GASS-WEB: a web server for identifying enzyme active sites based on genetic algorithms

Abstract

Enzyme active sites are important and conserved functional regions of proteins whose identification can be an invaluable step toward protein function prediction. Most of the existing methods for this task are based on active site similarity and present limitations including performing only exact matches on template residues, template size restraints, despite not being capable of finding inter-domain active sites. To fill this gap, we proposed GASS-WEB, a user-friendly web server that uses GASS (Genetic Active Site Search), a method based on an evolutionary algorithm to search for similar active sites in proteins. GASS-WEB can be used under two different scenarios: (i) given a protein of interest, to match a set of specific active site templates; or (ii) given an active site template, looking for it in a database of protein structures. The method has shown to be very effective on a range of experiments and was able to correctly identify >90% of the catalogued active sites from the Catalytic Site Atlas. It also managed to achieve a Matthew correlation coefficient of 0.63 using the Critical Assessment of protein Structure Prediction (CASP 10) dataset. In our analysis, GASS was ranking fourth among 18 methods. GASS-WEB is freely available at http://gass.unifei.edu.br/.

Predicted antiviral drugs Darunavir, Amprenavir, Rimantadine and Saquinavir can potentially bind to neutralize SARS-CoV-2 conserved proteins

“…Active sites of enzymes are surface regions that are highly conserved and involved in catalysis or substrate binding. In this study, active sites of SARS-CoV-2 enzymes were predicted by a web server, GASS-WEB ( http://gass.unifei.edu.br/ ) that uses Genetic Active Site Search based on genetic algorithms [ 51 ]. Active site residues and the drug binding interfaces of the four drugs viz.…”

“…GASS-WEB has been used to predict active sites of SARS-CoV-2 enzymes (NSP3, NSP5, NSP9, NSP12, NSP13, NSP14, NSP15 and NSP16) considered in this study. It uses genetic algorithms to find active sites of enzymes that are meant for catalytic activity or substrate binding [ 51 ].…”

Demystifying Chronic Kidney Disease of Unknown Etiology (CKDu): Computational Interaction Analysis of Pesticides and Metabolites with Vital Renal Enzymes

“…The results of these tests are tabulated in Table S2. Finding the protein active sites and substrate-binding sites was done using the GASS-WEB server (Table S4) [59]. All of the above-found amino acid sequences were subjected to NCBI-VAST database search [60] in order to confirm results.…”

“…Finding the protein active sites and substrate-binding sites was done using the GASS-WEB server [59]. The GASS-WEB server consists of active-site models and their respective Protein Data Bank structures.…”

High precision protein functional site detection using 3D convolutional neural networks

“…GASPS (Polacco and Babbitt, 2006) uses a genetic algorithm strategy to create 3D templates within a protein family to best identify family members from the background. GASS (Izidoro et al , 2015; Moraes et al , 2017), on the other hand, employs genetic algorithms to search for similar active sites in proteins, given active site templates. Structurally Aligned Local Sites of Activities (Wang et al , 2013) combines predicted functional residues from POOL (Somarowthu et al , 2011) with local structural alignments to create characteristic structural patterns within a functional family.…”