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Chaotic multiquenching annealing applied to the protein folding problem.

Juan Frausto-SolisErnesto Liñan-GarcíaMishael Sánchez-PérezJuan Paulo Sánchez-Hernández
Published in: TheScientificWorldJournal (2014)
The Chaotic Multiquenching Annealing algorithm (CMQA) is proposed. CMQA is a new algorithm, which is applied to protein folding problem (PFP). This algorithm is divided into three phases: (i) multiquenching phase (MQP), (ii) annealing phase (AP), and (iii) dynamical equilibrium phase (DEP). MQP enforces several stages of quick quenching processes that include chaotic functions. The chaotic functions can increase the exploration potential of solutions space of PFP. AP phase implements a simulated annealing algorithm (SA) with an exponential cooling function. MQP and AP are delimited by different ranges of temperatures; MQP is applied for a range of temperatures which goes from extremely high values to very high values; AP searches for solutions in a range of temperatures from high values to extremely low values. DEP phase finds the equilibrium in a dynamic way by applying least squares method. CMQA is tested with several instances of PFP.
Keyphrases
  • machine learning
  • transcription factor
  • deep learning
  • molecular dynamics simulations
  • molecular dynamics
  • single molecule
  • binding protein
  • human health
  • aqueous solution