Flexible protein folding by ant colony optimization

Protein structure prediction is one of the most challenging topics in bioinformatics. As the protein structure is found to be closely related to its functions, predicting the folding structure of a protein to judge its functions is meaningful to the humanity. This chapter proposes a flexible ant colony (FAC) algorithm for solving protein folding problems (PFPs) based on the hydrophobic-polar (HP) square lattice model. Different from the previous ant algorithms for PFPs, the pheromones in the proposed algorithm are placed on the arcs connecting adjacent squares in the lattice. Such pheromone placement model is similar to the one used in the traveling salesmen problems (TSPs), where pheromones are released on the arcs connecting the cities. Moreover, the collaboration of effective heuristic and pheromone strategies greatly enhances the performance of the algorithm so that the algorithm can achieve good results without local search methods. By testing some benchmark two-dimensional hydrophobic-polar (2D-HP) protein sequences, the performance shows that the proposed algorithm is quite competitive compared with some other well-known methods for solving the same protein folding problems

Fe/Ni ratio in the Ant Nebula Mz 3

We have analyzed the [Fe II] and [Ni II] emission lines in the bipolar planetary nebula Mz~3. We find that the [Fe II] and [Ni II] lines arise exclusively from the central regions. Fluorescence excitation in the formation process of these lines is negligible for this low-excitation nebula. From the [Fe II]/[Ni II] ratio, we obtain a higher Fe/Ni abundance ratio with respect to the solar value. The current result provides further supporting evidence for Mz 3 as a symbiotic Mira.Comment: 2 pages, 1 figure, to be published in the Proceedings of the IAU Symposium 234: Planetary Nebulae in Our Galaxy and Beyond, eds. M.J. Barlow, R.H. Mende