CycloAnt
peer-reviewed · Proceedings of the Genetic and Evolutionary Computation Conference · 2017
| Date | 2017-07-01 |
| Type | peer-reviewed |
| Venue | Proceedings of the Genetic and Evolutionary Computation Conference |
| Publisher | ACM |
| Contribution | algorithm |
| DOI | 10.1145/3071178.3071239 |
| Citations (OpenAlex) | 2 |
Abstract
Non ribosomal cyclic peptides have long been used as effective antibiotics in drug industry. Reconstruction of these peptide sequences extracted from natural elements remain a challenge till today. Introduction of mass spectrometry in this regard created scope for computer scientists to develop efficient algorithms to interpret a mass spectrum into a peptide sequence. Mass spectrum have a well known limitation of missing peaks which misleads the de novo sequencing process of cyclic peptides. In this paper, we present CycloAnt, a computational method that can reproduce correct cyclic amino acid sequence from distorted mass spectrum in an efficient way. We have used hybrid ants those construct the solution first and then try to improve quality of the solution using subsequent local search. We proposed a set of novel scoring functions which emphasize on the presence of sub-sequences of amino acids rather than approving equal contribution of all partial mass and precursor mass present in the spectrum. Moreover, we proposed a novel set of operators for the local search and refinement. Experiments show the effectiveness of our method on a standard set of benchmark and improvement over other methods.
Methods and tools
- CycloAnt: Hybrid ant colony optimisation with local search that reconstructs cyclic peptide sequences from distorted mass spectra.