Allows construction of positive and negative density profiles for each enzyme commission (EC) number, representing how sequences within a class align to one another and to other classes. DETECT considers the effect of sequence diversity when assigning enzymatic function to a protein sequence. This tool can be applied for studying the proteome of Caenorhabditis elegans. In summary, it permits users to reconstruct high confidence metabolic models.
Detects automatically enzyme in a fully sequenced genome, based on the classification of enzymes in the ENZYME database. PRIAM relies on sets of position-specific scoring matrices automatically tailored for each ENZYME entry. The tool was applied to predict metabolic pathways from the complete genome of the nitrogen fixing bacterium Sinorhizobium meliloti and on the plant pathogen Ralstonia solanacearum.
Analyzes DNA sequences for the presence of restriction enzyme sites in a convenient and easy to use manner. NEBcutter consists of a set of cooperating program modules. The module that finds recognition sites implements a brute force algorithm. The algorithm that detects open reading frames (ORFs) defines them as maximal length segments of DNA from start codons to stop codons in the same reading frame, assuming bacterial sequences and codons.
Converts g IC50 to Ki values for inhibitors of enzymes and of protein-ligand interactions. IC50-to-Ki converter is a web server that calculates Ki values from IC50 values using equations for enzyme-substrate and target-ligand interactions by different inhibitory mechanisms. The software provides results for classic and tight-binding inhibitors of enzyme activity and ligand-binding reactions that are assumed to follow relatively simple kinetic schemes. It aims to facilitate research and the development of potential therapeutic products.
Assists users to perform CAZome (all CAZymes of a genome) annotation. dbCAN is a web application that includes several functions: (1) CAZyme annotation; (2) submission of DNA sequences in addition to protein sequences; (3) identification of transcription factors (TFs), transporters (TCs), and further CAZyme gene clusters (CGCs) using CGC-Finder; and (4) combination of the results from the three tools, permitting visualization as a Venn diagram and detailed results as graphs.
A web-based tool with an underlying database providing users with the ability to link lists of mammalian proteins/genes with the kinases that phosphorylate them. The system draws from several available kinase-substrate databases to compute kinase enrichment probability based on the distribution of kinase-substrate proportions in the background kinase-substrate database compared with kinases found to be associated with an input list of genes/proteins.
Predict kinases, phosphatases and chains of phosphorylation events in signaling networks by combining mRNA expression levels of regulators and targets with a motif detection algorithm and optional prior information. It is implemented in Java.
Predicts the substrate of non-ribosomal peptide synthetases (NRPS) A-domains. SEQL-NRPS is a web application that uses Sequence Learner (SEQL), a discriminative classification method for sequences. Users can paste or upload A-domains in FASTA format. The sequences are then classified and the results page shows the sequence identifier, the predicted substrate specificity, and the probability given by SEQL that the sequence belongs to the predicted substrate.
Identifies an interior point that is near-uniquely defined by the enzyme profile. HCSA incorporates enzyme abundance into the stoichiometric model. It is a method to mimic steady-state ordinary differential equation (ODE) models. This tool is based on a Hyper-Cube Shrink algorithm integrating omics data to metabolic network.
Displays the hydrolysate and the prediction of sets of enzymes that have been involved in the generation of the current hydrolysate’s identified peptides. EnzymePredictor shows the areas that mass spectrometry (MS) identifies with the highest coverage. It focuses on each protein independently. This tool assists users to evaluate pockets of peptides with similar biochemical properties, peptides densely represented, and gray areas that MS fails to find.
Provides probabilistic enzymatic function predictions for uncharacterized protein sequences. ECPred is an automated enzyme commission (EC) number based enzymatic function prediction program. The software adopts a supervised ensemble classification approach by incorporating three different predictors based on homology, subsequence extraction and peptide physicochemical properties. The software can predict the enzymatic functions of uncharacterized proteins at all five levels of EC. It was trained and validated using the enzyme entries located in the UniProtKB/Swiss-Prot database.
Provides functions for enzyme class prediction. Figshare uses both structural and amino acid sequence information to build its predictions. It is based on single- and multi-label classification models and was tested on enzymes assumed to perform single or multiple reactions. This tool can automate exploitation of features and tuning of performance in a seamless fashion.
Predicts the effect of single amino acid substitutions on enzyme catalytic activity. This method allows users to predict if a given mutation, made anywhere in the enzyme, will cause a decrease in kcat/Km value of ≥ 95%. The accuracy of this technique allows the experimentalist to reduce the number of mutations necessary to probe the enzyme reaction mechanism. It has a 2.5-fold increase in precision.
Identifies and classifies beta-lactamases (BL). betaLactamase classification assists users for building profiles Hidden Markov Models (HMM) and sequence clustering using similarity underlie the workflow. This tool is based on a hierarchical scheme that reflects the distinct evolutionary origins of serine-beta-lactamases (SBLs) and class B of metallo-beta-lactamases (MBLs). It allows researchers to build a profile HMM for each BL class.
Provides hidden Markov models (HMMs) profiles for transposases (Tnps) of the remaining 40% of the insertion sequences (ISs) families. TnpPred is a web application that supplements and extends currently available programs and HMM profiles for the prediction of 19 prokaryotic transposase families. It can also be a useful aid to predict Tnps in microbial genomes.
These tools are to assist especially CAZyme researchers around the world with an easy "one-click-get-all"-system, to get better access to the immense amount of data that is available in the CAZy database only through a "click-one-get-one"-system. These tools can be used to extract all sequences of a given family within a few seconds or to analyse how CBMs are distributed in different GH families.