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Improving the Accuracy of Fitted Atomic Models in Cryo-EM Density Maps of Protein Assemblies Using Evolutionary Information from Aligned Homologous Proteins

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Data Mining Techniques for the Life Sciences

Part of the book series: Methods in Molecular Biology ((MIMB,volume 1415))

Abstract

Cryo-Electron Microscopy (cryo-EM) has become an important technique to obtain structural insights into large macromolecular assemblies. However the resolution of the density maps do not allow for its interpretation at atomic level. Hence they are combined with high resolution structures along with information from other experimental or bioinformatics techniques to obtain pseudo-atomic models. Here, we describe the use of evolutionary conservation of residues as obtained from protein structures and alignments of homologous proteins to detect errors in the fitting of atomic structures as well as improve accuracy of the protein–protein interfacial regions in the cryo-EM density maps.

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Acknowledgments

This research is supported by Department of Biotechnology, Government of India, Mathematical Biology initiative, Department of Science and Technology and the Indo-French collaborative grant (CEFIPRA). N.S. is a J.C. Bose National Fellow.

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Authors and Affiliations

  1. Molecular Biophysics Unit, Indian Institute of Science, Bangalore, 560012, India

    Ramachandran Rakesh & Narayanaswamy Srinivasan

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  1. Ramachandran Rakesh
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  2. Narayanaswamy Srinivasan
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Correspondence to Narayanaswamy Srinivasan .

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Editors and Affiliations

  1. Max F. Perutz Laboratories GmbH, Universität Wien, Wien, Austria

    Oliviero Carugo

  2. Technology and Research (A*STAR), Agency for Science, Singapore, Singapore

    Frank Eisenhaber

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Rakesh, R., Srinivasan, N. (2016). Improving the Accuracy of Fitted Atomic Models in Cryo-EM Density Maps of Protein Assemblies Using Evolutionary Information from Aligned Homologous Proteins. In: Carugo, O., Eisenhaber, F. (eds) Data Mining Techniques for the Life Sciences. Methods in Molecular Biology, vol 1415. Humana Press, New York, NY. https://doi.org/10.1007/978-1-4939-3572-7_10

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  • DOI: https://doi.org/10.1007/978-1-4939-3572-7_10

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  • Print ISBN: 978-1-4939-3570-3

  • Online ISBN: 978-1-4939-3572-7

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