Foldit is a multiplayer online game in which players collaborate and compete to create accurate protein structure models. For specific hard problems, Foldit player solutions can in some cases outperform state-of-the-art computational methods. However, very little is known about how collaborative gameplay produces these results and whether Foldit player strategies can be formalized and structured so that they can be used by computers. To determine whether high performing player strategies could be collectively codified, we augmented the Foldit gameplay mechanics with tools for players to encode their folding strategies as "recipes" and to share their recipes with other players, who are able to further modify and redistribute them. Here we describe the rapid social evolution of player-developed folding algorithms that took place in the year following the introduction of these tools. Players developed over 5,400 different recipes, both by creating new algorithms and by modifying and recombining successful recipes developed by other players. The most successful recipes rapidly spread through the Foldit player population, and two of the recipes became particularly dominant. Examination of the algorithms encoded in these two recipes revealed a striking similarity to an unpublished algorithm developed by scientists over the same period. Benchmark calculations show that the new algorithm independently discovered by scientists and by Foldit players outperforms previously published methods. Thus, online scientific game frameworks have the potential not only to solve hard scientific problems, but also to discover and formalize effective new strategies and algorithms.

Mason-Pfizer monkey virus (M-PMV), a D-type retrovirus assembling in the cytoplasm, causes simian acquired immunodeficiency syndrome (SAIDS) in rhesus monkeys. Its pepsin-like aspartic protease (retropepsin) is an integral part of the expressed retroviral polyproteins. As in all retroviral life cycles, release and dimerization of the protease (PR) is strictly required for polyprotein processing and virion maturation. Biophysical and NMR studies have indicated that in the absence of substrates or inhibitors M-PMV PR should fold into a stable monomer, but the crystal structure of this protein could not be solved by molecular replacement despite countless attempts. Ultimately, a solution was obtained in mr-rosetta using a model constructed by players of the online protein-folding game Foldit. The structure indeed shows a monomeric protein, with the N- and C-termini completely disordered. On the other hand, the flap loop, which normally gates access to the active site of homodimeric retropepsins, is clearly traceable in the electron density. The flap has an unusual curled shape and a different orientation from both the open and closed states known from dimeric retropepsins. The overall fold of the protein follows the retropepsin canon, but the C(α) deviations are large and the active-site 'DTG' loop (here NTG) deviates up to 2.7 Å from the standard conformation. This structure of a monomeric retropepsin determined at high resolution (1.6 Å) provides important extra information for the design of dimerization inhibitors that might be developed as drugs for the treatment of retroviral infections, including AIDS.

We have recently completed a full re-architecturing of the ROSETTA molecular modeling program, generalizing and expanding its existing functionality. The new architecture enables the rapid prototyping of novel protocols by providing easy-to-use interfaces to powerful tools for molecular modeling. The source code of this rearchitecturing has been released as ROSETTA3 and is freely available for academic use. At the time of its release, it contained 470,000 lines of code. Counting currently unpublished protocols at the time of this writing, the source includes 1,285,000 lines. Its rapid growth is a testament to its ease of use. This chapter describes the requirements for our new architecture, justifies the design decisions, sketches out central classes, and highlights a few of the common tasks that the new software can perform.

People exert large amounts of problem-solving effort playing computer games. Simple image- and text-recognition tasks have been successfully 'crowd-sourced' through games, but it is not clear if more complex scientific problems can be solved with human-directed computing. Protein structure prediction is one such problem: locating the biologically relevant native conformation of a protein is a formidable computational challenge given the very large size of the search space. Here we describe Foldit, a multiplayer online game that engages non-scientists in solving hard prediction problems. Foldit players interact with protein structures using direct manipulation tools and user-friendly versions of algorithms from the Rosetta structure prediction methodology, while they compete and collaborate to optimize the computed energy. We show that top-ranked Foldit players excel at solving challenging structure refinement problems in which substantial backbone rearrangements are necessary to achieve the burial of hydrophobic residues. Players working collaboratively develop a rich assortment of new strategies and algorithms; unlike computational approaches, they explore not only the conformational space but also the space of possible search strategies. The integration of human visual problem-solving and strategy development capabilities with traditional computational algorithms through interactive multiplayer games is a powerful new approach to solving computationally-limited scientific problems.

Computational enzyme design holds promise for the production of renewable fuels, drugs and chemicals. De novo enzyme design has generated catalysts for several reactions, but with lower catalytic efficiencies than naturally occurring enzymes. Here we report the use of game-driven crowdsourcing to enhance the activity of a computationally designed enzyme through the functional remodeling of its structure. Players of the online game Foldit were challenged to remodel the backbone of a computationally designed bimolecular Diels-Alderase to enable additional interactions with substrates. Several iterations of design and characterization generated a 24-residue helix-turn-helix motif, including a 13-residue insertion, that increased enzyme activity >18-fold. X-ray crystallography showed that the large insertion adopts a helix-turn-helix structure positioned as in the Foldit model. These results demonstrate that human creativity can extend beyond the macroscopic challenges encountered in everyday life to molecular-scale design problems.

Foldit is a multiplayer online game in which players collaborate and compete to create accurate protein structure models. For specific hard problems, Foldit player solutions can in some cases outperform state-of-the-art computational methods. However, very little is known about how collaborative gameplay produces these results and whether Foldit player strategies can be formalized and structured so that they can be used by computers. To determine whether high performing player strategies could be collectively codified, we augmented the Foldit gameplay mechanics with tools for players to encode their folding strategies as "recipes" and to share their recipes with other players, who are able to further modify and redistribute them. Here we describe the rapid social evolution of player-developed folding algorithms that took place in the year following the introduction of these tools. Players developed over 5,400 different recipes, both by creating new algorithms and by modifying and recombining successful recipes developed by other players. The most successful recipes rapidly spread through the Foldit player population, and two of the recipes became particularly dominant. Examination of the algorithms encoded in these two recipes revealed a striking similarity to an unpublished algorithm developed by scientists over the same period. Benchmark calculations show that the new algorithm independently discovered by scientists and by Foldit players outperforms previously published methods. Thus, online scientific game frameworks have the potential not only to solve hard scientific problems, but also to discover and formalize effective new strategies and algorithms.

We describe predictions made using the Rosetta structure prediction methodology for the Eighth Critical Assessment of Techniques for Protein Structure Prediction. Aggressive sampling and all-atom refinement were carried out for nearly all targets. A combination of alignment methodologies was used to generate starting models from a range of templates, and the models were then subjected to Rosetta all atom refinement. For the 64 domains with readily identified templates, the best submitted model was better than the best alignment to the best template in the Protein Data Bank for 24 cases, and improved over the best starting model for 43 cases. For 13 targets where only very distant sequence relationships to proteins of known structure were detected, models were generated using the Rosetta de novo structure prediction methodology followed by all-atom refinement; in several cases the submitted models were better than those based on the available templates. Of the 12 refinement challenges, the best submitted model improved on the starting model in seven cases. These improvements over the starting template-based models and refinement tests demonstrate the power of Rosetta structure refinement in improving model accuracy. Proteins 2009.(c) 2009 Wiley-Liss, Inc.

The combination of algorithms from the structure-modeling field with those of crystallographic structure determination can broaden the range of templates that are useful for structure determination by the method of molecular replacement. Automated tools in phenix.mr_rosetta simplify the application of these combined approaches by integrating Phenix crystallographic algorithms and Rosetta structure-modeling algorithms and by systematically generating and evaluating models with a combination of these methods. The phenix.mr_rosetta algorithms can be used to automatically determine challenging structures. The approaches used in phenix.mr_rosetta are described along with examples that show roles that structure-modeling can play in molecular replacement.

Although the physiological role of APOBEC2 is still largely unknown, a crystal structure of a truncated variant of this protein was determined several years ago [Prochnow, C.(2007) Nature445, 447-451]. This APOBEC2 structure had considerable impact in the HIV field because it was considered a good model for the structure of APOBEC3G, an important HIV restriction factor that abrogates HIV infectivity in the absence of the viral accessory protein Vif. The quaternary structure and the arrangement of the monomers of APOBEC2 in the crystal were taken as being representative for APOBEC3G and exploited in explaining its enzymatic and anti-HIV activity. Here we show, unambiguously, that in contrast to the findings for the crystal, APOBEC2 is monomeric in solution. The nuclear magnetic resonance solution structure of full-length APOBEC2 reveals that the N-terminal tail that was removed for crystallization resides close to strand β2, the dimer interface in the crystal structure, and shields this region of the protein from engaging in intermolecular contacts. In addition, the presence of the N-terminal region drastically alters the aggregation propensity of APOBEC2, rendering the full-length protein highly soluble and not prone to precipitation. In summary, our results cast doubt on all previous structure-function predictions for APOBEC3G that were based on the crystal structure of APOBEC2.

Initiation of the innate immune response requires agonist recognition by pathogen-recognition receptors such as the Toll-like receptors (TLRs). Toll/interleukin-1 receptor (TIR) domain-containing adaptors are critical in orchestrating the signal transduction pathways after TLR and interleukin-1 receptor activation. Myeloid differentiation primary response gene 88 (MyD88) adaptor-like (MAL)/TIR domain-containing adaptor protein (TIRAP) is involved in bridging MyD88 to TLR2 and TLR4 in response to bacterial infection. Genetic studies have associated a number of unique single-nucleotide polymorphisms in MAL with protection against invasive microbial infection, but a molecular understanding has been hampered by a lack of structural information. The present study describes the crystal structure of MAL TIR domain. Significant structural differences exist in the overall fold of MAL compared with other TIR domain structures: A sequence motif comprising a β-strand in other TIR domains instead corresponds to a long loop, placing the functionally important "BB loop" proline motif in a unique surface position in MAL. The structure suggests possible dimerization and MyD88-interacting interfaces, and we confirm the key interface residues by coimmunoprecipitation using site-directed mutants. Jointly, our results provide a molecular and structural basis for the role of MAL in TLR signaling and disease protection.

Cyclophilins constitute a class of peptidyl-prolyl isomerases which participate in processes related to protein folding, signalling and chaperoning. The crystal structure of the cytoplasmic cyclophilin A (CyPA) from the bacterium Azotobacter vinelandii complexed with a synthetic tetrapeptide was determined by molecular replacement at 2 Å resolution. The proline in the tetrapeptide is observed to adopt the cis-isomer conformation. Comparisons of this structure with other CyPA structures provide insights into the conformational variability, effects of peptide binding and structure-function relationships of this enzyme.

The combination of algorithms from the structure-modeling field with those of crystallographic structure determination can broaden the range of templates that are useful for structure determination by the method of molecular replacement. Automated tools in phenix.mr_rosetta simplify the application of these combined approaches by integrating Phenix crystallographic algorithms and Rosetta structure-modeling algorithms and by systematically generating and evaluating models with a combination of these methods. The phenix.mr_rosetta algorithms can be used to automatically determine challenging structures. The approaches used in phenix.mr_rosetta are described along with examples that show roles that structure-modeling can play in molecular replacement.

Mason-Pfizer monkey virus (M-PMV), a D-type retrovirus assembling in the cytoplasm, causes simian acquired immunodeficiency syndrome (SAIDS) in rhesus monkeys. Its pepsin-like aspartic protease (retropepsin) is an integral part of the expressed retroviral polyproteins. As in all retroviral life cycles, release and dimerization of the protease (PR) is strictly required for polyprotein processing and virion maturation. Biophysical and NMR studies have indicated that in the absence of substrates or inhibitors M-PMV PR should fold into a stable monomer, but the crystal structure of this protein could not be solved by molecular replacement despite countless attempts. Ultimately, a solution was obtained in mr-rosetta using a model constructed by players of the online protein-folding game Foldit. The structure indeed shows a monomeric protein, with the N- and C-termini completely disordered. On the other hand, the flap loop, which normally gates access to the active site of homodimeric retropepsins, is clearly traceable in the electron density. The flap has an unusual curled shape and a different orientation from both the open and closed states known from dimeric retropepsins. The overall fold of the protein follows the retropepsin canon, but the C(α) deviations are large and the active-site 'DTG' loop (here NTG) deviates up to 2.7 Å from the standard conformation. This structure of a monomeric retropepsin determined at high resolution (1.6 Å) provides important extra information for the design of dimerization inhibitors that might be developed as drugs for the treatment of retroviral infections, including AIDS.

Essentially the same steps are required to solve the crystal structure of a serpin as for any other protein: produce and purify protein, grow crystals, collect diffraction data, find estimates of the phase angles, and then refine and validate the structure. For the phasing step, experimental phasing methods involving heavy atom soaks were required for the first few structures, but with the large number of serpin structures now available, molecular replacement has become the method of choice. Two things are special about serpins. First, because of the central role of conformational change in serpin mechanism, it is advisable to consider a variety of molecular replacement models in different conformations and then to allow for rigid-body motions in the initial refinement steps. Second, probably owing to the flexibility of serpins, the average serpin crystal is significantly less well ordered than the average crystal of another protein, which increases the difficulty of solving and refining their structures.

Molecular replacement (MR) is widely used for addressing the phase problem in X-ray crystallography. Historically, crystallographers have had limited success using NMR structures as MR search models. Here, we report a comprehensive investigation of the utility of protein NMR ensembles as MR search models, using data for 25 pairs of X-ray and NMR structures solved and refined using modern NMR methods. Starting from NMR ensembles prepared by an improved protocol, FindCore, correct MR solutions were obtained for 22 targets. Based on these solutions, automatic model rebuilding could be done successfully. Rosetta refinement of NMR structures provided MR solutions for another two proteins. We also demonstrate that such properly prepared NMR ensembles and X-ray crystal structures have similar performance when used as MR search models for homologous structures, particularly for targets with sequence identity >40%.

P2, the major capsid protein of bacteriophage PM2, adopts the double β-barrel fold characteristic of the PRD1-adenoviral lineage. The 2.5 Å resolution X-ray data obtained by analysis of the two major lattices of a multiple crystal of P2 were phased by molecular replacement, using as a search model structure factors to 7.6 Å resolution obtained from electron density cut from the map of the entire PM2 virion. Phase extension to 2.5 Å resolution used solely sixfold cycling averaging and solvent flattening. This represents an atypical example of an oligomeric protein for which the structure has been determined at high resolution by bootstrapping from low-resolution initial phases.

Tfb5 interacts with the Tfb2 subunit of the general transcription factor TFIIH to ensure efficient nucleotide-excision repair in eukaryotes. The crystal structure of the complex between Tfb5 and the C-terminal region of Tfb2 (Tfb2C) from Saccharomyces cerevisiae has recently been reported. Here, the structure-determination process is described as a case study. Although crystals were obtained readily, it was not possible to determine experimental phases from a first crystal form (Tfb2(412-513)-Tfb5(2-72)) that diffracted to 2.6 A resolution. Shortening of the Tfb2C from its N-terminus was decisive and modified the crystal packing, leading to a second crystal form (Tfb2(435-513)-Tfb5(2-72)). These crystals diffracted to 1.7 A resolution with excellent mosaicity and allowed structure determination by conventional approaches using heavy atoms. The refined structure from the second crystal form was used to solve the structure of the first crystal form by molecular replacement. Comparison of the two structures revealed that the N-terminal region of Tfb2C and (to a lesser extent) the C-terminal region of Tfb5 contributed to the crystal packing. A detailed analysis illustrates how variation in domain boundaries influences crystal packing and quality.

An approach is presented for the structure determination of membrane proteins on the basis of poorly diffracting crystals which exploits molecular replacement for heavy-atom site identification at 6-9 A maximum resolution and improvement of the heavy-atom-derived phases by multi-crystal averaging using quasi-isomorphous data sets. The multi-crystal averaging procedure allows real-space density averaging followed by phase combination between non-isomorphous native data sets to exploit crystal-to-crystal nonisomorphism despite the crystals belonging to the same space group. This approach has been used in the structure determination of H(+)-ATPase and Na(+),K(+)-ATPase using Ca(2+)-ATPase models and its successful application to the Mhp1 symporter using LeuT as a search model is demonstrated.

Conventional NMR structure determination requires nearly complete assignment of the cross peaks of a refined NOESY peak list. Depending on the size of the protein and quality of the spectral data, this can be a time-consuming manual process requiring several rounds of peak list refinement and structure determination. Programs such as Aria, CYANA, and AutoStructure can generate models using unassigned NOESY data but are very sensitive to the quality of the input peak lists and can converge to inaccurate structures if the signal-to-noise of the peak lists is low. Here, we show that models with high accuracy and reliability can be produced by combining the strengths of the high-resolution structure prediction program Rosetta with global measures of the agreement between structure models and experimental data. A first round of models generated using CS-Rosetta (Rosetta supplemented with backbone chemical shift information) are filtered on the basis of their goodness-of-fit with unassigned NOESY peak lists using the DP-score, and the best fitting models are subjected to high resolution refinement with the Rosetta rebuild-and-refine protocol. This hybrid approach uses both local backbone chemical shift and the unassigned NOESY data to direct Rosetta trajectories toward the native structure and produces more accurate models than AutoStructure/CYANA or CS-Rosetta alone, particularly when using raw unedited NOESY peak lists. We also show that when accurate manually refined NOESY peak lists are available, Rosetta refinement can consistently increase the accuracy of models generated using CYANA and AutoStructure.

Toxoplasmosis is a chronic infection that affects approximately 30% of the human population and is caused by Toxoplasma gondii. Determination of the three dimensional structure of PNP from T. gondii could provide new insights into the purine binding site and sub-strate binding, and could be used for future rational design of new drugs against toxoplasmosis. This work describes the molecular model for three dimensional structure of PNP from T.gondii using, as a template, PNP from Plasmodium falciparum. Molecular dynamics showed that this model is stable during a trajectory of 3 ns.