SUMOylation site/SIM detection software tools | Post-translational modification data analysis
Post-translational modification by the Small Ubiquitin-like Modifier (SUMO) proteins, a process termed SUMOylation, is involved in many fundamental cellular processes. SUMO proteins are conjugated to a protein substrate, creating an interface for the recruitment of cofactors harboring SUMO-interacting motifs (SIMs). Mapping both SUMO-conjugation sites and SIMs is required to study the functional consequence of SUMOylation.
Allows the prediction of sumoylation sites within a submitted protein. SUMOplot is a web application allowing users to query a protein of interest through a sequence of interest or a protein ID derived from SwissProt, PIR, GenPept or RefSeq databases. Additionally, the platform also proposes a feature which is able to score sites detected in the investigated data with color-coded motifs signaling high and low probability.
Deduces both covalent sumoylation sites and non-covalent SUMO-interaction motifs (SIMs) in proteins. GPS-SUMO is a program based on a group-based prediction system (GPS) algorithm coupled to a particle swarm optimization approach. The application can be set by using different prediction thresholds. Predictions with files with a size up to 2M have to be performed with the standalone version of the application.
Uses a scoring system based on a position frequency matrix derived from the alignment of experimental SUMOylation sites or SUMO-interacting motifs (SIMs). Compared to existing web-tools, JASSA displays on par or better performances. Novel features were implemented towards a better evaluation of the prediction, including identification of database hits matching the query sequence and representation of candidate sites within the secondary structural elements and/or the 3D fold of the protein of interest, retrievable from deposited PDB files.
Predicts sumoylation lysine (K) sites in proteins by introduction of hydrophobicity to binary encoding. With the assistance of a support vector machine, SUMOhydro was trained and tested using a stringent non-redundant sumoylation dataset. In a leave-one-out cross-validation, the proposed method yielded an excellent performance with a correlation coefficient, specificity, sensitivity and accuracy equal to 0.690, 98.6%, 71.1% and 97.5%, respectively.
A web server for sequence-based prediction of protein sumoylation sites. Users can enter an amino acid sequence or multiple protein sequences in the FASTA format, specify the methods (either random forest or support vector machine), and input the proper threshold for prediction of protein sumoylation site.
This service can predict the SUMOAMVR types and sumoylation states. Here, we defined the SUMOAMVR as sumoylation related amino acid variations that affect sumoylation sites or enzymes involved in the process of connectivity, and categorized four types of potential SUMOAMVR. For each query protein, this web server uses the constructed lysine sumoylation prediction model (SumoPred) to assign a score for each lysine site. The SUMOAMVR could be identified when the sumoylation sites were altered between the original and variant sequence.
Provides a small ubiquitin-like modifier (SUMO) binding method. SUMOgo is a SUMOylation prediction system that was applied to both conserved-motif and nonconserved-motif screening models to reach separate predictions. It can also be used to predict the potential SUMOylation sites of CREB binding protein (CREBBP). This method was applied to both conserved-motif and nonconserved-motif screening models to reach separate predictions.