Corpus ID: 54440737

FoldingZero: Protein Folding from Scratch in Hydrophobic-Polar Model

  title={FoldingZero: Protein Folding from Scratch in Hydrophobic-Polar Model},
  author={Yanjun Li and Hengtong Kang and Ketian Ye and Shuyu Yin and Xiaolin Li},
De novo protein structure prediction from amino acid sequence is one of the most challenging problems in computational biology. As one of the extensively explored mathematical models for protein folding, Hydrophobic-Polar (HP) model enables thorough investigation of protein structure formation and evolution. Although HP model discretizes the conformational space and simplifies the folding energy function, it has been proven to be an NP-complete problem. In this paper, we propose a novel protein… Expand
The prediction of the three-dimensional protein structures from amino acid sequences has been a long-standing challenge in computational biophysics. In the last decade, considerable progress has beenExpand
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Fast Protein Folding in the Hydrophobic-Hydrophillic Model within Three-Eights of Optimal
These algorithms are the first approximation algorithms in the literature with guaranteed performance for this model and achieve a three-dimensional protein conformation that has a guaranteed free energy no worse than three-eighths of optimal. Expand
A Constraint-Based Approach to Fast and Exact Structure Prediction in Three-Dimensional Protein Models
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An ant colony optimisation algorithm for the 2D and 3D hydrophobic polar protein folding problem
The application of ACO to this bioinformatics problem compares favourably with specialised, state-of-the-art methods for the 2D and 3D HP protein folding problem; the empirical results indicate that the rather simple ACO algorithm scales worse with sequence length but usually finds a more diverse ensemble of native states. Expand
A hybrid approach to protein folding problem integrating constraint programming with local search
A novel hybrid approach to simulate the protein folding problem using constraint programming technique integrated within local search and encouraging results obtained show that these two approaches can be combined efficiently to obtain better quality solutions within acceptable time. Expand
Finding low-energy conformations of lattice protein models by quantum annealing
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A fast conformational search strategy for finding low energy structures of model proteins
  • T. Beutler, K. Dill
  • Mathematics, Medicine
  • Protein science : a publication of the Protein Society
  • 1996
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Exploration of two-dimensional hydrophobic-polar lattice model by combining local search with elastic net algorithm.
A novel hybrid of elastic net algorithm and local search method (ENLS) is applied successfully to simulations of protein folding on two-dimensional hydrophobic-polar lattice model and the numerical results show that it is drastically superior to other methods in finding the ground state of a protein. Expand
A novel state space representation for the solution of 2D-HP protein folding problem using reinforcement learning methods
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