Deep learning-driven insights into super protein complexes for outer membrane protein biogenesis in bacteria
To reach their final destinations, outer membrane proteins (OMPs) of gram-negative bacteria undertake an eventful journey beginning in the cytosol. Multiple molecular machines, chaperones, proteases, and other enzymes facilitate the translocation and assembly of OMPs. These helpers usually associate...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
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eLife Sciences Publications Ltd
2022-12-01
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| Series: | eLife |
| Subjects: | |
| Online Access: | https://elifesciences.org/articles/82885 |
| _version_ | 1797975469665026048 |
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| author | Mu Gao Davi Nakajima An Jeffrey Skolnick |
| author_facet | Mu Gao Davi Nakajima An Jeffrey Skolnick |
| author_sort | Mu Gao |
| collection | DOAJ |
| description | To reach their final destinations, outer membrane proteins (OMPs) of gram-negative bacteria undertake an eventful journey beginning in the cytosol. Multiple molecular machines, chaperones, proteases, and other enzymes facilitate the translocation and assembly of OMPs. These helpers usually associate, often transiently, forming large protein assemblies. They are not well understood due to experimental challenges in capturing and characterizing protein-protein interactions (PPIs), especially transient ones. Using AF2Complex, we introduce a high-throughput, deep learning pipeline to identify PPIs within the Escherichia coli cell envelope and apply it to several proteins from an OMP biogenesis pathway. Among the top confident hits obtained from screening ~1500 envelope proteins, we find not only expected interactions but also unexpected ones with profound implications. Subsequently, we predict atomic structures for these protein complexes. These structures, typically of high confidence, explain experimental observations and lead to mechanistic hypotheses for how a chaperone assists a nascent, precursor OMP emerging from a translocon, how another chaperone prevents it from aggregating and docks to a β-barrel assembly port, and how a protease performs quality control. This work presents a general strategy for investigating biological pathways by using structural insights gained from deep learning-based predictions. |
| first_indexed | 2024-04-11T04:36:03Z |
| format | Article |
| id | doaj.art-97c6484d891040a4b954c311f162650c |
| institution | Directory Open Access Journal |
| issn | 2050-084X |
| language | English |
| last_indexed | 2024-04-11T04:36:03Z |
| publishDate | 2022-12-01 |
| publisher | eLife Sciences Publications Ltd |
| record_format | Article |
| series | eLife |
| spelling | doaj.art-97c6484d891040a4b954c311f162650c2022-12-28T16:03:30ZengeLife Sciences Publications LtdeLife2050-084X2022-12-011110.7554/eLife.82885Deep learning-driven insights into super protein complexes for outer membrane protein biogenesis in bacteriaMu Gao0https://orcid.org/0000-0002-0378-3704Davi Nakajima An1Jeffrey Skolnick2https://orcid.org/0000-0002-1877-4958Center for the Study of Systems Biology, School of Biological Sciences, Georgia Institute of Technology, Atlanta, United StatesSchool of Computer Science, Georgia Institute of Technology, Atlanta, United StatesCenter for the Study of Systems Biology, School of Biological Sciences, Georgia Institute of Technology, Atlanta, United StatesTo reach their final destinations, outer membrane proteins (OMPs) of gram-negative bacteria undertake an eventful journey beginning in the cytosol. Multiple molecular machines, chaperones, proteases, and other enzymes facilitate the translocation and assembly of OMPs. These helpers usually associate, often transiently, forming large protein assemblies. They are not well understood due to experimental challenges in capturing and characterizing protein-protein interactions (PPIs), especially transient ones. Using AF2Complex, we introduce a high-throughput, deep learning pipeline to identify PPIs within the Escherichia coli cell envelope and apply it to several proteins from an OMP biogenesis pathway. Among the top confident hits obtained from screening ~1500 envelope proteins, we find not only expected interactions but also unexpected ones with profound implications. Subsequently, we predict atomic structures for these protein complexes. These structures, typically of high confidence, explain experimental observations and lead to mechanistic hypotheses for how a chaperone assists a nascent, precursor OMP emerging from a translocon, how another chaperone prevents it from aggregating and docks to a β-barrel assembly port, and how a protease performs quality control. This work presents a general strategy for investigating biological pathways by using structural insights gained from deep learning-based predictions.https://elifesciences.org/articles/82885protein-protein interactionprotein complex structure predictionvirtual screeningdeep learningouter membrane protein biogenesistranslocon |
| spellingShingle | Mu Gao Davi Nakajima An Jeffrey Skolnick Deep learning-driven insights into super protein complexes for outer membrane protein biogenesis in bacteria eLife protein-protein interaction protein complex structure prediction virtual screening deep learning outer membrane protein biogenesis translocon |
| title | Deep learning-driven insights into super protein complexes for outer membrane protein biogenesis in bacteria |
| title_full | Deep learning-driven insights into super protein complexes for outer membrane protein biogenesis in bacteria |
| title_fullStr | Deep learning-driven insights into super protein complexes for outer membrane protein biogenesis in bacteria |
| title_full_unstemmed | Deep learning-driven insights into super protein complexes for outer membrane protein biogenesis in bacteria |
| title_short | Deep learning-driven insights into super protein complexes for outer membrane protein biogenesis in bacteria |
| title_sort | deep learning driven insights into super protein complexes for outer membrane protein biogenesis in bacteria |
| topic | protein-protein interaction protein complex structure prediction virtual screening deep learning outer membrane protein biogenesis translocon |
| url | https://elifesciences.org/articles/82885 |
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