Danny W. Rice

Assigning amino acid sequences to 3-dimensional protein folds.

With the advent of genome sequencing projects, the amino acid sequences of thousands of proteins are determined every year. Each of these protein sequences must be identified with its function and its 3‐dimensional structure for us to gain a full understanding of the molecular biology of organisms. To meet this challenge, new methods are being developed for fold recognition, the computational assignment of newly determined amino acid sequences to 3‐dimensional protein structures. These methods start with a library of known 3‐dimensional target protein structures. The new probe sequence is then aligned to each target protein structure in the library and the compatibility of the sequence for that structure is scored. If a target structure is found to have a significantly high compatibility score, it is assumed that the probe sequence folds in much the same way as the target structure. The fundamental assumptions of this approach are that many different sequences fold in similar ways and there is a relatively high probability that a new sequence possesses a previously observed fold. We review various approaches to fold recognition and break down the process into its main steps: creation of a library of target folds; representation of the folds; alignment of the probe sequence to a target fold using a sequence‐to‐struc‐ ture compatibility scoring function; and assessment of significance of compatibility. We emphasize that even though this new field of fold recognition has made rapid progress, technical problems remain to be solved in most of the steps. Standard benchmarks may help identify the problem steps and find solutions to the problems.—Fischer, D., Rice, D., Bowie, J. U., Eisenberg, D. Assigning amino acid sequences to 3‐dimensional protein folds. FASEB J. 10, 126‐136 (1996)

A study of combined structure/sequence profiles

BACKGROUND For genome sequencing projects to achieve their full impact on biology and medicine, each protein sequence must be identified with its three-dimensional structure. Fold assignment methods (also called profile and threading methods) attempt to assign sequences to known protein folds by computing the compatibility of sequence to fold. RESULTS We have extended profile methods for the detection of protein folds having structural similarity but low sequence similarity to sequence probes. Our extension combines sequence substitution tables with structural properties to form a combined profile. The structural properties used in this study include distances between residues, exposed areas, areas buried by polar atoms, and properties of the original three-dimensional profile method. We compared the performance of these combined profiles with different sequence matrices and with the original three-dimensional profile method. To determine the optimal gap penalties and weights used with these profiles, we employed a genetic algorithm. The performance of these combined profiles was tested by cross validation using independent test and training sets. CONCLUSIONS These studies show that the combined profiles perform better than profiles based on either structural or sequence information alone.

Fold assignments for amino acid sequences of the CASP2 experiment

New and newly extended methods for fold assignment were tested for their abilities to assign folds to amino acid target sequences of unknown three‐dimensional structure. These target sequences, released through the CASP2 experiment, are not obviously related to any sequence of known three‐dimensional (3D) structure. We assigned 3D folds to target sequences and filed these predictions with CASP2 before their 3D structures were released. The methods tested were (1) Environmental 3D profiles of Bowie and colleagues [Bowie, J.U., Luthy, R., Eisenberg, D. Science 253:164–170, 1991]; (2) A variation of this is termed Directional Profiles; (3) The H3P2 five‐dimensional sequence‐structure substitution matrix of Rice and Eisenberg [Rice, D., Eisenberg, D.J. Mol. Biol. 267:1026–1037, 1997]; and (4) The Sequence Derived Property methods of Fischer and Eisenberg [Fischer, D., Eisenberg, D. Prot. Sci. 5:947–955, 1996]. When the 3D structures of the sequences were released, 17 of our predictions were evaluated. Of these 17, we assigned high probabilities to 11, of which 9 were correct. Five of these correct predictions were of known 3D structures similar to the targets and four of these were of new folds. The evaluation demonstrated that our methods were effective in assigning the proper fold to more than half of the CASP2 targets with known folds (5/9) and also were able to detect half of the sequences that corresponded to no known folds (4/8). Even when the correct fold is assigned to a sequence, proper alignment of the sequence to the structure remains a challenge. Our methods were able to produce accurate alignments (<1.2 mean residue shift error from the structural alignment) for four of the targets, including the particularly difficult alignment (only 7% residue identity in the structurally aligned regions) of the ferrochelatase sequence to the fold of a periplasmic binding protein. Proteins, Suppl. 1:113–122, 1997.