ArticleBioMed research international2013
iEzy-drug: a web server for identifying the interaction between enzymes and drugs in cellular networking.
Article in BioMed research international, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers.
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Who cites it
20 citing papers in PubMed.
- StructuralDPPIV: a novel deep learning model based on atom structure for predicting dipeptidyl peptidase-IV inhibitory peptides.Bioinformatics (Oxford, England) · 2024Article
- MOZART, a QSAR Multi-Target Web-Based Tool to Predict Multiple Drug-Enzyme Interactions.Molecules (Basel, Switzerland) · 2023Article
- Article
- Current Biochemical Applications and Future Prospects of Chlorotoxin in Cancer Diagnostics and Therapeutics.Advanced pharmaceutical bulletin · 2019Review
- Plant protection product dose rate estimation in apple orchards using a fuzzy logic system.PloS one · 2019Article
- A proteome-wide systems toxicological approach deciphers the interaction network of chemotherapeutic drugs in the cardiovascular milieu.RSC advances · 2018Article
- Heterodimer Binding Scaffolds Recognition via the Analysis of Kinetically Hot Residues.Pharmaceuticals (Basel, Switzerland) · 2018Article
- Pse-Analysis: a python package for DNA/RNA and protein/ peptide sequence analysis based on pseudo components and kernel methods.Oncotarget · 2017Article
- DrugECs: An Ensemble System with Feature Subspaces for Accurate Drug-Target Interaction Prediction.BioMed research international · 2017Article
- iAFP-Ense: An Ensemble Classifier for Identifying Antifreeze Protein by Incorporating Grey Model and PSSM into PseAAC.The Journal of membrane biology · 2016Article
- Article
- A high performance prediction of HPV genotypes by Chaos game representation and singular value decomposition.BMC bioinformatics · 2015Article
- Sequence-specific flexibility organization of splicing flanking sequence and prediction of splice sites in the human genome.Chromosome research : an international journal on the molecular, supramolecular and evolutionary aspects of chromosome biology · 2014Article
- iHyd-PseAAC: predicting hydroxyproline and hydroxylysine in proteins by incorporating dipeptide position-specific propensity into pseudo amino acid composition.International journal of molecular sciences · 2014Article
- iNR-Drug: predicting the interaction of drugs with nuclear receptors in cellular networking.International journal of molecular sciences · 2014Article
- Prediction of protein-protein interaction with pairwise kernel support vector machine.International journal of molecular sciences · 2014Article
- iRSpot-TNCPseAAC: identify recombination spots with trinucleotide composition and pseudo amino acid components.International journal of molecular sciences · 2014Article
- iCTX-type: a sequence-based predictor for identifying the types of conotoxins in targeting ion channels.BioMed research international · 2014Article
- Article
- iNitro-Tyr: prediction of nitrotyrosine sites in proteins with general pseudo amino acid composition.PloS one · 2014Article
Corrections and comments
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Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
With the features of extremely high selectivity and efficiency in catalyzing almost all the chemical reactions in cells, enzymes play vitally important roles for the life of an organism and hence have become frequent targets for drug design. An essential step in developing drugs by targeting enzymes is to identify drug-enzyme interactions in cells. It is both time-consuming and costly to do this purely by means of experimental techniques alone. Although some computational methods were developed in this regard based on the knowledge of the three-dimensional structure of enzyme, unfortunately their usage is quite limited because three-dimensional structures of many enzymes are still unknown. Here, we reported a sequence-based predictor, called "iEzy-Drug," in which each drug compound was formulated by a molecular fingerprint with 258 feature components, each enzyme by the Chou's pseudo amino acid composition generated via incorporating sequential evolution information and physicochemical features derived from its sequence, and the prediction engine was operated by the fuzzy K-nearest neighbor algorithm. The overall success rate achieved by iEzy-Drug via rigorous cross-validations was about 91%. Moreover, to maximize the convenience for the majority of experimental scientists, a user-friendly web server was established, by which users can easily obtain their desired results.
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