Name
Abstract | ||
|---|---|---|
We used Differential Evolution (DE) for the problem of protein structure prediction. We employed the HP model to represent the folding conformations of a protein in a lattice. In this model the nature of amino acids is reduced considering only two types: hydrophobic residues (H) and polar residues (P), which is based on the recognition that hydrophobic interactions are a dominant force in protein folding. Given a primary sequence of amino acids, the problem is to search for the folding structure in the lattice that minimizes an energy potential. This energy reflects the fact that the hydrophobic amino acids have a propensity to form a hydrophobic core. The complexity of the problem has been shown to be NP-hard, with minimal progress achieved in this category of ab initio folding. We combined DE with methods to transform illegal protein conformations to feasible ones, showing the capabilities of the hybridized DE with respect to previous works. |
Year | DOI | Venue |
|---|---|---|
2011 | 10.1007/978-3-642-21344-1_34 | IWINAC (1) |
Keywords | Field | DocType |
hp model,protein folding,ab initio folding,hydrophobic residue,hydrophobic interaction,differential evolution,protein structure prediction,hydrophobic core,hydrophobic amino acid,amino acid,illegal protein conformation,folding structure,folding conformation | Chemical physics,Protein structure prediction,Protein folding,Lattice (order),Amino acid,Computer science,Differential evolution,Polar,Artificial intelligence,Hydrophobic effect,Ab initio,Machine learning | Conference |
Volume | ISSN | Citations |
6686 | 0302-9743 | 14 |
PageRank | References | Authors |
0.64 | 10 | 2 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| José Santos | 1 | 97 | 14.77 |
| M. Diéguez | 2 | 14 | 0.64 |