GASS-Metal is a method based on a genetic algorithm to search for similar metal-binding sites in proteins. In addition to finding similar metal-binding sites, the method can find inter-domain sites and perform not exact matches using a substitution matrix (conservative mutations).

In this new version, GASS-Metal uses parallel genetic algorithms to create an initial population (seeds), improve accuracy and decrease processing time.

Available Resources:


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,

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,

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,

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, bioinformatics/btu746