GASS is a method based on a genetic algorithm to search for similar active sites (catalytic and binding) in proteins. In addition to finding similar active sites, the method can find inter-domain sites and perform not exact matches using a substitution matrix (conservative mutations). In this new version, GASS uses parallel genetic algorithms to create an initial population (seeds) to improve accuracy and decrease processing time.

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  • Catalytic Site Search: Given a PDB file, performs catalytic sites search using literature-derived templates from M-CSA.
  • Binding Sites Search: Given a PDB file, performs binding sites search using literature-derived templates from M-CSA.
  • One-to-one Site Search: Given a PDB file, performs a search using a user-provided template.

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Vinícius A Paiva, Murillo V Mendonça, Sabrina A Silveira, David B Ascher, Douglas E V Pires, Sandro C Izidoro, GASS-Metal: identifying metal-binding sites on protein structures using genetic algorithms, Briefings in Bioinformatics, 2022;, bbac178, https://doi.org/10.1093/bib/bbac178

João P. A. Moraes, Gisele L. Pappa, Douglas E. V. Pires, Sandro C. Izidoro, GASS-WEB: a web server for identifying enzyme active sites based on genetic algorithms, Nucleic Acids Research, Volume 45, Issue W1, 3 July 2017, Pages W315–W319, https://doi.org/10.1093/nar/gkx337

Sandro C. Izidoro, Anisio M. Lacerda, Gisele L. Pappa, MeGASS: Multi-Objective Genetic Active Site Search. Genetic and Evolutionary Computation Conference - GECCO 2015, Madrid, Spain, https://doi.org/10.1145/2739482.2768436

Sandro C. Izidoro, Raquel C. de Melo-Minardi, Gisele L. Pappa, GASS: identifying enzyme active sites with genetic algorithms, Bioinformatics, Volume 31, Issue 6, 15 March 2015, Pages 864–870, https://doi.org/10.1093/ bioinformatics/btu746