@article{Baryshev2024,

title = {Massively parallel measurement of protein–protein interactions by sequencing using MP3-seq},

author = {Alexandr Baryshev and Alyssa La Fleur and Benjamin Groves and Cirstyn Michel and David Baker and Ajasja Ljubetič and Georg Seelig},

url = {https://www.nature.com/articles/s41589-024-01718-x, Nature Chemical Biology [Open Access]},

doi = {10.1038/s41589-024-01718-x},

year  = {2024},

date = {2024-08-27},

urldate = {2024-08-27},

journal = {Nature Chemical Biology},

publisher = {Springer Science and Business Media LLC},

abstract = {Protein–protein interactions (PPIs) regulate many cellular processes and engineered PPIs have cell and gene therapy applications. Here, we introduce massively parallel PPI measurement by sequencing (MP3-seq), an easy-to-use and highly scalable yeast two-hybrid approach for measuring PPIs. In MP3-seq, DNA barcodes are associated with specific protein pairs and barcode enrichment can be read by sequencing to provide a direct measure of interaction strength. We show that MP3-seq is highly quantitative and scales to over 100,000 interactions. We apply MP3-seq to characterize interactions between families of rationally designed heterodimers and to investigate elements conferring specificity to coiled-coil interactions. Lastly, we predict coiled heterodimer structures using AlphaFold-Multimer (AF-M) and train linear models on physics-based energy terms to predict MP3-seq values. We find that AF-M-based models could be valuable for prescreening interactions but experimentally measuring interactions remains necessary to rank their strengths quantitatively.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Davila-Hernandez2023,

title = {Directing polymorph specific calcium carbonate formation with de novo protein templates},

author = {Fatima A Davila-Hernandez and Biao Jin and Harley Pyles and Shuai Zhang and Zheming Wang and Timothy F Huddy and Asim K Bera and Alex Kang and Chun-Long Chen and James J De Yoreo and David Baker},

url = {https://www.nature.com/articles/s41467-023-43608-1, Nature Communications (Open Access)},

doi = {10.1038/s41467-023-43608-1},

issn = {2041-1723},

year  = {2023},

date = {2023-12-01},

urldate = {2023-12-01},

journal = {Nature Communications},

volume = {14},

number = {1},

pages = {8191},

abstract = {Biomolecules modulate inorganic crystallization to generate hierarchically structured biominerals, but the atomic structure of the organic-inorganic interfaces that regulate mineralization remain largely unknown. We hypothesized that heterogeneous nucleation of calcium carbonate could be achieved by a structured flat molecular template that pre-organizes calcium ions on its surface. To test this hypothesis, we design helical repeat proteins (DHRs) displaying regularly spaced carboxylate arrays on their surfaces and find that both protein monomers and protein-Ca supramolecular assemblies directly nucleate nano-calcite with non-natural {110} or {202} faces while vaterite, which forms first in the absence of the proteins, is bypassed. These protein-stabilized nanocrystals then assemble by oriented attachment into calcite mesocrystals. We find further that nanocrystal size and polymorph can be tuned by varying the length and surface chemistry of the designed protein templates. Thus, bio-mineralization can be programmed using de novo protein design, providing a route to next-generation hybrid materials.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Yao2022,

title = {De novo design and directed folding of disulfide-bridged peptide heterodimers},

author = {Yao, Sicong and Moyer, Adam and Zheng, Yiwu and Shen, Yang and Meng, Xiaoting and Yuan, Chong and Zhao, Yibing and Yao, Hongwei and Baker, David and Wu, Chuanliu},

url = {https://www.nature.com/articles/s41467-022-29210-x, Nature Communications

https://www.bakerlab.org/wp-content/uploads/2022/03/Yao_etal_NatComms2022_Design_of_directed_folding_of_disulfile_bridged_peptide_heterodimers.pdf, Download PDF},

year  = {2022},

date = {2022-03-22},

urldate = {2022-03-22},

journal = {Nature Communications},

abstract = {Peptide heterodimers are prevalent in nature, which are not only functional macromolecules but molecular tools for chemical and synthetic biology. Computational methods have also been developed to design heterodimers of advanced functions. However, these peptide heterodimers are usually formed through noncovalent interactions, which are prone to dissociate and subject to concentration-dependent nonspecific aggregation. Heterodimers crosslinked with interchain disulfide bonds are more stable, but it represents a formidable challenge for both the computational design of heterodimers and the manipulation of disulfide pairing for heterodimer synthesis and applications. Here, we report the design, synthesis and application of interchain disulfide-bridged peptide heterodimers with mutual orthogonality by combining computational de novo designs with a directed disulfide pairing strategy. These heterodimers can be used as not only scaffolds for generating functional molecules but chemical tools or building blocks for protein labeling and construction of crosslinking hybrids. This study thus opens the door for using this unexplored dimeric structure space for many biological applications.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Cong2019,

title = {Protein interaction networks revealed by proteome coevolution},

author = {Qian Cong and Ivan Anishchenko and Sergey Ovchinnikov and David Baker},

url = {https://science.sciencemag.org/content/365/6449/185

https://www.bakerlab.org/wp-content/uploads/2019/07/2019_Cong_ProteomeCoevolution.pdf},

doi = {10.1126/science.aaw6718},

year  = {2019},

date = {2019-07-11},

journal = {Science},

abstract = {Residue-residue coevolution has been observed across a number of protein-protein interfaces, but the extent of residue coevolution between protein families on the whole-proteome scale has not been systematically studied. We investigate coevolution between 5.4 million pairs of proteins in Escherichia coli and between 3.9 millions pairs in Mycobacterium tuberculosis. We find strong coevolution for binary complexes involved in metabolism and weaker coevolution for larger complexes playing roles in genetic information processing. We take advantage of this coevolution, in combination with structure modeling, to predict protein-protein interactions (PPIs) with an accuracy that benchmark studies suggest is considerably higher than that of proteome-wide two-hybrid and mass spectrometry screens. We identify hundreds of previously uncharacterized PPIs in E. coli and M. tuberculosis that both add components to known protein complexes and networks and establish the existence of new ones.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Pyles2019,

title = {Controlling protein assembly on inorganic crystals through designed protein interfaces},

author = {Harley Pyles and Shuai Zhang and James J. De Yoreo and David Baker },

url = {https://www.nature.com/articles/s41586-019-1361-6

https://www.bakerlab.org/wp-content/uploads/2019/07/2019_Pyles_MicaBinder.pdf},

doi = {10.1038/s41586-019-1361-6},

year  = {2019},

date = {2019-07-10},

journal = {Nature},

abstract = {The ability of proteins and other macromolecules to interact with inorganic surfaces is essential to biological function. The proteins involved in these interactions are highly charged and often rich in carboxylic acid side chains, but the structures of most protein–inorganic interfaces are unknown. We explored the possibility of systematically designing structured protein–mineral interfaces, guided by the example of ice-binding proteins, which present arrays of threonine residues (matched to the ice lattice) that order clathrate waters into an ice-like structure6. Here we design proteins displaying arrays of up to 54 carboxylate residues geometrically matched to the potassium ion (K+) sublattice on muscovite mica (001). At low K+ concentration, individual molecules bind independently to mica in the designed orientations, whereas at high K+ concentration, the designs form two-dimensional liquid-crystal phases, which accentuate the inherent structural bias in the muscovite lattice to produce protein arrays ordered over tens of millimetres. Incorporation of designed protein–protein interactions preserving the match between the proteins and the K+ lattice led to extended self-assembled structures on mica: designed end-to-end interactions produced micrometre-long single-protein-diameter wires and a designed trimeric interface yielded extensive honeycomb arrays. The nearest-neighbour distances in these hexagonal arrays could be set digitally between 7.5 and 15.9 nanometres with 2.1-nanometre selectivity by changing the number of repeat units in the monomer. These results demonstrate that protein–inorganic lattice interactions can be systematically programmed and set the stage for designing protein–inorganic hybrid materials.



},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{PROT:PROT25006,

title = {Structure prediction using sparse simulated NOE restraints with Rosetta in CASP11},

author = {Ovchinnikov, Sergey and Park, Hahnbeom and Kim, David E. and Liu, Yuan and Wang, Ray Yu-Ruei and Baker, David},

url = {http://dx.doi.org/10.1002/prot.25006

https://www.bakerlab.org/wp-content/uploads/2016/05/Ovchinnikov_et_al-2016-Proteins__Structure_Function_and_Bioinformatics.pdf},

doi = {10.1002/prot.25006},

issn = {1097-0134},

year  = {2016},

date = {2016-01-01},

journal = {Proteins: Structure, Function, and Bioinformatics},

pages = {n/a--n/a},

abstract = {In CASP11 we generated protein structure models using simulated ambiguous and unambiguous nuclear Overhauser effect (NOE) restraints with a two stage protocol. Low resolution models were generated guided by the unambiguous restraints using continuous chain folding for alpha and alpha-beta proteins, and iterative annealing for all beta proteins to take advantage of the strand pairing information implicit in the restraints. The Rosetta fragment/model hybridization protocol was then used to recombine and regularize these models, and refine them in the Rosetta full atom energy function guided by both the unambiguous and the ambiguous restraints. Fifteen out of 19 targets were modeled with GDT-TS quality scores greater than 60 for Model 1, significantly improving upon the non-assisted predictions. Our results suggest that atomic level accuracy is achievable using sparse NOE data when there is at least one correctly assigned NOE for every residue. Proteins 2016. © 2016 Wiley Periodicals, Inc.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{S2015,

title = {Improved de novo structure prediction in CASP11 by incorporating Co-evolution information into rosetta},

author = {S Ovchinnikov and DE Kim and RY Wang and Y Liu and F DiMaio and D Baker},

url = {https://www.bakerlab.org/wp-content/uploads/2015/12/Ovchinnikov_Proteins_2015.pdf},

doi = {10.1002/prot.24974},

year  = {2015},

date = {2015-12-17},

journal = {Proteins},

abstract = {We describe CASP11 de novo blind structure predictions made using the Rosetta structure prediction methodology with both automatic and human assisted protocols. Model accuracy was generally improved using co-evolution derived residue-residue contact information as restraints during Rosetta conformational sampling and refinement, particularly when the number of sequences in the family was more than three times the length of the protein. The highlight was the human assisted prediction of T0806, a large and topologically complex target with no homologs of known structure, which had unprecedented accuracy - <3.0 Å root-mean-square deviation (RMSD) from the crystal structure over 223 residues. For this target, we increased the amount of conformational sampling over our fully automated method by employing an iterative hybridization protocol. Our results clearly demonstrate, in a blind prediction scenario, that co-evolution derived contacts can considerably increase the accuracy of template-free structure modeling. This article is protected by copyright. All rights reserved.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{611,

title = {A hybrid NMR/SAXS-based approach for discriminating oligomeric protein interfaces using Rosetta},

author = { Paolo Rossi and Lei Shi and Gaohua Liu and Christopher M Barbieri and Hsiau-Wei Lee and Thomas D Grant and Joseph R Luft and Rong Xiao and Thomas B Acton and Edward H Snell and Gaetano T Montelione and David Baker and Oliver F Lange and Nikolaos G Sgourakis},

url = {http://www.bakerlab.org/wp-content/uploads/2015/12/ahybridnmrsaxsbased_Baker2015.pdf},

doi = {10.1002/prot.24719},

issn = {1097-0134},

year  = {2015},

date = {2015-02-01},

journal = {Proteins},

volume = {83},

pages = {309-17},

abstract = {Oligomeric proteins are important targets for structure determination in solution. While in most cases the fold of individual subunits can be determined experimentally, or predicted by homology-based methods, protein-protein interfaces are challenging to determine de novo using conventional NMR structure determination protocols. Here we focus on a member of the bet-V1 superfamily, Aha1 from Colwellia psychrerythraea. This family displays a broad range of crystallographic interfaces none of which can be reconciled with the NMR and SAXS data collected for Aha1. Unlike conventional methods relying on a dense network of experimental restraints, the sparse data are used to limit conformational search during optimization of a physically realistic energy function. This work highlights a new approach for studying minor conformational changes due to structural plasticity within a single dimeric interface in solution.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{625,

title = {WeFold: a coopetition for protein structure prediction.},

author = { George A Khoury and Adam Liwo and Firas Khatib and Hongyi Zhou and Gaurav Chopra and Jaume Bacardit and Leandro O Bortot and Rodrigo A Faccioli and Xin Deng and Yi He and Pawel Krupa and Jilong Li and Magdalena A Mozolewska and Adam K Sieradzan and James Smadbeck and Tomasz Wirecki and Seth Cooper and Jeff Flatten and Kefan Xu and David Baker and Jianlin Cheng and Alexandre C B Delbem and Christodoulos A Floudas and Chen Keasar and Michael Levitt and Zoran Popovi'c and Harold A Scheraga and Jeffrey Skolnick and Silvia N Crivelli},

url = {http://www.bakerlab.org/wp-content/uploads/2015/12/Khoury_Proteins_2014.pdf},

doi = {10.1002/prot.24538},

issn = {1097-0134},

year  = {2014},

date = {2014-09-01},

journal = {Proteins},

volume = {82},

pages = {1850-68},

abstract = {The protein structure prediction problem continues to elude scientists. Despite the introduction of many methods, only modest gains were made over the last decade for certain classes of prediction targets. To address this challenge, a social-media based worldwide collaborative effort, named WeFold, was undertaken by 13 labs. During the collaboration, the laboratories were simultaneously competing with each other. Here, we present the first attempt at "coopetition" in scientific research applied to the protein structure prediction and refinement problems. The coopetition was possible by allowing the participating labs to contribute different components of their protein structure prediction pipelines and create new hybrid pipelines that they tested during CASP10. This manuscript describes both successes and areas needing improvement as identified throughout the first WeFold experiment and discusses the efforts that are underway to advance this initiative. A footprint of all contributions and structures are publicly accessible at http://www.wefold.org.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{620,

title = {High-resolution structure of the Shigella type-III secretion needle by solid-state NMR and cryo-electron microscopy.},

author = { Jean-Philippe Demers and Birgit Habenstein and Antoine Loquet and Suresh Kumar Vasa and Karin Giller and Stefan Becker and David Baker and Adam Lange and Nikolaos G Sgourakis},

url = {http://www.bakerlab.org/wp-content/uploads/2015/12/Demers_Nature_2014.pdf},

doi = {10.1038/ncomms5976},

issn = {2041-1723},

year  = {2014},

date = {2014-00-01},

journal = {Nature communications},

volume = {5},

pages = {4976},

abstract = {We introduce a general hybrid approach for determining the structures of supramolecular assemblies. Cryo-electron microscopy (cryo-EM) data define the overall envelope of the assembly and rigid-body orientation of the subunits while solid-state nuclear magnetic resonance (ssNMR) chemical shifts and distance constraints define the local secondary structure, protein fold and inter-subunit interactions. Finally, Rosetta structure calculations provide a general framework to integrate the different sources of structural information. Combining a 7.7-r A cryo-EM density map and 996 ssNMR distance constraints, the structure of the type-III secretion system needle of Shigella flexneri is determined to a precision of 0.4 r A. The calculated structures are cross-validated using an independent data set of 691 ssNMR constraints and scanning transmission electron microscopy measurements. The hybrid model resolves the conformation of the non-conserved N terminus, which occupies a protrusion in the cryo-EM density, and reveals conserved pore residues forming a continuous pattern of electrostatic interactions, thereby suggesting a mechanism for effector protein translocation.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{455,

title = {Engineering domain fusion chimeras from I-OnuI family LAGLIDADG homing endonucleases.},

author = { Sarah Baxter and Abigail R Lambert and Ryan Kuhar and Jordan Jarjour and Nadia Kulshina and Fabio Parmeggiani and Patrick Danaher and Jacob Gano and David Baker and Barry L Stoddard and Andrew M Scharenberg},

url = {http://www.bakerlab.org/wp-content/uploads/2015/12/Baxter_NuclAcRes_2012.pdf},

issn = {1362-4962},

year  = {2012},

date = {2012-09-01},

journal = {Nucleic acids research},

volume = {40},

pages = {7985-8000},

abstract = {Although engineered LAGLIDADG homing endonucleases (LHEs) are finding increasing applications in biotechnology, their generation remains a challenging, industrial-scale process. As new single-chain LAGLIDADG nuclease scaffolds are identified, however, an alternative paradigm is emerging: identification of an LHE scaffold whose native cleavage site is a close match to a desired target sequence, followed by small-scale engineering to modestly refine recognition specificity. The application of this paradigm could be accelerated if methods were available for fusing N- and C-terminal domains from newly identified LHEs into chimeric enzymes with hybrid cleavage sites. Here we have analyzed the structural requirements for fusion of domains extracted from six single-chain I-OnuI family LHEs, spanning 40-70% amino acid identity. Our analyses demonstrate that both the LAGLIDADG helical interface residues and the linker peptide composition have important effects on the stability and activity of chimeric enzymes. Using a simple domain fusion method in which linker peptide residues predicted to contact their respective domains are retained, and in which limited variation is introduced into the LAGLIDADG helix and nearby interface residues, catalytically active enzymes were recoverable for ~70% of domain chimeras. This method will be useful for creating large numbers of chimeric LHEs for genome engineering applications.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{443,

title = {Atomic model of the type III secretion system needle},

author = { Antoine Loquet and Nikolaos G Sgourakis and Rashmi Gupta and Karin Giller and Dietmar Riedel and Christian Goosmann and Christian Griesinger and Michael Kolbe and David Baker and Stefan Becker and Adam Lange},

url = {https://www.bakerlab.org/wp-content/uploads/2018/06/nature11079.pdf

https://www.nature.com/articles/nature11079},

doi = {10.1038/nature11079},

year  = {2012},

date = {2012-01-01},

journal = {Nature},

abstract = {Pathogenic bacteria using a type III secretion system (T3SS) to manipulate host cells cause many different infections including Shigella dysentery, typhoid fever, enterohaemorrhagic colitis and bubonic plague. An essential part of the T3SS is a hollow needlelike protein filament through which effector proteins are injected into eukaryotic host cells3–6. Currently, the three-dimensional structure of the needle is unknown because it is not amenable to X-ray crystallography and solution NMR, as a result of its inherent non-crystallinity and insolubility. Cryo-electron microscopy combined with crystal or solution NMRsubunit structures has recently provided a powerful hybrid approach for studying supramolecular assemblies7–12, esulting in low-resolution and medium-resolution models13–17. However, such approaches cannot deliver atomic details, especially of the crucial subunit–subunit interfaces, because of the limited cryo-electron microscopic resolution obtained in these studies. Here we report an alternative approach combining recombinant wild-type needle production, solid-state NMR, electron microscopy and Rosetta modelling to reveal the supramolecular interfaces and ultimately the complete atomic structure of the Salmonella typhimurium T3SS needle. We show that the 80-residue subunits form a right-handed helical assembly with roughly 11 subunits per two turns, similar to that of the flagellar filament of S. typhimurium. In contrast to established models of the needle in which the amino terminus of the protein subunit was assumed to be a-helical and positioned inside the needle, our model reveals an extended amino-terminal domain that is positioned on the surface of the needle, while the highly conserved carboxy terminus points towards the lumen.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{258,

title = {Accurate automated protein NMR structure determination using unassigned NOESY data},

author = { Srivatsan Raman and Yuanpeng J Huang and Binchen Mao and Paolo Rossi and James M Aramini and Gaohua Liu and Gaetano T Montelione and David Baker},

issn = {1520-5126},

year  = {2010},

date = {2010-01-01},

journal = {Journal of the American Chemical Society},

volume = {132},

pages = {202-7},

abstract = {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.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{132,

title = {Rationally designed integrin beta3 mutants stabilized in the high affinity conformation},

author = { Bing-Hao Luo and John Karanicolas and Laura D Harmacek and David Baker and Timothy A Springer},

issn = {0021-9258},

year  = {2009},

date = {2009-02-01},

journal = {The Journal of biological chemistry},

volume = {284},

pages = {3917-24},

abstract = {Integrins are important cell surface receptors that transmit bidirectional signals across the membrane. It has been shown that a conformational change of the integrin beta-subunit headpiece (i.e. the beta I domain and the hybrid domain) plays a critical role in regulating integrin ligand binding affinity and function. Previous studies have used coarse methods (a glycan wedge, mutations in transmembrane contacts) to force the beta-subunit into either the open or closed conformation. Here, we demonstrate a detailed understanding of this conformational change by applying computational design techniques to select five amino acid side chains that play an important role in the energetic balance between the open and closed conformations of alphaIIbbeta3. Eight single-point mutants were designed at these sites, of which five bound ligands much better than wild type. Further, these mutants were found to be in a more extended conformation than wild type, suggesting that the conformational change at the ligand binding headpiece was propagated to the legs of the integrin. This detailed understanding of the conformational change will assist in the development of allosteric drugs that either stabilize or destabilize specific integrin conformations without occluding the ligand-binding site.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{291,

title = {Ab initio modeling of the herpesvirus VP26 core domain assessed by CryoEM density},

author = { Matthew L Baker and Wen Jiang and William J Wedemeyer and Frazer J Rixon and David Baker and Wah Chiu},

url = {https://www.bakerlab.org/wp-content/uploads/2016/07/baker06B.pdf},

issn = {1553-7358},

year  = {2006},

date = {2006-10-01},

journal = {PLoS computational biology},

volume = {2},

pages = {e146},

abstract = {Efforts in structural biology have targeted the systematic determination of all protein structures through experimental determination or modeling. In recent years, 3-D electron cryomicroscopy (cryoEM) has assumed an increasingly important role in determining the structures of these large macromolecular assemblies to intermediate resolutions (6-10 A). While these structures provide a snapshot of the assembly and its components in well-defined functional states, the resolution limits the ability to build accurate structural models. In contrast, sequence-based modeling techniques are capable of producing relatively robust structural models for isolated proteins or domains. In this work, we developed and applied a hybrid modeling approach, utilizing cryoEM density and ab initio modeling to produce a structural model for the core domain of a herpesvirus structural protein, VP26. Specifically, this method, first tested on simulated data, utilizes the cryoEM density map as a geometrical constraint in identifying the most native-like models from a gallery of models generated by ab initio modeling. The resulting model for the core domain of VP26, based on the 8.5-A resolution herpes simplex virus type 1 (HSV-1) capsid cryoEM structure and mutational data, exhibited a novel fold. Additionally, the core domain of VP26 appeared to have a complementary interface to the known upper-domain structure of VP5, its cognate binding partner. While this new model provides for a better understanding of the assembly and interactions of VP26 in HSV-1, the approach itself may have broader applications in modeling the components of large macromolecular assemblies.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{100,

title = {Automated prediction of domain boundaries in CASP6 targets using Ginzu and RosettaDOM},

author = { David E Kim and Dylan Chivian and Lars Malmstr"om and David Baker},

url = {https://www.bakerlab.org/wp-content/uploads/2016/07/kim05A.pdf},

issn = {1097-0134},

year  = {2005},

date = {2005-00-01},

journal = {Proteins},

volume = {61 Suppl 7},

pages = {193-200},

abstract = {Domain boundary prediction is an important step in both experimental and computational protein structure characterization. We have developed two fully automated domain parsing methods: the first, Ginzu, which we have described previously, utilizes information from homologous sequences and structures, while the second, RosettaDOM, which has not been described previously, uses only information in the query sequence. Ginzu iteratively assigns domains by homology to structures and sequence families using successively less confident methods. RosettaDOM uses the Rosetta de novo structure prediction method to build three-dimensional models, and then applies Taylortextquoterights structure based domain assignment method to parse the models into domains. Domain boundaries observed repeatedly in the models are predicted to be domain boundaries for the protein. Interestingly, RosettaDOM produced quite good domain predictions for proteins of a size typically considered to be beyond the reach of de novo structure prediction methods. For remote fold recognition targets and new folds, both Ginzu and RosettaDOM produced promising results, and in some cases where one method failed to detect the correct domain boundary, it was correctly identified by the other method. We describe here the successes and failures using both methods, and address the possibility of incorporating both protocols into an improved hybrid method.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{314,

title = {Assigning function to yeast proteins by integration of technologies},

author = { Tony R Hazbun and Lars Malmstr"om and Scott Anderson and Beth J Graczyk and Bethany Fox and Michael Riffle and Bryan A Sundin and J Derringer Aranda and W Hayes McDonald and Chun-Hwei Chiu and Brian E Snydsman and Phillip Bradley and Eric G D Muller and Stanley Fields and David Baker and John R Yates and Trisha N Davis},

url = {https://www.bakerlab.org/wp-content/uploads/2016/06/hazbun03A.pdf},

issn = {1097-2765},

year  = {2003},

date = {2003-12-01},

journal = {Molecular cell},

volume = {12},

pages = {1353-65},

abstract = {Interpreting genome sequences requires the functional analysis of thousands of predicted proteins, many of which are uncharacterized and without obvious homologs. To assess whether the roles of large sets of uncharacterized genes can be assigned by targeted application of a suite of technologies, we used four complementary protein-based methods to analyze a set of 100 uncharacterized but essential open reading frames (ORFs) of the yeast Saccharomyces cerevisiae. These proteins were subjected to affinity purification and mass spectrometry analysis to identify copurifying proteins, two-hybrid analysis to identify interacting proteins, fluorescence microscopy to localize the proteins, and structure prediction methodology to predict structural domains or identify remote homologies. Integration of the data assigned function to 48 ORFs using at least two of the Gene Ontology (GO) categories of biological process, molecular function, and cellular component; 77 ORFs were annotated by at least one method. This combination of technologies, coupled with annotation using GO, is a powerful approach to classifying genes.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{182,

title = {Simple physical models connect theory and experiment in protein folding kinetics},

author = { Eric Alm and Alexandre V Morozov and Tanja Kortemme and David Baker},

url = {https://www.bakerlab.org/wp-content/uploads/2016/06/alm02A.pdf},

issn = {0022-2836},

year  = {2002},

date = {2002-09-01},

journal = {Journal of molecular biology},

volume = {322},

pages = {463-76},

abstract = {Our understanding of the principles underlying the protein-folding problem can be tested by developing and characterizing simple models that make predictions which can be compared to experimental data. Here we extend our earlier model of folding free energy landscapes, in which each residue is considered to be either folded as in the native state or completely disordered, by investigating the role of additional factors representing hydrogen bonding and backbone torsion strain, and by using a hybrid between the master equation approach and the simple transition state theory to evaluate kinetics near the free energy barrier in greater detail. Model calculations of folding phi-values are compared to experimental data for 19 proteins, and for more than half of these, experimental data are reproduced with correlation coefficients between r=0.41 and 0.88; calculations of transition state free energy barriers correlate with rates measured for 37 single domain proteins (r=0.69). The model provides insight into the contribution of alternative-folding pathways, the validity of quasi-equilibrium treatments of the folding landscape, and the magnitude of the Arrhenius prefactor for protein folding. Finally, we discuss the limitations of simple native-state-based models, and as a more general test of such models, provide predictions of folding rates and mechanisms for a comprehensive set of over 400 small protein domains of known structure.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}