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

被引：7

作者：

Tamo, Giorgio ^{[1
,2
]}

Maesani, Andrea ^{[3
]}

Traeger, Sylvain ^{[1
,2
]}

Degiacomi, Matteo T. ^{[4
]}

Floreano, Dario ^{[3
]}

Dal Peraro, Matteo ^{[1
,2
]}

机构：

[1] Ecole Polytech Fed Lausanne, Sch Life Sci, Inst Bioengn, Lab Biomol Modeling, CH-1015 Lausanne, Switzerland

[2] SIB, CH-1015 Lausanne, Switzerland

[3] Ecole Polytech Fed Lausanne, Inst Microengn, Lab Intelligent Syst, CH-1015 Lausanne, Switzerland

[4] Univ Oxford, Dept Chem, Chem Res Lab, Oxford, England

来源：

SCIENTIFIC REPORTS | 2017年 / 7卷

基金：

瑞士国家科学基金会;

关键词：

DOCKING; ARCHITECTURES; OPTIMIZATION; MAPS;

D O I：

10.1038/s41598-017-00266-w

中图分类号：

O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];

学科分类号：

07 ; 0710 ; 09 ;

摘要：

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.

引用

页数：9

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