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

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.

SUBMITTER: Tamo G

PROVIDER: S-EPMC5427971 | biostudies-literature | 2017 Mar

REPOSITORIES: biostudies-literature

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

Tamò Giorgio G Maesani Andrea A Träger Sylvain S Degiacomi Matteo T MT Floreano Dario D Dal Peraro Matteo M

Scientific reports 20170322 1

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 balan ...[more]

PMID: 28331186

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