Publications
Preprints available on bioRxiv.
Krzysiak, Troy C; Jung, Jinwon; Thompson, James; Baker, David; Gronenborn, Angela M
APOBEC2 is a monomer in solution: implications for APOBEC3G models Journal Article
In: Biochemistry, vol. 51, pp. 2008-17, 2012, ISSN: 1520-4995.
@article{604,
title = {APOBEC2 is a monomer in solution: implications for APOBEC3G models},
author = { Troy C Krzysiak and Jinwon Jung and James Thompson and David Baker and Angela M Gronenborn},
url = {http://beta.baker/wp-content/uploads/2015/12/apobec2isamonomer_Baker2012.pdf},
doi = {10.1021/bi300021s},
issn = {1520-4995},
year = {2012},
date = {2012-03-01},
journal = {Biochemistry},
volume = {51},
pages = {2008-17},
abstract = {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.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Lange, Oliver F; Baker, David
Resolution-adapted recombination of structural features significantly improves sampling in restraint-guided structure calculation. Journal Article
In: Proteins, vol. 80, pp. 884-95, 2012, ISSN: 1097-0134.
@article{460,
title = {Resolution-adapted recombination of structural features significantly improves sampling in restraint-guided structure calculation.},
author = { Oliver F Lange and David Baker},
url = {http://beta.baker/wp-content/uploads/2015/12/Lange_Proteins_2012.pdf},
issn = {1097-0134},
year = {2012},
date = {2012-03-01},
journal = {Proteins},
volume = {80},
pages = {884-95},
abstract = {Recent work has shown that NMR structures can be determined by integrating sparse NMR data with structure prediction methods such as Rosetta. The experimental data serve to guide the search for the lowest energy state towards the deep minimum at the native state which is frequently missed in Rosetta de novo structure calculations. However, as the protein size increases, sampling again becomes limiting; for example, the standard Rosetta protocol involving Monte Carlo fragment insertion starting from an extended chain fails to converge for proteins over 150 amino acids even with guidance from chemical shifts (CS-Rosetta) and other NMR data. The primary limitation of this protocol--that every folding trajectory is completely independent of every other--was recently overcome with the development of a new approach involving resolution-adapted structural recombination (RASREC). Here we describe the RASREC approach in detail and compare it to standard CS-Rosetta. We show that the improved sampling of RASREC is essential in obtaining accurate structures over a benchmark set of 11 proteins in the 15-25 kDa size range using chemical shifts, backbone RDCs and HN-HN NOE data; in a number of cases the improved sampling methodology makes a larger contribution than incorporation of additional experimental data. Experimental data are invaluable for guiding sampling to the vicinity of the global energy minimum, but for larger proteins, the standard Rosetta fold-from-extended-chain protocol does not converge on the native minimum even with experimental data and the more powerful RASREC approach is necessary to converge to accurate solutions.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Handl, Julia; Knowles, Joshua; Vernon, Robert; Baker, David; Lovell, Simon C
The dual role of fragments in fragment-assembly methods for de novo protein structure prediction Journal Article
In: Proteins, vol. 80, pp. 490-504, 2012, ISSN: 1097-0134.
@article{601,
title = {The dual role of fragments in fragment-assembly methods for de novo protein structure prediction},
author = { Julia Handl and Joshua Knowles and Robert Vernon and David Baker and Simon C Lovell},
url = {https://www.bakerlab.org/wp-content/uploads/2018/06/Handl_et_al-2012-Proteins3A_Structure2C_Function2C_and_Bioinformatics.pdf
https://onlinelibrary.wiley.com/doi/full/10.1002/prot.23215},
doi = {10.1002/prot.23215},
issn = {1097-0134},
year = {2012},
date = {2012-02-01},
journal = {Proteins},
volume = {80},
pages = {490-504},
abstract = {In fragment-assembly techniques for protein structure prediction, models of protein structure are assembled from fragments of known protein structures. This process is typically guided by a knowledge-based energy function and uses a heuristic optimization method. The fragments play two important roles in this process: they define the set of structural parameters available, and they also assume the role of the main variation operators that are used by the optimiser. Previous analysis has typically focused on the first of these roles. In particular, the relationship between local amino acid sequence and local protein structure has been studied by a range of authors. The correlation between the two has been shown to vary with the window length considered, and the results of these analyses have informed directly the choice of fragment length in state-of-the-art prediction techniques. Here, we focus on the second role of fragments and aim to determine the effect of fragment length from an optimization perspective. We use theoretical analyses to reveal how the size and structure of the search space changes as a function of insertion length. Furthermore, empirical analyses are used to explore additional ways in which the size of the fragment insertion influences the search both in a simulation model and for the fragment-assembly technique, Rosetta.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Fleishman, Sarel J; Whitehead, Timothy A; Strauch, Eva-Maria; Corn, Jacob E; Qin, Sanbo; Zhou, Huan-Xiang; Mitchell, Julie C; Demerdash, Omar N A; Takeda-Shitaka, Mayuko; Terashi, Genki; Moal, Iain H; Li, Xiaofan; Bates, Paul A; Zacharias, Martin; Park, Hahnbeom; Ko, Jun-su; Lee, Hasup; Seok, Chaok; Bourquard, Thomas; Bernauer, Julie; Poupon, Anne; Az’e, J’er^ome; Soner, Seren; Ovali, Sefik Kerem; Ozbek, Pemra; Tal, Nir Ben; Haliloglu, T"urkan; Hwang, Howook; Vreven, Thom; Pierce, Brian G; Weng, Zhiping; P’erez-Cano, Laura; Pons, Carles; Fern’andez-Recio, Juan; Jiang, Fan; Yang, Feng; Gong, Xinqi; Cao, Libin; Xu, Xianjin; Liu, Bin; Wang, Panwen; Li, Chunhua; Wang, Cunxin; Robert, Charles H; Guharoy, Mainak; Liu, Shiyong; Huang, Yangyu; Li, Lin; Guo, Dachuan; Chen, Ying; Xiao, Yi; London, Nir; Itzhaki, Zohar; Schueler-Furman, Ora; Inbar, Yuval; Potapov, Vladimir; Cohen, Mati; Schreiber, Gideon; Tsuchiya, Yuko; Kanamori, Eiji; Standley, Daron M; Nakamura, Haruki; Kinoshita, Kengo; Driggers, Camden M; Hall, Robert G; Morgan, Jessica L; Hsu, Victor L; Zhan, Jian; Yang, Yuedong; Zhou, Yaoqi; Kastritis, Panagiotis L; Bonvin, Alexandre M J J; Zhang, Weiyi; Camacho, Carlos J; Kilambi, Krishna P; Sircar, Aroop; Gray, Jeffrey J; Ohue, Masahito; Uchikoga, Nobuyuki; Matsuzaki, Yuri; Ishida, Takashi; Akiyama, Yutaka; Khashan, Raed; Bush, Stephen; Fouches, Denis; Tropsha, Alexander; Esquivel-Rodr’iguez, Juan; Kihara, Daisuke; Stranges, P Benjamin; Jacak, Ron; Kuhlman, Brian; Huang, Sheng-You; Zou, Xiaoqin; Wodak, Shoshana J; Janin, Joel; Baker, David
Community-wide assessment of protein-interface modeling suggests improvements to design methodology Journal Article
In: Journal of Molecular Biology, vol. 414, pp. 289-302, 2011, ISSN: 1089-8638.
@article{598,
title = {Community-wide assessment of protein-interface modeling suggests improvements to design methodology},
author = { Sarel J Fleishman and Timothy A Whitehead and Eva-Maria Strauch and Jacob E Corn and Sanbo Qin and Huan-Xiang Zhou and Julie C Mitchell and Omar N A Demerdash and Mayuko Takeda-Shitaka and Genki Terashi and Iain H Moal and Xiaofan Li and Paul A Bates and Martin Zacharias and Hahnbeom Park and Jun-su Ko and Hasup Lee and Chaok Seok and Thomas Bourquard and Julie Bernauer and Anne Poupon and J'er^ome Az'e and Seren Soner and Sefik Kerem Ovali and Pemra Ozbek and Nir Ben Tal and T"urkan Haliloglu and Howook Hwang and Thom Vreven and Brian G Pierce and Zhiping Weng and Laura P'erez-Cano and Carles Pons and Juan Fern'andez-Recio and Fan Jiang and Feng Yang and Xinqi Gong and Libin Cao and Xianjin Xu and Bin Liu and Panwen Wang and Chunhua Li and Cunxin Wang and Charles H Robert and Mainak Guharoy and Shiyong Liu and Yangyu Huang and Lin Li and Dachuan Guo and Ying Chen and Yi Xiao and Nir London and Zohar Itzhaki and Ora Schueler-Furman and Yuval Inbar and Vladimir Potapov and Mati Cohen and Gideon Schreiber and Yuko Tsuchiya and Eiji Kanamori and Daron M Standley and Haruki Nakamura and Kengo Kinoshita and Camden M Driggers and Robert G Hall and Jessica L Morgan and Victor L Hsu and Jian Zhan and Yuedong Yang and Yaoqi Zhou and Panagiotis L Kastritis and Alexandre M J J Bonvin and Weiyi Zhang and Carlos J Camacho and Krishna P Kilambi and Aroop Sircar and Jeffrey J Gray and Masahito Ohue and Nobuyuki Uchikoga and Yuri Matsuzaki and Takashi Ishida and Yutaka Akiyama and Raed Khashan and Stephen Bush and Denis Fouches and Alexander Tropsha and Juan Esquivel-Rodr'iguez and Daisuke Kihara and P Benjamin Stranges and Ron Jacak and Brian Kuhlman and Sheng-You Huang and Xiaoqin Zou and Shoshana J Wodak and Joel Janin and David Baker},
url = {https://www.bakerlab.org/wp-content/uploads/2018/06/1-s2.0-S0022283611010552-main.pdf
https://www.sciencedirect.com/science/article/pii/S0022283611010552?via%3Dihub},
doi = {10.1016/j.jmb.2011.09.031},
issn = {1089-8638},
year = {2011},
date = {2011-11-01},
journal = {Journal of Molecular Biology},
volume = {414},
pages = {289-302},
abstract = {The CAPRI (Critical Assessment of Predicted Interactions) and CASP (Critical Assessment of protein Structure Prediction) experiments have demonstrated the power of community-wide tests of methodology in assessing the current state of the art and spurring progress in the very challenging areas of protein docking and structure prediction. We sought to bring the power of community-wide experiments to bear on a very challenging protein design problem that provides a complementary but equally fundamental test of current understanding of protein-binding thermodynamics. We have generated a number of designed protein-protein interfaces with very favorable computed binding energies but which do not appear to be formed in experiments, suggesting that there may be important physical chemistry missing in the energy calculations. A total of 28 research groups took up the challenge of determining what is missing: we provided structures of 87 designed complexes and 120 naturally occurring complexes and asked participants to identify energetic contributions and/or structural features that distinguish between the two sets. The community found that electrostatics and solvation terms partially distinguish the designs from the natural complexes, largely due to the nonpolar character of the designed interactions. Beyond this polarity difference, the community found that the designed binding surfaces were, on average, structurally less embedded in the designed monomers, suggesting that backbone conformational rigidity at the designed surface is important for realization of the designed function. These results can be used to improve computational design strategies, but there is still much to be learned; for example, one designed complex, which does form in experiments, was classified by all metrics as a nonbinder.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Thompson, James; Baker, David
Incorporation of evolutionary information into Rosetta comparative modeling. Journal Article
In: Proteins, vol. 79, pp. 2380-8, 2011, ISSN: 1097-0134.
@article{421,
title = {Incorporation of evolutionary information into Rosetta comparative modeling.},
author = { James Thompson and David Baker},
url = {https://www.bakerlab.org/wp-content/uploads/2018/06/7a8a6bd9c93cfb06e1f3c0416a914b7494ffd1d2e15654117ed9e259a487cf33.pdf
https://onlinelibrary.wiley.com/doi/abs/10.1002/prot.23046},
doi = {10.1002/prot.23046},
issn = {1097-0134},
year = {2011},
date = {2011-08-01},
journal = {Proteins},
volume = {79},
pages = {2380-8},
abstract = {Prediction of protein structures from sequences is a fundamental problem in computational biology. Algorithms that attempt to predict a structure from sequence primarily use two sources of information. The first source is physical in nature: proteins fold into their lowest energy state. Given an energy function that describes the interactions governing folding, a method for constructing models of protein structures, and the amino acid sequence of a protein of interest, the structure prediction problem becomes a search for the lowest energy structure. Evolution provides an orthogonal source of information: proteins of similar sequences have similar structure, and therefore proteins of known structure can guide modeling. The relatively successful Rosetta approach takes advantage of the first, but not the second source of information during model optimization. Following the classic work by Andrej Sali and colleagues, we develop a probabilistic approach to derive spatial restraints from proteins of known structure using advances in alignment technology and the growth in the number of structures in the Protein Data Bank. These restraints define a region of conformational space that is high-probability, given the template information, and we incorporate them into Rosettatextquoterights comparative modeling protocol. The combined approach performs considerably better on a benchmark based on previous CASP experiments. Incorporating evolutionary information into Rosetta is analogous to incorporating sparse experimental data: in both cases, the additional information eliminates large regions of conformational space and increases the probability that energy-based refinement will hone in on the deep energy minimum at the native state.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Kellogg, Elizabeth H; Leaver-Fay, Andrew; Baker, David
Role of conformational sampling in computing mutation-induced changes in protein structure and stability Journal Article
In: Proteins, vol. 79, pp. 830-8, 2011, ISSN: 1097-0134.
@article{354,
title = {Role of conformational sampling in computing mutation-induced changes in protein structure and stability},
author = { Elizabeth H Kellogg and Andrew Leaver-Fay and David Baker},
doi = {10.1002/prot.22921},
issn = {1097-0134},
year = {2011},
date = {2011-03-01},
journal = {Proteins},
volume = {79},
pages = {830-8},
abstract = {The prediction of changes in protein stability and structure resulting from single amino acid substitutions is both a fundamental test of macromolecular modeling methodology and an important current problem as high throughput sequencing reveals sequence polymorphisms at an increasing rate. In principle, given the structure of a wild-type protein and a point mutation whose effects are to be predicted, an accurate method should recapitulate both the structural changes and the change in the folding-free energy. Here, we explore the performance of protocols which sample an increasing diversity of conformations. We find that surprisingly similar performances in predicting changes in stability are achieved using protocols that involve very different amounts of conformational sampling, provided that the resolution of the force field is matched to the resolution of the sampling method. Methods involving backbone sampling can in some cases closely recapitulate the structural changes accompanying mutations but not surprisingly tend to do more harm than good in cases where structural changes are negligible. Analysis of the outliers in the stability change calculations suggests areas needing particular improvement; these include the balance between desolvation and the formation of favorable buried polar interactions, and unfolded state modeling.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
DiMaio, Frank; Leaver-Fay, Andrew; Bradley, Phil; Baker, David; Andr’e, Ingemar
Modeling symmetric macromolecular structures in Rosetta3 Journal Article
In: PloS One, vol. 6, pp. e20450, 2011, ISSN: 1932-6203.
@article{590,
title = {Modeling symmetric macromolecular structures in Rosetta3},
author = { Frank DiMaio and Andrew Leaver-Fay and Phil Bradley and David Baker and Ingemar Andr'e},
doi = {10.1371/journal.pone.0020450},
issn = {1932-6203},
year = {2011},
date = {2011-00-01},
journal = {PloS One},
volume = {6},
pages = {e20450},
abstract = {Symmetric protein assemblies play important roles in many biochemical processes. However, the large size of such systems is challenging for traditional structure modeling methods. This paper describes the implementation of a general framework for modeling arbitrary symmetric systems in Rosetta3. We describe the various types of symmetries relevant to the study of protein structure that may be modeled using Rosettatextquoterights symmetric framework. We then describe how this symmetric framework is efficiently implemented within Rosetta, which restricts the conformational search space by sampling only symmetric degrees of freedom, and explicitly simulates only a subset of the interacting monomers. Finally, we describe structure prediction and design applications that utilize the Rosetta3 symmetric modeling capabilities, and provide a guide to running simulations on symmetric systems.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Fleishman, Sarel J; Corn, Jacob E; Strauch, Eva M; Whitehead, Tim A; Andre, Ingemar; Thompson, James; Havranek, James J; Das, Rhiju; Bradley, Philip; Baker, David
Rosetta in CAPRI rounds 13-19. Journal Article
In: Proteins, vol. 78, pp. 3212-8, 2010, ISSN: 1097-0134.
@article{578,
title = {Rosetta in CAPRI rounds 13-19.},
author = { Sarel J Fleishman and Jacob E Corn and Eva M Strauch and Tim A Whitehead and Ingemar Andre and James Thompson and James J Havranek and Rhiju Das and Philip Bradley and David Baker},
doi = {10.1002/prot.22784},
issn = {1097-0134},
year = {2010},
date = {2010-11-01},
journal = {Proteins},
volume = {78},
pages = {3212-8},
abstract = {Modeling the conformational changes that occur on binding of macromolecules is an unsolved challenge. In previous rounds of the Critical Assessment of PRediction of Interactions (CAPRI), it was demonstrated that the Rosetta approach to macromolecular modeling could capture side chain conformational changes on binding with high accuracy. In rounds 13-19 we tested the ability of various backbone remodeling strategies to capture the main-chain conformational changes observed during binding events. These approaches span a wide range of backbone motions, from limited refinement of loops to relieve clashes in homologous docking, through extensive remodeling of loop segments, to large-scale remodeling of RNA. Although the results are encouraging, major improvements in sampling and energy evaluation are clearly required for consistent high accuracy modeling. Analysis of our failures in the CAPRI challenges suggest that conformational sampling at the termini of exposed beta strands is a particularly pressing area for improvement.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Tyka, Michael D; Keedy, Daniel A; Andr’e, Ingemar; DiMaio, Frank; Song, Yifan; Richardson, David C; Richardson, Jane S; Baker, David
Alternate States of Proteins Revealed by Detailed Energy Landscape Mapping Journal Article
In: Journal of molecular biology, 2010, ISSN: 1089-8638.
@article{260,
title = {Alternate States of Proteins Revealed by Detailed Energy Landscape Mapping},
author = { Michael D Tyka and Daniel A Keedy and Ingemar Andr'e and Frank DiMaio and Yifan Song and David C Richardson and Jane S Richardson and David Baker},
issn = {1089-8638},
year = {2010},
date = {2010-11-01},
journal = {Journal of molecular biology},
abstract = {What conformations do protein molecules populate in solution? Crystallography provides a high-resolution description of protein structure in the crystal environment, while NMR describes structure in solution but using less data. NMR structures display more variability, but is this because crystal contacts are absent or because of fewer data constraints? Here we report unexpected insight into this issue obtained through analysis of detailed protein energy landscapes generated by large-scale, native-enhanced sampling of conformational space with Rosetta@home for 111 protein domains. In the absence of tightly associating binding partners or ligands, the lowest-energy Rosetta models were nearly all <2.5~r A C(α)RMSD from the experimental structure; this result demonstrates that structure prediction accuracy for globular proteins is limited mainly by the ability to sample close to the native structure. While the lowest-energy models are similar to deposited structures, they are not identical; the largest deviations are most often in regions involved in ligand, quaternary, or crystal contacts. For ligand binding proteins, the low energy models may resemble the apo structures, and for oligomeric proteins, the monomeric assembly intermediates. The deviations between the low energy models and crystal structures largely disappear when landscapes are computed in the context of the crystal lattice or multimer. The computed low-energy ensembles, with tight crystal-structure-like packing in the core, but more NMR-structure-like variability in loops, may in some cases resemble the native state ensembles of proteins better than individual crystal or NMR structures, and can suggest experimentally testable hypotheses relating alternative states and structural heterogeneity to function.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Cooper, Seth; Khatib, Firas; Treuille, Adrien; Barbero, Janos; Lee, Jeehyung; Beenen, Michael; Leaver-Fay, Andrew; Baker, David; Popovi’c, Zoran; Players, Foldit
Predicting protein structures with a multiplayer online game Journal Article
In: Nature, vol. 466, pp. 756-60, 2010, ISSN: 1476-4687.
@article{16,
title = {Predicting protein structures with a multiplayer online game},
author = { Seth Cooper and Firas Khatib and Adrien Treuille and Janos Barbero and Jeehyung Lee and Michael Beenen and Andrew Leaver-Fay and David Baker and Zoran Popovi'c and Foldit Players},
issn = {1476-4687},
year = {2010},
date = {2010-08-01},
journal = {Nature},
volume = {466},
pages = {756-60},
abstract = {People exert large amounts of problem-solving effort playing computer games. Simple image- and text-recognition tasks have been successfully textquoterightcrowd-sourcedtextquoteright 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.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Blum, Ben; Jordan, Michael I; Baker, David
Feature space resampling for protein conformational search Journal Article
In: Proteins, vol. 78, pp. 1583-93, 2010, ISSN: 1097-0134.
@article{271,
title = {Feature space resampling for protein conformational search},
author = { Ben Blum and Michael I Jordan and David Baker},
issn = {1097-0134},
year = {2010},
date = {2010-05-01},
journal = {Proteins},
volume = {78},
pages = {1583-93},
abstract = {De novo protein structure prediction requires location of the lowest energy state of the polypeptide chain among a vast set of possible conformations. Powerful approaches include conformational space annealing, in which search progressively focuses on the most promising regions of conformational space, and genetic algorithms, in which features of the best conformations thus far identified are recombined. We describe a new approach that combines the strengths of these two approaches. Protein conformations are projected onto a discrete feature space which includes backbone torsion angles, secondary structure, and beta pairings. For each of these there is one "native" value: the one found in the native structure. We begin with a large number of conformations generated in independent Monte Carlo structure prediction trajectories from Rosetta. Native values for each feature are predicted from the frequencies of feature value occurrences and the energy distribution in conformations containing them. A second round of structure prediction trajectories are then guided by the predicted native feature distributions. We show that native features can be predicted at much higher than background rates, and that using the predicted feature distributions improves structure prediction in a benchmark of 28 proteins. The advantages of our approach are that features from many different input structures can be combined simultaneously without producing atomic clashes or otherwise physically inviable models, and that the features being recombined have a relatively high chance of being correct.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Wang, Chu; Vernon, Robert; Lange, Oliver; Tyka, Michael; Baker, David
Prediction of structures of zinc-binding proteins through explicit modeling of metal coordination geometry Journal Article
In: Protein science, vol. 19, pp. 494-506, 2010, ISSN: 1469-896X.
@article{257,
title = {Prediction of structures of zinc-binding proteins through explicit modeling of metal coordination geometry},
author = { Chu Wang and Robert Vernon and Oliver Lange and Michael Tyka and David Baker},
issn = {1469-896X},
year = {2010},
date = {2010-03-01},
journal = {Protein science},
volume = {19},
pages = {494-506},
abstract = {Metal ions play an essential role in stabilizing protein structures and contributing to protein function. Ions such as zinc have well-defined coordination geometries, but it has not been easy to take advantage of this knowledge in protein structure prediction efforts. Here, we present a computational method to predict structures of zinc-binding proteins given knowledge of the positions of zinc-coordinating residues in the amino acid sequence. The method takes advantage of the "atom-tree" representation of molecular systems and modular architecture of the Rosetta3 software suite to incorporate explicit metal ion coordination geometry into previously developed de novo prediction and loop modeling protocols. Zinc cofactors are tethered to their interacting residues based on coordination geometries observed in natural zinc-binding proteins. The incorporation of explicit zinc atoms and their coordination geometry in both de novo structure prediction and loop modeling significantly improves sampling near the native conformation. The method can be readily extended to predict protein structures bound to other metal and/or small chemical cofactors with well-defined coordination or ligation geometry.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Shen, Yang; Bryan, Philip N; He, Yanan; Orban, John; Baker, David; Bax, Ad
De novo structure generation using chemical shifts for proteins with high-sequence identity but different folds Journal Article
In: Protein Science : A Publication of the Protein Society, vol. 19, pp. 349-56, 2010, ISSN: 1469-896X.
@article{584,
title = {De novo structure generation using chemical shifts for proteins with high-sequence identity but different folds},
author = { Yang Shen and Philip N Bryan and Yanan He and John Orban and David Baker and Ad Bax},
doi = {10.1002/pro.303},
issn = {1469-896X},
year = {2010},
date = {2010-02-01},
journal = {Protein Science : A Publication of the Protein Society},
volume = {19},
pages = {349-56},
abstract = {Proteins with high-sequence identity but very different folds present a special challenge to sequence-based protein structure prediction methods. In particular, a 56-residue three-helical bundle protein (GA(95)) and an alpha/beta-fold protein (GB(95)), which share 95% sequence identity, were targets in the CASP-8 structure prediction contest. With only 12 out of 300 submitted server-CASP8 models for GA(95) exhibiting the correct fold, this protein proved particularly challenging despite its small size. Here, we demonstrate that the information contained in NMR chemical shifts can readily be exploited by the CS-Rosetta structure prediction program and yields adequate convergence, even when input chemical shifts are limited to just amide (1)H(N) and (15)N or (1)H(N) and (1)H(alpha) values.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Raman, Srivatsan; Huang, Yuanpeng J; Mao, Binchen; Rossi, Paolo; Aramini, James M; Liu, Gaohua; Montelione, Gaetano T; Baker, David
Accurate automated protein NMR structure determination using unassigned NOESY data Journal Article
In: Journal of the American Chemical Society, vol. 132, pp. 202-7, 2010, ISSN: 1520-5126.
@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}
}
Das, Rhiju; Andr’e, Ingemar; Shen, Yang; Wu, Yibing; Lemak, Alexander; Bansal, Sonal; Arrowsmith, Cheryl H; Szyperski, Thomas; Baker, David
Simultaneous prediction of protein folding and docking at high resolution Journal Article
In: Proceedings of the National Academy of Sciences of the United States of America, vol. 106, pp. 18978-83, 2009, ISSN: 1091-6490.
@article{124,
title = {Simultaneous prediction of protein folding and docking at high resolution},
author = { Rhiju Das and Ingemar Andr'e and Yang Shen and Yibing Wu and Alexander Lemak and Sonal Bansal and Cheryl H Arrowsmith and Thomas Szyperski and David Baker},
issn = {1091-6490},
year = {2009},
date = {2009-11-01},
journal = {Proceedings of the National Academy of Sciences of the United States of America},
volume = {106},
pages = {18978-83},
abstract = {Interleaved dimers and higher order symmetric oligomers are ubiquitous in biology but present a challenge to de novo structure prediction methodology: The structure adopted by a monomer can be stabilized largely by interactions with other monomers and hence not the lowest energy state of a single chain. Building on the Rosetta framework, we present a general method to simultaneously model the folding and docking of multiple-chain interleaved homo-oligomers. For more than a third of the cases in a benchmark set of interleaved homo-oligomers, the method generates near-native models of large alpha-helical bundles, interlocking beta sandwiches, and interleaved alpha/beta motifs with an accuracy high enough for molecular replacement based phasing. With the incorporation of NMR chemical shift information, accurate models can be obtained consistently for symmetric complexes with as many as 192 total amino acids; a blind prediction was within 1 A rmsd of the traditionally determined NMR structure, and fit independently collected RDC data equally well. Together, these results show that the Rosetta "fold-and-dock" protocol can produce models of homo-oligomeric complexes with near-atomic-level accuracy and should be useful for crystallographic phasing and the rapid determination of the structures of multimers with limited NMR information.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Kim, David E; Blum, Ben; Bradley, Philip; Baker, David
Sampling bottlenecks in de novo protein structure prediction Journal Article
In: Journal of molecular biology, vol. 393, pp. 249-60, 2009, ISSN: 1089-8638.
@article{131,
title = {Sampling bottlenecks in de novo protein structure prediction},
author = { David E Kim and Ben Blum and Philip Bradley and David Baker},
issn = {1089-8638},
year = {2009},
date = {2009-10-01},
journal = {Journal of molecular biology},
volume = {393},
pages = {249-60},
abstract = {The primary obstacle to de novo protein structure prediction is conformational sampling: the native state generally has lower free energy than nonnative structures but is exceedingly difficult to locate. Structure predictions with atomic level accuracy have been made for small proteins using the Rosetta structure prediction method, but for larger and more complex proteins, the native state is virtually never sampled, and it has been unclear how much of an increase in computing power would be required to successfully predict the structures of such proteins. In this paper, we develop an approach to determining how much computer power is required to accurately predict the structure of a protein, based on a reformulation of the conformational search problem as a combinatorial sampling problem in a discrete feature space. We find that conformational sampling for many proteins is limited by critical "linchpin" features, often the backbone torsion angles of individual residues, which are sampled very rarely in unbiased trajectories and, when constrained, dramatically increase the sampling of the native state. These critical features frequently occur in less regular and likely strained regions of proteins that contribute to protein function. In a number of proteins, the linchpin features are in regions found experimentally to form late in folding, suggesting a correspondence between folding in silico and in reality.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Davis, Ian W; Raha, Kaushik; Head, Martha S; Baker, David
Blind docking of pharmaceutically relevant compounds using RosettaLigand Journal Article
In: Protein science, vol. 18, pp. 1998-2002, 2009, ISSN: 1469-896X.
@article{126,
title = {Blind docking of pharmaceutically relevant compounds using RosettaLigand},
author = { Ian W Davis and Kaushik Raha and Martha S Head and David Baker},
issn = {1469-896X},
year = {2009},
date = {2009-09-01},
journal = {Protein science},
volume = {18},
pages = {1998-2002},
abstract = {It is difficult to properly validate algorithms that dock a small molecule ligand into its protein receptor using data from the public domain: the predictions are not blind because the correct binding mode is already known, and public test cases may not be representative of compounds of interest such as drug leads. Here, we use private data from a real drug discovery program to carry out a blind evaluation of the RosettaLigand docking methodology and find that its performance is on average comparable with that of the best commercially available current small molecule docking programs. The strength of RosettaLigand is the use of the Rosetta sampling methodology to simultaneously optimize protein sidechain, protein backbone and ligand degrees of freedom; the extensive benchmark test described here identifies shortcomings in other aspects of the protocol and suggests clear routes to improving the method.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Kidd, Brian A; Baker, David; Thomas, Wendy E
Computation of conformational coupling in allosteric proteins Journal Article
In: PLoS computational biology, vol. 5, pp. e1000484, 2009, ISSN: 1553-7358.
@article{130,
title = {Computation of conformational coupling in allosteric proteins},
author = { Brian A Kidd and David Baker and Wendy E Thomas},
issn = {1553-7358},
year = {2009},
date = {2009-08-01},
journal = {PLoS computational biology},
volume = {5},
pages = {e1000484},
abstract = {In allosteric regulation, an effector molecule binding a protein at one site induces conformational changes, which alter structure and function at a distant active site. Two key challenges in the computational modeling of allostery are the prediction of the structure of one allosteric state starting from the structure of the other, and elucidating the mechanisms underlying the conformational coupling of the effector and active sites. Here we approach these two challenges using the Rosetta high-resolution structure prediction methodology. We find that the method can recapitulate the relaxation of effector-bound forms of single domain allosteric proteins into the corresponding ligand-free states, particularly when sampling is focused on regions known to change conformation most significantly. Analysis of the coupling between contacting pairs of residues in large ensembles of conformations spread throughout the landscape between and around the two allosteric states suggests that the transitions are built up from blocks of tightly coupled interacting sets of residues that are more loosely coupled to one another.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Sadreyev, Ruslan I; Shi, ShuoYong; Baker, David; Grishin, Nick V
Structure similarity measure with penalty for close non-equivalent residues Journal Article
In: Bioinformatics, vol. 25, pp. 1259-63, 2009, ISSN: 1367-4811.
@article{135,
title = {Structure similarity measure with penalty for close non-equivalent residues},
author = { Ruslan I Sadreyev and ShuoYong Shi and David Baker and Nick V Grishin},
issn = {1367-4811},
year = {2009},
date = {2009-05-01},
journal = {Bioinformatics},
volume = {25},
pages = {1259-63},
abstract = {MOTIVATION: Recent improvement in homology-based structure modeling emphasizes the importance of sensitive evaluation measures that help identify and correct modest distortions in models compared with the target structures. Global Distance Test Total Score (GDT_TS), otherwise a very powerful and effective measure for model evaluation, is still insensitive to and can even reward such distortions, as observed for remote homology modeling in the latest CASP8 (Comparative Assessment of Structure Prediction). RESULTS: We develop a new measure that balances GDT_TS reward for the closeness of equivalent model and target residues (textquoterightattractiontextquoteright term) with the penalty for the closeness of non-equivalent residues (textquoterightrepulsiontextquoteright term). Compared with GDT_TS, the resulting score, TR (total score with repulsion), is much more sensitive to structure compression both in real remote homologs and in CASP models. TR is correlated yet different from other measures of structure similarity. The largest difference from GDT_TS is observed in models of mid-range quality based on remote homology modeling. AVAILABILITY: The script for TR calculation is included in Supplementary Material. TR scores for all server models in CASP8 are available at http://prodata.swmed.edu/CASP8.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Barth, P; Wallner, B; Baker, David
Prediction of membrane protein structures with complex topologies using limited constraints Journal Article
In: Proceedings of the National Academy of Sciences of the United States of America, vol. 106, pp. 1409-14, 2009, ISSN: 1091-6490.
@article{123,
title = {Prediction of membrane protein structures with complex topologies using limited constraints},
author = { P Barth and B Wallner and David Baker},
issn = {1091-6490},
year = {2009},
date = {2009-02-01},
journal = {Proceedings of the National Academy of Sciences of the United States of America},
volume = {106},
pages = {1409-14},
abstract = {Reliable structure-prediction methods for membrane proteins are important because the experimental determination of high-resolution membrane protein structures remains very difficult, especially for eukaryotic proteins. However, membrane proteins are typically longer than 200 aa and represent a formidable challenge for structure prediction. We have developed a method for predicting the structures of large membrane proteins by constraining helix-helix packing arrangements at particular positions predicted from sequence or identified by experiments. We tested the method on 12 membrane proteins of diverse topologies and functions with lengths ranging between 190 and 300 residues. Enforcing a single constraint during the folding simulations enriched the population of near-native models for 9 proteins. In 4 of the cases in which the constraint was predicted from the sequence, 1 of the 5 lowest energy models was superimposable within 4 A on the native structure. Near-native structures could also be selected for heme-binding and pore-forming domains from simulations in which pairs of conserved histidine-chelating hemes and one experimentally determined salt bridge were constrained, respectively. These results suggest that models within 4 A of the native structure can be achieved for complex membrane proteins if even limited information on residue-residue interactions can be obtained from protein structure databases or experiments.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
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