered structures for candidate selection. The combination of the ratio of the relative number of contacts to the protein length and the number of clusters generated by the folding algorithm is a reliable indicator of the likelihood of successful fold prediction, thereby opening the way for genome-scale ab initio folding.

Figure 1

The number of the predicted long-range contacts and their accuracy (within onr or two residues) are shown. Proteins of the different structural type are plotted separately: ▵, small proteins; ●, α-helical proteins; □, β-proteins; ⋄, αβ-proteins. Nc, number of clusters.

Figure 2

Superimposition of representative experimentally observed and predicted structures. The predicted structures are shown by thick lines, and the native structures are shown by thin lines. (A) 1aoy, rmsd 4.5 Å. (B) 1mba, rmsd 2.7 Å. (C) 2pcy, rmsd 4.0 Å. (D) 2azaA, rmsd 4.5 Å. (E) 1shaA, rmsd 3.6 Å. (F) 1erv, rmsd 2.3 Å. (G) 1cewI, rmsd 7.2 Å. (H) 1tsg, rmsd 8.7 Å. (I) 5fd1, rmsd 9.7 Å.

Figure 3

The number of successful cases relative to the number of clusters. Black, the successful cluster (rmsd <6.5 Å) is obtained as the first cluster; crosshatch, the second cluster; horizontal hatch, one of the other clusters; white, successful cluster not obtained.

Figure 4

The number of long-range restraints and the quality of the clusters for each protein. (A) rmsd of the best cluster centroid. (B) rmsd of the best structure among all of the simulations. ▵, small proteins; ●, α-helical proteins; □, β-proteins; ⋄, αβ-proteins. Nc, number of clusters.