An Ant Colony Optimization Algorithm for the 2D HP Protein Folding Problem

Shmygelska, Alena; Hernández, Rosalía Aguirre; Hoos, Holger H.

doi:10.1007/3-540-45724-0_4

Cited by 80 publications

(115 citation statements)

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“…Elsewhere, various search methods have been tested in lattice models 26,27,28,29 . However, we were interested in comparing zipping and assembly with replica-exchange methods, which are generalized ensemble approaches to reducing barriers and increasing sampling efficiencies 30,31 .…”

Section: Zanda Outperforms Replica-exchange Monte Carlo (Remc) In Reachmentioning

confidence: 99%

Exploring zipping and assembly as a protein folding principle

Voelz

Dill

2007

Proteins

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It has been proposed that proteins fold by a process called "Zipping & Assembly" (Z&A). Zipping refers to the growth of local substructures within the chain, and assembly refers to the coming together of already-formed pieces. Our interest here is in whether Z&A is a general method that can fold most of sequence space, to global minima, efficiently. Using the HP model, we can address this question by enumerating full conformation and sequence spaces. We find that Z&A reaches the global energy minimum native states, even though it searches only a very small fraction of conformational space, for most sequences in the full sequence space. We find that Z&A, a mechanism-based search, is more efficient in our tests than the Replica Exchange search method. Folding efficiency is increased for chains having: (a) small loop-closure steps, consistent with observations by Plaxco et al. 1 that folding rates correlate with contact order, (b) neither too few nor too many nucleation sites per chain, and (c) assembly steps that do not occur too early in the folding process. We find that the efficiency increases with chain length, although our range of chain lengths is limited. We believe these insights may be useful for developing faster protein conformational search algorithms.

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Section: Zanda Outperforms Replica-exchange Monte Carlo (Remc) In Reachmentioning

confidence: 99%

Exploring zipping and assembly as a protein folding principle

Voelz

Dill

2007

Proteins

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“…Such pheromone laying approach is similar to those on the arcs connecting cities in a traveling salesman problem (TSP). However, it is different from existing ant algorithms proposed for solving PFPs, whose pheromones are on three relative folding directions of the protein [37]- [41]. In fact, if the pheromones only indicate the relative directions of the protein folding (as the ones in [37]- [41] do), the ants may not grasp the folding situations entirely.…”

Section: Introductionmentioning

confidence: 90%

“…However, it is different from existing ant algorithms proposed for solving PFPs, whose pheromones are on three relative folding directions of the protein [37]- [41]. In fact, if the pheromones only indicate the relative directions of the protein folding (as the ones in [37]- [41] do), the ants may not grasp the folding situations entirely. On the contrary, if the pheromones guide the protein to fold on an absolute lattice, as the proposed algorithm does, each ant can sense the solutions which have been configured by the other ants.…”

Section: Introductionmentioning

confidence: 90%

“…It has four special mechanisms, including the path construction, the path retrieval, the pheromone attraction, and the folding heuristics. These novel mechanisms make it behave differently from previous ant algorithms for solving PFPs with the HP square lattice model [37]- [41].…”

Section: Introductionmentioning

confidence: 94%

“…Since a number of simplified models have been proposed, various methods have been developed to solve the PFPs, such as the dynamic programming (DP), neural network (NN) [23], Monte Carlo (MC) [24]- [28], genetic algorithm (GA) [29]- [36], ant colony optimization (ACO) [37]- [41], particle swarm optimization (PSO) [22], and immune algorithm (IA) [42] [43] methods. The PFPs are proven to be NP-complete [44], which cannot be solved by a deterministic polynomial algorithm.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Flexible Protein Folding by Ant Colony Optimization

Zhang

Studies in Computational Intelligence

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An Improved Ant Colony Optimisation Algorithm for the 2D HP Protein Folding Problem

Shmygelska

Hoos

2003

Advances in Artificial Intelligence

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121

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Abstract. The prediction of a protein's structure from its amino-acid sequence is one of the most important problems in computational biology. In the current work, we focus on a widely studied abstraction of this problem, the 2-dimensional hydrophobic-polar (2D HP) protein folding problem. We present an improved version of our recently proposed Ant Colony Optimisation (ACO) algorithm for this £ ¥ ¤ -hard combinatorial problem and demonstrate its ability to solve standard benchmark instances substantially better than the original algorithm; the performance of our new algorithm is comparable with state-of-the-art Evolutionary and Monte Carlo algorithms for this problem. The improvements over our previous ACO algorithm include long range moves that allows us to perform modification of the protein at high densities, the use of improving ants, and selective local search. Overall, the results presented here establish our new ACO algorithm for 2D HP protein folding as a state-of-the-art method for this highly relevant problem from bioinformatics.

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An Ant Colony Optimization Algorithm for the 2D HP Protein Folding Problem

Cited by 80 publications

References 12 publications

Exploring zipping and assembly as a protein folding principle

Exploring zipping and assembly as a protein folding principle

Flexible Protein Folding by Ant Colony Optimization

An Improved Ant Colony Optimisation Algorithm for the 2D HP Protein Folding Problem

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