  We have developed an analytical, ligand-specific and scalable algorithm that
detects a "signature" of the 3D binding site of a given ligand in a protein 3D
structure. The said signature is a 3D motif in the form of an irregular
tetrahedron whose vertices represent the backbone or side-chain centroids of
the amino acid residues at the binding site that physically interact with the
bound ligand atoms. The motif is determined from a set of solved training
structures, all of which bind the ligand. Just as alignment of linear amino
acid sequences enables one to determine consensus sequences in proteins, the
present method allows the determination of three-dimensional consensus
structures or "motifs" in folded proteins. Although such is accomplished by the
present method not by alignment of 3D protein structures or parts thereof
(e.g., alignment of ligand atoms from different structures) but by
nearest-neighbor analysis of ligand atoms in protein-bound forms, the same
effect, and thus the same goal, is achieved. We have applied our method to the
prediction of GTP- and ATP-binding protein families, namely, the small Ras-type
G-protein and ser/thr protein kinase families. Validation tests reveal that the
specificity of our method is nearly 100% for both protein families, and a
sensitivity of greater than 60% for the ser/thr protein kinase family and
approx. 93% for the small, Ras-type G-protein family. Further tests reveal that
our algorithm can distinguish effectively between GTP and GTP-like ligands, and
between ATP- and ATP-like ligands. The method was applied to a set of predicted
(by 123D threading) protein structures from the slime mold (D. dictyostelium)
proteome, with promising results.
