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Disentangling constraints using viability evolution principles in integrative modeling of macromolecular assemblies

Tamò, G.; Maesani, A.; Träger, S.; Degiacomi, M.T.; Floreano, D.; Dal Peraro, Matteo

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Authors

G. Tamò

A. Maesani

S. Träger

D. Floreano

Matteo Dal Peraro



Abstract

Predicting the structure of large molecular assemblies remains a challenging task in structural biology when using integrative modeling approaches. One of the main issues stems from the treatment of heterogeneous experimental data used to predict the architecture of native complexes. We propose a new method, applied here for the first time to a set of symmetrical complexes, based on evolutionary computation that treats every available experimental input independently, bypassing the need to balance weight components assigned to aggregated fitness functions during optimization.

Citation

Tamò, G., Maesani, A., Träger, S., Degiacomi, M., Floreano, D., & Dal Peraro, M. (2017). Disentangling constraints using viability evolution principles in integrative modeling of macromolecular assemblies. Scientific Reports, 7(1), Article 235. https://doi.org/10.1038/s41598-017-00266-w

Journal Article Type Article
Acceptance Date Feb 14, 2017
Online Publication Date Mar 22, 2017
Publication Date Mar 22, 2017
Deposit Date Jul 26, 2017
Publicly Available Date Mar 28, 2024
Journal Scientific Reports
Publisher Nature Research
Peer Reviewed Peer Reviewed
Volume 7
Issue 1
Article Number 235
DOI https://doi.org/10.1038/s41598-017-00266-w

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This work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/





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