A new framework for computational protein design through cost function network optimization | Zendy

Seydou Traoré | Zendy; David Allouche | Zendy; Isabelle André | Zendy; Simon de Givry | Zendy; George Katsirelos | Zendy; Thomas Schiex | Zendy; Sophie Barbe | Zendy

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A new framework for computational protein design through cost function network optimization

Author(s) -

Seydou Traoré,

David Allouche,

Isabelle André,

Simon de Givry,

George Katsirelos,

Thomas Schiex,

Sophie Barbe

Publication year - 2013

Publication title -

bioinformatics

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 3.599

H-Index - 390

eISSN - 1367-4811

pISSN - 1367-4803

DOI - 10.1093/bioinformatics/btt374

Subject(s) - perl , solver , computer science , pipeline (software) , mathematical optimization , protein design , function (biology) , combinatorial optimization , theoretical computer science , algorithm , mathematics , protein structure , programming language , physics , nuclear magnetic resonance , evolutionary biology , biology

The main challenge for structure-based computational protein design (CPD) remains the combinatorial nature of the search space. Even in its simplest fixed-backbone formulation, CPD encompasses a computationally difficult NP-hard problem that prevents the exact exploration of complex systems defining large sequence-conformation spaces.

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