DE-NOVO AND INVERSE FOLDING PREDICTIONS OF PROTEIN-STRUCTURE AND DYNAMICS

In the last two years, the use of simplified models has facilitated ma jor progress in the globular protein folding problem, viz., the predic tion of the three-dimensional (3D) structure of a globular protein fro m its amino acid sequence. A number of groups have addressed the inver se folding problem where one examines the compatibility of a given seq uence with a given (and already determined) structure. A comparison of extant inverse protein-folding algorithms is presented, and methodolo gies for identifying sequences likely to adopt identical folding topol ogies, even when they lack sequence homology, are described. Extension to produce structural templates or fingerprints from idealized struct ures is discussed, and for eight-membered beta-barrel proteins, it is shown that idealized fingerprints constructed from simple topology dia grams can correctly identify sequences having the appropriate topology . Furthermore, this inverse folding algorithm is generalized to predic t elements of supersecondary structure including beta-hairpins, helica l hairpins and alpha/beta/alpha fragments. Then, we describe a very hi gh coordination number lattice model that can predict the 3D structure of a number of globular proteins de novo; i.e. using just the amino a cid sequence. Applications to sequences designed by DeGrado and co-wor kers [Biophys. J., 61 (1992) A265] predict folding intermediates, nati ve states and relative stabilities in accord with experiment. The meth odology has also been applied to the four-helix bundle designed by Ric hardson and co-workers [Science, 249 (1990) 884] and a redesigned mono meric version of a naturally occurring four-helix dimer, rop. Based on comparison to the rop dimer, the simulations predict conformations wi th rms values of 3-4 angstrom from native. Furthermore, the de novo al gorithms can assess the stability of the folds predicted from the inve rse algorithm, while the inverse folding algorithms can assess the qua lity of the de novo models. Thus, the synergism of the de novo and inv erse folding algorithm approaches provides a set of complementary tool s that will facilitate further progress on the protein-folding problem .