Abstract

Segment match modeling uses a data base of highly refined known protein X-ray structures to build an unknown target structure from its amino acid sequence and the atomic coordinates of a few of its atoms (generally only the C alpha atoms). The target structure is first broken into a set of short segments. The data base is then searched for matching segments, which are fitted onto the framework of the target structure. Three criteria are used for choosing a matching data base segment: amino acid sequence similarity, conformational similarity (atomic co-ordinates), and compatibility with the target structure (van der Waals' interactions). The new method works surprisingly well: for eight test proteins ranging in size from 46 to 323 residues, the all-atom root-mean-square deviation of the modeled structures is between 0.93 A and 1.73 A (the average is 1.26 A). Deviations of this magnitude are comparable with those found for protein co-ordinates before and after refinement against X-ray data or for co-ordinates of the same protein in different crystal packings. These results are insensitive to errors in the C alpha positions or to missing C alpha atoms: accurate models can be built with C alpha errors of up to 1 A or by using only half the C alpha atoms. The fit to the X-ray structures is improved significantly by building several independent models based on different random choices and then averaging co-ordinates; this novel concept has general implications for other modeling tasks. The segment match modeling method is fully automatic, yields a complete set of atomic co-ordinates without any human intervention and is efficient (14 s/residue on the Silicon Graphics 4D/25 Personal Iris workstation.