The Rosetta software suite for macromolecular modeling, docking, and design is widely used in pharmaceutical, industrial, academic, non-profit, and government laboratories. Despite its broad modeling capabilities, Rosetta remains consistently among leading software suites when compared to other methods created for highly specialized protein modeling and design tasks. Developed for over two decades by a global community of over 60 laboratories, Rosetta has undergone multiple refactorings, and now comprises over three million lines of code. Here we discuss methods developed in the last five years in Rosetta, involving the latest protocols for structure prediction; protein-protein and protein-small molecule docking; protein structure and interface design; loop modeling; the incorporation of various types of experimental data; modeling of peptides, antibodies and proteins in the immune system, nucleic acids, non-standard chemistries, carbohydrates, and membrane proteins. We briefly discuss improvements to the energy function, user interfaces, and usability of the software. Rosetta is available at www.rosettacommons.org.

The crystal structure of dihydrofolate reductase (EC 1.5.1.3) from Escherichia coli has been solved as the binary complex with NADP+ (the holoenzyme) and as the ternary complex with NADP+ and folate. The Bragg law resolutions of the structures are 2.4 and 2.5 A, respectively. The new crystal forms are nonisomorphous with each other and with the methotrexate binary complex reported earlier [Bolin, J. T., Filman, D. J., Matthews, D. A., Hamlin, R. C., & Kraut, J. (1982) J. Biol. Chem. 257, 13650-13662]. In general, NADP+ and folate binding conform to predictions, but the nicotinamide moiety of NADP+ is disordered in the holoenzyme and ordered in the ternary complex. A mobile loop (residues 16-20) involved in binding the nicotinamide is also disordered in the holoenzyme. We report a detailed analysis of the binding interactions for both ligands, paying special attention to several apparently strained interactions that may favor the transition state for hydride transfer. Hypothetical models are presented for the binding of 7,8-dihydrofolate in the Michaelis complex and for the transition-state complex.

We describe a new method for local protein structure prediction based on a library of short sequence pattern that correlate strongly with protein three-dimensional structural elements. The library was generated using an automated method for ®nding correlations between protein sequence and local structure, and contains most previously described local sequence-structure correlations as well as new relationships, including a diverging type-II b-turn, a frayed helix, and a proline-terminated helix. The query sequence is scanned for segments 7 to 19 residues in length that strongly match one of the 82 patterns in the library. Matching segments are assigned the three-dimensional structure characteristic of the corresponding sequence pattern, and backbone torsion angles for the entire query sequence are then predicted by piecing together mutually compatible segment predictions. In predictions of local structure in a test set of 55 proteins, about 50% of all residues, and 76% of residues covered by high-con®dence predictions, were found in eight-residue segments within 1.4 A Ê of their true structures. The predictions are complementary to traditional secondary structure predictions because they are considerably more speci®c in turn regions, and may contribute to ab initio tertiary structure prediction and fold recognition.

We describe the development of a scoring function based on the decomposition P(structure/sequence) proportional to P(sequence/structure) *P(structure), which outperforms previous scoring functions in correctly identifying native-like protein structures in large ensembles of compact decoys. The first term captures sequence-dependent features of protein structures, such as the burial of hydrophobic residues in the core, the second term, universal sequence-independent features, such as the assembly of beta-strands into beta-sheets. The efficacies of a wide variety of sequence-dependent and sequence-independent features of protein structures for recognizing native-like structures were systematically evaluated using ensembles of approximately 30,000 compact conformations with fixed secondary structure for each of 17 small protein domains. The best results were obtained using a core scoring function with P(sequence/structure) parameterized similarly to our previous work (Simons et al., J Mol Biol 1997;268:209-225] and P(structure) focused on secondary structure packing preferences; while several additional features had some discriminatory power on their own, they did not provide any additional discriminatory power when combined with the core scoring function. Our results, on both the training set and the independent decoy set of Park and Levitt (J Mol Biol 1996;258:367-392), suggest that this scoring function should contribute to the prediction of tertiary structure from knowledge of sequence and secondary structure.

The crystal structure of unliganded dihydrofolate reductase (DHFR) from Escherichia coli has been solved and refined to an R factor of 19% at 2.3-A resolution in a crystal form that is nonisomorphous with each of the previously reported E. coli DHFR crystal structures [Bolin, J. T., Filman, D. J., Matthews, D. A., Hamlin, B. C., & Kraut, J. (1982) J. Biol. Chem. 257, 13650-13662; Bystroff, C., Oatley, S. J., & Kraut, J. (1990) Biochemistry 29, 3263-3277]. Significant conformational changes occur between the apoenzyme and each of the complexes: the NADP+ holoenzyme, the folate-NADP+ ternary complex, and the methotrexate (MTX) binary complex. The changes are small, with the largest about 3 A and most of them less than 1 A. For simplicity a two-domain description is adopted in which one domain contains the NADP+ 2'-phosphate binding site and the binding sites for the rest of the coenzyme and for the substrate lie between the two domains. Binding of either NADP+ or MTX induces a closing of the PABG-binding cleft and realignment of alpha-helices C and F which bind the pyrophosphate of the coenzyme. Formation of the ternary complex from the holoenzyme does not involve further relative domain shifts but does involve a shift of alpha-helix B and a floppy loop (the Met-20 loop) that precedes alpha B. These observations suggest a mechanism for cooperativity in binding between substrate and coenzyme wherein the greatest degree of cooperativity is expressed in the transition-state complex. We explore the idea that the MTX binary complex in some ways resembles the transition-state complex.

We describe a hidden Markov model, HMMSTR, for general protein sequence based on the I-sites library of sequence-structure motifs. Unlike the linear hidden Markov models used to model individual protein families, HMMSTR has a highly branched topology and captures recurrent local features of protein sequences and structures that transcend protein family boundaries. The model extends the I-sites library by describing the adjacencies of different sequence-structure motifs as observed in the protein database and, by representing overlapping motifs in a much more compact form, achieves a great reduction in parameters. The HMM attributes a considerably higher probability to coding sequence than does an equivalent dipeptide model, predicts secondary structure with an accuracy of 74.3 %, backbone torsion angles better than any previously reported method and the structural context of b strands and turns with an accuracy that should be useful for tertiary structure prediction.

We describe the development of a scoring function based on the decomposition P(structure/sequence) proportional to P(sequence/structure) *P(structure), which outperforms previous scoring functions in correctly identifying native-like protein structures in large ensembles of compact decoys. The first term captures sequence-dependent features of protein structures, such as the burial of hydrophobic residues in the core, the second term, universal sequence-independent features, such as the assembly of beta-strands into beta-sheets. The efficacies of a wide variety of sequence-dependent and sequence-independent features of protein structures for recognizing native-like structures were systematically evaluated using ensembles of approximately 30,000 compact conformations with fixed secondary structure for each of 17 small protein domains. The best results were obtained using a core scoring function with P(sequence/structure) parameterized similarly to our previous work (Simons et al., J Mol Biol 1997;268:209-225] and P(structure) focused on secondary structure packing preferences; while several additional features had some discriminatory power on their own, they did not provide any additional discriminatory power when combined with the core scoring function. Our results, on both the training set and the independent decoy set of Park and Levitt (J Mol Biol 1996;258:367-392), suggest that this scoring function should contribute to the prediction of tertiary structure from knowledge of sequence and secondary structure.

The 2.4 A crystal structure (R = 0.180) of the serine protease inhibitor ecotin was determined in a complex with trypsin. Ecotin's dimer structure provides a second discrete and distal binding site for trypsin and, as shown by modelling experiments, other serine proteases. The second site is approximately 45 A from the reactive/active site of the complex and features 13 hydrogen bonds, including six that involve carbonyl oxygen atoms and four bridged by water molecules. Contacts ecotin makes with trypsin's active site are similar to, though more extensive than, those found between trypsin and basic pancreatic trypsin inhibitor. The side chain of ecotin Met84 is found in the substrate binding pocket of trypsin where it makes few contacts, but also does not disrupt the solvent structure or cause misalignment of the scissile bond. This first case of protein dimerization being used to augment binding energy and allow chelation of a target protein provides a new model for protein‐protein interactions and for protease inhibition.