Preprints
Available on bioRxiv.
Publications
Berhanu, Samuel; Majumder, Sagardip; Müntener, Thomas; Whitehouse, James; Berner, Carolin; Bera, Asim K.; Kang, Alex; Liang, Binyong; Khan, Nasir; Sankaran, Banumathi; Tamm, Lukas K.; Brockwell, David J.; Hiller, Sebastian; Radford, Sheena E.; Baker, David; Vorobieva, Anastassia A.
Sculpting conducting nanopore size and shape through de novo protein design Journal Article
In: Science, 2024.
@article{Berhanu2024,
title = {Sculpting conducting nanopore size and shape through de novo protein design},
author = {Samuel Berhanu and Sagardip Majumder and Thomas Müntener and James Whitehouse and Carolin Berner and Asim K. Bera and Alex Kang and Binyong Liang and Nasir Khan and Banumathi Sankaran and Lukas K. Tamm and David J. Brockwell and Sebastian Hiller and Sheena E. Radford and David Baker and Anastassia A. Vorobieva},
url = {https://www.science.org/doi/10.1126/science.adn3796, Science},
doi = {10.1126/science.adn3796},
year = {2024},
date = {2024-07-19},
urldate = {2024-07-19},
journal = {Science},
publisher = {American Association for the Advancement of Science (AAAS)},
abstract = {Transmembrane β-barrels have considerable potential for a broad range of sensing applications. Current engineering approaches for nanopore sensors are limited to naturally occurring channels, which provide suboptimal starting points. By contrast, de novo protein design can in principle create an unlimited number of new nanopores with any desired properties. Here we describe a general approach to designing transmembrane β-barrel pores with different diameters and pore geometries. Nuclear magnetic resonance and crystallographic characterization show that the designs are stably folded with structures resembling those of the design models. The designs have distinct conductances that correlate with their pore diameter, ranging from 110 picosiemens (~0.5 nanometer pore diameter) to 430 picosiemens (~1.1 nanometer pore diameter). Our approach opens the door to the custom design of transmembrane nanopores for sensing and sequencing applications.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
An, Linna; Said, Meerit; Tran, Long; Majumder, Sagardip; Goreshnik, Inna; Lee, Gyu Rie; Juergens, David; Dauparas, Justas; Anishchenko, Ivan; Coventry, Brian; Bera, Asim K.; Kang, Alex; Levine, Paul M.; Alvarez, Valentina; Pillai, Arvind; Norn, Christoffer; Feldman, David; Zorine, Dmitri; Hicks, Derrick R.; Li, Xinting; Sanchez, Mariana Garcia; Vafeados, Dionne K.; Salveson, Patrick J.; Vorobieva, Anastassia A.; Baker, David
Binding and sensing diverse small molecules using shape-complementary pseudocycles Journal Article
In: Science, 2024.
@article{An2024,
title = {Binding and sensing diverse small molecules using shape-complementary pseudocycles},
author = {Linna An and Meerit Said and Long Tran and Sagardip Majumder and Inna Goreshnik and Gyu Rie Lee and David Juergens and Justas Dauparas and Ivan Anishchenko and Brian Coventry and Asim K. Bera and Alex Kang and Paul M. Levine and Valentina Alvarez and Arvind Pillai and Christoffer Norn and David Feldman and Dmitri Zorine and Derrick R. Hicks and Xinting Li and Mariana Garcia Sanchez and Dionne K. Vafeados and Patrick J. Salveson and Anastassia A. Vorobieva and David Baker},
url = {https://www.science.org/doi/10.1126/science.adn3780, Science},
doi = {10.1126/science.adn3780},
year = {2024},
date = {2024-07-19},
urldate = {2024-07-19},
journal = {Science},
publisher = {American Association for the Advancement of Science (AAAS)},
abstract = {We describe an approach for designing high-affinity small molecule–binding proteins poised for downstream sensing. We use deep learning–generated pseudocycles with repeating structural units surrounding central binding pockets with widely varying shapes that depend on the geometry and number of the repeat units. We dock small molecules of interest into the most shape complementary of these pseudocycles, design the interaction surfaces for high binding affinity, and experimentally screen to identify designs with the highest affinity. We obtain binders to four diverse molecules, including the polar and flexible methotrexate and thyroxine. Taking advantage of the modular repeat structure and central binding pockets, we construct chemically induced dimerization systems and low-noise nanopore sensors by splitting designs into domains that reassemble upon ligand addition.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Lutz, Isaac D.; Wang, Shunzhi; Norn, Christoffer; Courbet, Alexis; Borst, Andrew J.; Zhao, Yan Ting; Dosey, Annie; Cao, Longxing; Xu, Jinwei; Leaf, Elizabeth M.; Treichel, Catherine; Litvicov, Patrisia; Li, Zhe; Goodson, Alexander D.; Rivera-Sánchez, Paula; Bratovianu, Ana-Maria; Baek, Minkyung; King, Neil P.; Ruohola-Baker, Hannele; Baker, David
Top-down design of protein architectures with reinforcement learning Journal Article
In: Science, 2023.
@article{Lutz2023,
title = {Top-down design of protein architectures with reinforcement learning},
author = {Lutz, Isaac D.
and Wang, Shunzhi
and Norn, Christoffer
and Courbet, Alexis
and Borst, Andrew J.
and Zhao, Yan Ting
and Dosey, Annie
and Cao, Longxing
and Xu, Jinwei
and Leaf, Elizabeth M.
and Treichel, Catherine
and Litvicov, Patrisia
and Li, Zhe
and Goodson, Alexander D.
and Rivera-Sánchez, Paula
and Bratovianu, Ana-Maria
and Baek, Minkyung
and King, Neil P.
and Ruohola-Baker, Hannele
and Baker, David},
url = {https://www.science.org/doi/10.1126/science.adf6591, Science
https://www.ipd.uw.edu/wp-content/uploads/2023/04/science.adf6591.pdf, PDF},
doi = {10.1126/science.adf6591},
year = {2023},
date = {2023-04-20},
journal = {Science},
abstract = {As a result of evolutionary selection, the subunits of naturally occurring protein assemblies often fit together with substantial shape complementarity to generate architectures optimal for function in a manner not achievable by current design approaches. We describe a “top-down” reinforcement learning–based design approach that solves this problem using Monte Carlo tree search to sample protein conformers in the context of an overall architecture and specified functional constraints. Cryo–electron microscopy structures of the designed disk-shaped nanopores and ultracompact icosahedra are very close to the computational models. The icosohedra enable very-high-density display of immunogens and signaling molecules, which potentiates vaccine response and angiogenesis induction. Our approach enables the top-down design of complex protein nanomaterials with desired system properties and demonstrates the power of reinforcement learning in protein design.
},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Vorobieva, Anastassia A.; White, Paul; Liang, Binyong; Horne, Jim E.; Bera, Asim K.; Chow, Cameron M.; Gerben, Stacey; Marx, Sinduja; Kang, Alex; Stiving, Alyssa Q.; Harvey, Sophie R.; Marx, Dagan C.; Khan, G. Nasir; Fleming, Karen G.; Wysocki, Vicki H.; Brockwell, David J.; Tamm, Lukas K.; Radford, Sheena E.; Baker, David
De novo design of transmembrane beta barrels Journal Article
In: Science, vol. 371, no. 6531, 2021.
@article{Vorobieva2021,
title = {De novo design of transmembrane beta barrels},
author = {Vorobieva, Anastassia A. and White, Paul and Liang, Binyong and Horne, Jim E. and Bera, Asim K. and Chow, Cameron M. and Gerben, Stacey and Marx, Sinduja and Kang, Alex and Stiving, Alyssa Q. and Harvey, Sophie R. and Marx, Dagan C. and Khan, G. Nasir and Fleming, Karen G. and Wysocki, Vicki H. and Brockwell, David J. and Tamm, Lukas K. and Radford, Sheena E. and Baker, David},
url = {https://science.sciencemag.org/content/371/6531/eabc8182, Science
https://www.bakerlab.org/wp-content/uploads/2021/02/Vorobieva_etal_Science2021_De_Novo_Transmembrane_beta_barrels.pdf, Download PDF},
doi = {10.1126/science.abc8182},
year = {2021},
date = {2021-02-19},
urldate = {2021-02-19},
journal = {Science},
volume = {371},
number = {6531},
abstract = {Computational design offers the possibility of making proteins with customized structures and functions. The range of accessible protein scaffolds has expanded with the design of increasingly complex cytoplasmic proteins and, recently, helical membrane proteins. Vorobieva et al. describe the successful computational design of eight-stranded transmembrane β-barrel proteins (TMBs). Using an iterative approach, they show the importance of negative design to prevent off-target structures and gain insight into the sequence determinants of TMB folding. Twenty-three designs satisfied biochemical screens for a TMB structure, and two structures were experimentally validated by nuclear magnetic resonance spectroscopy or x-ray crystallography. This is a step toward the custom design of pores for applications such as single-molecule sequencing.Science, this issue p. eabc8182INTRODUCTIONDespite their key biological roles, only a few proteins that fold into lipid membranes have been designed de novo. A class of membrane proteins{textemdash}transmembrane β barrels (TMBs){textemdash}forms a continuous sheet that closes on itself in lipid membranes. In addition to the challenge of designing β-sheet proteins, which are prone to misfolding and aggregation if folding is not properly controlled, the computational design of TMBs is complicated by limited understanding of TMB folding. As a result, no TMB has been designed de novo to date.Although the folding of TMBs in vivo is catalyzed by the β-barrel assembly machinery (BAM), many TMBs can also fold spontaneously in synthetic membranes to form stable pores, making them attractive for biotechnology and single-molecule analytical applications. Hence, de novo design of TMBs has potential both for understanding the determinants of TMB folding and membrane insertion and for the custom engineering of TMB nanopores.RATIONALEWe used de novo protein design to distill key principles of TMB folding through several design-build-test cycles. We iterated between hypothesis formulation, its implementation into computational design methods, and experimental characterization of the resulting proteins. To focus on the fundamental principles of TMB folding in the absence of complications due to interactions with chaperones and BAM in vivo, we focused on the challenge of de novo design of eight-stranded TMBs, which can fold and assemble into synthetic lipid membranes.RESULTSWe used a combination of purely geometric models and explicit Rosetta protein structure simulations to determine the constraints that β-strand connectivity and membrane embedding place on the TMB architecture. Through a series of design-build-test cycles, we found that, unlike almost all other classes of proteins, locally destabilizing sequences are critical for expression and folding of TMBs, and that the β-turns that translocate through the bilayer during folding have to be destabilized to enable correct assembly in the membrane. Our results suggest that premature formation of β hairpins may result in off-target β-sheet structures that compete with proper membrane insertion and folding, and hence the β hairpins of TMBs must be designed such that they are only transiently formed prior to membrane insertion, when the protein is in an aqueous environment. In the hydrophobic environment of the lipid bilayer, the full TMB can assemble because the membrane-facing nonpolar residues, which would tend to cluster nonspecifically in an aqueous environment, instead make favorable interactions with the lipids. As the TMB assembles, the β hairpins are stabilized by interactions with the neighboring β strands.Using computational methods that incorporate the above insights, we designed TMB sequences that successfully fold and assemble into both detergent micelles and lipid bilayers. Two of the designs were highly stable and could fold into liposomes more rapidly and reversibly than the transmembrane domain of the model outer membrane protein A (tOmpA) of Escherichia coli. A nuclear magnetic resonance solution structure and a high-resolution crystal structure for two different designs closely match the design models, showing that the TMB design method developed here can generate new structures with atomic-level accuracy.CONCLUSIONThis study elucidates key principles for de novo design of transmembrane β barrels, ranging from constraints on β-barrel architecture and β-hairpin design, as well as local and global sequence features. Our designs provide starting points for the bottom-up elucidation of the molecular mechanisms underlying TMB folding and interactions with the cellular outer membrane folding and insertion machinery. More generally, our work demonstrates that TMBs can be designed with atomic-level accuracy and opens the door to custom design of nanopores tailored for applications such as single-molecule sensing and sequencing.De novo{textendash}designed eight-stranded transmembrane β barrels fold spontaneously and reversibly into synthetic lipid membranes.The illustration shows the crystal structure of the protein TMB2.17 designed in this study, which adopts a structure identical to the design model.Credit: Ian Haydon.Transmembrane β-barrel proteins (TMBs) are of great interest for single-molecule analytical technologies because they can spontaneously fold and insert into membranes and form stable pores, but the range of pore properties that can be achieved by repurposing natural TMBs is limited. We leverage the power of de novo computational design coupled with a {textquotedblleft}hypothesis, design, and test{textquotedblright} approach to determine TMB design principles, notably, the importance of negative design to slow β-sheet assembly. We design new eight-stranded TMBs, with no homology to known TMBs, that insert and fold reversibly into synthetic lipid membranes and have nuclear magnetic resonance and x-ray crystal structures very similar to the computational models. These advances should enable the custom design of pores for a wide range of applications.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Xu, Chunfu; Lu, Peilong; El-Din, Tamer M. Gamal; Pei, Xue Y.; Johnson, Matthew C.; Uyeda, Atsuko; Bick, Matthew J.; Xu, Qi; Jiang, Daohua; Bai, Hua; Reggiano, Gabriella; Hsia, Yang; Brunette, T J; Dou, Jiayi; Ma, Dan; Lynch, Eric M.; Boyken, Scott E.; Huang, Po-Ssu; Stewart, Lance; DiMaio, Frank; Kollman, Justin M.; Luisi, Ben F.; Matsuura, Tomoaki; Catterall, William A.; Baker, David
Computational design of transmembrane pores Journal Article
In: Nature, vol. 585, pp. 129–134, 2020.
@article{Xu2020,
title = {Computational design of transmembrane pores},
author = {Chunfu Xu and Peilong Lu and Tamer M. Gamal El-Din and Xue Y. Pei and Matthew C. Johnson and Atsuko Uyeda and Matthew J. Bick and Qi Xu and Daohua Jiang and Hua Bai and Gabriella Reggiano and Yang Hsia and T J Brunette and Jiayi Dou and Dan Ma and Eric M. Lynch and Scott E. Boyken and Po-Ssu Huang and Lance Stewart and Frank DiMaio and Justin M. Kollman and Ben F. Luisi and Tomoaki Matsuura and William A. Catterall and David Baker },
url = {https://www.bakerlab.org/wp-content/uploads/2020/08/Xuetal_Nature2020_DeNovoPores.pdf
https://www.nature.com/articles/s41586-020-2646-5},
doi = {10.1038/s41586-020-2646-5},
year = {2020},
date = {2020-08-26},
journal = {Nature},
volume = {585},
pages = {129–134},
abstract = {Transmembrane channels and pores have key roles in fundamental biological processes and in biotechnological applications such as DNA nanopore sequencing, resulting in considerable interest in the design of pore-containing proteins. Synthetic amphiphilic peptides have been found to form ion channels, and there have been recent advances in de novo membrane protein design and in redesigning naturally occurring channel-containing proteins. However, the de novo design of stable, well-defined transmembrane protein pores that are capable of conducting ions selectively or are large enough to enable the passage of small-molecule fluorophores remains an outstanding challenge. Here we report the computational design of protein pores formed by two concentric rings of α-helices that are stable and monodisperse in both their water-soluble and their transmembrane forms. Crystal structures of the water-soluble forms of a 12-helical pore and a 16-helical pore closely match the computational design models. Patch-clamp electrophysiology experiments show that, when expressed in insect cells, the transmembrane form of the 12-helix pore enables the passage of ions across the membrane with high selectivity for potassium over sodium; ion passage is blocked by specific chemical modification at the pore entrance. When incorporated into liposomes using in vitro protein synthesis, the transmembrane form of the 16-helix pore—but not the 12-helix pore—enables the passage of biotinylated Alexa Fluor 488. A cryo-electron microscopy structure of the 16-helix transmembrane pore closely matches the design model. The ability to produce structurally and functionally well-defined transmembrane pores opens the door to the creation of designer channels and pores for a wide variety of applications.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
2025
FROM THE LAB
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COLLABORATOR LED
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2024
FROM THE LAB
Linna An, Meerit Said, Long Tran, Sagardip Majumder, Inna Goreshnik, Gyu Rie Lee, David Juergens, Justas Dauparas, Ivan Anishchenko, Brian Coventry, Asim K. Bera, Alex Kang, Paul M. Levine, Valentina Alvarez, Arvind Pillai, Christoffer Norn, David Feldman, Dmitri Zorine, Derrick R. Hicks, Xinting Li, Mariana Garcia Sanchez, Dionne K. Vafeados, Patrick J. Salveson, Anastassia A. Vorobieva, David Baker
Binding and sensing diverse small molecules using shape-complementary pseudocycles Journal Article
In: Science, 2024.
@article{An2024,
title = {Binding and sensing diverse small molecules using shape-complementary pseudocycles},
author = {Linna An and Meerit Said and Long Tran and Sagardip Majumder and Inna Goreshnik and Gyu Rie Lee and David Juergens and Justas Dauparas and Ivan Anishchenko and Brian Coventry and Asim K. Bera and Alex Kang and Paul M. Levine and Valentina Alvarez and Arvind Pillai and Christoffer Norn and David Feldman and Dmitri Zorine and Derrick R. Hicks and Xinting Li and Mariana Garcia Sanchez and Dionne K. Vafeados and Patrick J. Salveson and Anastassia A. Vorobieva and David Baker},
url = {https://www.science.org/doi/10.1126/science.adn3780, Science},
doi = {10.1126/science.adn3780},
year = {2024},
date = {2024-07-19},
urldate = {2024-07-19},
journal = {Science},
publisher = {American Association for the Advancement of Science (AAAS)},
abstract = {We describe an approach for designing high-affinity small molecule–binding proteins poised for downstream sensing. We use deep learning–generated pseudocycles with repeating structural units surrounding central binding pockets with widely varying shapes that depend on the geometry and number of the repeat units. We dock small molecules of interest into the most shape complementary of these pseudocycles, design the interaction surfaces for high binding affinity, and experimentally screen to identify designs with the highest affinity. We obtain binders to four diverse molecules, including the polar and flexible methotrexate and thyroxine. Taking advantage of the modular repeat structure and central binding pockets, we construct chemically induced dimerization systems and low-noise nanopore sensors by splitting designs into domains that reassemble upon ligand addition.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Samuel Berhanu, Sagardip Majumder, Thomas Müntener, James Whitehouse, Carolin Berner, Asim K. Bera, Alex Kang, Binyong Liang, Nasir Khan, Banumathi Sankaran, Lukas K. Tamm, David J. Brockwell, Sebastian Hiller, Sheena E. Radford, David Baker, Anastassia A. Vorobieva
Sculpting conducting nanopore size and shape through de novo protein design Journal Article
In: Science, 2024.
@article{Berhanu2024,
title = {Sculpting conducting nanopore size and shape through de novo protein design},
author = {Samuel Berhanu and Sagardip Majumder and Thomas Müntener and James Whitehouse and Carolin Berner and Asim K. Bera and Alex Kang and Binyong Liang and Nasir Khan and Banumathi Sankaran and Lukas K. Tamm and David J. Brockwell and Sebastian Hiller and Sheena E. Radford and David Baker and Anastassia A. Vorobieva},
url = {https://www.science.org/doi/10.1126/science.adn3796, Science},
doi = {10.1126/science.adn3796},
year = {2024},
date = {2024-07-19},
urldate = {2024-07-19},
journal = {Science},
publisher = {American Association for the Advancement of Science (AAAS)},
abstract = {Transmembrane β-barrels have considerable potential for a broad range of sensing applications. Current engineering approaches for nanopore sensors are limited to naturally occurring channels, which provide suboptimal starting points. By contrast, de novo protein design can in principle create an unlimited number of new nanopores with any desired properties. Here we describe a general approach to designing transmembrane β-barrel pores with different diameters and pore geometries. Nuclear magnetic resonance and crystallographic characterization show that the designs are stably folded with structures resembling those of the design models. The designs have distinct conductances that correlate with their pore diameter, ranging from 110 picosiemens (~0.5 nanometer pore diameter) to 430 picosiemens (~1.1 nanometer pore diameter). Our approach opens the door to the custom design of transmembrane nanopores for sensing and sequencing applications.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
COLLABORATOR LED
Sorry, no publications matched your criteria.
2023
FROM THE LAB
Lutz, Isaac D. and Wang, Shunzhi and Norn, Christoffer and Courbet, Alexis and Borst, Andrew J. and Zhao, Yan Ting and Dosey, Annie and Cao, Longxing and Xu, Jinwei and Leaf, Elizabeth M. and Treichel, Catherine and Litvicov, Patrisia and Li, Zhe and Goodson, Alexander D. and Rivera-Sánchez, Paula and Bratovianu, Ana-Maria and Baek, Minkyung and King, Neil P. and Ruohola-Baker, Hannele and Baker, David
Top-down design of protein architectures with reinforcement learning Journal Article
In: Science, 2023.
@article{Lutz2023,
title = {Top-down design of protein architectures with reinforcement learning},
author = {Lutz, Isaac D.
and Wang, Shunzhi
and Norn, Christoffer
and Courbet, Alexis
and Borst, Andrew J.
and Zhao, Yan Ting
and Dosey, Annie
and Cao, Longxing
and Xu, Jinwei
and Leaf, Elizabeth M.
and Treichel, Catherine
and Litvicov, Patrisia
and Li, Zhe
and Goodson, Alexander D.
and Rivera-Sánchez, Paula
and Bratovianu, Ana-Maria
and Baek, Minkyung
and King, Neil P.
and Ruohola-Baker, Hannele
and Baker, David},
url = {https://www.science.org/doi/10.1126/science.adf6591, Science
https://www.ipd.uw.edu/wp-content/uploads/2023/04/science.adf6591.pdf, PDF},
doi = {10.1126/science.adf6591},
year = {2023},
date = {2023-04-20},
journal = {Science},
abstract = {As a result of evolutionary selection, the subunits of naturally occurring protein assemblies often fit together with substantial shape complementarity to generate architectures optimal for function in a manner not achievable by current design approaches. We describe a “top-down” reinforcement learning–based design approach that solves this problem using Monte Carlo tree search to sample protein conformers in the context of an overall architecture and specified functional constraints. Cryo–electron microscopy structures of the designed disk-shaped nanopores and ultracompact icosahedra are very close to the computational models. The icosohedra enable very-high-density display of immunogens and signaling molecules, which potentiates vaccine response and angiogenesis induction. Our approach enables the top-down design of complex protein nanomaterials with desired system properties and demonstrates the power of reinforcement learning in protein design.
},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
COLLABORATOR LED
Sorry, no publications matched your criteria.
2022
FROM THE LAB
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COLLABORATOR LED
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2021
FROM THE LAB
Vorobieva, Anastassia A., White, Paul, Liang, Binyong, Horne, Jim E., Bera, Asim K., Chow, Cameron M., Gerben, Stacey, Marx, Sinduja, Kang, Alex, Stiving, Alyssa Q., Harvey, Sophie R., Marx, Dagan C., Khan, G. Nasir, Fleming, Karen G., Wysocki, Vicki H., Brockwell, David J., Tamm, Lukas K., Radford, Sheena E., Baker, David
De novo design of transmembrane beta barrels Journal Article
In: Science, vol. 371, no. 6531, 2021.
@article{Vorobieva2021,
title = {De novo design of transmembrane beta barrels},
author = {Vorobieva, Anastassia A. and White, Paul and Liang, Binyong and Horne, Jim E. and Bera, Asim K. and Chow, Cameron M. and Gerben, Stacey and Marx, Sinduja and Kang, Alex and Stiving, Alyssa Q. and Harvey, Sophie R. and Marx, Dagan C. and Khan, G. Nasir and Fleming, Karen G. and Wysocki, Vicki H. and Brockwell, David J. and Tamm, Lukas K. and Radford, Sheena E. and Baker, David},
url = {https://science.sciencemag.org/content/371/6531/eabc8182, Science
https://www.bakerlab.org/wp-content/uploads/2021/02/Vorobieva_etal_Science2021_De_Novo_Transmembrane_beta_barrels.pdf, Download PDF},
doi = {10.1126/science.abc8182},
year = {2021},
date = {2021-02-19},
urldate = {2021-02-19},
journal = {Science},
volume = {371},
number = {6531},
abstract = {Computational design offers the possibility of making proteins with customized structures and functions. The range of accessible protein scaffolds has expanded with the design of increasingly complex cytoplasmic proteins and, recently, helical membrane proteins. Vorobieva et al. describe the successful computational design of eight-stranded transmembrane β-barrel proteins (TMBs). Using an iterative approach, they show the importance of negative design to prevent off-target structures and gain insight into the sequence determinants of TMB folding. Twenty-three designs satisfied biochemical screens for a TMB structure, and two structures were experimentally validated by nuclear magnetic resonance spectroscopy or x-ray crystallography. This is a step toward the custom design of pores for applications such as single-molecule sequencing.Science, this issue p. eabc8182INTRODUCTIONDespite their key biological roles, only a few proteins that fold into lipid membranes have been designed de novo. A class of membrane proteins{textemdash}transmembrane β barrels (TMBs){textemdash}forms a continuous sheet that closes on itself in lipid membranes. In addition to the challenge of designing β-sheet proteins, which are prone to misfolding and aggregation if folding is not properly controlled, the computational design of TMBs is complicated by limited understanding of TMB folding. As a result, no TMB has been designed de novo to date.Although the folding of TMBs in vivo is catalyzed by the β-barrel assembly machinery (BAM), many TMBs can also fold spontaneously in synthetic membranes to form stable pores, making them attractive for biotechnology and single-molecule analytical applications. Hence, de novo design of TMBs has potential both for understanding the determinants of TMB folding and membrane insertion and for the custom engineering of TMB nanopores.RATIONALEWe used de novo protein design to distill key principles of TMB folding through several design-build-test cycles. We iterated between hypothesis formulation, its implementation into computational design methods, and experimental characterization of the resulting proteins. To focus on the fundamental principles of TMB folding in the absence of complications due to interactions with chaperones and BAM in vivo, we focused on the challenge of de novo design of eight-stranded TMBs, which can fold and assemble into synthetic lipid membranes.RESULTSWe used a combination of purely geometric models and explicit Rosetta protein structure simulations to determine the constraints that β-strand connectivity and membrane embedding place on the TMB architecture. Through a series of design-build-test cycles, we found that, unlike almost all other classes of proteins, locally destabilizing sequences are critical for expression and folding of TMBs, and that the β-turns that translocate through the bilayer during folding have to be destabilized to enable correct assembly in the membrane. Our results suggest that premature formation of β hairpins may result in off-target β-sheet structures that compete with proper membrane insertion and folding, and hence the β hairpins of TMBs must be designed such that they are only transiently formed prior to membrane insertion, when the protein is in an aqueous environment. In the hydrophobic environment of the lipid bilayer, the full TMB can assemble because the membrane-facing nonpolar residues, which would tend to cluster nonspecifically in an aqueous environment, instead make favorable interactions with the lipids. As the TMB assembles, the β hairpins are stabilized by interactions with the neighboring β strands.Using computational methods that incorporate the above insights, we designed TMB sequences that successfully fold and assemble into both detergent micelles and lipid bilayers. Two of the designs were highly stable and could fold into liposomes more rapidly and reversibly than the transmembrane domain of the model outer membrane protein A (tOmpA) of Escherichia coli. A nuclear magnetic resonance solution structure and a high-resolution crystal structure for two different designs closely match the design models, showing that the TMB design method developed here can generate new structures with atomic-level accuracy.CONCLUSIONThis study elucidates key principles for de novo design of transmembrane β barrels, ranging from constraints on β-barrel architecture and β-hairpin design, as well as local and global sequence features. Our designs provide starting points for the bottom-up elucidation of the molecular mechanisms underlying TMB folding and interactions with the cellular outer membrane folding and insertion machinery. More generally, our work demonstrates that TMBs can be designed with atomic-level accuracy and opens the door to custom design of nanopores tailored for applications such as single-molecule sensing and sequencing.De novo{textendash}designed eight-stranded transmembrane β barrels fold spontaneously and reversibly into synthetic lipid membranes.The illustration shows the crystal structure of the protein TMB2.17 designed in this study, which adopts a structure identical to the design model.Credit: Ian Haydon.Transmembrane β-barrel proteins (TMBs) are of great interest for single-molecule analytical technologies because they can spontaneously fold and insert into membranes and form stable pores, but the range of pore properties that can be achieved by repurposing natural TMBs is limited. We leverage the power of de novo computational design coupled with a {textquotedblleft}hypothesis, design, and test{textquotedblright} approach to determine TMB design principles, notably, the importance of negative design to slow β-sheet assembly. We design new eight-stranded TMBs, with no homology to known TMBs, that insert and fold reversibly into synthetic lipid membranes and have nuclear magnetic resonance and x-ray crystal structures very similar to the computational models. These advances should enable the custom design of pores for a wide range of applications.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
COLLABORATOR LED
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2020
FROM THE LAB
Chunfu Xu, Peilong Lu, Tamer M. Gamal El-Din, Xue Y. Pei, Matthew C. Johnson, Atsuko Uyeda, Matthew J. Bick, Qi Xu, Daohua Jiang, Hua Bai, Gabriella Reggiano, Yang Hsia, T J Brunette, Jiayi Dou, Dan Ma, Eric M. Lynch, Scott E. Boyken, Po-Ssu Huang, Lance Stewart, Frank DiMaio, Justin M. Kollman, Ben F. Luisi, Tomoaki Matsuura, William A. Catterall, David Baker
Computational design of transmembrane pores Journal Article
In: Nature, vol. 585, pp. 129–134, 2020.
@article{Xu2020,
title = {Computational design of transmembrane pores},
author = {Chunfu Xu and Peilong Lu and Tamer M. Gamal El-Din and Xue Y. Pei and Matthew C. Johnson and Atsuko Uyeda and Matthew J. Bick and Qi Xu and Daohua Jiang and Hua Bai and Gabriella Reggiano and Yang Hsia and T J Brunette and Jiayi Dou and Dan Ma and Eric M. Lynch and Scott E. Boyken and Po-Ssu Huang and Lance Stewart and Frank DiMaio and Justin M. Kollman and Ben F. Luisi and Tomoaki Matsuura and William A. Catterall and David Baker },
url = {https://www.bakerlab.org/wp-content/uploads/2020/08/Xuetal_Nature2020_DeNovoPores.pdf
https://www.nature.com/articles/s41586-020-2646-5},
doi = {10.1038/s41586-020-2646-5},
year = {2020},
date = {2020-08-26},
journal = {Nature},
volume = {585},
pages = {129–134},
abstract = {Transmembrane channels and pores have key roles in fundamental biological processes and in biotechnological applications such as DNA nanopore sequencing, resulting in considerable interest in the design of pore-containing proteins. Synthetic amphiphilic peptides have been found to form ion channels, and there have been recent advances in de novo membrane protein design and in redesigning naturally occurring channel-containing proteins. However, the de novo design of stable, well-defined transmembrane protein pores that are capable of conducting ions selectively or are large enough to enable the passage of small-molecule fluorophores remains an outstanding challenge. Here we report the computational design of protein pores formed by two concentric rings of α-helices that are stable and monodisperse in both their water-soluble and their transmembrane forms. Crystal structures of the water-soluble forms of a 12-helical pore and a 16-helical pore closely match the computational design models. Patch-clamp electrophysiology experiments show that, when expressed in insect cells, the transmembrane form of the 12-helix pore enables the passage of ions across the membrane with high selectivity for potassium over sodium; ion passage is blocked by specific chemical modification at the pore entrance. When incorporated into liposomes using in vitro protein synthesis, the transmembrane form of the 16-helix pore—but not the 12-helix pore—enables the passage of biotinylated Alexa Fluor 488. A cryo-electron microscopy structure of the 16-helix transmembrane pore closely matches the design model. The ability to produce structurally and functionally well-defined transmembrane pores opens the door to the creation of designer channels and pores for a wide variety of applications.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
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