@article{An2023,

title = {Hallucination of closed repeat proteins containing central pockets},

author = {An L, Hicks DR, Zorine D, Dauparas J, Wicky BIM, Milles LF, Courbet A, Bera AK, Nguyen H, Kang A, Carter L, Baker D},

url = {https://www.nature.com/articles/s41594-023-01112-6, Nature Structural & Molecular Biology [Open Access] },

doi = {10.1038/s41594-023-01112-6},

year  = {2023},

date = {2023-09-28},

urldate = {2023-09-28},

journal = {Nature Structural & Molecular Biology},

abstract = {In pseudocyclic proteins, such as TIM barrels, β barrels, and some helical transmembrane channels, a single subunit is repeated in a cyclic pattern, giving rise to a central cavity that can serve as a pocket for ligand binding or enzymatic activity. Inspired by these proteins, we devised a deep-learning-based approach to broadly exploring the space of closed repeat proteins starting from only a specification of the repeat number and length. Biophysical data for 38 structurally diverse pseudocyclic designs produced in Escherichia coli are consistent with the design models, and the three crystal structures we were able to obtain are very close to the designed structures. Docking studies suggest the diversity of folds and central pockets provide effective starting points for designing small-molecule binders and enzymes.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Watson2023,

title = {De novo design of protein structure and function with RFdiffusion},

author = {Watson, Joseph L.

and Juergens, David

and Bennett, Nathaniel R.

and Trippe, Brian L.

and Yim, Jason

and Eisenach, Helen E.

and Ahern, Woody

and Borst, Andrew J.

and Ragotte, Robert J.

and Milles, Lukas F.

and Wicky, Basile I. M.

and Hanikel, Nikita

and Pellock, Samuel J.

and Courbet, Alexis

and Sheffler, William

and Wang, Jue

and Venkatesh, Preetham

and Sappington, Isaac

and Torres, Susana Vázquez

and Lauko, Anna

and De Bortoli, Valentin

and Mathieu, Emile

and Ovchinnikov, Sergey

and Barzilay, Regina

and Jaakkola, Tommi S.

and DiMaio, Frank

and Baek, Minkyung

and Baker, David},

url = {https://www.nature.com/articles/s41586-023-06415-8, Nature

https://www.bakerlab.org/wp-content/uploads/2023/07/s41586-023-06415-8_reference.pdf, PDF (29MB)},

doi = {10.1038/s41586-023-06415-8},

year  = {2023},

date = {2023-07-11},

journal = {Nature},

abstract = {There has been considerable recent progress in designing new proteins using deep learning methods1–9. Despite this progress, a general deep learning framework for protein design that enables solution of a wide range of design challenges, including de novo binder design and design of higher order symmetric architectures, has yet to be described. Diffusion models10,11 have had considerable success in image and language generative modeling but limited success when applied to protein modeling, likely due to the complexity of protein backbone geometry and sequence-structure relationships. Here we show that by fine tuning the RoseTTAFold structure prediction network on protein structure denoising tasks, we obtain a generative model of protein backbones that achieves outstanding performance on unconditional and topology-constrained protein monomer design, protein binder design, symmetric oligomer design, enzyme active site scaffolding, and symmetric motif scaffolding for therapeutic and metal-binding protein design. We demonstrate the power and generality of the method, called RoseTTAFold Diffusion (RFdiffusion), by experimentally characterizing the structures and functions of hundreds of designed symmetric assemblies, metal binding proteins and protein binders. The accuracy of RFdiffusion is confirmed by the cryo-EM structure of a designed binder in complex with Influenza hemagglutinin which is nearly identical to the design model. In a manner analogous to networks which produce images from user-specified inputs, RFdiffusion enables the design of diverse functional proteins from simple molecular specifications.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Kim2023,

title = {De novo design of small beta barrel proteins},

author = {Kim, David E.

and Jensen, Davin R.

and Feldman, David

and Tischer, Doug

and Saleem, Ayesha

and Chow, Cameron M.

and Li, Xinting

and Carter, Lauren

and Milles, Lukas

and Nguyen, Hannah

and Kang, Alex

and Bera, Asim K.

and Peterson, Francis C.

and Volkman, Brian F.

and Ovchinnikov, Sergey

and Baker, David},

url = {https://www.pnas.org/doi/10.1073/pnas.2207974120, PNAS (Open Access)},

doi = {10.1073/pnas.2207974120},

year  = {2023},

date = {2023-03-10},

urldate = {2023-03-10},

journal = {Proceedings of the National Academy of Sciences},

abstract = {Small beta barrel proteins are attractive targets for computational design because of their considerable functional diversity despite their very small size (<70 amino acids). However, there are considerable challenges to designing such structures, and there has been little success thus far. Because of the small size, the hydrophobic core stabilizing the fold is necessarily very small, and the conformational strain of barrel closure can oppose folding; also intermolecular aggregation through free beta strand edges can compete with proper monomer folding. Here, we explore the de novo design of small beta barrel topologies using both Rosetta energy–based methods and deep learning approaches to design four small beta barrel folds: Src homology 3 (SH3) and oligonucleotide/oligosaccharide-binding (OB) topologies found in nature and five and six up-and-down-stranded barrels rarely if ever seen in nature. Both approaches yielded successful designs with high thermal stability and experimentally determined structures with less than 2.4 Å rmsd from the designed models. Using deep learning for backbone generation and Rosetta for sequence design yielded higher design success rates and increased structural diversity than Rosetta alone. The ability to design a large and structurally diverse set of small beta barrel proteins greatly increases the protein shape space available for designing binders to protein targets of interest.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Agarwal2022,

title = {Rapid and Sensitive Detection of Antigen from SARS-CoV-2 Variants of Concern by a Multivalent Minibinder-Functionalized Nanomechanical Sensor},

author = {Agarwal, Dilip Kumar

and Hunt, Andrew C.

and Shekhawat, Gajendra S.

and Carter, Lauren

and Chan, Sidney

and Wu, Kejia

and Cao, Longxing

and Baker, David

and Lorenzo-Redondo, Ramon

and Ozer, Egon A.

and Simons, Lacy M.

and Hultquist, Judd F.

and Jewett, Michael C.

and Dravid, Vinayak P.},

url = {https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9211039/, Analytical Chemistry},

year  = {2022},

date = {2022-06-06},

urldate = {2022-06-06},

journal = {Analytical Chemistry},

abstract = {New platforms for the rapid and sensitive detection of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants of concern are urgently needed. Here we report the development of a nanomechanical sensor based on the deflection of a microcantilever capable of detecting the SARS-CoV-2 spike (S) glycoprotein antigen using computationally designed multivalent minibinders immobilized on a microcantilever surface. The sensor exhibits rapid (<5 min) detection of the target antigens down to concentrations of 0.05 ng/mL (362 fM) and is more than an order of magnitude more sensitive than an antibody-based cantilever sensor. Validation of the sensor with clinical samples from 33 patients, including 9 patients infected with the Omicron (BA.1) variant observed detection of antigen from nasopharyngeal swabs with cycle threshold (Ct) values as high as 39, suggesting a limit of detection similar to that of the quantitative reverse transcription polymerase chain reaction (RT-qPCR). Our findings demonstrate the use of minibinders and nanomechanical sensors for the rapid and sensitive detection of SARS-CoV-2 and potentially other disease markers.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Hunt2022,

title = {Multivalent designed proteins neutralize SARS-CoV-2 variants of concern and confer protection against infection in mice},

author = {Andrew C. Hunt and James Brett Case and Young-Jun Park and Longxing Cao and Kejia Wu and Alexandra C. Walls and Zhuoming Liu and John E. Bowen and Hsien-Wei Yeh and Shally Saini and Louisa Helms and Yan Ting Zhao and Tien-Ying Hsiang and Tyler N. Starr and Inna Goreshnik and Lisa Kozodoy and Lauren Carter and Rashmi Ravichandran and Lydia B. Green and Wadim L. Matochko and Christy A. Thomson and Bastian Vögeli and Antje Krüger and Laura A. VanBlargan and Rita E. Chen and Baoling Ying and Adam L. Bailey and Natasha M. Kafai and Scott E. Boyken and Ajasja Ljubetič and Natasha Edman and George Ueda and Cameron M. Chow and Max Johnson and Amin Addetia and Mary Jane Navarro and Nuttada Panpradist and Michael Gale and Benjamin S. Freedman and Jesse D. Bloom and Hannele Ruohola-Baker and Sean P. J. Whelan and Lance Stewart and Michael S. Diamond and David Veesler and Michael C. Jewett and David Baker},

url = {https://www.science.org/doi/abs/10.1126/scitranslmed.abn1252, Science Translational Medicine

https://www.bakerlab.org/wp-content/uploads/2022/04/scitranslmed.abn1252.pdf, Download PDF},

doi = {10.1126/scitranslmed.abn1252},

year  = {2022},

date = {2022-04-12},

urldate = {2022-04-12},

journal = {Science Translational Medicine},

abstract = {New variants of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) continue to arise and prolong the coronavirus disease 2019 (COVID-19) pandemic. Here we used a cell-free expression workflow to rapidly screen and optimize constructs containing multiple computationally designed miniprotein inhibitors of SARS-CoV-2. We found the broadest efficacy with a homo-trimeric version of the 75-residue angiotensin converting enzyme 2 (ACE2) mimic AHB2 (TRI2-2) designed to geometrically match the trimeric spike architecture. In the cryo-electron microscopy structure, TRI2 formed a tripod on top of the spike protein which engaged all three receptor binding domains (RBDs) simultaneously as in the design model. TRI2-2 neutralized Omicron (B.1.1.529), Delta (B.1.617.2), and all other variants tested with greater potency than that of monoclonal antibodies used clinically for the treatment of COVID-19. TRI2-2 also conferred prophylactic and therapeutic protection against SARS-CoV-2 challenge when administered intranasally in mice. Designed miniprotein receptor mimics geometrically arrayed to match pathogen receptor binding sites could be a widely applicable antiviral therapeutic strategy with advantages over antibodies and native receptor traps. By comparison, the designed proteins have resistance to viral escape and antigenic drift by construction, precisely tuned avidity, and greatly reduced chance of autoimmune responses. Computationally designed trivalent minibinders provide therapeutic protection in mice against emerging SARS-CoV-2 variants of concern.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Cao2022,

title = {Design of protein binding proteins from target structure alone},

author = {Cao, Longxing and Coventry, Brian and Goreshnik, Inna and Huang, Buwei and Park, Joon Sung and Jude, Kevin M. and Marković, Iva and Kadam, Rameshwar U. and Verschueren, Koen H. G. and Verstraete, Kenneth and Walsh, Scott Thomas Russell and Bennett, Nathaniel and Phal, Ashish and Yang, Aerin and Kozodoy, Lisa and DeWitt, Michelle and Picton, Lora and Miller, Lauren and Strauch, Eva-Maria and DeBouver, Nicholas D. and Pires, Allison and Bera, Asim K. and Halabiya, Samer and Hammerson, Bradley and Yang, Wei and Bernard, Steffen and Stewart, Lance and Wilson, Ian A. and Ruohola-Baker, Hannele and Schlessinger, Joseph and Lee, Sangwon and Savvides, Savvas N. and Garcia, K. Christopher and Baker, David},

url = {https://www.nature.com/articles/s41586-022-04654-9, Nature

https://www.bakerlab.org/wp-content/uploads/2022/03/Cao_etal_Nature2022_Design_of_binders_from_target_structure_alone.pdf, Download PDF},

doi = {10.1038/s41586-022-04654-9},

year  = {2022},

date = {2022-03-24},

urldate = {2022-03-24},

journal = {Nature},

abstract = {The design of proteins that bind to a specific site on the surface of a target protein using no information other than the three-dimensional structure of the target remains an outstanding challenge1–5. We describe a general solution to this problem which starts with a broad exploration of the very large space of possible binding modes to a selected region of a protein surface, and then intensifies the search in the vicinity of the most promising binding modes. We demonstrate its very broad applicability by de novo design of binding proteins to 12 diverse protein targets with very different shapes and surface properties. Biophysical characterization shows that the binders, which are all smaller than 65 amino acids, are hyperstable and following experimental optimization bind their targets with nanomolar to picomolar affinities. We succeeded in solving crystal structures of five of the binder-target complexes, and all five are very close to the corresponding computational design models. Experimental data on nearly half a million computational designs and hundreds of thousands of point mutants provide detailed feedback on the strengths and limitations of the method and of our current understanding of protein-protein interactions, and should guide improvement of both. Our approach now enables targeted design of binders to sites of interest on a wide variety of proteins for therapeutic and diagnostic applications.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Hosseinzadeh2021,

title = {Anchor extension: a structure-guided approach to design cyclic peptides targeting enzyme active sites},

author = {Hosseinzadeh, Parisa

and Watson, Paris R.

and Craven, Timothy W.

and Li, Xinting

and Rettie, Stephen

and Pardo-Avila, Fátima

and Bera, Asim K.

and Mulligan, Vikram Khipple

and Lu, Peilong

and Ford, Alexander S.

and Weitzner, Brian D.

and Stewart, Lance J.

and Moyer, Adam P.

and Di Piazza, Maddalena

and Whalen, Joshua G.

and Greisen, Per Jr.

and Christianson, David W.

and Baker, David},

url = {https://www.nature.com/articles/s41467-021-23609-8, Nature Communications

https://www.bakerlab.org/wp-content/uploads/2021/06/Hosseinzadeh_etal_NatureComms2021_AnchorExtention.pdf, Download PDF},

doi = {10.1038/s41467-021-23609-8},

year  = {2021},

date = {2021-06-07},

urldate = {2021-06-07},

journal = {Nature Communications},

abstract = {Despite recent success in computational design of structured cyclic peptides, de novo design of cyclic peptides that bind to any protein functional site remains difficult. To address this challenge, we develop a computational “anchor extension” methodology for targeting protein interfaces by extending a peptide chain around a non-canonical amino acid residue anchor. To test our approach using a well characterized model system, we design cyclic peptides that inhibit histone deacetylases 2 and 6 (HDAC2 and HDAC6) with enhanced potency compared to the original anchor (IC50 values of 9.1 and 4.4 nM for the best binders compared to 5.4 and 0.6 µM for the anchor, respectively). The HDAC6 inhibitor is among the most potent reported so far. These results highlight the potential for de novo design of high-affinity protein-peptide interfaces, as well as the challenges that remain.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Sahtoe2021,

title = {Transferrin receptor targeting by de novo sheet extension},

author = {Sahtoe, Danny D. and Coscia, Adrian and Mustafaoglu, Nur and Miller, Lauren M. and Olal, Daniel and Vulovic, Ivan and Yu, Ta-Yi and Goreshnik, Inna and Lin, Yu-Ru and Clark, Lars and Busch, Florian and Stewart, Lance and Wysocki, Vicki H. and Ingber, Donald E. and Abraham, Jonathan and Baker, David},

url = {https://www.pnas.org/content/118/17/e2021569118, PNAS

},

doi = {10.1073/pnas.2021569118},

year  = {2021},

date = {2021-04-27},

urldate = {2021-04-27},

journal = {Proceedings of the National Academy of Sciences},

abstract = {The de novo design of proteins that bind natural target proteins is useful for a variety of biomedical and biotechnological applications. We describe a design strategy to target proteins containing an exposed beta edge strand. We use the approach to design binders to the human transferrin receptor which shuttles back and forth across the blood{textendash}brain barrier. Such binders could be useful for the delivery of therapeutics into the brain.The de novo design of polar protein{textendash}protein interactions is challenging because of the thermodynamic cost of stripping water away from the polar groups. Here, we describe a general approach for designing proteins which complement exposed polar backbone groups at the edge of beta sheets with geometrically matched beta strands. We used this approach to computationally design small proteins that bind to an exposed beta sheet on the human transferrin receptor (hTfR), which shuttles interacting proteins across the blood{textendash}brain barrier (BBB), opening up avenues for drug delivery into the brain. We describe a design which binds hTfR with a 20 nM Kd, is hyperstable, and crosses an in vitro microfluidic organ-on-a-chip model of the human BBB. Our design approach provides a general strategy for creating binders to protein targets with exposed surface beta edge strands.Crystal structures have been deposited in the RCSB PDB with the accession nos. 6WRX, 6WRW, and 6WRV. Additional supporting data has been deposited in the online Zenodo repository (https://zenodo.org/record/4594115) (47). All other study data are included in the article and/or supporting information.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Cao2020,

title = {De novo design of picomolar SARS-CoV-2 miniprotein inhibitors},

author = {Cao, Longxing and Goreshnik, Inna and Coventry, Brian and Case, James Brett and Miller, Lauren and Kozodoy, Lisa and Chen, Rita E. and Carter, Lauren and Walls, Alexandra C. and Park, Young-Jun and Strauch, Eva-Maria and Stewart, Lance and Diamond, Michael S. and Veesler, David and Baker, David},

url = {https://science.sciencemag.org/content/early/2020/09/08/science.abd9909

https://www.bakerlab.org/wp-content/uploads/2020/09/Cao_etal_Science_COVID_spike_binders.pdf},

doi = {10.1126/science.abd9909},

year  = {2020},

date = {2020-09-09},

journal = {Science},

abstract = {Targeting the interaction between the SARS-CoV-2 Spike protein and the human ACE2 receptor is a promising therapeutic strategy. We designed inhibitors using two de novo design approaches. Computer generated scaffolds were either built around an ACE2 helix that interacts with the Spike receptor binding domain (RBD), or docked against the RBD to identify new binding modes, and their amino acid sequences designed to optimize target binding, folding and stability. Ten designs bound the RBD with affinities ranging from 100pM to 10nM, and blocked ARS-CoV-2 infection of Vero E6 cells with IC 50 values between 24 pM and 35 nM; The most potent, with new binding modes, are 56 and 64 residue proteins (IC 50 ~ 0.16 ng/ml). Cryo-electron microscopy structures of these minibinders in complex with the SARS-CoV-2 spike ectodomain trimer with all three RBDs bound are nearly identical to the computational models. These hyperstable minibinders provide starting points for SARS-CoV-2 therapeutics.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Brunette2020,

title = {Modular repeat protein sculpting using rigid helical junctions},

author = {Brunette, TJ and Bick, Matthew J. and Hansen, Jesse M. and Chow, Cameron M. and Kollman, Justin M. and Baker, David},

url = {https://www.bakerlab.org/wp-content/uploads/2020/04/Brunette2020_Junctions.pdf

https://www.pnas.org/content/early/2020/04/02/1908768117},

doi = {10.1073/pnas.1908768117},

year  = {2020},

date = {2020-04-02},

journal = {Proceedings of the National Academy of Sciences},

abstract = {The ability to precisely design large proteins with diverse shapes would enable applications ranging from the design of protein binders that wrap around their target to the positioning of multiple functional sites in specified orientations. We describe a protein backbone design method for generating a wide range of rigid fusions between helix-containing proteins and use it to design 75,000 structurally unique junctions between monomeric and homo-oligomeric de novo designed and ankyrin repeat proteins (RPs). Of the junction designs that were experimentally characterized, 82% have circular dichroism and solution small-angle X-ray scattering profiles consistent with the design models and are stable at 95 °C. Crystal structures of four designed junctions were in close agreement with the design models with rmsds ranging from 0.9 to 1.6 Å. Electron microscopic images of extended tetrameric structures and ∼10-nm-diameter “L” and “V” shapes generated using the junctions are close to the design models, demonstrating the control the rigid junctions provide for protein shape sculpting over multiple nanometer length scales.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Silva2018,

title = {Structures and disulfide cross‐linking of de novo designed therapeutic mini‐proteins},

author = {Silva, Daniel-Adriano and Stewart, Lance and Lam, Kwok-Ho and Jin, Rongsheng and Baker, David},

url = {https://febs.onlinelibrary.wiley.com/doi/abs/10.1111/febs.14394

},

doi = {10.1111/febs.14394},

year  = {2018},

date = {2018-02-01},

journal = {FEBS Journal},

volume = {285},

number = {10},

pages = {1783-1785},

abstract = {Recent advances in computational protein design now enable the massively parallel de novo design and experimental characterization of small hyperstable binding proteins with potential therapeutic activity. By providing experimental feedback on tens of thousands of designed proteins, the design-build-test-learn pipeline provides a unique opportunity to systematically improve our understanding of protein folding and binding. Here, we review the structures of mini-protein binders in complex with Influenza hemagglutinin and Bot toxin, and illustrate in the case of disulfide bond placement how analysis of the large datasets of computational models and experimental data can be used to identify determinants of folding and binding.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Chevalier2017,

title = {Massively parallel de novo protein design for targeted therapeutics},

author = {Aaron Chevalier* and Daniel-Adriano Silva* and Gabriel J. Rocklin* and Derrick R. Hicks and Renan Vergara and Patience Murapa and Steffen M. Bernard and Lu Zhang and Kwok-Ho Lam and Guorui Yao and Christopher D. Bahl and Shin-Ichiro Miyashita and Inna Goreshnik and 	James T. Fuller and	Merika T. Koday and Cody M. Jenkins and Tom Colvin and Lauren Carter and Alan Bohn and Cassie M. Bryan and D. Alejandro Fernández-Velasco and Lance Stewart and Min Dong and Xuhui Huang and Rongsheng Jin and Ian A. Wilson and Deborah H. Fuller and David Baker	},

url = {https://www.nature.com/nature/journal/v550/n7674/full/nature23912.html

https://www.bakerlab.org/wp-content/uploads/2017/12/Nature_Chevalier_etal_2017.pdf},

doi = {10.1038/nature23912},

issn = {0028-0836},

year  = {2017},

date = {2017-10-05},

journal = {Nature},

volume = {550},

number = {7674},

pages = {74-79},

abstract = {De novo protein design holds promise for creating small stable proteins with shapes customized to bind therapeutic targets. We describe a massively parallel approach for designing, manufacturing and screening mini-protein binders, integrating large-scale computational design, oligonucleotide synthesis, yeast display screening and next-generation sequencing. We designed and tested 22,660 mini-proteins of 37–43 residues that target influenza haemagglutinin and botulinum neurotoxin B, along with 6,286 control sequences to probe contributions to folding and binding, and identified 2,618 high-affinity binders. Comparison of the binding and non-binding design sets, which are two orders of magnitude larger than any previously investigated, enabled the evaluation and improvement of the computational model. Biophysical characterization of a subset of the binder designs showed that they are extremely stable and, unlike antibodies, do not lose activity after exposure to high temperatures. The designs elicit little or no immune response and provide potent prophylactic and therapeutic protection against influenza, even after extensive repeated dosing.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{626,

title = {Immobilizing affinity proteins to nitrocellulose: a toolbox for paper-based assay developers.},

author = { Carly A Holstein and Aaron Chevalier and Steven Bennett and Caitlin E Anderson and Karen Keniston and Cathryn Olsen and Bing Li and Brian Bales and David R Moore and Elain Fu and David Baker and Paul Yager},

url = {http://www.bakerlab.org/wp-content/uploads/2015/12/Holstien_Anal_Bioanal_Chem_2015.pdf},

doi = {10.1007/s00216-015-9052-0},

issn = {1618-2650},

year  = {2015},

date = {2015-10-01},

journal = {Analytical and bioanalytical chemistry},

abstract = {To enable enhanced paper-based diagnostics with improved detection capabilities, new methods are needed to immobilize affinity reagents to porous substrates, especially for capture molecules other than IgG. To this end, we have developed and characterized three novel methods for immobilizing protein-based affinity reagents to nitrocellulose membranes. We have demonstrated these methods using recombinant affinity proteins for the influenza surface protein hemagglutinin, leveraging the customizability of these recombinant "flu binders" for the design of features for immobilization. The three approaches shown are: (1) covalent attachment of thiolated affinity protein to an epoxide-functionalized nitrocellulose membrane, (2) attachment of biotinylated affinity protein through a nitrocellulose-binding streptavidin anchor protein, and (3) fusion of affinity protein to a novel nitrocellulose-binding anchor protein for direct coupling and immobilization. We also characterized the use of direct adsorption for the flu binders, as a point of comparison and motivation for these novel methods. Finally, we demonstrated that these novel methods can provide improved performance to an influenza hemagglutinin assay, compared to a traditional antibody-based capture system. Taken together, this work advances the toolkit available for the development of next-generation paper-based diagnostics.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{505,

title = {Community-wide evaluation of methods for predicting the effect of mutations on protein-protein interactions.},

author = { Rocco Moretti and Sarel J Fleishman and Rudi Agius and Mieczyslaw Torchala and Paul A Bates and Panagiotis L Kastritis and Jo~ao P G L M Rodrigues and Mika"el Trellet and Alexandre M J J Bonvin and Meng Cui and Marianne Rooman and Dimitri Gillis and Yves Dehouck and Iain Moal and Miguel Romero-Durana and Laura Perez-Cano and Chiara Pallara and Brian Jimenez and Juan Fernandez-Recio and Samuel Flores and Michael Pacella and Krishna Praneeth Kilambi and Jeffrey J Gray and Petr Popov and Sergei Grudinin and Juan Esquivel-Rodr'iguez and Daisuke Kihara and Nan Zhao and Dmitry Korkin and Xiaolei Zhu and Omar N A Demerdash and Julie C Mitchell and Eiji Kanamori and Yuko Tsuchiya and Haruki Nakamura and Hasup Lee and Hahnbeom Park and Chaok Seok and Jamica Sarmiento and Shide Liang and Shusuke Teraguchi and Daron M Standley and Hiromitsu Shimoyama and Genki Terashi and Mayuko Takeda-Shitaka and Mitsuo Iwadate and Hideaki Umeyama and Dmitri Beglov and David R Hall and Dima Kozakov and Sandor Vajda and Brian G Pierce and Howook Hwang and Thom Vreven and Zhiping Weng and Yangyu Huang and Haotian Li and Xiufeng Yang and Xiaofeng Ji and Shiyong Liu and Yi Xiao and Martin Zacharias and Sanbo Qin and Huan-Xiang Zhou and Sheng-You Huang and Xiaoqin Zou and Sameer Velankar and Jo"el Janin and Shoshana J Wodak and David Baker},

url = {http://www.bakerlab.org/wp-content/uploads/2015/12/Moretti_Proteins_2013.pdf},

doi = {10.1002/prot.24356},

issn = {1097-0134},

year  = {2013},

date = {2013-11-01},

journal = {Proteins},

volume = {81},

pages = {1980-7},

abstract = {Community-wide blind prediction experiments such as CAPRI and CASP provide an objective measure of the current state of predictive methodology. Here we describe a community-wide assessment of methods to predict the effects of mutations on protein-protein interactions. Twenty-two groups predicted the effects of comprehensive saturation mutagenesis for two designed influenza hemagglutinin binders and the results were compared with experimental yeast display enrichment data obtained using deep sequencing. The most successful methods explicitly considered the effects of mutation on monomer stability in addition to binding affinity, carried out explicit side-chain sampling and backbone relaxation, evaluated packing, electrostatic, and solvation effects, and correctly identified around a third of the beneficial mutations. Much room for improvement remains for even the best techniques, and large-scale fitness landscapes should continue to provide an excellent test bed for continued evaluation of both existing and new prediction methodologies.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{480,

title = {Computational design of ligand-binding proteins with high affinity and selectivity},

author = { Christine E Tinberg and Sagar D Khare and Jiayi Dou and Lindsey Doyle and Jorgen W Nelson and Alberto Schena and Wojciech Jankowski and Charalampos G Kalodimos and Kai Johnsson and Barry L Stoddard and David Baker},

url = {http://www.bakerlab.org/wp-content/uploads/2015/12/Tinberg13K.pdf},

doi = {10.1038/nature12443},

issn = {1476-4687},

year  = {2013},

date = {2013-09-01},

journal = {Nature},

volume = {501},

pages = {212-6},

abstract = {The ability to design proteins with high affinity and selectivity for any given small molecule is a rigorous test of our understanding of the physiochemical principles that govern molecular recognition. Attempts to rationally design ligand-binding proteins have met with little success, however, and the computational design of protein-small-molecule interfaces remains an unsolved problem. Current approaches for designing ligand-binding proteins for medical and biotechnological uses rely on raising antibodies against a target antigen in immunized animals and/or performing laboratory-directed evolution of proteins with an existing low affinity for the desired ligand, neither of which allows complete control over the interactions involved in binding. Here we describe a general computational method for designing pre-organized and shape complementary small-molecule-binding sites, and use it to generate protein binders to the steroid digoxigenin (DIG). Of seventeen experimentally characterized designs, two bind DIG; the model of the higher affinity binder has the most energetically favourable and pre-organized interface in the design set. A comprehensive binding-fitness landscape of this design, generated by library selections and deep sequencing, was used to optimize its binding affinity to a picomolar level, and X-ray co-crystal structures of two variants show atomic-level agreement with the corresponding computational models. The optimized binder is selective for DIG over the related steroids digitoxigenin, progesterone and β-oestradiol, and this steroid binding preference can be reprogrammed by manipulation of explicitly designed hydrogen-bonding interactions. The computational design method presented here should enable the development of a new generation of biosensors, therapeutics and diagnostics.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{474,

title = {Computational design of novel protein binders and experimental affinity maturation},

author = { Timothy A Whitehead and David Baker and Sarel J Fleishman},

url = {http://www.bakerlab.org/wp-content/uploads/2015/12/Whitehead_MethEnzymology_13V.pdf},

doi = {10.1016/B978-0-12-394292-0.00001-1},

issn = {1557-7988},

year  = {2013},

date = {2013-00-01},

journal = {Methods in enzymology},

volume = {523},

pages = {1-19},

abstract = {Computational design of novel protein binders has recently emerged as a useful technique to study biomolecular recognition and generate molecules for use in biotechnology, research, and biomedicine. Current limitations in computational design methodology have led to the adoption of high-throughput screening and affinity maturation techniques to diagnose modeling inaccuracies and generate high activity binders. Here, we scrutinize this combination of computational and experimental aspects and propose areas for future methodological improvements.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{592,

title = {Hotspot-centric de novo design of protein binders},

author = { Sarel J Fleishman and Jacob E Corn and Eva-Maria Strauch and Timothy A Whitehead and John Karanicolas and David Baker},

url = {https://www.bakerlab.org/wp-content/uploads/2018/06/1-s2.0-S0022283611009909-main.pdf

https://www.sciencedirect.com/science/article/pii/S0022283611009909?via%3Dihub},

doi = {10.1016/j.jmb.2011.09.001},

issn = {1089-8638},

year  = {2011},

date = {2011-11-01},

journal = {Journal of molecular biology},

volume = {413},

pages = {1047-62},

abstract = {Protein-protein interactions play critical roles in biology, and computational design of interactions could be useful in a range of applications. We describe in detail a general approach to de novo design of protein interactions based on computed, energetically optimized interaction hotspots, which was recently used to produce high-affinity binders of influenza hemagglutinin. We present several alternative approaches to identify and build the key hotspot interactions within both core secondary structural elements and variable loop regions and evaluate the methodtextquoterights performance in natural-interface recapitulation. We show that the method generates binding surfaces that are more conformationally restricted than previous design methods, reducing opportunities for off-target interactions.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}