As methods for determining protein three-dimensional (3D) structure develop, a continuing problem is how to verify that the final protein model is correct. The revision of several protein models to correct errors has prompted the development of new criteria for judging the validity of X-ray and NMR structures, as well as the formation of energetic and empirical methods to evaluate the correctness of protein models. The challenge is to distinguish between a mistraced or wrongly folded model, and one that is basically correct, but not adequately refined. We show that an effective test of the accuracy of a 3D protein model is a comparison of the model to its own amino-acid sequence, using a 3D profile, computed from the atomic coordinates of the structure 3D profiles of correct protein structures match their own sequences with high scores. In contrast, 3D profiles for protein models known to be wrong score poorly. An incorrectly modelled segment in an otherwise correct structure can be identified by examining the profile score in a moving-window scan. The accuracy of a protein model can be assessed by its 3D profile, regardless of whether the model has been derived by X-ray, NMR or computational procedures.

The inverse protein folding problem, the problem of finding which amino acid sequences fold into a known three-dimensional (3D) structure, can be effectively attacked by finding sequences that are most compatible with the environments of the residues in the 3D structure. The environments are described by: (i) the area of the residue buried in the protein and inaccessible to solvent; (ii) the fraction of side-chain area that is covered by polar atoms (O and N); and (iii) the local secondary structure. Examples of this 3D profile method are presented for four families of proteins: the globins, cyclic AMP (adenosine 3',5'-monophosphate) receptor-like proteins, the periplasmic binding proteins, and the actins. This method is able to detect the structural similarity of the actins and 70- kilodalton heat shock proteins, even though these protein families share no detectable sequence similarity.

No abstract

One of the great challenges for molecular biologists is to learn how a protein sequence defines its three-dimensional structure. For many years, the problem was even more difficult for membrane proteins because so little was known about what they looked like. The situation has improved markedly in recent years, and we now know over 90 unique structures. Our enhanced view of the structure universe, combined with an increasingly quantitative understanding of fold determination, engenders optimism that a solution to the folding problem for membrane proteins can be achieved.

An amino acid sequence encodes a message that determines the shape and function of a protein. This message is highly degenerate in that many different sequences can code for proteins with essentially the same structure and activity. Comparison of different sequences with similar messages can reveal key features of the code and improve understanding of how a protein folds and how it performs its function.