Abstract
Inverse protein folding or protein design stands for searching a particular amino acids sequence whose native structure or folding matches a pre specified target.
The problem of finding the corresponding folded structure of a particular sequence is, per se, a hard computational problem.
We use a genetic algorithm for searching the space of potential sequences, and the fitness of each individual is measured with the output of a second GA performing a minimization process in the space of structures.
Using an off-lattice protein-like 2D model, we show how the implemented techniques are able to obtain a variety of sequences attaining the target structures proposed.
Keywords
- Genetic Algorithm
- Protein Design
- Interaction Matrix
- Target Structure
- Protein Structure Prediction
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
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Pelta, D., Carrascal, A. (2007). Inverse Protein Folding on 2D Off-Lattice Model: Initial Results and Perspectives. In: Marchiori, E., Moore, J.H., Rajapakse, J.C. (eds) Evolutionary Computation,Machine Learning and Data Mining in Bioinformatics. EvoBIO 2007. Lecture Notes in Computer Science, vol 4447. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-71783-6_20
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DOI: https://doi.org/10.1007/978-3-540-71783-6_20
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-71782-9
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