Evolutionary Algorithms for the Inverse Protein Folding Problem

Sune S. Nielsen (), Grégoire Danoy (), Wiktor Jurkowski (), Roland Krause (), Reinhard Schneider (), El-Ghazali Talbi () and Pascal Bouvry ()
Additional contact information
Sune S. Nielsen: University of Luxembourg, Computer Science and Communications (CSC) Research Unit, FSTC
Grégoire Danoy: University of Luxembourg, Computer Science and Communications (CSC) Research Unit, FSTC
Wiktor Jurkowski: Norwich Research Park, The Genome Analysis Centre (TGAC)
Roland Krause: University of Luxembourg, Luxembourg Centre for Systems Biomedicine (LCSB)
Reinhard Schneider: University of Luxembourg, Luxembourg Centre for Systems Biomedicine (LCSB)
El-Ghazali Talbi: Université des sciences et technologies de Lille, INRIA Lille Nord Europe
Pascal Bouvry: University of Luxembourg, Computer Science and Communications (CSC) Research Unit, FSTC

Chapter 33 in Handbook of Heuristics, 2018, pp 999-1023 from Springer

Abstract: Abstract Protein structure prediction is an essential step in understanding the molecular mechanisms of living cells with widespread application in biotechnology and health. The inverse folding problem (IFP) of finding sequences that fold into a defined structure is in itself an important research problem at the heart of rational protein design. In this chapter, a multi-objective genetic algorithm (MOGA) using the diversity-as-objective (DAO) variant of multi-objectivization is presented, which optimizes the secondary structure similarity and the sequence diversity at the same time and hence searches deeper in the sequence solution space. To validate the final optimization results, a subset of the best sequences was selected for tertiary structure prediction. Comparing secondary structure annotation and tertiary structure of the predicted model to the original protein structure demonstrates that relying on fast approximation during the optimization process permits to obtain meaningful sequences.

Keywords: Genetic algorithm; Diversity preservation; Inverse folding problem (search for similar items in EconPapers)
Date: 2018
References: Add references at CitEc
Citations:

There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-3-319-07124-4_59

Ordering information: This item can be ordered from
http://www.springer.com/9783319071244

DOI: 10.1007/978-3-319-07124-4_59

Access Statistics for this chapter

More chapters in Springer Books from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().