Adhesin/adhesin-like protein detection software tools | Immune system data analysis
Adhesins are important virulence factors used by pathogens during establishment of infection. Therefore, targeting the adhesins in vaccine development can help efficiently combat fungal infections by blocking their function and preventing adherence to host cell.
Allows users to detect proteins which could be identified as adhesins. SPAAN is a non-homology-based method using 105 compositional properties combined with artificial neural networks (ANNs) to identify adhesins and adhesin-like proteins in species belonging to a wide phylogenetic spectrum.
Allows users to identify fungal adhesins. FaaPred uses two classifiers : ACHM and PSSM-a, in order to perform predictions with a range from -1.0 to 1.5. Both classifiers may be picked together to make comparative predictions. This software includes a dataset composed of 75 well annotated fungal adhesins and 341 non-adhesins proteins. It’s a Support Vector Machine (SVM)-based method which aims to improve knowledge about role of adhesins in fungal infections.
Identifies candidates for vaccines in case of fungal infections. FungalRV uses candidate occurrence in immuno-compromised or otherwise debilitated host to make its predictions. It is based on highly accurate support vector machine (SVM) models. The platform provides a database that offers immuno-informatics data on 307 predicted adhesins and adhesin like proteins obtained by the tool run on entire proteomes of eight human pathogenic fungal species.
Predicts Malarial adhesins-like proteins. MAAP uses a support vector machine (SVM) approach. It returns a score to determine the probability of a malarial protein having an adhesin-like or adhesin features. The tool was run on Plasmodium falciparum, P. vivax and P. yoelii and achieves an efficiency of 0.86-0.89 with sensitivity of 95.9 per cent for P. falciparum and 100 per cent for others.