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

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: Aug 2, 2017
• Journal: Scientific Reports
• Electronic ISSN: 2045-2322
• Publisher: Nature Research
• Peer Reviewed: Peer Reviewed
• Volume: 7
• Issue: 1
• Article Number: 235
• DOI: https://doi.org/10.1038/s41598-017-00266-w
• Public URL: https://durham-repository.worktribe.com/output/1353549