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Matching of EM Map Segments to Structurally-Relevant Bio-molecular Regions

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Book cover High Performance Computing (CARLA 2019)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1087))

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Abstract

Electron microscopy is a technique used to determine the structure of bio-molecular machines via three-dimensional images (called maps). The state-of-the-art is able to determine structures at resolutions that allow us to identify up to secondary structural features, in some cases, but it is not widespread. Furthermore, because molecular interactions often require atomic-level details to be understood, it is still necessary to complement current maps with techniques that provide finer-grain structural details. We applied segmentation techniques to maps in the Electron Microscopy Data Bank (EMDB), the standard community repository for these data. We assessed the potential of these algorithms to match functionally relevant regions in their atomic-resolution image counterparts by comparing against three protein systems, each with multiple atomic-detailed domains. We found that at least 80% of amino acid residues in 7 out of 12 domains were assigned to single segments, suggesting there is potential to match the lower resolution segmented regions to the atomic counterparts. We also qualitatively analyzed the potential on other EMDB structures, as well as generating the raw segmentation information for the complete EMDB, for interested researchers to use. Results can be accessed online and the library developed is provided as part of an open-source project.

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Notes

  1. 1.

    This method is based on the combination of physico-chemical, shape and cross correlation features between each of the domains and the EM map. This work is not part of a stand-alone article as of this writing.

  2. 2.

    Note that for 1010 there are 8 missing residues, observed in the C-\(\alpha \) trace but not the PDB with all atomic details. They are ommitted for analysis purposes.

  3. 3.

    The production version of EM-SURFER is hosted at http://kiharalab.org/em-surfer. An example result from our alpha release of the latest version, that includes segmentation results, can be accessed at is available at http://emsurfer.tecdatalab.org/result/0185.

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Acknowledgements

Funded by the Vicerrrectoría de Investigación y Extensión at Instituto Tecnológico de Costa Rica.

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Authors and Affiliations

  1. Instituto Tecnológico de Costa Rica, Escuela de Computación, Campus Cartago, Cartago, Costa Rica

    Manuel Zumbado-Corrales, Luis Castillo-Valverde, José Salas-Bonilla, Julio Víquez-Murillo & Juan Esquivel-Rodríguez

  2. Advanced Computing Laboratory, National High Technology Center, San José, Costa Rica

    Manuel Zumbado-Corrales

  3. Department of Biological Sciences/Department of Computer Science, Purdue University, West Lafayette, IN, USA

    Daisuke Kihara

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  1. Manuel Zumbado-Corrales
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  2. Luis Castillo-Valverde
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  3. José Salas-Bonilla
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  5. Daisuke Kihara
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  6. Juan Esquivel-Rodríguez
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Correspondence to Juan Esquivel-Rodríguez .

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Editors and Affiliations

  1. Costa Rica Institute of Technology, Cartago, Costa Rica

    Juan Luis Crespo-Mariño

  2. Costa Rica Institute of Technology, Cartago, Costa Rica

    Esteban Meneses-Rojas

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Zumbado-Corrales, M., Castillo-Valverde, L., Salas-Bonilla, J., Víquez-Murillo, J., Kihara, D., Esquivel-Rodríguez, J. (2020). Matching of EM Map Segments to Structurally-Relevant Bio-molecular Regions. In: Crespo-Mariño, J., Meneses-Rojas, E. (eds) High Performance Computing. CARLA 2019. Communications in Computer and Information Science, vol 1087. Springer, Cham. https://doi.org/10.1007/978-3-030-41005-6_32

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  • DOI: https://doi.org/10.1007/978-3-030-41005-6_32

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