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A local landscape mapping method for protein structure prediction in the HP model

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Abstract

The hydrophobic-polar (HP) model has been widely studied in the field of protein structure prediction both for theoretical purposes and as a benchmark for new optimization strategies. In this work we present results of the recently proposed Hybrid Monte Carlo Ant Colony Optimization heuristic in the HP model using a fragment assembly-like strategy. Moreover we extend that method introducing a general framework for optimization in the HP model, called Local Landscape Mapping, and we test it using the pull moves set to generate solutions. We describe the heuristic and compare results obtained on well known HP instances in the 3-dimensional cubic lattice to those obtained with standard Ant Colony optimization and Simulated Annealing. Fragment assembly-like tests were performed using a modified objective function to prevent the creation of overlapping walks. Results show that our method performs better than the other heuristics in all benchmark instances when the fragment assembly-like strategy is used while in the case of pull moves-based neighborhood its performance is comparable to that of simulated annealing.

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Notes

  1. ACO and LLM have been implemented using the definitions in Eqs. 11 and  16 respectively in place of those in Eqs.  9 and 12 of Citrolo and Mauri (2013), moreover a different pheromone model has been used for ACO.

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Authors and Affiliations

  1. Dipartimento di Informatica Sistemistica e Comunicazione (DISCo), Universitá degli studi di Milano-Bicocca, Milan, Italy

    Andrea G. Citrolo & Giancarlo Mauri

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  1. Andrea G. Citrolo
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  2. Giancarlo Mauri
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Correspondence to Andrea G. Citrolo.

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Citrolo, A.G., Mauri, G. A local landscape mapping method for protein structure prediction in the HP model. Nat Comput 13, 309–319 (2014). https://doi.org/10.1007/s11047-014-9427-8

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